nips_2016_videos_pdfs | pdfs ... Nips 2016 in just a table | Machine Learning library

nips_2016_videos_pdfs is a R library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. nips_2016_videos_pdfs has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Talks, videos, pdfs ... Nips 2016 in just a table :). | type_talk | name_talk | authors | url_talk_description | PDF | Video | Video_1 | Video_2 | Slides | Spotlight_Video | Notes | |--------------------------------|--------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------|---------------------------------------------------------------|---------------------------------------------------------------------------------------------|-------------------------------------------------------------| | Tutorial | Variational Inference: Foundations and Modern Methods | David Blei · Shakir Mohamed · Rajesh Ranganath | | | | | | | | | | Tutorial | Deep Reinforcement Learning Through Policy Optimization | Pieter Abbeel · John Schulman | | | | | | | | | | Tutorial | Crowdsourcing: Beyond Label Generation | Jennifer Wortman Vaughan | | | | | | | | | | Tutorial | Theory and Algorithms for Forecasting Non-Stationary Time Series | Vitaly Kuznetsov · Mehryar Mohri | | | | | | | | | | Tutorial | Natural Language Processing for Computational Social Science | Cristian Danescu-Niculescu-Mizil · Lillian Lee | | | | | | | | | | Tutorial | Nuts and Bolts of Building Applications using Deep Learning | Andrew Y Ng | | | | | | | | | | Tutorial | Large-Scale Optimization: Beyond Stochastic Gradient Descent and Convexity | Suvrit Sra · Francis Bach | | | | | | | | | | Tutorial | Generative Adversarial Networks | Ian Goodfellow | | | | | | | | | | Tutorial | ML Foundations and Methods for Precision Medicine and Healthcare | Suchi Saria · Peter Schulam | | | | | | | | | | Invited Talk (Posner Lecture) | Predictive Learning | Yann LeCun | | | | | | | | | | Poster | Improved Dropout for Shallow and Deep Learning | Zhe Li · Boqing Gong · Tianbao Yang | | | | | | | | | | Poster | Communication-Optimal Distributed Clustering | Jiecao Chen · He Sun · David Woodruff · Qin Zhang | | | | | | | | | | Poster | On Robustness of Kernel Clustering | Bowei Yan · Purnamrita Sarkar | | | | | | | | | | Poster | Combinatorial semi-bandit with known covariance | Rémy Degenne · Vianney Perchet | | | | | | | | | | Poster | A posteriori error bounds for joint matrix decomposition problems | Nicolò Colombo · Nikos Vlassis | | | | | | | | | | Poster | Object based Scene Representations using Fisher Scores of Local Subspace Projections | Mandar D Dixit · Nuno Vasconcelos | | | | | | | | | | Poster | MoCap-guided Data Augmentation for 3D Pose Estimation in the Wild | Gregory Rogez · Cordelia Schmid | | | | | | | | | | Poster | Regret of Queueing Bandits | Subhashini Krishnasamy · Rajat Sen · Ramesh Johari · Sanjay Shakkottai | | | | | | | | | | Poster | Efficient Nonparametric Smoothness Estimation | Shashank Singh · Simon S Du · Barnabas Poczos | | | | | | | | | | Poster | Completely random measures for modelling block-structured sparse networks | Tue Herlau · Mikkel N Schmidt · Morten Mørup | | | | | | | | | | Poster | DISCO Nets : DISsimilarity COefficients Networks | Diane Bouchacourt · Pawan K Mudigonda · Sebastian Nowozin | | | | | | | | | | Poster | An Architecture for Deep, Hierarchical Generative Models | Philip Bachman | | | | | | | | | | Poster | A Multi-Batch L-BFGS Method for Machine Learning | Albert S Berahas · Jorge Nocedal · Martin Takac | | | | | | | | | | Poster | Higher-Order Factorization Machines | Mathieu Blondel · Akinori Fujino · Naonori Ueda · Masakazu Ishihata | | | | | | | | | | Poster | A Bio-inspired Redundant Sensing Architecture | Anh Tuan Nguyen · Jian Xu · Zhi Yang | | | | | | | | | | Poster | Learning Supervised PageRank with Gradient-Based and Gradient-Free Optimization Methods | Lev Bogolubsky · Pavel Dvurechensky · Alexander Gasnikov · Gleb Gusev · Yurii Nesterov · Andrei M Raigorodskii · Aleksey Tikhonov · Maksim Zhukovskii | | | | | | | | | | Poster | Linear Relaxations for Finding Diverse Elements in Metric Spaces | Aditya Bhaskara · Mehrdad Ghadiri · Vahab Mirrokni · Ola Svensson | | | | | | | | | | Poster | Stochastic Optimization for Large-scale Optimal Transport | Aude Genevay · Marco Cuturi · Gabriel Peyré · Francis Bach | | | | | | | | | | Poster | Threshold Bandits, With and Without Censored Feedback | Jacob D Abernethy · Kareem Amin · Ruihao Zhu | | | | | | | | | | Poster | Mistake Bounds for Binary Matrix Completion | Mark Herbster · Stephen Pasteris · Massimiliano Pontil | | | | | | | | | | Poster | SoundNet: Learning Sound Representations from Unlabeled Video | Yusuf Aytar · Carl Vondrick · Antonio Torralba | | | | | | | | | | Poster | Doubly Convolutional Neural Networks | Shuangfei Zhai · Yu Cheng · Weining Lu · Zhongfei (Mark) Zhang | | | | | | | | | | Poster | Maximizing Influence in an Ising Network: A Mean-Field Optimal Solution | Christopher W Lynn · Daniel D Lee | | | | | | | | | | Poster | Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs | Shahin Jabbari · Ryan M Rogers · Aaron Roth · Steven Z. Wu | | | | | | | | | | Poster | Fairness in Learning: Classic and Contextual Bandits | Matthew Joseph · Michael Kearns · Jamie H Morgenstern · Aaron Roth | | | | | | | | | | Poster | A Powerful Generative Model Using Random Weights for the Deep Image Representation | Kun He · Yan Wang · John Hopcroft | | | | | | | | | | Poster | Improved Error Bounds for Tree Representations of Metric Spaces | Samir Chowdhury · Facundo Mémoli · Zane T Smith | | | | | | | | | | Poster | Adaptive optimal training of animal behavior | Ji Hyun Bak · Jung Choi · Athena Akrami · Ilana Witten · Jonathan W Pillow | | | | | | | | | | Poster | PAC-Bayesian Theory Meets Bayesian Inference | Pascal Germain · Francis Bach · Alexandre Lacoste · Simon Lacoste-Julien | | | | | | | | | | Poster | Nearly Isometric Embedding by Relaxation | James McQueen · Marina Meila · Dominique Joncas | | | | | | | | | | Poster | Graph Clustering: Block-models and model free results | Yali Wan · Marina Meila | | | | | | | | | | Poster | Learning Transferrable Representations for Unsupervised Domain Adaptation | Ozan Sener · Hyun Oh Song · Ashutosh Saxena · Silvio Savarese | | | | | | | | | | Poster | Measuring Neural Net Robustness with Constraints | Osbert Bastani · Yani Ioannou · Leonidas Lampropoulos · Dimitrios Vytiniotis · Aditya Nori · Antonio Criminisi | | | | | | | | | | Poster | A forward model at Purkinje cell synapses facilitates cerebellar anticipatory control | Ivan Herreros · Xerxes Arsiwalla · Paul Verschure | | | | | | | | | | Poster | Estimating Nonlinear Neural Response Functions using GP Priors and Kronecker Methods | Cristina Savin · Gasper Tkacik | | | | | | | | | | Poster | A Bayesian method for reducing bias in neural representational similarity analysis | Mingbo Cai · Nicolas W Schuck · Jonathan W Pillow · Yael Niv | | | | | | | | | | Poster | Learning to Communicate with Deep Multi-Agent Reinforcement Learning | Jakob Foerster · Yannis M. Assael · Nando de Freitas · Shimon Whiteson | | | | | | | | | | Poster | Total Variation Classes Beyond 1d: Minimax Rates, and the Limitations of Linear Smoothers | Veeranjaneyulu Sadhanala · Yu-Xiang Wang · Ryan J Tibshirani | | | | | | | | | | Poster | Exponential Family Embeddings | Maja Rudolph · Francisco Ruiz · Stephan Mandt · David Blei | | | | | | | | | | Poster | k*-Nearest Neighbors: From Global to Local | Oren Anava · Kfir Levy | | | | | | | | | | Poster | Reward Augmented Maximum Likelihood for Neural Structured Prediction | Mohammad Norouzi · Samy Bengio · zhifeng Chen · Navdeep Jaitly · Mike Schuster · Yonghui Wu · Dale Schuurmans | | | | | | | | | | Poster | A Probabilistic Model of Social Decision Making based on Reward Maximization | Koosha Khalvati · Seongmin A. Park · Jean-Claude Dreher · Rajesh P Rao | | | | | | | | | | Poster | Active Learning with Oracle Epiphany | Tzu-Kuo Huang · Lihong Li · Ara Vartanian · Saleema Amershi · Xiaojin Zhu | | | | | | | | | | Poster | On Regularizing Rademacher Observation Losses | Richard Nock | | | | | | | | | | Poster | A Non-generative Framework and Convex Relaxations for Unsupervised Learning | Elad Hazan · Tengyu Ma | | | | | | | | | | Poster | Learning Tree Structured Potential Games | Vikas Garg · Tommi Jaakkola | | | | | | | | | | Poster | Equality of Opportunity in Supervised Learning | Moritz Hardt · · Eric Price · Nati Srebro | | | | | | | | | | Poster | Interaction Networks for Learning about Objects, Relations and Physics | Peter Battaglia · Razvan Pascanu · Matthew Lai · Danilo Jimenez Rezende · koray kavukcuoglu | | | | | | | | | | Poster | beta-risk: a New Surrogate Risk for Learning from Weakly Labeled Data | Valentina Zantedeschi · Rémi Emonet · Marc Sebban | | | | | | | | | | Poster | Binarized Neural Networks | Itay Hubara · Matthieu Courbariaux · Daniel Soudry · Ran El-Yaniv · Yoshua Bengio | | | | | | | | | | Poster | Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning | Mehdi Sajjadi · Mehran Javanmardi · Tolga Tasdizen | | | | | | | | | | Poster | Generating Images with Perceptual Similarity Metrics based on Deep Networks | Alexey Dosovitskiy · Thomas Brox | | | | | | | | | | Poster | Exploiting Tradeoffs for Exact Recovery in Heterogeneous Stochastic Block Models | Amin Jalali · Qiyang Han · Ioana Dumitriu · Maryam Fazel | | | | | | | | | | Poster | Tensor Switching Networks | Chuan-Yung Tsai · Andrew M Saxe · David Cox | | | | | | | | | | Poster | Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models | Juho Lee · Lancelot F James · Seungjin Choi | | | | | | | | | | Poster | Temporal Regularized Matrix Factorization for High-dimensional Time Series Prediction | Hsiang-Fu Yu · Nikhil Rao · Inderjit S Dhillon | | | | | | | | | | Poster | Composing graphical models with neural networks for structured representations and fast inference | Matthew Johnson · David Duvenaud · Alex Wiltschko · Ryan P Adams · Sandeep R Datta | | | | | | | | | | Poster | PAC Reinforcement Learning with Rich Observations | Akshay Krishnamurthy · Alekh Agarwal · John Langford | | | | | | | | | | Poster | Algorithms and matching lower bounds for approximately-convex optimization | Andrej Risteski · Yuanzhi Li | | | | | | | | | | Poster | Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization | Sashank J. Reddi · Suvrit Sra · Barnabas Poczos · Alexander J Smola | | | | | | | | | | Poster | A Simple Practical Accelerated Method for Finite Sums | Aaron Defazio | | | | | | | | | | Poster | Unsupervised Learning for Physical Interaction through Video Prediction | Chelsea Finn · Ian Goodfellow · Sergey Levine | | | | | | | | | | Poster | Threshold Learning for Optimal Decision Making | Nathan F Lepora | | | | | | | | | | Poster | Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks | Hao Wang · Xingjian SHI · Dit-Yan Yeung | | | | | | | | | | Poster | Finding significant combinations of features in the presence of categorical covariates | Laetitia Papaxanthos · Felipe Llinares-Lopez · Dean Bodenham · Karsten Borgwardt | | | | | | | | | | Poster | Synthesizing the preferred inputs for neurons in neural networks via deep generator networks | Anh Nguyen · Alexey Dosovitskiy · Jason Yosinski · Thomas Brox · Jeff Clune | | | | | | | | | | Poster | Learning Infinite RBMs with Frank-Wolfe | Wei Ping · Qiang Liu · Alexander Ihler | | | | | | | | | | Poster | Sorting out typicality with the inverse moment matrix SOS polynomial | Edouard Pauwels · Jean B Lasserre | | | | | | | | | | Poster | Improving PAC Exploration Using the Median Of Means | Jason Pazis · Ronald Parr · Jonathan P How | | | | | | | | | | Poster | Reconstructing Parameters of Spreading Models from Partial Observations | Andrey Lokhov | | | | | | | | | | Poster | Dynamic Filter Networks | Xu Jia · Bert De Brabandere · Tinne Tuytelaars · Luc V Gool | | | | | | | | | | Poster | Generating Long-term Trajectories Using Deep Hierarchical Networks | Stephan Zheng · Yisong Yue · Patrick Lucey | | | | | | | | | | Poster | Cooperative Inverse Reinforcement Learning | Dylan Hadfield-Menell · Stuart J Russell · Pieter Abbeel · Anca Dragan | | | | | | | | | | Poster | Review Networks for Caption Generation | Zhilin Yang · Ye Yuan · Yuexin Wu · William W Cohen · Ruslan Salakhutdinov | | | | | | | | | | Poster | Gradient-based Sampling: An Adaptive Importance Sampling for Least-squares | Rong Zhu | | | | | | | | | | Poster | Robust k-means: a Theoretical Revisit | ALEXANDROS GEORGOGIANNIS | | | | | | | | | | Poster | Boosting with Abstention | Corinna Cortes · Giulia DeSalvo · Mehryar Mohri | | | | | | | | | | Poster | Estimating the class prior and posterior from noisy positives and unlabeled data | Shantanu J Jain · Martha White · Predrag Radivojac | | | | | | | | | | Poster | Bootstrap Model Aggregation for Distributed Statistical Learning | JUN HAN · Qiang Liu | | | | | | | | | | Poster | Noise-Tolerant Life-Long Matrix Completion via Adaptive Sampling | Maria-Florina Balcan · Hongyang Zhang | | | | | | | | | | Poster | FPNN: Field Probing Neural Networks for 3D Data | Yangyan Li · Soeren Pirk · Hao Su · Charles R Qi · Leonidas J Guibas | | | | | | | | | | Poster | Causal meets Submodular: Subset Selection with Directed Information | Yuxun Zhou · Costas J Spanos | | | | | | | | | | Poster | Improving Variational Autoencoders with Inverse Autoregressive Flow | Diederik P Kingma · Tim Salimans · Rafal Jozefowicz · Xi Chen · Xi Chen · Ilya Sutskever · Max Welling | | | | | | | | | | Poster | Adaptive Smoothed Online Multi-Task Learning | Keerthiram Murugesan · Hanxiao Liu · Jaime Carbonell · Yiming Yang | | | | | | | | | | Poster | The Limits of Learning with Missing Data | Brian Bullins · Elad Hazan · Tomer Koren | | | | | | | | | | Poster | Safe Exploration in Finite Markov Decision Processes with Gaussian Processes | Matteo Turchetta · Felix Berkenkamp · Andreas Krause | | | | | | | | | | Poster | Sparse Support Recovery with Non-smooth Loss Functions | Kévin Degraux · Gabriel Peyré · Jalal Fadili · Laurent Jacques | | | | | | | | | | Poster | Crowdsourced Clustering: Querying Edges vs Triangles | Ramya Korlakai Vinayak · Babak Hassibi | | | | | | | | | | Poster | Dual Decomposed Learning with Factorwise Oracle for Structural SVM of Large Output Domain | Ian En-Hsu Yen · Xiangru Huang · Kai Zhong · Ruohan Zhang · Pradeep K Ravikumar · Inderjit S Dhillon | | | | | | | | | | Poster | Sampling for Bayesian Program Learning | Kevin Ellis · Armando Solar-Lezama · Josh Tenenbaum | | | | | | | | | | Poster | Multiple-Play Bandits in the Position-Based Model | Paul Lagrée · Claire Vernade · Olivier Cappe | | | | | | | | | | Poster | Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip Connections | Xiaojiao Mao · Chunhua Shen · Yu-Bin Yang | | | | | | | | | | Poster | Optimistic Bandit Convex Optimization | Scott Yang · Mehryar Mohri | | | | | | | | | | Poster | Computing and maximizing influence in linear threshold and triggering models | Justin T Khim · Varun Jog · Po-Ling Loh | | | | | | | | | | Poster | Clustering with Bregman Divergences: an Asymptotic Analysis | Chaoyue Liu · Mikhail Belkin | | | | | | | | | | Poster | Community Detection on Evolving Graphs | Stefano Leonardi · Aris Anagnostopoulos · Jakub Łącki · Silvio Lattanzi · Mohammad Mahdian | | | | | | | | | | Poster | Dueling Bandits: Beyond Condorcet Winners to General Tournament Solutions | Siddartha Y. Ramamohan · Arun Rajkumar · Shivani Agarwal · Shivani Agarwal | | | | | | | | | | Poster | Learning a Metric Embedding for Face Recognition using the Multibatch Method | Oren Tadmor · Tal Rosenwein · Shai Shalev-Shwartz · Yonatan Wexler · Amnon Shashua | | | | | | | | | | Poster | Convergence guarantees for kernel-based quadrature rules in misspecified settings | Motonobu Kanagawa · Bharath K. Sriperumbudur · Kenji Fukumizu | | | | | | | | | | Poster | Stochastic Variational Deep Kernel Learning | Andrew G Wilson · Zhiting Hu · Ruslan Salakhutdinov · Eric P Xing | | | | | | | | | | Poster | Deep Submodular Functions: Definitions and Learning | Brian W Dolhansky · Jeff A Bilmes | | | | | | | | | | Poster | Scaled Least Squares Estimator for GLMs in Large-Scale Problems | Murat A Erdogdu · Lee H Dicker · Mohsen Bayati | | | | | | | | | | Poster | High-Rank Matrix Completion and Clustering under Self-Expressive Models | Ehsan Elhamifar | | | | | | | | | | Poster | Stochastic Three-Composite Convex Minimization | Alp Yurtsever · Bang Cong Vu · Volkan Cevher | | | | | | | | | | Poster | Tree-Structured Reinforcement Learning for Sequential Object Localization | Zequn Jie · Xiaodan Liang · Jiashi Feng · Xiaojie Jin · Wen Lu · Shuicheng Yan | | | | | | | | | | Poster | The non-convex Burer-Monteiro approach works on smooth semidefinite programs | Nicolas Boumal · Vlad Voroninski · Afonso Bandeira | | | | | | | | | | Poster | Neurons Equipped with Intrinsic Plasticity Learn Stimulus Intensity Statistics | Travis Monk · Cristina Savin · Jörg Lücke | | | | | | | | | | Poster | Greedy Feature Construction | Dino Oglic · Thomas Gärtner | | | | | | | | | | Poster | Dynamic Mode Decomposition with Reproducing Kernels for Koopman Spectral Analysis | Yoshinobu Kawahara | | | | | | | | | | Poster | Learning the Number of Neurons in Deep Networks | Jose M Alvarez · Mathieu Salzmann | | | | | | | | | | Poster | Strategic Attentive Writer for Learning Macro-Actions | Alexander (Sasha) Vezhnevets · Volodymyr Mnih · Simon Osindero · Alex Graves · Oriol Vinyals · John Agapiou · koray kavukcuoglu | | | | | | | | | | Poster | Active Learning from Imperfect Labelers | Songbai Yan · Kamalika Chaudhuri · Tara Javidi | | | | | | | | | | Poster | Probabilistic Linear Multistep Methods | Onur Teymur · Kostas Zygalakis · Ben Calderhead | | | | | | | | | | Poster | More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning | Xinyang Yi · Zhaoran Wang · Zhuoran Yang · Constantine Caramanis · Han Liu | | | | | | | | | | Poster | Mutual information for symmetric rank-one matrix estimation: A proof of the replica formula | jean barbier · Mohamad Dia · Nicolas Macris · Lenka Zdeborova · Thibault Lesieur · Florent Krzakala | | | | | | | | | | Poster | Coin Betting and Parameter-Free Online Learning | Francesco Orabona · David Pal | | | | | | | | | | Poster | Normalized Spectral Map Synchronization | Yanyao Shen · Qixing Huang · Nati Srebro · Sujay Sanghavi | | | | | | | | | | Poster | On Explore-Then-Commit strategies | Aurelien Garivier · Tor Lattimore · Emilie Kaufmann | | | | | | | | | | Poster | Learning Kernels with Random Features | Aman Sinha · John C Duchi | | | | | | | | | | Poster | Robustness of classifiers: from adversarial to random noise | Alhussein Fawzi · Seyed-Mohsen Moosavi-Dezfooli · Pascal Frossard | | | | | | | | | | Poster | Adaptive Skills Adaptive Partitions (ASAP) | Daniel J Mankowitz · Timothy A Mann · Shie Mannor | | | | | | | | | | Poster | Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations | Kirthevasan Kandasamy · Gautam Dasarathy · Junier B Oliva · Jeff Schneider · Barnabas Poczos | | | | | | | | | | Poster | Flexible Models for Microclustering with Application to Entity Resolution | Brenda Betancourt · Giacomo Zanella · Jeffrey Miller · Hanna Wallach · Abbas Zaidi · Beka Steorts | | | | | | | | | | Poster | Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo | Alain Durmus · Umut Simsekli · Eric Moulines · Roland Badeau · Gaël RICHARD | | | | | | | | | | Poster | Online and Differentially-Private Tensor Decomposition | Yining Wang · Anima Anandkumar | | | | | | | | | | Poster | Maximal Sparsity with Deep Networks? | Bo Xin · Yizhou Wang · Wen Gao · Baoyuan Wang · David Wipf | | | | | | | | | | Poster | Efficient High-Order Interaction-Aware Feature Selection Based on Conditional Mutual Information | Alexander Shishkin · Anastasia Bezzubtseva · Alexey Drutsa · Ilia Shishkov · Ekaterina Gladkikh · Gleb Gusev · Pavel Serdyukov | | | | | | | | | | Poster | Geometric Dirichlet Means Algorithm for topic inference | Mikhail Yurochkin · XuanLong Nguyen | | | | | | | | | | Poster | Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models | Marc Vuffray · Sidhant Misra · Andrey Lokhov · Michael Chertkov | | | | | | | | | | Poster | Multi-armed Bandits: Competing with Optimal Sequences | Zohar Karnin · Oren Anava | | | | | | | | | | Poster | Catching heuristics are optimal control policies | Boris Belousov · Gerhard Neumann · Constantin A Rothkopf · Jan R Peters | | | | | | | | | | Poster | Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds | Hongyi Zhang · Sashank J. Reddi · Suvrit Sra | | | | | | | | | | Poster | A Comprehensive Linear Speedup Analysis for Asynchronous Stochastic Parallel Optimization from Zeroth-Order to First-Order | Xiangru Lian · Huan Zhang · Cho-Jui Hsieh · Yijun Huang · Ji Liu | | | | | | | | | | Poster | Stochastic Gradient MCMC with Stale Gradients | Changyou Chen · Nan Ding · Chunyuan Li · Yizhe Zhang · Lawrence Carin | | | | | | | | | | Poster | Disentangling factors of variation in deep representation using adversarial training | Michael F Mathieu · Junbo Zhao · Junbo Jake Zhao · Aditya Ramesh · Pablo Sprechmann · Yann LeCun | | | | | | | | | | Poster | Consistent Kernel Mean Estimation for Functions of Random Variables | Carl-Johann Simon-Gabriel · Adam Scibior · Ilya Tolstikhin · Prof. Bernhard Schölkopf | | | | | | | | | | Poster | DECOrrelated feature space partitioning for distributed sparse regression | Xiangyu Wang · David B Dunson · Chenlei Leng | | | | | | | | | | Poster | Coupled Generative Adversarial Networks | Ming-Yu Liu · Oncel Tuzel | | | | | | | | | | Poster | Matching Networks for One Shot Learning | Oriol Vinyals · Charles Blundell · Tim Lillicrap · koray kavukcuoglu · Daan Wierstra | | | | | | | | | | Poster | Distributed Flexible Nonlinear Tensor Factorization | Shandian Zhe · Kai Zhang · Pengyuan Wang · Kuang-chih Lee · Zenglin Xu · Yuan Qi · Zoubin Ghahramani | | | | | | | | | | Poster | Tracking the Best Expert in Non-stationary Stochastic Environments | Chen-Yu Wei · Yi-Te Hong · Chi-Jen Lu | | | | | | | | | | Poster | Deep Alternative Neural Network: Exploring Contexts as Early as Possible for Action Recognition | Jinzhuo Wang · Wenmin Wang · xiongtao Chen · Ronggang Wang · Wen Gao | | | | | | | | | | Poster | Learning Parametric Sparse Models for Image Super-Resolution | Yongbo Li · Weisheng Dong · Xuemei Xie · GUANGMING Shi · Xin Li · Donglai Xu | | | | | | | | | | Poster | Kernel Observers: Systems-Theoretic Modeling and Inference of Spatiotemporally Evolving Processes | Hassan A Kingravi · Harshal R Maske · Girish Chowdhary | | | | | | | | | | Poster | Learning brain regions via large-scale online structured sparse dictionary learning | Elvis DOHMATOB · Arthur Mensch · Gael Varoquaux · Bertrand Thirion | | | | | | | | | | Poster | Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without Messages | Yin Cheng Ng · Pawel M Chilinski · Ricardo Silva | | | | | | | | | | Poster | A Bandit Framework for Strategic Regression | Yang Liu · Yiling Chen | | | | | | | | | | Poster | Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering | Michaël Defferrard · Xavier Bresson · Pierre Vandergheynst | | | | | | | | | | Poster | Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm | Qiang Liu · Dilin Wang | | | | | | | | | | Poster | Deep Learning Models of the Retinal Response to Natural Scenes | Lane McIntosh · Niru Maheswaranathan · Aran Nayebi · Surya Ganguli · Stephen Baccus | | | | | | | | | | Poster | Safe and Efficient Off-Policy Reinforcement Learning | Remi Munos · Tom Stepleton · Anna Harutyunyan · Marc Bellemare | | | | | | | | | | Poster | Yggdrasil: An Optimized System for Training Deep Decision Trees at Scale | Firas Abuzaid · Joseph K Bradley · Feynman T Liang · Andrew Feng · Lee Yang · Matei Zaharia · Ameet S Talwalkar | | | | | | | | | | Poster | Sample Complexity of Automated Mechanism Design | Maria-Florina Balcan · Tuomas Sandholm · Ellen Vitercik | | | | | | | | | | Poster | Deep Exploration via Bootstrapped DQN | Ian Osband · Charles Blundell · Alexander Pritzel · Benjamin Van Roy | | | | | | | | | | Poster | Search Improves Label for Active Learning | Alina Beygelzimer · Daniel Hsu · John Langford · Chicheng Zhang | | | | | | | | | | Poster | Efficient and Robust Spiking Neural Circuit for Navigation Inspired by Echolocating Bats | Bipin Rajendran · Pulkit Tandon · Yash H Malviya | | | | | | | | | | Poster | Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning | Gang Niu · Marthinus Christoffel du Plessis · Tomoya Sakai · Yao Ma · Masashi Sugiyama | | | | | | | | | | Poster | Quantized Random Projections and Non-Linear Estimation of Cosine Similarity | Ping Li · Michael Mitzenmacher · Martin Slawski | | | | | | | | | | Poster | CNNpack: Packing Convolutional Neural Networks in the Frequency Domain | Yunhe Wang · Chang Xu · Shan You · Dacheng Tao · Chao Xu | | | | | | | | | | Poster | Verification Based Solution for Structured MAB Problems | Zohar Karnin | | | | | | | | | | Poster | Neurally-Guided Procedural Models: Amortized Inference for Procedural Graphics Programs using Neural Networks | Daniel Ritchie · Anna Thomas · Pat Hanrahan · Noah Goodman | | | | | | | | | | Poster | Edge-exchangeable graphs and sparsity | Diana Cai · Trevor Campbell · Tamara Broderick | | | | | | | | | | Poster | Learning and Forecasting Opinion Dynamics in Social Networks | Abir De · Isabel Valera · Niloy Ganguly · Sourangshu Bhattacharya · Manuel Gomez Rodriguez | | | | | | | | | | Poster | Probing the Compositionality of Intuitive Functions | Eric Schulz · Josh Tenenbaum · David Duvenaud · Maarten Speekenbrink · Samuel J Gershman | | | | | | | | | | Poster | Learning shape correspondence with anisotropic convolutional neural networks | Davide Boscaini · Jonathan Masci · Emanuele Rodolà · Michael Bronstein | | | | | | | | | | Poster | Improved Techniques for Training GANs | Tim Salimans · Ian Goodfellow · Wojciech Zaremba · Vicki Cheung · Alec Radford · Xi Chen · Xi Chen | | | | | | | | | | Poster | Automated scalable segmentation of neurons from multispectral images | Uygar Sümbül · Douglas Roossien · Fei Chen · Dawen Cai · Nicholas Barry · John Cunningham · Liam Paninski · Edward Boyden | | | | | | | | | | Poster | Optimal Cluster Recovery in the Labeled Stochastic Block Model | Se-Young Yun · Alexandre Proutiere | | | | | | | | | | Poster | Phased Exploration with Greedy Exploitation in Stochastic Combinatorial Partial Monitoring Games | Sougata Chaudhuri · Ambuj Tewari | | | | | | | | | | Poster | Dual Space Gradient Descent for Online Learning | Trung Le · Tu Nguyen · Vu Nguyen · Dinh Phung | | | | | | | | | | Poster | Data Programming: Creating Large Training Sets, Quickly | Alexander J Ratner · Christopher M De Sa · Sen Wu · Daniel Selsam · Christopher Ré | | | | | | | | | | Poster | Near-Optimal Smoothing of Structured Conditional Probability Matrices | Moein Falahatgar · Mesrob I Ohannessian · Alon Orlitsky | | | | | | | | | | Poster | An urn model for majority voting in classification ensembles | Victor Soto · Alberto Suárez · Gonzalo Martinez-Muñoz | | | | | | | | | | Invited Talk | Intelligent Biosphere | Drew Purves | | | | | | | | | | Oral | Value Iteration Networks | Aviv Tamar · Sergey Levine · Pieter Abbeel · YI WU · Garrett Thomas | | | | | | | | | | Oral | Graphons, mergeons, and so on! | Justin Eldridge · Mikhail Belkin · Yusu Wang | | | | | | | | | | Oral | Tractable Operations for Arithmetic Circuits of Probabilistic Models | Yujia Shen · Arthur Choi · Adnan Darwiche | | | | | | | | | | Oral | Hierarchical Clustering via Spreading Metrics | Aurko Roy · Sebastian Pokutta | | | | | | | | | | Oral | Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity | Eugene Belilovsky · Gaël Varoquaux · Matthew B Blaschko | | | | | | | | | | Oral | Clustering with Same-Cluster Queries | Hassan Ashtiani · Shrinu Kushagra · Shai Ben-David | | | | | | | | | | Oral | SDP Relaxation with Randomized Rounding for Energy Disaggregation | Kiarash Shaloudegi · András György · Csaba Szepesvari · Wilsun Xu | | | | | | | | | | Oral | Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA | Aapo Hyvarinen · Hiroshi Morioka | | | | | | | | | | Oral | Bayesian Intermittent Demand Forecasting for Large Inventories | Matthias W Seeger · David Salinas · Valentin Flunkert | | | | | | | | | | Oral | Fast and Provably Good Seedings for k-Means | Olivier Bachem · Mario Lucic · Hamed Hassani · Andreas Krause | | | | | | | | | | Oral | Synthesis of MCMC and Belief Propagation | Sung-Soo Ahn · Michael Chertkov · Jinwoo Shin | | | | | | | | | | Invited Talk | Engineering Principles From Stable and Developing Brains | Saket Navlakha | | | | | | | | | | Oral | Deep Learning for Predicting Human Strategic Behavior | Jason S Hartford · James R Wright · Kevin Leyton-Brown | | | | | | | | | | Oral | Supervised learning through the lens of compression | Ofir David · Shay Moran · Amir Yehudayoff | | | | | | | | | | Oral | Using Fast Weights to Attend to the Recent Past | Jimmy Ba · Geoffrey E Hinton · Volodymyr Mnih · Joel Z Leibo · Catalin Ionescu | | | | | | | | | | Oral | MetaGrad: Multiple Learning Rates in Online Learning | Tim van Erven · Wouter M Koolen | | | | | | | | | | Oral | Sequential Neural Models with Stochastic Layers | Marco Fraccaro · Søren Kaae Sønderby · Ulrich Paquet · Ole Winther | | | | | | | | | | Oral | Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning | Jean-Bastien Grill · Michal Valko · Remi Munos | | | | | | | | | | Oral | Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences | Daniel Neil · Michael Pfeiffer · Shih-Chii Liu | | | | | | | | | | Oral | Global Analysis of Expectation Maximization for Mixtures of Two Gaussians | Ji Xu · Daniel Hsu · Adrian Maleki | | | | | | | | | | Demonstration | Deep Reinforcement Learning for Robotics in DIANNE | Steven Bohez · Elias De Coninck · Sam Leroux · Tim Verbelen | | | | | | | | | | Demonstration | Brain-machine interface spelling device based on reinforcement learning | Inaki Iturrate · Ricardo Chavarriaga | | | | | | | | | | Demonstration | Movidius Fathom: Deep Learning in a USB stick | Cormac Brick · Sofiane Yous · Marko Vitez · Ian F Hunter · Jack Dashwood | | | | | | | | | | Demonstration | Real-time interactive sequence generation with Recurrent Neural Network ensembles | Memo Akten | | | | | | | | | | Demonstration | Logically Complex Symbol Grounding for Interactive Robots by Seq2seq Learning with an LSTM-RNN | Tatsuro Yamada · Shingo Murata · Hiroaki Arie · Tetsuya Ogata | | | | | | | | | | Demonstration | Autonomous exploration, active learning and human guidance with open-source Poppy humanoid robot platform and Explauto library | Sébastien Forestier · Yoan Mollard · Pierre-Yves Oudeyer | | | | | | | | | | Demonstration | Content-based Related Video Recommendations | Joonseok Lee | | | | | | | | | | Demonstration | Detecting Unexpected Obstacles for Self-Driving Cars: Fusing Deep Learning and Geometric Modeling | Sebastian Ramos · Peter Pinggera · stefan gehrig · Daimler AG · Carsten Rother | | | | | | | | | | Demonstration | Project Malmo - Minecraft for AI Research | Katja Hofmann · Matthew A Johnson · Fernando Diaz · Alekh Agarwal · Tim Hutton · David Bignell · Evelyne Viegas | | | | | | | | | | Poster | The Multi-fidelity Multi-armed Bandit | Kirthevasan Kandasamy · Gautam Dasarathy · Barnabas Poczos · Jeff Schneider | | | | | | | | | | Poster | Probabilistic Inference with Generating Functions for Poisson Latent Variable Models | Kevin Winner · Daniel Sheldon | | | | | | | | | | Poster | Adaptive Maximization of Pointwise Submodular Functions With Budget Constraint | Nguyen Viet Cuong · Huan Xu | | | | | | | | | | Poster | Dual Learning for Machine Translation | Di He · Yingce Xia · Tao Qin · Liwei Wang · Nenghai Yu · Tieyan Liu · Wei-Ying Ma | | | | | | | | | | Poster | Iterative Refinement of the Approximate Posterior for Directed Belief Networks | Devon Hjelm · Ruslan Salakhutdinov · Kyunghyun Cho · Nebojsa Jojic · Vince Calhoun · Junyoung Chung | | | | | | | | | | Poster | Unsupervised Risk Estimation Using Only Conditional Independence Structure | Jacob Steinhardt · Percy S Liang | | | | | | | | | | Poster | Hierarchical Question-Image Co-Attention for Visual Question Answering | Jiasen Lu · Jianwei Yang · Dhruv Batra · Devi Parikh | | | | | | | | | | Poster | Bayesian Optimization with a Finite Budget: An Approximate Dynamic Programming Approach | Remi Lam · Karen Willcox · David Wolpert | | | | | | | | | | Poster | Learning to learn by gradient descent by gradient descent | Marcin Andrychowicz · Misha Denil · Sergio Gómez · Matthew W Hoffman · David Pfau · Tom Schaul · Nando de Freitas | | | | | | | | | | Poster | Computational and Statistical Tradeoffs in Learning to Rank | Ashish Khetan · Sewoong Oh | | | | | | | | | | Poster | Pairwise Choice Markov Chains | Stephen Ragain · Johan Ugander | | | | | | | | | | Poster | Incremental Variational Sparse Gaussian Process Regression | Ching-An Cheng · Byron Boots | | | | | | | | | | Poster | Combinatorial Multi-Armed Bandit with General Reward Functions | Wei Chen · Wei Hu · Fu Li · Jian Li · Yu Liu · Pinyan Lu | | | | | | | | | | Poster | Observational-Interventional Priors for Dose-Response Learning | Ricardo Silva | | | | | | | | | | Poster | On Graph Reconstruction via Empirical Risk Minimization: Fast Learning Rates and Scalability | Guillaume Papa · Aurélien Bellet · Stephan Clémençon | | | | | | | | | | Poster | DeepMath - Deep Sequence Models for Premise Selection | Geoffrey Irving · Christian Szegedy · Niklas Een · Alexander A Alemi · Francois Chollet · Josef Urban | | | | | | | | | | Poster | Efficient Second Order Online Learning by Sketching | Haipeng Luo · Alekh Agarwal · Nicolò Cesa-Bianchi · John Langford | | | | | | | | | | Poster | Gaussian Processes for Survival Analysis | Tamara Fernandez · Nicolas Rivera · Yee Whye Teh | | | | | | | | | | Poster | The Power of Optimization from Samples | Eric Balkanski · Aviad Rubinstein · Yaron Singer | | | | | | | | | | Poster | Global Optimality of Local Search for Low Rank Matrix Recovery | Srinadh Bhojanapalli · Behnam Neyshabur · Nati Srebro | | | | | | | | | | Poster | A state-space model of cross-region dynamic connectivity in MEG/EEG | Ying Yang · Elissa Aminoff · Michael Tarr · Kass E Robert | | | | | | | | | | Poster | Hypothesis Testing in Unsupervised Domain Adaptation with Applications in Alzheimer's Disease | Hao Zhou · Vamsi K Ithapu · Sathya Narayanan Ravi · Vikas Singh · Grace Wahba · Sterling C Johnson | | | | | | | | | | Poster | Bi-Objective Online Matching and Submodular Allocations | Hossein Esfandiari · Nitish Korula · Vahab Mirrokni | | | | | | | | | | Poster | A Constant-Factor Bi-Criteria Approximation Guarantee for k-means++ | Dennis Wei | | | | | | | | | | Poster | Causal Bandits: Learning Good Interventions via Causal Inference | Finnian Lattimore · Tor Lattimore · Mark Reid | | | | | | | | | | Poster | Unsupervised Domain Adaptation with Residual Transfer Networks | Mingsheng Long · Han Zhu · Jianmin Wang · Michael I Jordan | | | | | | | | | | Poster | Data driven estimation of Laplace-Beltrami operator | Frederic Chazal · Ilaria Giulini · Bertrand Michel | | | | | | | | | | Poster | Fast Algorithms for Robust PCA via Gradient Descent | Xinyang Yi · Dohyung Park · Yudong Chen · Constantine Caramanis | | | | | | | | | | Poster | NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization | Davood Hajinezhad · Mingyi Hong · Tuo Zhao · Zhaoran Wang | | | | | | | | | | Poster | Fundamental Limits of Budget-Fidelity Trade-off in Label Crowdsourcing | Farshad Lahouti · Babak Hassibi | | | | | | | | | | Poster | Supervised Learning with Tensor Networks | Edwin Stoudenmire · David J Schwab | | | | | | | | | | Poster | Understanding Probabilistic Sparse Gaussian Process Approximations | Matthias Bauer · Mark van der Wilk · Carl Edward Rasmussen | | | | | | | | | | Poster | A Locally Adaptive Normal Distribution | Georgios Arvanitidis · Lars K Hansen · Søren Hauberg | | | | | | | | | | Poster | Anchor-Free Correlated Topic Modeling: Identifiability and Algorithm | Kejun Huang · Xiao Fu · Nikolaos D. Sidiropoulos | | | | | | | | | | Poster | Optimal Learning for Multi-pass Stochastic Gradient Methods | Junhong Lin · Lorenzo Rosasco | | | | | | | | | | Poster | Contextual semibandits via supervised learning oracles | Akshay Krishnamurthy · Alekh Agarwal · Miro Dudik | | | | | | | | | | Poster | One-vs-Each Approximation to Softmax for Scalable Estimation of Probabilities | Michalis Titsias RC AUEB | | | | | | | | | | Poster | Satisfying Real-world Goals with Dataset Constraints | Gabriel Goh · Andrew Cotter · Maya Gupta · Michael P Friedlander | | | | | | | | | | Poster | Blind Regression: Nonparametric Regression for Latent Variable Models via Collaborative Filtering | Dogyoon Song · Christina E. Lee · Yihua Li · Devavrat Shah | | | | | | | | | | Poster | Generative Adversarial Imitation Learning | Jonathan Ho · Stefano Ermon | | | | | | | | | | Poster | Fast Active Set Methods for Online Spike Inference from Calcium Imaging | Johannes Friedrich · Liam Paninski | | | | | | | | | | Poster | Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations | Behnam Neyshabur · Yuhuai Wu · Ruslan Salakhutdinov · Nati Srebro | | | | | | | | | | Poster | Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits | Vasilis Syrgkanis · Haipeng Luo · Akshay Krishnamurthy · Robert Schapire | | | | | | | | | | Poster | Diffusion-Convolutional Neural Networks | James Atwood · Don Towsley | | | | | | | | | | Poster | Faster Projection-free Convex Optimization over the Spectrahedron | Dan Garber · Dan Garber | | | | | | | | | | Poster | Structured Matrix Recovery via the Generalized Dantzig Selector | Sheng Chen · Arindam Banerjee | | | | | | | | | | Poster | Convex Two-Layer Modeling with Latent Structure | Vignesh Ganapathiraman · Xinhua Zhang · Yaoliang Yu · Junfeng Wen | | | | | | | | | | Poster | Finite-Sample Analysis of Fixed-k Nearest Neighbor Density Functional Estimators | Shashank Singh · Barnabas Poczos | | | | | | | | | | Poster | Deep Learning Games | Dale Schuurmans · Martin A Zinkevich | | | | | | | | | | Poster | “Congruent” and “Opposite” Neurons: Sisters for Multisensory Integration and Segregation | Wen-Hao Zhang · He Wang · K. Y. Michael Wong · Si Wu | | | | | | | | | | Poster | Statistical Inference for Cluster Trees | Jisu KIM · Yen-Chi Chen · Sivaraman Balakrishnan · Alessandro Rinaldo · Larry Wasserman | | | | | | | | | | Poster | Minimizing Regret on Reflexive Banach Spaces and Nash Equilibria in Continuous Zero-Sum Games | Maximilian Balandat · Walid Krichene · Claire Tomlin · Alexandre Bayen | | | | | | | | | | Poster | An Online Sequence-to-Sequence Model Using Partial Conditioning | Navdeep Jaitly · Quoc V Le · Oriol Vinyals · Ilya Sutskever · David Sussillo · Samy Bengio | | | | | | | | | | Poster | Feature selection in functional data classification with recursive maxima hunting | José L. Torrecilla · Alberto Suárez | | | | | | | | | | Poster | Homotopy Smoothing for Non-Smooth Problems with Lower Complexity than $O(1/\epsilon)$ | Yi Xu · Yan Yan · Qihang Lin · Tianbao Yang | | | | | | | | | | Poster | Nested Mini-Batch K-Means | James Newling · François Fleuret | | | | | | | | | | Poster | Density Estimation via Discrepancy Based Adaptive Sequential Partition | Dangna Li · Kun Yang · Wing Hung Wong | | | | | | | | | | Poster | Budgeted stream-based active learning via adaptive submodular maximization | Kaito Fujii · Hisashi Kashima | | | | | | | | | | Poster | Lifelong Learning with Weighted Majority Votes | Anastasia Pentina · Ruth Urner | | | | | | | | | | Poster | How Deep is the Feature Analysis underlying Rapid Visual Categorization? | Sven Eberhardt · Jonah G Cader · Thomas Serre | | | | | | | | | | Poster | Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition | Shizhong Han · Zibo Meng · AHMED-SHEHAB KHAN · Yan Tong | | | | | | | | | | Poster | Multivariate tests of association based on univariate tests | Ruth Heller · Yair Heller | | | | | | | | | | Poster | SURGE: Surface Regularized Geometry Estimation from a Single Image | Peng Wang · Xiaohui Shen · Bryan Russell · Scott Cohen · Brian Price · Alan L Yuille | | | | | | | | | | Poster | Memory-Efficient Backpropagation Through Time | Audrunas Gruslys · Remi Munos · Ivo Danihelka · Marc Lanctot · Alex Graves | | | | | | | | | | Poster | Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much | Bryan He · Christopher M De Sa · Ioannis Mitliagkas · Christopher Ré | | | | | | | | | | Poster | LightRNN: Memory and Computation-Efficient Recurrent Neural Networks | Xiang Li · Tao Qin · Jian Yang · Xiaolin Hu · Tieyan Liu | | | | | | | | | | Poster | Direct Feedback Alignment Provides Learning in Deep Neural Networks | Arild Nøkland | | | | | | | | | | Poster | Variational Bayes on Monte Carlo Steroids | Aditya Grover · Stefano Ermon | | | | | | | | | | Poster | Agnostic Estimation for Misspecified Phase Retrieval Models | Matey Neykov · Zhaoran Wang · Han Liu | | | | | | | | | | Poster | Following the Leader and Fast Rates in Linear Prediction: Curved Constraint Sets and Other Regularities | Ruitong Huang · Tor Lattimore · András György · Csaba Szepesvari | | | | | | | | | | Poster | Combining Fully Convolutional and Recurrent Neural Networks for 3D Biomedical Image Segmentation | Jianxu Chen · Lin Yang · Yizhe Zhang · Mark Alber · Danny Z Chen | | | | | | | | | | Poster | The Product Cut | Thomas Laurent · James von Brecht · Xavier Bresson · arthur szlam | | | | | | | | | | Poster | Stochastic Gradient Methods for Distributionally Robust Optimization with f-divergences | Hongseok Namkoong · John C Duchi | | | | | | | | | | Poster | Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings | Tolga Bolukbasi · Kai-Wei Chang · James Y Zou · Venkatesh Saligrama · Adam T Kalai | | | | | | | | | | Poster | Optimal spectral transportation with application to music transcription | Rémi Flamary · Cédric Févotte · Nicolas Courty · Valentin Emiya | | | | | | | | | | Poster | Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning | Wouter M Koolen · Peter Grünwald · Tim van Erven | | | | | | | | | | Poster | Towards Conceptual Compression | Karol Gregor · Frederic Besse · Danilo Jimenez Rezende · Ivo Danihelka · Daan Wierstra | | | | | | | | | | Poster | Can Peripheral Representations Improve Clutter Metrics on Complex Scenes? | Arturo Deza · Miguel Eckstein | | | | | | | | | | Poster | GAP Safe Screening Rules for Sparse-Group Lasso | Eugene Ndiaye · Olivier Fercoq · Alexandre Gramfort · Joseph Salmon | | | | | | | | | | Poster | Learning Treewidth-Bounded Bayesian Networks with Thousands of Variables | Mauro Scanagatta · Giorgio Corani · Cassio P de Campos · Marco Zaffalon | | | | | | | | | | Poster | Ancestral Causal Inference | Sara Magliacane · Tom Claassen · Joris M Mooij | | | | | | | | | | Poster | Visual Question Answering with Question Representation Update (QRU) | Ruiyu Li · Jiaya Jia | | | | | | | | | | Poster | Identification and Overidentification of Linear Structural Equation Models | Bryant Chen | | | | | | | | | | Poster | On Valid Optimal Assignment Kernels and Applications to Graph Classification | Nils M. Kriege · Pierre-Louis Giscard · Richard Wilson | | | | | | | | | | Poster | Constraints Based Convex Belief Propagation | Yaniv Tenzer · Alex Schwing · Kevin Gimpel · Tamir Hazan | | | | | | | | | | Poster | Combinatorial Energy Learning for Image Segmentation | Jeremy B Maitin-Shepard · Viren Jain · Michal Januszewski · Peter Li · Pieter Abbeel | | | | | | | | | | Poster | A scalable end-to-end Gaussian process adapter for irregularly sampled time series classification | Steven Cheng-Xian Li · Benjamin M Marlin | | | | | | | | | | Poster | Stochastic Variance Reduction Methods for Saddle-Point Problems | Balamurugan Palaniappan · Francis Bach | | | | | | | | | | Poster | Dimensionality Reduction of Massive Sparse Datasets Using Coresets | Dan Feldman · Mikhail Volkov · Daniela Rus | | | | | | | | | | Poster | Efficient state-space modularization for planning: theory, behavioral and neural signatures | Daniel McNamee · Daniel M Wolpert · Mate Lengyel | | | | | | | | | | Poster | Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy | Aryan Mokhtari · Hadi Daneshmand · Aurelien Lucchi · Thomas Hofmann · Alejandro Ribeiro | | | | | | | | | | Poster | RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism | Edward Choi · Mohammad Taha Bahadori · Joshua Kulas · Jimeng Sun · Andy Schuetz · Walter Stewart | | | | | | | | | | Poster | Joint quantile regression in vector-valued RKHSs | Maxime Sangnier · Olivier Fercoq · Florence d'Alché-Buc | | | | | | | | | | Poster | Learnable Visual Markers | Oleg Grinchuk · Vadim Lebedev · Victor Lempitsky | | | | | | | | | | Poster | Exponential expressivity in deep neural networks through transient chaos | Ben Poole · Subhaneil Lahiri · Maithreyi Raghu · Jascha Sohl-Dickstein · Surya Ganguli | | | | | | | | | | Poster | On Multiplicative Integration with Recurrent Neural Networks | Yuhuai Wu · Saizheng Zhang · Ying Zhang · Yoshua Bengio · Ruslan Salakhutdinov | | | | | | | | | | Poster | Interpretable Nonlinear Dynamic Modeling of Neural Trajectories | Yuan Zhao · Il Memming Park | | | | | | | | | | Poster | Globally Optimal Training of Generalized Polynomial Neural Networks with Nonlinear Spectral Methods | Antoine Gautier · Quynh N Nguyen · Matthias Hein | | | | | | | | | | Poster | Linear Feature Encoding for Reinforcement Learning | Zhao Song · Ronald Parr · Xuejun Liao · Lawrence Carin | | | | | | | | | | Poster | Graphical Time Warping for Joint Alignment of Multiple Curves | Yizhi Wang · David J Miller · Kira Poskanzer · Yue Wang · Lin Tian · Guoqiang Yu | | | | | | | | | | Poster | Mixed Linear Regression with Multiple Components | Kai Zhong · Prateek Jain · Inderjit S Dhillon | | | | | | | | | | Poster | Statistical Inference for Pairwise Graphical Models Using Score Matching | Ming Yu · Mladen Kolar · Varun Gupta | | | | | | | | | | Poster | Hardness of Online Sleeping Combinatorial Optimization Problems | Satyen Kale · Chansoo Lee · David Pal | | | | | | | | | | Poster | An algorithm for L1 nearest neighbor search via monotonic embedding | Xinan Wang · Sanjoy Dasgupta | | | | | | | | | | Poster | Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences | Chi Jin · Yuchen Zhang · Sivaraman Balakrishnan · Martin J Wainwright · Michael I Jordan | | | | | | | | | | Poster | Learning User Perceived Clusters with Feature-Level Supervision | Ting-Yu Cheng · Guiguan Lin · xinyang gong · Kang-Jun Liu · Shan-Hung Wu | | | | | | | | | | Poster | InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets | Xi Chen · Xi Chen · Yan Duan · Rein Houthooft · John Schulman · Ilya Sutskever · Pieter Abbeel | | | | | | | | | | Poster | Neural Universal Discrete Denoiser | Taesup Moon · Seonwoo Min · Byunghan Lee · Sungroh Yoon | | | | | | | | | | Poster | A primal-dual method for conic constrained distributed optimization problems | Necdet Serhat Aybat · Erfan Yazdandoost Hamedani | | | | | | | | | | Poster | Simple and Efficient Weighted Minwise Hashing | Anshumali Shrivastava | | | | | | | | | | Poster | Eliciting Categorical Data for Optimal Aggregation | Chien-Ju Ho · Rafael Frongillo · Yiling Chen | | | | | | | | | | Poster | Depth from a Single Image by Harmonizing Overcomplete Local Network Predictions | Ayan Chakrabarti · Jingyu Shao · Greg Shakhnarovich | | | | | | | | | | Poster | SEBOOST - Boosting Stochastic Learning Using Subspace Optimization Techniques | Elad Richardson · Rom Herskovitz · Boris Ginsburg · Michael Zibulevsky | | | | | | | | | | Poster | Reshaped Wirtinger Flow for Solving Quadratic System of Equations | Huishuai Zhang · Yingbin Liang | | | | | | | | | | Poster | Training and Evaluating Multimodal Word Embeddings with Large-scale Web Annotated Images | Junhua Mao · Jiajing Xu · Kevin Jing · Alan L Yuille | | | | | | | | | | Poster | Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes | Chris Junchi Li · Zhaoran Wang · Han Liu | | | | | | | | | | Poster | VIME: Variational Information Maximizing Exploration | Rein Houthooft · Xi Chen · Xi Chen · Yan Duan · John Schulman · Filip De Turck · Pieter Abbeel | | | | | | | | | | Poster | Deconvolving Feedback Loops in Recommender Systems | Ayan Sinha · David Gleich · Karthik Ramani | | | | | | | | | | Poster | A Non-parametric Learning Method for Confidently Estimating Patient's Clinical State and Dynamics | William Hoiles · Mihaela Van Der Schaar | | | | | | | | | | Poster | Semiparametric Differential Graph Models | Pan Xu · Quanquan Gu | | | | | | | | | | Poster | A Non-convex One-Pass Framework for Generalized Factorization Machine and Rank-One Matrix Sensing | Ming Lin · Jieping Ye | | | | | | | | | | Poster | Sublinear Time Orthogonal Tensor Decomposition | Zhao Song · David Woodruff · Huan Zhang | | | | | | | | | | Poster | Achieving budget-optimality with adaptive schemes in crowdsourcing | Ashish Khetan · Sewoong Oh | | | | | | | | | | Poster | Joint Line Segmentation and Transcription for End-to-End Handwritten Paragraph Recognition | Theodore Bluche | | | | | | | | | | Poster | Human Decision-Making under Limited Time | Pedro A Ortega · Alan A Stocker | | | | | | | | | | Poster | Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization | Alexander Kirillov · Alexander Shekhovtsov · Carsten Rother · Bogdan Savchynskyy | | | | | | | | | | Poster | Even Faster SVD Decomposition Yet Without Agonizing Pain | Zeyuan Allen-Zhu · Yuanzhi Li | | | | | | | | | | Poster | Fast and accurate spike sorting of high-channel count probes with KiloSort | Marius Pachitariu · Nicholas A Steinmetz · Shabnam N Kadir · Matteo Carandini · Kenneth D Harris | | | | | | | | | | Poster | Batched Gaussian Process Bandit Optimization via Determinantal Point Processes | Tarun Kathuria · Amit Deshpande · Pushmeet Kohli | | | | | | | | | | Poster | Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles | Stefan Lee · Senthil Purushwalkam Shiva Prakash · Michael Cogswell · Viresh Ranjan · David Crandall · Dhruv Batra | | | | | | | | | | Poster | Optimal Sparse Linear Encoders and Sparse PCA | Malik Magdon-Ismail · Christos Boutsidis | | | | | | | | | | Poster | Using Social Dynamics to Make Individual Predictions: Variational Inference with a Stochastic Kinetic Model | Zhen Xu · Wen Dong · Sargur N Srihari | | | | | | | | | | Poster | Learning Additive Exponential Family Graphical Models via $\ell{2,1}$-norm Regularized M-Estimation | Xiaotong Yuan · Ping Li · Tong Zhang · Qingshan Liu · Guangcan Liu | | | | | | | | | | Poster | Residual Networks Behave Like Ensembles of Relatively Shallow Networks | Andreas Veit · Michael J Wilber · Serge Belongie | | | | | | | | | | Poster | Full-Capacity Unitary Recurrent Neural Networks | Scott Wisdom · Thomas Powers · John Hershey · Jonathan Le Roux · Les Atlas | | | | | | | | | | Poster | Quantum Perceptron Models | Ashish Kapoor · Nathan Wiebe · Krysta Svore | | | | | | | | | | Poster | Mapping Estimation for Discrete Optimal Transport | Michaël Perrot · Nicolas Courty · Rémi Flamary · Amaury Habrard | | | | | | | | | | Poster | Stochastic Gradient Geodesic MCMC Methods | Chang Liu · Jun Zhu · Yang Song | | | | | | | | | | Poster | Variational Information Maximization for Feature Selection | Shuyang Gao · Greg Ver Steeg · Aram Galstyan | | | | | | | | | | Poster | A Minimax Approach to Supervised Learning | Farzan Farnia · David Tse | | | | | | | | | | Poster | Fast Distributed Submodular Cover: Public-Private Data Summarization | Baharan Mirzasoleiman · Morteza Zadimoghaddam · Amin Karbasi | | | | | | | | | | Poster | Domain Separation Networks | Konstantinos Bousmalis · George Trigeorgis · Nathan Silberman · Dilip Krishnan · Dumitru Erhan | | | | | | | | | | Poster | Multimodal Residual Learning for Visual QA | Jin-Hwa Kim · Sang-Woo Lee · Donghyun Kwak · Min-Oh Heo · Jeonghee Kim · Jung-Woo Ha · Byoung-Tak Zhang | | | | | | | | | | Poster | Optimizing affinity-based binary hashing using auxiliary coordinates | Ramin Raziperchikolaei · Miguel A. Carreira-Perpinan | | | | | | | | | | Poster | Coresets for Scalable Bayesian Logistic Regression | Jonathan Huggins · Trevor Campbell · Tamara Broderick | | | | | | | | | | Poster | The Parallel Knowledge Gradient Method for Batch Bayesian Optimization | Jian Wu · Peter Frazier | | | | | | | | | | Poster | Learning Multiagent Communication with Backpropagation | Sainbayar Sukhbaatar · arthur szlam · Rob Fergus | | | | | | | | | | Poster | Optimal Binary Classifier Aggregation for General Losses | Akshay Balsubramani · Yoav S Freund | | | | | | | | | | Poster | The Generalized Reparameterization Gradient | Francisco R Ruiz · Michalis Titsias RC AUEB · David Blei | | | | | | | | | | Poster | Conditional Generative Moment-Matching Networks | Yong Ren · Jun Zhu · Jialian Li · Yucen Luo | | | | | | | | | | Poster | A Credit Assignment Compiler for Joint Prediction | Kai-Wei Chang · He He · Stephane Ross · Hal Daume III · John Langford | | | | | | | | | | Poster | Short-Dot: Computing Large Linear Transforms Distributedly Using Coded Short Dot Products | Sanghamitra Dutta · Viveck Cadambe · Pulkit Grover | | | | | | | | | | Poster | Spatio-Temporal Hilbert Maps for Continuous Occupancy Representation in Dynamic Environments | Ransalu Senanayake · Lionel Ott · Simon O'Callaghan · Fabio Ramos | | | | | | | | | | Poster | Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices | Kirthevasan Kandasamy · Maruan Al-Shedivat · Eric P Xing | | | | | | | | | | Poster | Integrated perception with recurrent multi-task neural networks | Hakan Bilen · Andrea Vedaldi | | | | | | | | | | Poster | Blind Attacks on Machine Learners | Alex Beatson · Zhaoran Wang · Han Liu | | | | | | | | | | Poster | Optimistic Gittins Indices | Eli Gutin · Vivek Farias | | | | | | | | | | Poster | Sub-sampled Newton Methods with Non-uniform Sampling | Peng Xu · Jiyan Yang · Farbod Roosta-Khorasani · Christopher Ré · Michael W Mahoney | | | | | | | | | | Poster | Learned Region Sparsity and Diversity Also Predicts Visual Attention | Zijun Wei · Hossein Adeli · Minh Hoai · Greg Zelinsky · Dimitris Samaras | | | | | | | | | | Poster | Adaptive Concentration Inequalities for Sequential Decision Problems | Shengjia Zhao · Enze Zhou · Ashish Sabharwal · Stefano Ermon | | | | | | | | | | Poster | Cooperative Graphical Models | Josip Djolonga · Stefanie Jegelka · Sebastian Tschiatschek · Andreas Krause | | | | | | | | | | Poster | Correlated-PCA: Principal Components' Analysis when Data and Noise are Correlated | Namrata Vaswani · Han Guo | | | | | | | | | | Poster | Hierarchical Object Representation for Open-Ended Object Category Learning and Recognition | Seyed Hamidreza Kasaei · Ana Maria Tomé · Luís Seabra Lopes | | | | | | | | | | Poster | Optimal Tagging with Markov Chain Optimization | Nir Rosenfeld · Amir Globerson | | | | | | | | | | Poster | Bayesian optimization for automated model selection | Gustavo Malkomes · Charles Schaff · Roman Garnett | | | | | | | | | | Poster | Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models | Tomoharu Iwata · Makoto Yamada | | | | | | | | | | Poster | Inference by Reparameterization in Neural Population Codes | Rajkumar Vasudeva Raju · Xaq Pitkow | | | | | | | | | | Poster | Efficient Neural Codes under Metabolic Constraints | Zhuo Wang · Xue-Xin Wei · Alan A Stocker · Daniel D Lee | | | | | | | | | | Poster | Learning Deep Parsimonious Representations | Renjie Liao · Alex Schwing · Richard Zemel · Raquel Urtasun | | | | | | | | | | Poster | An equivalence between high dimensional Bayes optimal inference and M-estimation | Madhu Advani · Surya Ganguli | | | | | | | | | | Poster | Minimizing Quadratic Functions in Constant Time | Kohei Hayashi · Yuichi Yoshida | | | | | | | | | | Poster | Learning Structured Sparsity in Deep Neural Networks | Wei Wen · Chunpeng Wu · Yandan Wang · Yiran Chen · Hai Li | | | | | | | | | | Poster | Adversarial Multiclass Classification: A Risk Minimization Perspective | Rizal Fathony · Anqi Liu · Kaiser Asif · Brian Ziebart | | | | | | | | | | Poster | Unified Methods for Exploiting Piecewise Linear Structure in Convex Optimization | Tyler B Johnson · Carlos Guestrin | | | | | | | | | | Poster | Fast and Provably Good Seedings for k-Means | Olivier Bachem · Mario Lucic · Hamed Hassani · Andreas Krause | | | | | | | | | | Poster | Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity | Eugene Belilovsky · Gaël Varoquaux · Matthew B Blaschko | | | | | | | | | | Poster | Synthesis of MCMC and Belief Propagation | Sung-Soo Ahn · Michael Chertkov · Jinwoo Shin | | | | | | | | | | Poster | Value Iteration Networks | Aviv Tamar · Sergey Levine · Pieter Abbeel · YI WU · Garrett Thomas | | | | | | | | | | Poster | Sequential Neural Models with Stochastic Layers | Marco Fraccaro · Søren Kaae Sønderby · Ulrich Paquet · Ole Winther | | | | | | | | | | Poster | Graphons, mergeons, and so on! | Justin Eldridge · Mikhail Belkin · Yusu Wang | | | | | | | | | | Poster | Hierarchical Clustering via Spreading Metrics | Aurko Roy · Sebastian Pokutta | | | | | | | | | | Poster | Deep Learning for Predicting Human Strategic Behavior | Jason S Hartford · James R Wright · Kevin Leyton-Brown | | | | | | | | | | Poster | Global Analysis of Expectation Maximization for Mixtures of Two Gaussians | Ji Xu · Daniel Hsu · Adrian Maleki | | | | | | | | | | Poster | Supervised learning through the lens of compression | Ofir David · Shay Moran · Amir Yehudayoff | | | | | | | | | | Poster | Matrix Completion has No Spurious Local Minimum | Rong Ge · Jason Lee · Tengyu Ma | | | | | | | | | | Poster | Clustering with Same-Cluster Queries | Hassan Ashtiani · Shrinu Kushagra · Shai Ben-David | | | | | | | | | | Poster | MetaGrad: Multiple Learning Rates in Online Learning | Tim van Erven · Wouter M Koolen | | | | | | | | | | Poster | Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA | Aapo Hyvarinen · Hiroshi Morioka | | | | | | | | | | Poster | Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences | Daniel Neil · Michael Pfeiffer · Shih-Chii Liu | | | | | | | | | | Poster | Tractable Operations for Arithmetic Circuits of Probabilistic Models | Yujia Shen · Arthur Choi · Adnan Darwiche | | | | | | | | | | Poster | Using Fast Weights to Attend to the Recent Past | Jimmy Ba · Geoffrey E Hinton · Volodymyr Mnih · Joel Z Leibo · Catalin Ionescu | | | | | | | | | | Poster | Bayesian Intermittent Demand Forecasting for Large Inventories | Matthias W Seeger · David Salinas · Valentin Flunkert | | | | | | | | | | Poster | Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning | Jean-Bastien Grill · Michal Valko · Remi Munos | | | | | | | | | | Poster | SDP Relaxation with Randomized Rounding for Energy Disaggregation | Kiarash Shaloudegi · András György · Csaba Szepesvari · Wilsun Xu | | | | | | | | | | Invited Talk | Machine Learning and Likelihood-Free Inference in Particle Physics | Kyle Cranmer | | | | | | | | | | Oral | Matrix Completion has No Spurious Local Minimum | Rong Ge · Jason Lee · Tengyu Ma | | | | | | | | | | Oral | Achieving the KS threshold in the general stochastic block model with linearized acyclic belief propagation | Emmanuel Abbe · Colin Sandon | | | | | | | | | | Oral | Large-Scale Price Optimization via Network Flow | Shinji Ito · Ryohei Fujimaki | | | | | | | | | | Oral | Orthogonal Random Features | Felix X Yu · Ananda Theertha Suresh · Krzysztof M Choromanski · Daniel N Holtmann-Rice · Sanjiv Kumar | | | | | | | | | | Oral | Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks | Tianfan Xue · Jiajun Wu · Katherine Bouman · Bill Freeman | | | | | | | | | | Oral | Poisson-Gamma dynamical systems | Aaron Schein · Hanna Wallach · Mingyuan Zhou | | | | | | | | | | Oral | Supervised Word Mover's Distance | Gao Huang · Chuan Guo · Matt J Kusner · Yu Sun · Fei Sha · Kilian Q Weinberger | | | | | | | | | | Oral | The Multiscale Laplacian Graph Kernel | Risi Kondor · Horace Pan | | | | | | | | | | Oral | Beyond Exchangeability: The Chinese Voting Process | Moontae Lee · Seok Hyun Jin · David Mimno | | | | | | | | | | Oral | Stochastic Online AUC Maximization | Yiming Ying · Longyin Wen · Siwei Lyu | | | | | | | | | | Oral | Protein contact prediction from amino acid co-evolution using convolutional networks for graph-valued images | Vladimir Golkov · Marcin J Skwark · Antonij Golkov · Alexey Dosovitskiy · Thomas Brox · Jens Meiler · Daniel Cremers | |.