NeurIPS 2017

679 papers

Convergence of Gradient EM on Multi-component Mixture of Gaussians

Bowei Yan, Mingzhang Yin, Purnamrita Sarkar

MMD GAN: Towards Deeper Understanding of Moment Matching Network

Chun-Liang Li, Wei-Cheng Chang, Yu Cheng, Yiming Yang, Barnabás Póczos

Differentially private Bayesian learning on distributed data

Mikko Heikkilä, Eemil Lagerspetz, Samuel Kaski, Kana Shimizu, Sasu Tarkoma

Multi-Information Source Optimization

Matthias Poloczek, Jialei Wang, Peter Frazier

Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search

Luigi Acerbi, Wei Ji Ma

Tractability in Structured Probability Spaces

Arthur Choi, Yujia Shen, Adnan Darwiche

Multi-output Polynomial Networks and Factorization Machines

Mathieu Blondel, Vlad Niculae, Takuma Otsuka, Naonori Ueda

Efficient Approximation Algorithms for Strings Kernel Based Sequence Classification

Muhammad Farhan, Juvaria Tariq, Arif Zaman, Mudassir Shabbir, Imdad Ullah Khan

A Dirichlet Mixture Model of Hawkes Processes for Event Sequence Clustering

Hongteng Xu, Hongyuan Zha

Discovering Potential Correlations via Hypercontractivity

Hyeji Kim, Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath

Identifying Outlier Arms in Multi-Armed Bandit

Honglei Zhuang, Chi Wang, Yifan Wang

Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe

Quentin Berthet, Vianney Perchet

SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability

Maithra Raghu, Justin Gilmer, Jason Yosinski, Jascha Sohl-dickstein

Unsupervised Image-to-Image Translation Networks

Ming-Yu Liu, Thomas Breuel, Jan Kautz

DropoutNet: Addressing Cold Start in Recommender Systems

Maksims Volkovs, Guangwei Yu, Tomi Poutanen

Subspace Clustering via Tangent Cones

Amin Jalali, Rebecca Willett

Maxing and Ranking with Few Assumptions

Moein Falahatgar, Yi Hao, Alon Orlitsky, Venkatadheeraj Pichapati, Vaishakh Ravindrakumar

Compression-aware Training of Deep Networks

Mathieu Salzmann, Jose M. Alvarez, Jose M Alvarez

Clustering with Noisy Queries

Arya Mazumdar, Barna Saha

Structured Bayesian Pruning via Log-Normal Multiplicative Noise

Kirill Neklyudov, Dmitry Molchanov, Arsenii Ashukha, Dmitry P Vetrov

Online Convex Optimization with Stochastic Constraints

Hao Yu, Michael Neely, Xiaohan Wei

Adaptive Classification for Prediction Under a Budget

Feng Nan, Venkatesh Saligrama

Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice

Jeffrey Pennington, Samuel Schoenholz, Surya Ganguli

Learning Combinatorial Optimization Algorithms over Graphs

Elias Khalil, Hanjun Dai, Yuyu Zhang, Bistra Dilkina, Le Song

Thinking Fast and Slow with Deep Learning and Tree Search

Thomas Anthony, Zheng Tian, David Barber

Approximation Bounds for Hierarchical Clustering: Average Linkage, Bisecting K-means, and Local Search

Benjamin Moseley, Joshua Wang

PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Charles Ruizhongtai Qi, Li Yi, Hao Su, Leonidas Guibas

Subset Selection under Noise

Chao Qian, Jing-Cheng Shi, Yang Yu, Ke Tang, Zhi-Hua Zhou

Deep Reinforcement Learning from Human Preferences

Paul F Christiano, Jan Leike, Tom Brown, Miljan Martic, Shane Legg

Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin

Ritambhara Singh, Jack Lanchantin, Arshdeep Sekhon, Yanjun Qi

Clustering Stable Instances of Euclidean k-means.

Aravindan Vijayaraghavan, Abhratanu Dutta, Alex Wang

Houdini: Fooling Deep Structured Visual and Speech Recognition Models with Adversarial Examples

Moustapha M Cisse, Yossi Adi, Natalia Neverova, Joseph Keshet

Semi-supervised Learning with GANs: Manifold Invariance with Improved Inference

Abhishek Kumar, Prasanna Sattigeri, Tom Fletcher

Welfare Guarantees from Data

Darrell Hoy, Denis Nekipelov, Vasilis Syrgkanis

Expectation Propagation with Stochastic Kinetic Model in Complex Interaction Systems

Le Fang, Fan Yang, Wen Dong, Tong Guan, Chunming Qiao

Hunt For The Unique, Stable, Sparse And Fast Feature Learning On Graphs

Saurabh Verma, Zhi-Li Zhang

Neural Expectation Maximization

Klaus Greff, Sjoerd van Steenkiste, Jürgen Schmidhuber

Graph Matching via Multiplicative Update Algorithm

Bo Jiang, Jin Tang, Chris Ding, Yihong Gong, Bin Luo

Large-Scale Quadratically Constrained Quadratic Program via Low-Discrepancy Sequences

Kinjal Basu, Ankan Saha, Shaunak Chatterjee

AdaGAN: Boosting Generative Models

Ilya O Tolstikhin, Sylvain Gelly, Olivier Bousquet, Carl-Johann Simon-Gabriel, Bernhard Schölkopf

Improved Dynamic Regret for Non-degenerate Functions

Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou

Influence Maximization with ε-Almost Submodular Threshold Functions

Qiang Li, Wei Chen, Institute of Computing Xiaoming Sun, Institute of Computing Jialin Zhang

Inferring Generative Model Structure with Static Analysis

Paroma Varma, Bryan D He, Payal Bajaj, Nishith Khandwala, Imon Banerjee

Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network

Wengong Jin, Connor Coley, Regina Barzilay, Tommi Jaakkola

Online to Offline Conversions, Universality and Adaptive Minibatch Sizes

Kfir Levy

PRUNE: Preserving Proximity and Global Ranking for Network Embedding

Yi-An Lai, Chin-Chi Hsu, Wen Hao Chen, Mi-Yen Yeh, Shou-De Lin

Random Permutation Online Isotonic Regression

Wojciech Kotlowski, Wouter M. Koolen, Alan Malek

Unified representation of tractography and diffusion-weighted MRI data using sparse multidimensional arrays

Cesar F. Caiafa, Olaf Sporns, Andrew Saykin, Franco Pestilli

Unsupervised learning of object frames by dense equivariant image labelling

James Thewlis, Hakan Bilen, Andrea Vedaldi

Prototypical Networks for Few-shot Learning

Jake Snell, Kevin Swersky, Richard Zemel

Dynamic Revenue Sharing

Santiago Balseiro, Max Lin, Vahab Mirrokni, Renato Leme, IIIS Song Zuo

Random Projection Filter Bank for Time Series Data

Amir-massoud Farahmand, Sepideh Pourazarm, Daniel Nikovski

Fitting Low-Rank Tensors in Constant Time

Kohei Hayashi, Yuichi Yoshida

On-the-fly Operation Batching in Dynamic Computation Graphs

Graham Neubig, Yoav Goldberg, Chris Dyer

Self-Supervised Intrinsic Image Decomposition

Michael Janner, Jiajun Wu, Tejas D Kulkarni, Ilker Yildirim, Josh Tenenbaum

Adversarial Surrogate Losses for Ordinal Regression

Rizal Fathony, Mohammad Ali Bashiri, Brian Ziebart

A graph-theoretic approach to multitasking

Noga Alon, Daniel Reichman, Igor Shinkar, Tal Wagner, Sebastian Musslick

Minimizing a Submodular Function from Samples

Eric Balkanski, Yaron Singer

Extracting low-dimensional dynamics from multiple large-scale neural population recordings by learning to predict correlations

Marcel Nonnenmacher, Srinivas C. Turaga, Jakob H. Macke, Jakob H Macke

Non-Stationary Spectral Kernels

Sami Remes, Markus Heinonen, Samuel Kaski

Do Deep Neural Networks Suffer from Crowding?

Anna Volokitin, Gemma Roig, Tomaso A Poggio

Deliberation Networks: Sequence Generation Beyond One-Pass Decoding

Yingce Xia, Fei Tian, Lijun Wu, Jianxin Lin, Tao Qin

Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon

Xin Dong, Shangyu Chen, Sinno Pan

Eigen-Distortions of Hierarchical Representations

Alexander Berardino, Valero Laparra, Johannes Ballé, Eero Simoncelli

Deep Voice 2: Multi-Speaker Neural Text-to-Speech

Andrew Gibiansky, Sercan Arik, Gregory Diamos, John Miller, Kainan Peng

Position-based Multiple-play Bandit Problem with Unknown Position Bias

Junpei Komiyama, Junya Honda, Akiko Takeda

Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models

Sergey Ioffe

Near Optimal Sketching of Low-Rank Tensor Regression

Xingguo Li, Jarvis Haupt, David Woodruff

A New Alternating Direction Method for Linear Programming

Sinong Wang, Ness Shroff

Hierarchical Methods of Moments

Matteo Ruffini, Guillaume Rabusseau, Borja Balle

Fast, Sample-Efficient Algorithms for Structured Phase Retrieval

Gauri Jagatap, Chinmay Hegde

Dynamic-Depth Context Tree Weighting

Shimon Whiteson, João V. Messias, Joao V Messias

Structured Generative Adversarial Networks

Zhijie Deng, Hao Zhang, Xiaodan Liang, Luona Yang, Shizhen Xu

Linear regression without correspondence

Daniel J. Hsu, Kevin Shi, Xiaorui Sun

Stochastic Approximation for Canonical Correlation Analysis

Raman Arora, Teodor Vanislavov Marinov, Poorya Mianjy, Nati Srebro

Stochastic Submodular Maximization: The Case of Coverage Functions

Mohammad Karimi, Mario Lucic, Hamed Hassani, Andreas Krause

Policy Gradient With Value Function Approximation For Collective Multiagent Planning

Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau

Multi-view Matrix Factorization for Linear Dynamical System Estimation

Mahdi Karami, Martha White, Dale Schuurmans, Csaba Szepesvári

Gated Recurrent Convolution Neural Network for OCR

Jianfeng Wang, Xiaolin Hu

Learning Affinity via Spatial Propagation Networks

Sifei Liu, Shalini De Mello, Jinwei Gu, Guangyu Zhong, Ming-Hsuan Yang

Decomposable Submodular Function Minimization: Discrete and Continuous

Alina Ene, Huy Nguyen, László A. Végh

Streaming Weak Submodularity: Interpreting Neural Networks on the Fly

Ethan Elenberg, Alexandros G Dimakis, Moran Feldman, Amin Karbasi

Q-LDA: Uncovering Latent Patterns in Text-based Sequential Decision Processes

Jianshu Chen, Chong Wang, Lin Xiao, Ji He, Lihong Li

A KL-LUCB algorithm for Large-Scale Crowdsourcing

Ervin Tanczos, Robert Nowak, Bob Mankoff

The Unreasonable Effectiveness of Structured Random Orthogonal Embeddings

Krzysztof M Choromanski, Mark Rowland, Adrian Weller

Integration Methods and Optimization Algorithms

Damien Scieur, Vincent Roulet, Francis Bach, Alexandre D'aspremont

Diving into the shallows: a computational perspective on large-scale shallow learning

SIYUAN MA, Mikhail Belkin

Adversarial Ranking for Language Generation

Kevin Lin, Dianqi Li, Xiaodong He, Zhengyou Zhang, Ming-ting Sun

Regularized Modal Regression with Applications in Cognitive Impairment Prediction

Xiaoqian Wang, Hong Chen, Weidong Cai, Dinggang Shen, Heng Huang

Conservative Contextual Linear Bandits

Abbas Kazerouni, Mohammad Ghavamzadeh, Yasin Abbasi Yadkori, Benjamin Van Roy

Structured Embedding Models for Grouped Data

Maja Rudolph, Francisco Ruiz, Susan Athey, David Blei

Multi-Armed Bandits with Metric Movement Costs

Tomer Koren, Roi Livni, Yishay Mansour

Learning Populations of Parameters

Kevin Tian, Weihao Kong, Gregory Valiant

Triangle Generative Adversarial Networks

Zhe Gan, Liqun Chen, Weiyao Wang, Yuchen Pu, Yizhe Zhang

One-Shot Imitation Learning

Yan Duan, Marcin Andrychowicz, Bradly Stadie, OpenAI Jonathan Ho, Jonas Schneider

On Fairness and Calibration

Geoff Pleiss, Manish Raghavan, Felix Wu, Jon Kleinberg, Kilian Q. Weinberger

Active Learning from Peers

Keerthiram Murugesan, Jaime Carbonell

Kernel Feature Selection via Conditional Covariance Minimization

Jianbo Chen, Mitchell Stern, Martin J. Wainwright, Michael I. Jordan, Michael I Jordan

Perturbative Black Box Variational Inference

Robert Bamler, Cheng Zhang, Manfred Opper, Stephan Mandt

Bregman Divergence for Stochastic Variance Reduction: Saddle-Point and Adversarial Prediction

Zhan Shi, Xinhua Zhang, Yaoliang Yu