NeurIPS 2018

1,009 papers

Searching for Efficient Multi-Scale Architectures for Dense Image Prediction

Liang-Chieh Chen, Maxwell Collins, Yukun Zhu, George Papandreou, Barret Zoph

Geometry Based Data Generation

Ofir Lindenbaum, Jay Stanley, Guy Wolf, Smita Krishnaswamy

Fairness Through Computationally-Bounded Awareness

Michael Kim, Omer Reingold, Guy Rothblum

Group Equivariant Capsule Networks

Jan Eric Lenssen, Matthias Fey, Pascal Libuschewski

Unsupervised Image-to-Image Translation Using Domain-Specific Variational Information Bound

Hadi Kazemi, Sobhan Soleymani, Fariborz Taherkhani, Seyed Iranmanesh, Nasser Nasrabadi

M-Walk: Learning to Walk over Graphs using Monte Carlo Tree Search

Yelong Shen, Jianshu Chen, Po-Sen Huang, Yuqing Guo, Jianfeng Gao

Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal Distributions using Simulated Tempering Langevin Monte Carlo

Holden Lee, Andrej Risteski, Rong Ge

Context-aware Synthesis and Placement of Object Instances

Donghoon Lee, Sifei Liu, Jinwei Gu, Ming-Yu Liu, Ming-Hsuan Yang

Community Exploration: From Offline Optimization to Online Learning

Xiaowei Chen, Weiran Huang, Wei Chen, John C.S. Lui, John C. S. Lui

Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives

Amit Dhurandhar, Pin-Yu Chen, Ronny Luss, Chun-Chen Tu, Paishun Ting

Deep Homogeneous Mixture Models: Representation, Separation, and Approximation

Priyank Jaini, Pascal Poupart, Yaoliang Yu

Graphical Generative Adversarial Networks

Chongxuan Li, Max Welling, Jun Zhu, Bo Zhang

Estimators for Multivariate Information Measures in General Probability Spaces

Arman Rahimzamani, Himanshu Asnani, Pramod Viswanath, Sreeram Kannan

FD-GAN: Pose-guided Feature Distilling GAN for Robust Person Re-identification

Yixiao Ge, Zhuowan Li, Haiyu Zhao, Guojun Yin, Shuai Yi

Submodular Field Grammars: Representation, Inference, and Application to Image Parsing

Abram L. Friesen, Pedro M Domingos

Cooperative Learning of Audio and Video Models from Self-Supervised Synchronization

Bruno Korbar, Du Tran, Lorenzo Torresani

Sublinear Time Low-Rank Approximation of Distance Matrices

Ainesh Bakshi, David Woodruff

Blockwise Parallel Decoding for Deep Autoregressive Models

Mitchell Stern, Noam Shazeer, Jakob Uszkoreit

Sample Efficient Stochastic Gradient Iterative Hard Thresholding Method for Stochastic Sparse Linear Regression with Limited Attribute Observation

Tomoya Murata, Taiji Suzuki

Global Geometry of Multichannel Sparse Blind Deconvolution on the Sphere

Yanjun Li, Yoram Bresler

Trading robust representations for sample complexity through self-supervised visual experience

Andrea Tacchetti, Stephen Voinea, Georgios Evangelopoulos

Deep Attentive Tracking via Reciprocative Learning

Shi Pu, Yibing Song, Chao Ma, Honggang Zhang, Ming-Hsuan Yang

Scaling Gaussian Process Regression with Derivatives

David Eriksson, Kun Dong, Eric Lee, David Bindel, Andrew G Wilson

Distributed Multi-Player Bandits - a Game of Thrones Approach

Ilai Bistritz, Amir Leshem

Out of the Box: Reasoning with Graph Convolution Nets for Factual Visual Question Answering

Medhini Narasimhan, Svetlana Lazebnik, Alexander Schwing

DifNet: Semantic Segmentation by Diffusion Networks

Peng Jiang, Fanglin Gu, Yunhai Wang, Changhe Tu, Baoquan Chen

Revisiting Decomposable Submodular Function Minimization with Incidence Relations

Pan Li, Olgica Milenkovic

Long short-term memory and Learning-to-learn in networks of spiking neurons

Guillaume Bellec, Darjan Salaj, Anand Subramoney, Robert Legenstein, Wolfgang Maass

Realistic Evaluation of Deep Semi-Supervised Learning Algorithms

Avital Oliver, Augustus Odena, Colin A Raffel, Ekin Dogus Cubuk, Ian Goodfellow

Online Learning of Quantum States

Scott Aaronson, Xinyi Chen, Elad Hazan, Satyen Kale, Ashwin Nayak

Ex ante coordination and collusion in zero-sum multi-player extensive-form games

Gabriele Farina, Andrea Celli, Nicola Gatti, Tuomas Sandholm

Scalar Posterior Sampling with Applications

Georgios Theocharous, Zheng Wen, Yasin Abbasi Yadkori, Nikos Vlassis

Structural Causal Bandits: Where to Intervene?

Sanghack Lee, Elias Bareinboim

Training deep learning based denoisers without ground truth data

Shakarim Soltanayev, Se Young Chun

Self-Erasing Network for Integral Object Attention

Qibin Hou, PengTao Jiang, Yunchao Wei, Ming-Ming Cheng

Wavelet regression and additive models for irregularly spaced data

Asad Haris, Ali Shojaie, Noah Simon

Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners

Yuxin Chen, Adish Singla, Oisin Mac Aodha, Pietro Perona, Yisong Yue

Can We Gain More from Orthogonality Regularizations in Training Deep Networks?

Nitin Bansal, Xiaohan Chen, Zhangyang Wang

Lifted Weighted Mini-Bucket

Nicholas Gallo, Alex Ihler

A Unified View of Piecewise Linear Neural Network Verification

Rudy R Bunel, Ilker Turkaslan, Philip Torr, Pushmeet Kohli, Pawan K Mudigonda

Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making

Hoda Heidari, Claudio Ferrari, Krishna Gummadi, Andreas Krause

Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs

Timur Garipov, Pavel Izmailov, Dmitrii Podoprikhin, Dmitry P Vetrov, Andrew G Wilson

Transfer Learning with Neural AutoML

Catherine Wong, Neil Houlsby, Yifeng Lu, Andrea Gesmundo

Binary Classification from Positive-Confidence Data

Takashi Ishida, Gang Niu, Masashi Sugiyama

Algebraic tests of general Gaussian latent tree models

Dennis Leung, Mathias Drton

Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model

Aaron Sidford, Mengdi Wang, Xian Wu, Lin Yang, Yinyu Ye

Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization

Sijia Liu, Bhavya Kailkhura, Pin-Yu Chen, Paishun Ting, Shiyu Chang

Differentiable MPC for End-to-end Planning and Control

Brandon Amos, Ivan Jimenez, Jacob Sacks, Byron Boots, J. Zico Kolter

Reinforcement Learning with Multiple Experts: A Bayesian Model Combination Approach

Michael Gimelfarb, Scott Sanner, Chi-Guhn Lee

Experimental Design for Cost-Aware Learning of Causal Graphs

Erik Lindgren, Murat Kocaoglu, Alexandros G Dimakis, Sriram Vishwanath

Recurrent Relational Networks

Rasmus Palm, Ulrich Paquet, Ole Winther

Learning To Learn Around A Common Mean

Giulia Denevi, Carlo Ciliberto, Dimitris Stamos, Massimiliano Pontil

Attacks Meet Interpretability: Attribute-steered Detection of Adversarial Samples

Guanhong Tao, Shiqing Ma, Yingqi Liu, Xiangyu Zhang

Learning Disentangled Joint Continuous and Discrete Representations

Emilien Dupont

Learning without the Phase: Regularized PhaseMax Achieves Optimal Sample Complexity

Fariborz Salehi, Ehsan Abbasi, Babak Hassibi

Hardware Conditioned Policies for Multi-Robot Transfer Learning

Tao Chen, Adithyavairavan Murali, Abhinav Gupta

Constrained Graph Variational Autoencoders for Molecule Design

Qi Liu, Miltiadis Allamanis, Marc Brockschmidt, Alexander Gaunt

Infinite-Horizon Gaussian Processes

Arno Solin, James Hensman, Richard E Turner

On the Local Hessian in Back-propagation

Huishuai Zhang, Wei Chen, Tie-yan Liu

Porcupine Neural Networks: Approximating Neural Network Landscapes

Soheil Feizi, Hamid Javadi, Jesse Zhang, David Tse

The Pessimistic Limits and Possibilities of Margin-based Losses in Semi-supervised Learning

Jesse Krijthe, Marco Loog

Latent Alignment and Variational Attention

Yuntian Deng, Yoon Kim, Justin Chiu, Demi Guo, Alexander Rush

Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification

Dimitrios Milios, Raffaello Camoriano, Pietro Michiardi, Lorenzo Rosasco, Maurizio Filippone

Generalizing Point Embeddings using the Wasserstein Space of Elliptical Distributions

Boris Muzellec, Marco Cuturi

Norm-Ranging LSH for Maximum Inner Product Search

Xiao Yan, Jinfeng Li, Xinyan Dai, Hongzhi Chen, James Cheng

Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data

Dominik Linzner, Heinz Koeppl

REFUEL: Exploring Sparse Features in Deep Reinforcement Learning for Fast Disease Diagnosis

Yu-Shao Peng, Kai-Fu Tang, Hsuan-tien Lin, Edward Chang

Probabilistic Matrix Factorization for Automated Machine Learning

Nicolo Fusi, Rishit Sheth, Melih Elibol

Large Scale computation of Means and Clusters for Persistence Diagrams using Optimal Transport

Theo Lacombe, Marco Cuturi, Steve OUDOT

On the Dimensionality of Word Embedding

Zi Yin, Yuanyuan Shen

Nonparametric learning from Bayesian models with randomized objective functions

Simon Lyddon, Stephen Walker, Chris C Holmes

Mental Sampling in Multimodal Representations

Jianqiao Zhu, Adam Sanborn, Nick Chater

Model Agnostic Supervised Local Explanations

Gregory Plumb, Denali Molitor, Ameet S Talwalkar

Convergence of Cubic Regularization for Nonconvex Optimization under KL Property

Yi Zhou, Zhe Wang, Yingbin Liang

Sparsified SGD with Memory

Sebastian U Stich, Jean-Baptiste Cordonnier, Martin Jaggi

Submodular Maximization via Gradient Ascent: The Case of Deep Submodular Functions

Wenruo Bai, William Stafford Noble, Jeff A. Bilmes

The Lingering of Gradients: How to Reuse Gradients Over Time

Zeyuan Allen-Zhu, David Simchi-Levi, Xinshang Wang

Geometrically Coupled Monte Carlo Sampling

Mark Rowland, Krzysztof M Choromanski, François Chalus, Aldo Pacchiano, Tamas Sarlos

A Structured Prediction Approach for Label Ranking

Anna Korba, Alexandre Garcia, Florence d'Alché-Buc

A theory on the absence of spurious solutions for nonconvex and nonsmooth optimization

Cedric Josz, Yi Ouyang, Richard Zhang, Javad Lavaei, Somayeh Sojoudi

Statistical mechanics of low-rank tensor decomposition

Jonathan Kadmon, Surya Ganguli

Bounded-Loss Private Prediction Markets

Rafael Frongillo, Bo Waggoner

SimplE Embedding for Link Prediction in Knowledge Graphs

Seyed Mehran Kazemi, David Poole

Computing Kantorovich-Wasserstein Distances on d-dimensional histograms using (d+1)-partite graphs

Gennaro Auricchio, Federico Bassetti, Stefano Gualandi, Marco Veneroni

Safe Active Learning for Time-Series Modeling with Gaussian Processes

Christoph Zimmer, Mona Meister, Duy Nguyen-tuong

Generalizing Tree Probability Estimation via Bayesian Networks

Cheng Zhang, Frederick A Matsen IV

Optimistic optimization of a Brownian

Jean-Bastien Grill, Michal Valko, Rémi Munos

Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents

Edoardo Conti, Vashisht Madhavan, Felipe Petroski Such, Joel Lehman, Kenneth Stanley

Reparameterization Gradient for Non-differentiable Models

Wonyeol Lee, Hangyeol Yu, Hongseok Yang

Online Adaptive Methods, Universality and Acceleration

Kfir Y. Levy, Alp Yurtsever, Volkan Cevher

Relating Leverage Scores and Density using Regularized Christoffel Functions

Edouard Pauwels, Francis Bach, Jean-philippe Vert

Fast Estimation of Causal Interactions using Wold Processes

Flavio Figueiredo, Guilherme Resende Borges, Pedro O.S. Vaz de Melo, Renato Assunção

Found Graph Data and Planted Vertex Covers

Austin R Benson, Jon Kleinberg

Generative modeling for protein structures

Namrata Anand, Possu Huang

Dual Principal Component Pursuit: Improved Analysis and Efficient Algorithms

Zhihui Zhu, Yifan Wang, Daniel Robinson, Daniel Naiman, René Vidal

Constant Regret, Generalized Mixability, and Mirror Descent

Zakaria Mhammedi, Robert C. Williamson

Thwarting Adversarial Examples: An L_0-Robust Sparse Fourier Transform

Mitali Bafna, Jack Murtagh, Nikhil Vyas

Learning to Multitask

Yu Zhang, Ying Wei, Qiang Yang

Masking: A New Perspective of Noisy Supervision

Bo Han, Jiangchao Yao, Gang Niu, Mingyuan Zhou, Ivor Tsang

Practical Deep Stereo (PDS): Toward applications-friendly deep stereo matching

Stepan Tulyakov, Anton Ivanov, Francois Fleuret