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NeurIPS2019机器学习顶会接受论文列表!

专知 • 2 周前 • 107 次点击  

【导读】人工智能和机器学习领域的国际顶级会议NeurIPS 2019公布了接受论文,有效提交论文6743篇论文, 总共有1428接受论文, 21.1%接受率,包括36篇Oral,164篇Spotlights。最近,NeurIPS 2019接受论文列表公布出来,大家可以查找自己感兴趣的提前看。



NeurIPS是人工智能和机器学习领域的国际顶级会议,由NIPS基金会负责运营。该会议全称为神经信息处理系统大会(Conference and Workshop on Neural Information Processing Systems,NIPS),自1987年开始,每年的12月份,来自世界各地的从事AI和ML相关的专家学者和从业人士汇聚一堂。受其名称歧义带来的压力(部分原因是其首字母缩写具有「暧昧的内涵」,带有性别歧视的意义),2018年的会议名称改为NeurIPS 。


NeurIPS 2019接受论文推荐

链接:

https://neurips.cc/Conferences/2019/AcceptedPapersInitial


Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation
Risto Vuorio (University of Michigan) · Shao-Hua Sun (University of Southern California) · Hexiang Hu (University of Southern California) · Joseph J Lim (University of Southern California)

ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks
Jiasen Lu (Georgia Tech) · Dhruv Batra (Georgia Tech / Facebook AI Research (FAIR)) · Devi Parikh (Georgia Tech / Facebook AI Research (FAIR)) · Stefan Lee (Georgia Institute of Technology)

Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers
Liwei Wu (University of California, Davis) · Shuqing Li (University of California, Davis) · Cho-Jui Hsieh (UCLA) · James Sharpnack (UC Davis)

Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video
JiaWang Bian (The University of Adelaide) · Zhichao Li (Tusimple) · Naiyan Wang (Hong Kong University of Science and Technology) · Huangying Zhan (The University of Adelaide) · Chunhua Shen (University of Adelaide) · Ming-Ming Cheng (Nankai University) · Ian Reid (University of Adelaide)

Zero-shot Learning via Simultaneous Generating and Learning
Hyeonwoo Yu (Seoul National University) · Beomhee Lee (Seoul National University)

Ask not what AI can do for you, but what AI should do: Towards a framework of task delegability
Brian Lubars (University of Colorado Boulder) · Chenhao Tan (University of Colorado Boulder)

Stand-Alone Self-Attention in Vision Models
Niki Parmar (Google) · Prajit Ramachandran (Google Brain) · Ashish Vaswani (Google Brain) · Irwan Bello (Google) · Anselm Levskaya (Google) · Jon Shlens (Google Research)

High Fidelity Video Prediction with Large Neural Nets
Ruben Villegas (Adobe Research / U. Michigan) · Arkanath Pathak (Google) · Harini Kannan (Google Brain) · Honglak Lee (Google / U. Michigan) · Dumitru Erhan (Google Brain) · Quoc V Le (Google)

Unsupervised learning of object structure and dynamics from videos
Matthias Minderer (Google Research) · Chen Sun (Google Research) · Ruben Villegas (Adobe Research / U. Michigan) · Forrester Cole (Google Research) · Kevin P Murphy (Google) · Honglak Lee (Google Brain)

TensorPipe: Easy Scaling with Micro-Batch Pipeline Parallelism
Yanping Huang (Google Brain) · Youlong Cheng (Google) · Ankur Bapna (Google) · Orhan Firat (Google) · Dehao Chen (Google) · Mia Chen (Google Brain) · HyoukJoong Lee (Google) · Jiquan Ngiam (Google Brain) · Quoc V Le (Google) · Yonghui Wu (Google) · zhifeng Chen (Google Brain)

Meta-Learning with Implicit Gradients
Aravind Rajeswaran (University of Washington) · Chelsea Finn (Stanford University) · Sham Kakade (University of Washington) · Sergey Levine (UC Berkeley)

Adversarial Examples Are Not Bugs, They Are Features
Andrew Ilyas (MIT) · Shibani Santurkar (MIT) · Dimitris Tsipras (MIT) · Logan Engstrom (MIT) · Brandon Tran (Massachusetts Institute of Technology) · Aleksander Madry (MIT)

Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks
Vineet Kosaraju (Stanford University) · Amir Sadeghian (Stanford University) · Roberto Martín-Martín (Stanford University) · Ian Reid (University of Adelaide) · Hamid Rezatofighi (University of Adelaide) · Silvio Savarese (Stanford University)

FreeAnchor: Learning to Match Anchors for Visual Object Detection
Xiaosong Zhang (University of Chinese Academy of Sciences) · Fang Wan (University of Chinese Academy of Sciences) · Chang Liu (University of Chinese Academy of Sciences) · Rongrong Ji (Xiamen University, China) · Qixiang Ye (University of Chinese Academy of Sciences, China)

Differentially Private Hypothesis Selection
Mark Bun (Princeton University) · Gautam Kamath (University of Waterloo) · Thomas Steinke (IBM, Almaden) · Steven Wu (Microsoft Research)

New Differentially Private Algorithms for Learning Mixtures of Well-Separated Gaussians
Gautam Kamath (University of Waterloo) · Or Sheffet (University of Alberta) · Vikrant Singhal (Northeastern University) · Jonathan Ullman (Northeastern University)

Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation
Mark Bun (Princeton University) · Thomas Steinke (IBM, Almaden)

Multi-Resolution Weak Supervision for Sequential Data
Paroma Varma (Stanford University) · Frederic Sala (Stanford) · Shiori Sagawa (Stanford University) · Jason Fries (Stanford University) · Daniel Fu (Stanford University) · Saelig Khattar (Stanford University) · Ashwini Ramamoorthy (Stanford University) · Ke Xiao (Stanford University) · Kayvon Fatahalian (Stanford) · James Priest (Stanford University) · Christopher Ré (Stanford)

DeepUSPS: Deep Robust Unsupervised Saliency Prediction via Self-supervision
Tam Nguyen (Freiburg Computer Vision Lab) · Maximilian Dax (Bosch GmbH) · Chaithanya Kumar Mummadi (Robert Bosch GmbH) · Nhung Ngo (Bosch Center for Artificial Intelligence) · Thi Hoai Phuong Nguyen (KIT) · Zhongyu Lou (Robert Bosch Gmbh) · Thomas Brox (University of Freiburg)

The Point Where Reality Meets Fantasy: Mixed Adversarial Generators for Image Splice Detection
Vladimir V. Kniaz (IEEE) · Vladimir Knyaz (State Research Institute of Aviation Systems) · Fabio Remondino ("Fondazione Bruno Kessler, Italy")

You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle
Dinghuai Zhang (Peking University) · Tianyuan Zhang (Peking University) · Yiping Lu (Peking University) · Zhanxing Zhu (Peking University) · Bin Dong (Peking University)

Imitation Learning from Observations by Minimizing Inverse Dynamics Disagreement
Chao Yang (Tsinghua University) · Xiaojian Ma (University of California, Los Angeles) · Wenbing Huang (Tsinghua University) · Fuchun Sun (Tsinghua) · 刘 华平 (清华大学) · Junzhou Huang (University of Texas at Arlington / Tencent AI Lab) · Chuang Gan (MIT-IBM Watson AI Lab)

Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance
Kimia Nadjahi ( Télécom ParisTech) · Alain Durmus (ENS) · Umut Simsekli (Institut Polytechnique de Paris) · Roland Badeau (Télécom ParisTech)

Generalized Sliced Wasserstein Distances
Soheil Kolouri (HRL Laboratories LLC) · Kimia Nadjahi ( Télécom ParisTech) · Umut Simsekli (Institut Polytechnique de Paris) · Roland Badeau (Télécom ParisTech) · Gustavo Rohde (University of Virginia)

First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise
Than Huy Nguyen (Telecom ParisTech) · Umut Simsekli (Institut Polytechnique de Paris) · Mert Gurbuzbalaban (Rutgers) · Gaël RICHARD (Télécom ParisTech)

Blind Super-Resolution Kernel Estimation using an Internal-GAN
Yosef Bell Kligler (Weizmann Istitute of Science) · Assaf Shocher (Weizmann Institute of Science) · Michal Irani (The Weizmann Institute of Science)

Noise-tolerant fair classification
Alex Lamy (Columbia University) · Ziyuan Zhong (Columbia University) · Aditya Menon (Google) · Nakul Verma (Columbia University)

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection
Bingzhe Wu (Peeking University) · Shiwan Zhao (IBM Research - China) · Haoyang Xu (Peking University) · Chaochao Chen (Ant Financial) · Li Wang (Ant Financial) · Xiaolu Zhang (Ant Financial Services Group) · Guangyu Sun (Peking University) · Jun Zhou (Ant Financial)

Joint-task Self-supervised Learning for Temporal Correspondence
xueting li (uc merced) · Sifei Liu (NVIDIA) · Shalini De Mello (NVIDIA) · Xiaolong Wang (CMU) · Jan Kautz (NVIDIA) · Ming-Hsuan Yang (UC Merced / Google)

Provable Gradient Variance Guarantees for Black-Box Variational Inference
Justin Domke (University of Massachusetts, Amherst)

Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation
Justin Domke (University of Massachusetts, Amherst) · Daniel Sheldon (University of Massachusetts Amherst)

Experience Replay for Continual Learning
David Rolnick (UPenn) · Arun Ahuja (DeepMind) · Jonathan Schwarz (DeepMind) · Timothy Lillicrap (Google DeepMind) · Gregory Wayne (Google DeepMind)

Deep ReLU Networks Have Surprisingly Few Activation Patterns
Boris Hanin (Texas A&M) · David Rolnick (UPenn)

Chasing Ghosts: Instruction Following as Bayesian State Tracking
Peter Anderson (Georgia Tech) · Ayush Shrivastava (Georgia Institute of Technology) · Devi Parikh (Georgia Tech / Facebook AI Research (FAIR)) · Dhruv Batra (Georgia Tech / Facebook AI Research (FAIR)) · Stefan Lee (Georgia Institute of Technology)

Block Coordinate Regularization by Denoising
Yu Sun (Washington University in St. Louis) · Jiaming Liu (Washington University in St. Louis) · Ulugbek Kamilov (Washington University in St. Louis)

Reducing Noise in GAN Training with Variance Reduced Extragradient
Tatjana Chavdarova (Mila & Idiap & EPFL) · Gauthier Gidel (Mila) · François Fleuret (Idiap Research Institute) · Simon Lacoste-Julien (Mila, Université de Montréal)

Learning Erdos-Renyi Random Graphs via Edge Detecting Queries
Zihan Li (National University of Singapore) · Matthias Fresacher (University of Adelaide) · Jonathan Scarlett (National University of Singapore)

A Primal-Dual link between GANs and Autoencoders
Hisham Husain (The Australian National University) · Richard Nock (Data61, the Australian National University and the University of Sydney) · Robert Williamson (Australian National University & Data61)

muSSP: Efficient Min-cost Flow Algorithm for Multi-object Tracking
CONGCHAO WANG (Virginia Tech) · Yizhi Wang (Virginia Tech) · Yinxue Wang (Virginia Tech) · Chiung-Ting Wu (Virginia Tech) · Guoqiang Yu (Virginia Tech)

Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation
Qiming Zhang (the University of Sydney) · Jing Zhang (The University of Sydney) · Wei Liu (Tencent AI Lab) · Dacheng Tao (University of Sydney)

Invert to Learn to Invert
Patrick Putzky (University of Amsterdam) · Max Welling (University of Amsterdam / Qualcomm AI Research)

Equitable Stable Matchings in Quadratic Time
Nikolaos Tziavelis (Northeastern University) · Ioannis Giannakopoulos (National Technical University of Athens) · Katerina Doka (NTUA) · Nectarios Koziris (NTUA) · Panagiotis Karras (Aarhus University)

Zero-Shot Semantic Segmentation
Maxime Bucher (Valeo.ai) · Tuan-Hung VU (Valeo.ai) · Matthieu Cord (Sorbonne University) · Patrick Pérez (Valeo.ai)

Metric Learning for Adversarial Robustness
Chengzhi Mao (Columbia University) · Ziyuan Zhong (Columbia University) · Junfeng Yang (Columbia University) · Carl Vondrick (Columbia University) · Baishakhi Ray (Columbia University)

DISN: Deep Implicit Surface Network for High-quality Single-view 3D Reconstruction
Qiangeng Xu (USC) · Weiyue Wang (USC) · Duygu Ceylan (Adobe Research) · Radomir Mech (Adobe Systems Incorporated) · Ulrich Neumann (USC)

Batched Multi-armed Bandits Problem
Zijun Gao (Stanford University) · Yanjun Han (Stanford University) · Zhimei Ren (Stanford University) · Zhengqing Zhou (Stanford University)

vGraph: A Generative Model for Joint Community Detection and Node Representation Learning
Fan-Yun Sun (National Taiwan University) · Meng Qu (MILA) · Jordan Hoffmann (Harvard University/Mila) · Chin-Wei Huang (MILA) · Jian Tang (HEC Montreal & MILA)

Differentially Private Bayesian Linear Regression
Garrett Bernstein (University of Massachusetts Amherst) · Daniel Sheldon (University of Massachusetts Amherst)

Semantic Conditioned Dynamic Modulation for Temporal Sentence Grounding in Videos
Yitian Yuan (Tsinghua University) · Lin Ma (Tencent AI Lab) · Jingwen Wang (Tencent AI Lab) · Wei Liu (Tencent AI Lab) · Wenwu Zhu (Tsinghua University)

AGEM: Solving Linear Inverse Problems via Deep Priors and Sampling
Bichuan Guo (Tsinghua University) · Yuxing Han (South China Agriculture University) · Jiangtao Wen (Tsinghua University)

CPM-Nets: Cross Partial Multi-View Networks
Changqing Zhang (Tianjin university) · han zongbo (Tianjin University) · yajie cui (tianjin university) · Huazhu Fu (Inception Institute of Artificial Intelligence) · Joey Tianyi Zhou (IHPC, A*STAR) · Qinghua Hu (Tianjin University)

Learning to Predict Layout-to-image Conditional Convolutions for Semantic Image Synthesis
Xihui Liu (The Chinese University of Hong Kong) · Guojun Yin (University of Science and Technology of China) · Jing Shao (Sensetime) · Xiaogang Wang (The Chinese University of Hong Kong) · hongsheng Li (cuhk)

Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling
Andrey Kolobov (Microsoft Research) · Yuval Peres (N/A) · Cheng Lu (Microsoft) · Eric J Horvitz (Microsoft Research)

SySCD: A System-Aware Parallel Coordinate Descent Algorithm
Celestine Mendler-Dünner (UC Berkeley) · Nikolas Ioannou (IBM Research) · Thomas Parnell (IBM Research)

Importance Weighted Hierarchical Variational Inference
Artem Sobolev (Samsung) · Dmitry Vetrov (Higher School of Economics, Samsung AI Center, Moscow)

RSN: Randomized Subspace Newton
Robert Gower (Telecom-Paristech) · Dmitry Koralev (KAUST) · Felix Lieder (Heinrich-Heine-Universität Düsseldorf) · Peter Richtarik (KAUST)

Trust Region-Guided Proximal Policy Optimization
Yuhui Wang (Nanjing University of Aeronautics and Astronautics, China) · Hao He (Nanjing University of Aeronautics and Astronautics) · Xiaoyang Tan (Nanjing University of Aeronautics and Astronautics, China) · Yaozhong Gan (Nanjing University of Aeronautics and Astronautics, China)

Adversarial Self-Defense for Cycle-Consistent GANs
Dina Bashkirova (Boston University) · Ben Usman (Boston University) · Kate Saenko (Boston University)

Towards closing the gap between the theory and practice of SVRG
Othmane Sebbouh (Télécom ParisTech) · Nidham Gazagnadou (Télécom ParisTech) · Samy Jelassi (Princeton University) · Francis Bach (INRIA - Ecole Normale Superieure) · Robert Gower (Telecom-Paristech)

Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control
Armin Lederer (Technical University of Munich) · Jonas Umlauft (Technical University of Munich) · Sandra Hirche (Technische Universitaet Muenchen)

ETNet: Error Transition Network for Arbitrary Style Transfer
Chunjin Song (Shenzhen University) · Zhijie Wu (Shenzhen University) · Yang Zhou (Shenzhen University) · Minglun Gong (Memorial Univ) · Hui Huang (Shenzhen University)

No Pressure! Addressing the Problem of Local Minima in Manifold Learning Algorithms
Max Vladymyrov (Google)

Deep Equilibrium Models
Shaojie Bai (Carnegie Mellon University) · J. Zico Kolter (Carnegie Mellon University / Bosch Center for AI) · Vladlen Koltun (Intel Labs)

Saccader: Accurate, Interpretable Image Classification with Hard Attention
Gamaleldin Elsayed (Google Brain) · Simon Kornblith (Google Brain) · Quoc V Le (Google)

Multiway clustering via tensor block models 
Miaoyan Wang (University of Wisconsin - Madison) · Yuchen Zeng (University of Wisconsin - Madison)

Regret Minimization for Reinforcement Learning on Multi-Objective Online Markov Decision Processes
Wang Chi Cheung (Department of Industrial Systems Engineering and Management, National University of Singapore)

NAT: Neural Architecture Transformer for Accurate and Compact Architectures
Yong Guo (South China University of Technology) · Yin Zheng (Tencent AI Lab) · Mingkui Tan (South China University of Technology) · Qi Chen (South China University of Technology) · Jian Chen ("South China University of Technology, China") · Peilin Zhao (Tencent AI Lab) · Junzhou Huang (University of Texas at Arlington / Tencent AI Lab)

Selecting Optimal Decisions via Distributionally Robust Nearest-Neighbor Regression
Ruidi Chen (Boston University) · Ioannis Paschalidis (Boston University)

Network Pruning via Transformable Architecture Search
Xuanyi Dong (University of Technology Sydney) · Yi Yang (UTS)

Differentiable Cloth Simulation for Inverse Problems
Junbang Liang (University of Maryland, College Park) · Ming Lin (UMD-CP & UNC-CH ) · Vladlen Koltun (Intel Labs)

Poisson-randomized Gamma Dynamical Systems
Aaron Schein (UMass Amherst) · Scott Linderman (Columbia University) · Mingyuan Zhou (University of Texas at Austin) · David Blei (Columbia University) · Hanna Wallach (MSR NYC)

Volumetric Correspondence Networks for Optical Flow
Gengshan Yang (Carnegie Mellon University) · Deva Ramanan (Carnegie Mellon University)

Learning Conditional Deformable Templates with Convolutional Networks
Adrian Dalca (MIT, HMS) · Marianne Rakic (ETH Zürich) · John Guttag (Massachusetts Institute of Technology) · Mert Sabuncu (Cornell)

Fast Low-rank Metric Learning for Large-scale and High-dimensional Data
Han Liu (Tsinghua University) · Zhizhong Han (University of Maryland, College Park) · Yu-Shen Liu (Tsinghua University) · Ming Gu (Tsinghua University)

Efficient Symmetric Norm Regression via Linear Sketching
Zhao Song (University of Washington) · Ruosong Wang (Carnegie Mellon University) · Lin Yang (Johns Hopkins University) · Hongyang Zhang (Carnegie Mellon University) · Peilin Zhong (Columbia University)

RUBi: Reducing Unimodal Biases in Visual Question Answering
Remi Cadene (LIP6) · Corentin Dancette (LIP6) · Hedi Ben younes (Université Pierre & Marie Curie / Heuritech) · Matthieu Cord (Sorbonne University) · Devi Parikh (Georgia Tech / Facebook AI Research (FAIR))

Reducing Scene Bias of Convolutional Neural Networks for Human Action Understanding
Jinwoo Choi (Virginia Tech) · Chen Gao (Virginia Tech) · Joseph C.E. Messou (Virginia Tech) · Jia-Bin Huang (Virginia Tech)

NeurVPS: Neural Vanishing Point Scanning via Conic Convolution
Yichao Zhou (UC Berkeley) · Haozhi Qi (UC Berkeley) · Jingwei Huang (Stanford University) · Yi Ma (UC Berkeley)

DATA: Differentiable ArchiTecture Approximation
Jianlong Chang (National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences) · xinbang zhang (Institute of Automation,Chinese Academy of Science) · Yiwen Guo (Intel Labs China) · GAOFENG MENG (Institute of Automation, Chinese Academy of Sciences) · SHIMING XIANG (Chinese Academy of Sciences, China) · Chunhong Pan (Institute of Automation, Chinese Academy of Sciences)

由于字数限制,未完待续


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