We are proud to present the following papers at the 33rd Conference on Neural Information Processing Systems (NeurIPS) in Vancouver, Canada.
If you are attending NeurIPS 2019, please stop by to say hello and hear more about what we are doing!
Full List of Accepted Papers
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)
Deep Equilibrium Models
Shaojie Bai (Carnegie Mellon University) · J. Zico Kolter (Carnegie Mellon University / Bosch Center for AI) · Vladlen Koltun (Intel Labs)
Volumetric Correspondence Networks for Optical Flow
Gengshan Yang (Carnegie Mellon University) · Deva Ramanan (Carnegie Mellon 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)
Envy-Free Classification
Maria-Florina Balcan (Carnegie Mellon University) · Travis Dick (Carnegie Mellon University) · Ritesh Noothigattu (Carnegie Mellon University) · Ariel D Procaccia (Carnegie Mellon University)
Twin Auxilary Classifiers GAN
Mingming Gong (University of Melbourne) · Yanwu Xu (University of Pittsburgh) · Chunyuan Li (Microsoft Research) · Kun Zhang (CMU) · Kayhan Batmanghelich (University of Pittsburgh)
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift
Stephan Rabanser (Amazon) · Stephan Günnemann (Technical University of Munich) · Zachary Lipton (Carnegie Mellon University)
Backprop with Approximate Activations for Memory-efficient Network Training
Ayan Chakrabarti (Washington University in St. Louis) · Benjamin Moseley (Carnegie Mellon University)
Total Least Squares Regression in Input Sparsity Time
Huaian Diao (Northeast Normal University) · Zhao Song (Harvard University & University of Washington) · David Woodruff (Carnegie Mellon University) · Xin Yang (University of Washington)
Conformal Prediction Under Covariate Shift
Rina Foygel Barber (University of Chicago) · Emmanuel Candes (Stanford University) · Aaditya Ramdas (CMU) · Ryan Tibshirani (Carnegie Mellon University)
Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation
Chen Dan (Carnegie Mellon University) · Hong Wang (Massachusetts Institute of Technology) · Hongyang Zhang (Carnegie Mellon University) · Yuchen Zhou (University of Wisconsin, Madison) · Pradeep Ravikumar (Carnegie Mellon University)
Third-Person Visual Imitation Learning via Decoupled Hierarchical Control
Pratyusha Sharma (Carnegie Mellon University) · Deepak Pathak (UC Berkeley) · Abhinav Gupta (Facebook AI Research/CMU)
Visual Sequence Learning in Hierarchical Prediction Networks and Primate Visual Cortex
JIELIN QIU (Shanghai Jiao Tong University) · Ge Huang (Carnegie Mellon University) · Tai Sing Lee (Carnegie Mellon University)
Optimal Decision Tree with Noisy Outcomes
Su Jia (CMU) · viswanath nagarajan (Univ Michigan, Ann Arbor) · Fatemeh Navidi (University of Michigan) · R Ravi (CMU)
Learning Sample-Specific Models with Low-Rank Personalized Regression
Ben Lengerich (Carnegie Mellon University) · Bryon Aragam (University of Chicago) · Eric Xing (Petuum Inc. / Carnegie Mellon University)
A Normative Theory for Causal Inference and Bayes Factor Computation in Neural Circuits
Wenhao Zhang (Carnegie Mellon & U. of Pittsburgh) · Si Wu (Peking University) · Brent Doiron (University of Pittsburgh) · Tai Sing Lee (Carnegie Mellon University)
Regularized Weighted Low Rank Approximation
Frank Ban (UC Berkeley) · David Woodruff (Carnegie Mellon University) · Richard Zhang (UC Berkeley)
Partially Encrypted Deep Learning using Functional Encryption
Theo Ryffel (École Normale Supérieure) · David Pointcheval (École Normale Supérieure) · Francis Bach (INRIA – Ecole Normale Superieure) · Edouard Dufour-Sans (Carnegie Mellon University) · Romain Gay (UC Berkeley)
Learning low-dimensional state embeddings and metastable clusters from time series data
Yifan Sun (Carnegie Mellon University) · Yaqi Duan (Princeton University) · Hao Gong (Princeton University) · Mengdi Wang (Princeton University)
Offline Contextual Bayesian Optimization
Ian Char (Carnegie Mellon University) · Youngseog Chung (Carnegie Mellon University) · Willie Neiswanger (Carnegie Mellon University) · Kirthevasan Kandasamy (Carnegie Mellon University) · Oak Nelson (Princeton Plasma Physics Lab) · Mark Boyer (Princeton Plasma Physics Lab) · Egemen Kolemen (Princeton Plasma Physics Lab) · Jeff Schneider (Carnegie Mellon University)
Game Design for Eliciting Distinguishable Behavior
Fan Yang (Carnegie Mellon University) · Liu Leqi (Carnegie Mellon University) · Yifan Wu (Carnegie Mellon University) · Zachary Lipton (Carnegie Mellon University) · Pradeep Ravikumar (Carnegie Mellon University) · Tom M Mitchell (Carnegie Mellon University) · William Cohen (Google AI)
Optimal Sketching for Kronecker Product Regression and Low Rank Approximation
Huaian Diao (Northeast Normal University) · Rajesh Jayaram (Carnegie Mellon University) · Zhao Song (UT-Austin) · Wen Sun (Microsoft Research) · David Woodruff (Carnegie Mellon University)
Online Learning for Auxiliary Task Weighting for Reinforcement Learning
Xingyu Lin (Carnegie Mellon University) · Harjatin Baweja (CMU) · George Kantor (CMU) · David Held (CMU)
Cost Effective Active Search
Shali Jiang (Washington University in St. Louis) · Roman Garnett (Washington University in St. Louis) · Benjamin Moseley (Carnegie Mellon University)
Mutually Regressive Point Processes
Ifigeneia Apostolopoulou (Carnegie Mellon University) · Scott Linderman (Stanford University) · Kyle Miller (Carnegie Mellon University) · Artur Dubrawski (Carnegie Mellon University)
Efficient Regret Minimization Algorithm for Extensive-Form Correlated Equilibrium
Gabriele Farina (Carnegie Mellon University) · Chun Kai Ling (Carnegie Mellon University) · Fei Fang (Carnegie Mellon University) · Tuomas Sandholm (Carnegie Mellon University)
Optimistic Regret Minimization for Extensive-Form Games via Dilated Distance-Generating Functions
Gabriele Farina (Carnegie Mellon University) · Christian Kroer (Columbia University) · Tuomas Sandholm (Carnegie Mellon University)
Face Reconstruction from Voice using Generative Adversarial Networks
Yandong Wen (Carnegie Mellon University) · Bhiksha Raj (Carnegie Mellon University) · Rita Singh (Carnegie Mellon University)
On Testing for Biases in Peer Review
Ivan Stelmakh (Carnegie Mellon University) · Nihar Shah (CMU) · Aarti Singh (CMU)
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels
Simon Du (Carnegie Mellon University) · Kangcheng Hou (Zhejiang University) · Ruslan Salakhutdinov (Carnegie Mellon University) · Barnabas Poczos (Carnegie Mellon University) · Ruosong Wang (Carnegie Mellon University) · Keyulu Xu (MIT)
Acceleration via Symplectic Discretization of High-Resolution Differential Equations
Bin Shi (UC Berkeley) · Simon Du (Carnegie Mellon University) · Weijie Su (University of Pennsylvania) · Michael Jordan (UC Berkeley)
XLNet: Generalized Autoregressive Pretraining for Language Understanding
Zhilin Yang (Tsinghua University) · Zihang Dai (Carnegie Mellon University) · Yiming Yang (CMU) · Jaime Carbonell (CMU) · Ruslan Salakhutdinov (Carnegie Mellon University) · Quoc V Le (Google)
Mixtape: Breaking the Softmax Bottleneck Efficiently
Zhilin Yang (Tsinghua University) · Thang Luong (Google) · Ruslan Salakhutdinov (Carnegie Mellon University) · Quoc V Le (Google)
MaCow: Masked Convolutional Generative Flow
Xuezhe Ma (Carnegie Mellon University) · Xiang Kong (Carnegie Mellon University) · Shanghang Zhang (Carnegie Mellon University) · Eduard Hovy (Carnegie Mellon University)
Adaptive Gradient-Based Meta-Learning Methods
Mikhail Khodak (CMU) · Maria-Florina Balcan (Carnegie Mellon University) · Ameet Talwalkar (CMU)
Towards a Zero-One Law for Column Subset Selection
Zhao Song (University of Washington) · David Woodruff (Carnegie Mellon University) · Peilin Zhong (Columbia University)
Dual Adversarial Semantics-Consistent Network for Generalized Zero-Shot Learning
Jian Ni (University of Science and Technology of China) · Shanghang Zhang (Carnegie Mellon University) · Haiyong Xie (University of Science and Technology of China)
Likelihood-Free Overcomplete ICA and ApplicationsIn Causal Discovery
Chenwei DING (The University of Sydney) · Mingming Gong (University of Melbourne) · Kun Zhang (CMU) · Dacheng Tao (University of Sydney)
The bias of the sample mean in multi-armed bandits can be positive or negative
Jaehyeok Shin (Carnegie Mellon University) · Aaditya Ramdas (Carnegie Mellon University) · Alessandro Rinaldo (CMU)
Efficient and Thrifty Voting by Any Means Necessary
Debmalya Mandal (Columbia University) · Ariel D Procaccia (Carnegie Mellon University) · Nisarg Shah (University of Toronto) · David Woodruff (Carnegie Mellon University)
Re-examination of the Role of Latent Variables in Sequence Modeling
Guokun Lai (Carnegie Mellon University) · Zihang Dai (Carnegie Mellon University)
Towards Understanding the Importance of Shortcut Connections in Residual Networks
Tianyi Liu (Georgia Institute of Technolodgy) · Minshuo Chen (Georgia Tech) · Mo Zhou (Duke University) · Simon Du (Carnegie Mellon University) · Enlu Zhou (Georgia Institute of Technology) · Tuo Zhao (Gatech)
Learning Local Search Heuristics for Boolean Satisfiability
Emre Yolcu (Carnegie Mellon University) · Barnabas Poczos (Carnegie Mellon University)
Difference Maximization Q-learning: Provably Efficient Q-learning with Function Approximation
Simon Du (Carnegie Mellon University) · Yuping Luo (Princeton University) · Ruosong Wang (Carnegie Mellon University) · Hanrui Zhang (Duke University)
On Exact Computation with an Infinitely Wide Neural Net
Sanjeev Arora (Princeton University) · Simon Du (Carnegie Mellon University) · Wei Hu (Princeton University) · zhiyuan li (Princeton University) · Ruslan Salakhutdinov (Carnegie Mellon University) · Ruosong Wang (Carnegie Mellon University)
Paradoxes in Fair Machine Learning
Paul Goelz (Carnegie Mellon University) · Anson Kahng (Carnegie Mellon University) · Ariel D Procaccia (Carnegie Mellon University)
Graph Agreement Models for Semi-Supervised Learning
Otilia Stretcu (Carnegie Mellon University) · Krishnamurthy Viswanathan (Google Research) · Dana Movshovitz-Attias (Google) · Emmanouil Platanios (Carnegie Mellon University) · Sujith Ravi (Google Research) · Andrew Tomkins (Google)
Nonparametric Density Estimation & Convergence Rates for GANs under Besov IPM Losses
Ananya Uppal (Carnegie Mellon University) · Shashank Singh (Carnegie Mellon University) · Barnabas Poczos (Carnegie Mellon University)
Correlation in Extensive-Form Games: Saddle-Point Formulation and Benchmarks
Gabriele Farina (Carnegie Mellon University) · Chun Kai Ling (Carnegie Mellon University) · Fei Fang (Carnegie Mellon University) · Tuomas Sandholm (Carnegie Mellon University)
ADDIS: an adaptive discarding algorithm for online FDR control with conservative nulls
Jinjin Tian (Carnegie Mellon University) · Aaditya Ramdas (Carnegie Mellon University)
Tight Dimensionality Reduction for Sketching Low Degree Polynomial Kernels
Michela Meister (Google) · Tamas Sarlos (Google Research) · David Woodruff (Carnegie Mellon University)
Differentiable Convex Optimization Layers
Akshay Agrawal (Stanford University) · Brandon Amos (Facebook) · Shane Barratt (Stanford University) · Stephen Boyd (Stanford University) · Steven Diamond (Stanford University) · J. Zico Kolter (Carnegie Mellon University / Bosch Center for AI)
Average Case Column Subset Selection for Entrywise $\ell_1$-Norm Loss
Zhao Song (University of Washington) · David Woodruff (Carnegie Mellon University) · Peilin Zhong (Columbia University)
Efficient Forward Architecture Search
Hanzhang Hu (Carnegie Mellon University) · John Langford (Microsoft Research New York) · Rich Caruana (Microsoft) · Saurajit Mukherjee (microsoft) · Eric J Horvitz (Microsoft Research) · Debadeepta Dey (Microsoft Research AI)
Efficient Near-Optimal Testing of Community Changes in Balanced Stochastic Block Models
Aditya Gangrade (Boston University) · Praveen Venkatesh (Carnegie Mellon University) · Bobak Nazer (Boston University) · Venkatesh Saligrama (Boston University)
Learning Robust Global Representations by Penalizing Local Predictive Power
Haohan Wang (Carnegie Mellon University) · Songwei Ge (Carnegie Mellon University) · Zachary Lipton (Carnegie Mellon University) · Eric Xing (Petuum Inc. / Carnegie Mellon University)
Unsupervised Curricula for Visual Meta-Reinforcement Learning
Allan Jabri (UC Berkeley) · Kyle Hsu (University of Toronto) · Ben Eysenbach (Carnegie Mellon University) · Abhishek Gupta (University of California, Berkeley) · Alexei Efros (UC Berkeley) · Sergey Levine (UC Berkeley) · Chelsea Finn (Stanford University)
Deep Gamblers: Learning to Abstain with Portfolio Theory
Ziyin Liu (University of Tokyo) · Zhikang Wang (University of Tokyo) · Paul Pu Liang (Carnegie Mellon University) · Ruslan Salakhutdinov (Carnegie Mellon University) · Louis-Philippe Morency (Carnegie Mellon University) · Masahito Ueda (University of Tokyo)
Statistical Analysis of Nearest Neighbor Methods for Anomaly Detection
Xiaoyi Gu (Carnegie Mellon University) · Leman Akoglu (CMU) · Alessandro Rinaldo (CMU)
On the (in)fidelity and sensitivity of explanations
Chih-Kuan Yeh (Carnegie Mellon University) · Cheng-Yu Hsieh (National Taiwan University) · Arun Suggala (Carnegie Mellon University) · David Inouye (Carnegie Mellon University) · Pradeep Ravikumar (Carnegie Mellon University)
Learning Stable Deep Dynamics Models
J. Zico Kolter (Carnegie Mellon University / Bosch Center for AI) · Gaurav Manek (Carnegie Mellon University)
Learning Neural Networks with Adaptive Regularization
Han Zhao (Carnegie Mellon University) · Yao-Hung Tsai (Carnegie Mellon University) · Ruslan Salakhutdinov (Carnegie Mellon University) · Geoffrey Gordon (MSR Montréal & CMU)
Uniform convergence may be unable to explain generalization in deep learning
Vaishnavh Nagarajan (Carnegie Mellon University) · J. Zico Kolter (Carnegie Mellon University / Bosch Center for AI)
Adversarial Music: Real world Audio Adversary against Wake-word Detection System
Juncheng Li (Carnegie Mellon University) · Shuhui Qu (Stanford University) · Xinjian Li (Carnegie Mellon University) · Joseph Szurley (Bosch Center for Artificial Intelligence) · J. Zico Kolter (Carnegie Mellon University / Bosch Center for AI) · Florian Metze (Carnegie Mellon University)
Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation
Ruibo Tu (KTH Royal Institute of Technology) · Kun Zhang (CMU) · Bo Bertilson (KI Karolinska Institutet) · Hedvig Kjellstrom (KTH Royal Institute of Technology) · Cheng Zhang (Microsoft)
Triad Constraints for Learning Causal Structure of Latent Variables
Ruichu Cai (Guangdong University of Technology) · Feng Xie (Guangdong University of Technology) · Clark Glymour (Carnegie Mellon University) · Zhifeng Hao (Guangdong University of Technology) · Kun Zhang (CMU)
Kalman Filter, Sensor Fusion, and Constrained Regression: Equivalences and Insights
David Farrow (Carnegie Mellon University) · Maria Jahja (Carnegie Mellon University) · Roni Rosenfeld (Carnegie Mellon University) · Ryan Tibshirani (Carnegie Mellon University)
Specific and Shared Causal Relation Modeling and Mechanism-based Clustering
Biwei Huang (Carnegie Mellon University) · Kun Zhang (CMU) · Pengtao Xie (Petuum / CMU) · Mingming Gong (University of Melbourne) · Eric Xing (Petuum Inc.) · Clark Glymour (Carnegie Mellon University)
Towards modular and programmable architecture search
Renato Negrinho (Carnegie Mellon University) · Matthew Gormley (Carnegie Mellon University) · Geoffrey Gordon (MSR Montréal & CMU) · Darshan Patil (Carnegie Mellon University) · Nghia Le (Carnegie Mellon University) · Daniel Ferreira (TU Wien)
Are Sixteen Heads Really Better than One?
Paul Michel (Carnegie Mellon University, Language Technologies Institute) · Omer Levy (Facebook) · Graham Neubig (Carnegie Mellon University)
Inducing brain-relevant bias in natural language processing models
Dan Schwartz (Carnegie Mellon University) · Mariya Toneva (Carnegie Mellon University) · Leila Wehbe (Carnegie Mellon University)
Differentially Private Covariance Estimation
Kareem Amin (Google Research) · Travis Dick (Carnegie Mellon University) · Alex Kulesza (Google) · Andres Munoz (Google) · Sergei Vassilvitskii (Google)
Missing Not at Random in Matrix Completion: The Effectiveness of Estimating Missingness Probabilities Under a Low Nuclear Norm Assumption
Wei Ma (Carnegie Mellon University) · George Chen (Carnegie Mellon University)
Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain)
Mariya Toneva (Carnegie Mellon University) · Leila Wehbe (Carnegie Mellon University)
On Human-Aligned Risk Minimization
Liu Leqi (Carnegie Mellon University) · Adarsh Prasad (Carnegie Mellon University) · Pradeep Ravikumar (Carnegie Mellon University)
Search on the Replay Buffer: Bridging Planning and Reinforcement Learning
Ben Eysenbach (Carnegie Mellon University) · Ruslan Salakhutdinov (Carnegie Mellon University) · Sergey Levine (UC Berkeley)
Multiple Futures Prediction
Charlie Tang (Apple Inc.) · Ruslan Salakhutdinov (Carnegie Mellon University)
Neural Taskonomy: Inferring the Similarity of Task-Derived Representations from Brain Activity
Aria Y Wang (Carnegie Mellon University) · Leila Wehbe (Carnegie Mellon University) · Michael J Tarr (Carnegie Mellon University)
Inherent Tradeoffs in Learning Fair Representation
Han Zhao (Carnegie Mellon University) · Geoff Gordon (Microsoft)
Learning Data Manipulation for Augmentation and Weighting
Zhiting Hu (Carnegie Mellon University) · Bowen Tan (CMU) · Ruslan Salakhutdinov (Carnegie Mellon University) · Tom Mitchell (Carnegie Mellon University) · Eric Xing (Petuum Inc. / Carnegie Mellon University)