NeurIPS 2021

2,334 papers

Sparse Quadratic Optimisation over the Stiefel Manifold with Application to Permutation Synchronisation

Florian Bernard, Daniel Cremers, Johan Thunberg

Multi-Scale Representation Learning on Proteins

Vignesh Ram Somnath, Charlotte Bunne, Andreas Krause

On Margin-Based Cluster Recovery with Oracle Queries

Marco Bressan, Nicolò Cesa-bianchi, Silvio Lattanzi, Andrea Paudice

NovelD: A Simple yet Effective Exploration Criterion

Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer

Learning the optimal Tikhonov regularizer for inverse problems

Giovanni S Alberti, Ernesto De Vito, Matti Lassas, Luca Ratti, Matteo Santacesaria

Improving Coherence and Consistency in Neural Sequence Models with Dual-System, Neuro-Symbolic Reasoning

Maxwell Nye, Michael Tessler, Josh Tenenbaum, Brenden M Lake

Adversarial Training Helps Transfer Learning via Better Representations

Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Y Zou

The functional specialization of visual cortex emerges from training parallel pathways with self-supervised predictive learning

Shahab Bakhtiari, Patrick Mineault, Timothy Lillicrap, Christopher Pack, Blake Richards

Learning to Synthesize Programs as Interpretable and Generalizable Policies

Dweep Trivedi, Jesse Zhang, Shao-Hua Sun, Joseph J. Lim

Scallop: From Probabilistic Deductive Databases to Scalable Differentiable Reasoning

Jiani Huang, Ziyang Li, Binghong Chen, Karan Samel, Mayur Naik

Learning Debiased Representation via Disentangled Feature Augmentation

Jungsoo Lee, Eungyeup Kim, Juyoung Lee, Jihyeon Lee, Jaegul Choo

Using Random Effects to Account for High-Cardinality Categorical Features and Repeated Measures in Deep Neural Networks

Giora Simchoni, Saharon Rosset

A/B/n Testing with Control in the Presence of Subpopulations

Yoan Russac, Christina Katsimerou, Dennis Bohle, Olivier Cappe, Aurélien Garivier

Robust Optimization for Multilingual Translation with Imbalanced Data

Xian Li, Hongyu Gong

Counterfactual Maximum Likelihood Estimation for Training Deep Networks

Xinyi Wang, Wenhu Chen, Michael Saxon, William Yang Wang

Not All Low-Pass Filters are Robust in Graph Convolutional Networks

Heng Chang, Yu Rong, Tingyang Xu, Yatao Bian, Shiji Zhou

Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning)

Sadegh Farhadkhani, Rachid Guerraoui, Arsany Guirguis, Lê-Nguyên Hoang, Sébastien Rouault

Never Go Full Batch (in Stochastic Convex Optimization)

Idan Amir, Yair Carmon, Tomer Koren, Roi Livni

Dynamics-regulated kinematic policy for egocentric pose estimation

Zhengyi Luo, Ryo Hachiuma, Ye Yuan, Kris Kitani

Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning

Timo Milbich, Karsten Roth, Samarth Sinha, Ludwig Schmidt, Marzyeh Ghassemi

Canonical Capsules: Self-Supervised Capsules in Canonical Pose

Weiwei Sun, Andrea Tagliasacchi, Boyang Deng, Sara Sabour, Soroosh Yazdani

Learning Hard Optimization Problems: A Data Generation Perspective

James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck

Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions

Lijun Zhang, Guanghui Wang, Wei-Wei Tu, Wei Jiang, Zhi-Hua Zhou

Differentially Private Multi-Armed Bandits in the Shuffle Model

Jay Tenenbaum, Haim Kaplan, Yishay Mansour, Uri Stemmer

A Causal Lens for Controllable Text Generation

Zhiting Hu, Li Erran Li

Choose a Transformer: Fourier or Galerkin

Shuhao Cao

Symbolic Regression via Deep Reinforcement Learning Enhanced Genetic Programming Seeding

Terrell Mundhenk, Mikel Landajuela, Ruben Glatt, Claudio P Santiago, Daniel faissol

IA-RED$^2$: Interpretability-Aware Redundancy Reduction for Vision Transformers

Bowen Pan, Rameswar Panda, Yifan Jiang, Zhangyang Wang, Rogerio Feris

Local Signal Adaptivity: Provable Feature Learning in Neural Networks Beyond Kernels

Stefani Karp, Ezra Winston, Yuanzhi Li, Aarti Singh

Topological Attention for Time Series Forecasting

Sebastian Zeng, Florian Graf, Christoph Hofer, Roland Kwitt

Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroimaging

Ali Hashemi, Yijing Gao, Chang Cai, Sanjay Ghosh, Klaus-Robert Müller

Causal Effect Inference for Structured Treatments

Jean Kaddour, Yuchen Zhu, Qi Liu, Matt J Kusner, Ricardo Silva

Piper: Multidimensional Planner for DNN Parallelization

Jakub M Tarnawski, Deepak Narayanan, Amar Phanishayee

Causal Bandits with Unknown Graph Structure

Yangyi Lu, Amirhossein Meisami, Ambuj Tewari

CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation

Yusuke Tashiro, Jiaming Song, Yang Song, Stefano Ermon

Domain Adaptation with Invariant Representation Learning: What Transformations to Learn?

Petar Stojanov, Zijian Li, Mingming Gong, Ruichu Cai, Jaime G. Carbonell

Adaptive Ensemble Q-learning: Minimizing Estimation Bias via Error Feedback

Hang Wang, Sen Lin, Junshan Zhang

Asymptotics of representation learning in finite Bayesian neural networks

Jacob Zavatone-Veth, Abdulkadir Canatar, Ben Ruben, Cengiz Pehlevan

Locally differentially private estimation of functionals of discrete distributions

Cristina Butucea, Yann ISSARTEL

Neural Human Performer: Learning Generalizable Radiance Fields for Human Performance Rendering

Youngjoong Kwon, Dahun Kim, Duygu Ceylan, Henry Fuchs

Modular Gaussian Processes for Transfer Learning

Pablo Moreno-Muñoz, Antonio Artés, Mauricio Alvarez

PLUGIn: A simple algorithm for inverting generative models with recovery guarantees

Babhru Joshi, Xiaowei Li, Yaniv Plan, Ozgur Yilmaz

Planning from Pixels in Environments with Combinatorially Hard Search Spaces

Marco Bagatella, Miroslav Olšák, Michal Rolinek, Georg Martius

Rot-Pro: Modeling Transitivity by Projection in Knowledge Graph Embedding

Tengwei Song, Jie Luo, Lei Huang

Trash or Treasure? An Interactive Dual-Stream Strategy for Single Image Reflection Separation

Qiming Hu, Xiaojie Guo

Information-theoretic generalization bounds for black-box learning algorithms

Hrayr Harutyunyan, Maxim Raginsky, Greg Ver Steeg, Aram Galstyan

Understanding Bandits with Graph Feedback

Houshuang Chen, zengfeng Huang, Shuai Li, Chihao Zhang

Unsupervised Representation Transfer for Small Networks: I Believe I Can Distill On-the-Fly

Hee Min Choi, Hyoa Kang, Dokwan Oh

Active Offline Policy Selection

Ksenia Konyushova, Yutian Chen, Thomas Paine, Caglar Gulcehre, Cosmin Paduraru

Federated Split Task-Agnostic Vision Transformer for COVID-19 CXR Diagnosis

Sangjoon Park, Gwanghyun Kim, Jeongsol Kim, Boah Kim, Jong Chul Ye

CHIP: CHannel Independence-based Pruning for Compact Neural Networks

Yang Sui, Miao Yin, Yi Xie, Huy Phan, Saman Aliari Zonouz

Pointwise Bounds for Distribution Estimation under Communication Constraints

Wei-Ning Chen, Peter Kairouz, Ayfer Ozgur

On Episodes, Prototypical Networks, and Few-Shot Learning

Steinar Laenen, Luca Bertinetto

Recognizing Vector Graphics without Rasterization

XINYANG JIANG, LU LIU, Caihua Shan, Yifei Shen, Xuanyi Dong

Variational Continual Bayesian Meta-Learning

Qiang Zhang, Jinyuan Fang, Zaiqiao Meng, Shangsong Liang, Emine Yilmaz

Structured in Space, Randomized in Time: Leveraging Dropout in RNNs for Efficient Training

Anup Sarma, Sonali Singh, Huaipan Jiang, Rui Zhang, Mahmut Kandemir

Adaptive Sampling for Minimax Fair Classification

Shubhanshu Shekhar, Greg Fields, Mohammad Ghavamzadeh, Tara Javidi

RL for Latent MDPs: Regret Guarantees and a Lower Bound

Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor

AutoGEL: An Automated Graph Neural Network with Explicit Link Information

Zhili Wang, Shimin DI, Lei Chen

Coupled Gradient Estimators for Discrete Latent Variables

Zhe Dong, Andriy Mnih, George Tucker

Detecting Individual Decision-Making Style: Exploring Behavioral Stylometry in Chess

Reid McIlroy-Young, Yu Wang, Siddhartha Sen, Jon M. Kleinberg, Ashton Anderson

VidLanKD: Improving Language Understanding via Video-Distilled Knowledge Transfer

Zineng Tang, Jaemin Cho, Hao Tan, Mohit Bansal

Understanding Adaptive, Multiscale Temporal Integration In Deep Speech Recognition Systems

Menoua Keshishian, Samuel Norman-Haignere, Nima Mesgarani

Dr Jekyll & Mr Hyde: the strange case of off-policy policy updates

Romain Laroche, Remi Tachet des Combes

Stochastic Online Linear Regression: the Forward Algorithm to Replace Ridge

Reda Ouhamma, Odalric-ambrym Maillard, Vianney Perchet

On the Power of Edge Independent Graph Models

Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos Tsourakakis

Distributionally Robust Imitation Learning

Mohammad Ali Bashiri, Brian Ziebart, Xinhua Zhang

Understanding and Improving Early Stopping for Learning with Noisy Labels

Yingbin Bai, Erkun Yang, Bo Han, Yanhua Yang, Jiatong Li

Discovering and Achieving Goals via World Models

Russell Mendonca, Oleh Rybkin, Kostas Daniilidis, Danijar Hafner, Deepak Pathak

Adaptive Proximal Gradient Methods for Structured Neural Networks

Jihun Yun, Aurelie C. Lozano, Eunho Yang

Can we globally optimize cross-validation loss? Quasiconvexity in ridge regression

Will Stephenson, Zachary Frangella, Madeleine Udell, Tamara Broderick

On the Power of Differentiable Learning versus PAC and SQ Learning

Emmanuel Abbe, Pritish Kamath, Eran Malach, Colin Sandon, Nathan Srebro

Memory Efficient Meta-Learning with Large Images

John Bronskill, Daniela Massiceti, Massimiliano Patacchiola, Katja Hofmann, Sebastian Nowozin

Communication-efficient SGD: From Local SGD to One-Shot Averaging

Artin Spiridonoff, Alex Olshevsky, Yannis Paschalidis

Fast and accurate randomized algorithms for low-rank tensor decompositions

Linjian Ma, Edgar Solomonik

One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective

Jiun Tian Hoe, Kam Woh Ng, Tianyu Zhang, Chee Seng Chan, Yi-Zhe Song

A Framework to Learn with Interpretation

Jayneel Parekh, Pavlo Mozharovskyi, Florence d'Alché-Buc

MLP-Mixer: An all-MLP Architecture for Vision

Ilya O Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai

On Training Implicit Models

Zhengyang Geng, Shaojie Bai, Yisen Wang, Zhouchen Lin, Xinyu Zhang

Learning to Schedule Heuristics in Branch and Bound

Antonia Chmiela, Elias Khalil, Ambros Gleixner, Andrea Lodi, Sebastian Pokutta

Analyzing the Generalization Capability of SGLD Using Properties of Gaussian Channels

Hao Wang, Yizhe Huang, RUI GAO, Flavio Calmon

VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Text

Hassan Akbari, Liangzhe Yuan, Rui Qian, Wei-Hong Chuang, Shih-fu Chang

Training Neural Networks with Fixed Sparse Masks

Yi-Lin Sung, Varun Nair, Colin A Raffel

Instance-Dependent Bounds for Zeroth-order Lipschitz Optimization with Error Certificates

Francois Bachoc, Tom Cesari, Sébastien Gerchinovitz

Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation

Ke Wang, Vidya Muthukumar, CHRISTOS THRAMPOULIDIS

Residual2Vec: Debiasing graph embedding with random graphs

Sadamori Kojaku, Jisung Yoon, Isabel Constantino, Yong-Yeol Ahn

FINE Samples for Learning with Noisy Labels

Taehyeon Kim, Jongwoo Ko, sangwook Cho, JinHwan Choi, Se-Young Yun

Nonparametric estimation of continuous DPPs with kernel methods

Michaël Fanuel, Rémi Bardenet

DiBS: Differentiable Bayesian Structure Learning

Lars Lorch, Jonas Rothfuss, Bernhard Schölkopf, Andreas Krause

Learning Nonparametric Volterra Kernels with Gaussian Processes

Magnus Ross, Michael T Smith, Mauricio Alvarez

Efficiently Learning One Hidden Layer ReLU Networks From Queries

Sitan Chen, Adam Klivans, Raghu Meka

An Efficient Pessimistic-Optimistic Algorithm for Stochastic Linear Bandits with General Constraints

Xin Liu, Bin Li, Pengyi Shi, Lei Ying

Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning

Aakash Kaku, Sahana Upadhya, Narges Razavian

Multiwavelet-based Operator Learning for Differential Equations

Gaurav Gupta, Xiongye Xiao, Paul Bogdan

On the Stochastic Stability of Deep Markov Models

Jan Drgona, Sayak Mukherjee, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar

VAST: Value Function Factorization with Variable Agent Sub-Teams

Thomy Phan, Fabian Ritz, Lenz Belzner, Philipp Altmann, Thomas Gabor

Fair Algorithms for Multi-Agent Multi-Armed Bandits

Safwan Hossain, Evi Micha, Nisarg Shah

Subgame solving without common knowledge

Brian Zhang, Tuomas Sandholm

Snowflake: Scaling GNNs to high-dimensional continuous control via parameter freezing

Charles Blake, Vitaly Kurin, Maximilian Igl, Shimon Whiteson

Densely connected normalizing flows

Matej Grcić, Ivan Grubišić, Siniša Šegvić