NeurIPS 2022

2,834 papers

Look More but Care Less in Video Recognition

Yitian Zhang, Yue Bai, Huan Wang, Yi Xu, Yun Fu

OGC: Unsupervised 3D Object Segmentation from Rigid Dynamics of Point Clouds

Ziyang Song, Bo Yang

Generalized Laplacian Eigenmaps

Hao Zhu, Piotr Koniusz

On Optimal Learning Under Targeted Data Poisoning

Steve Hanneke, Amin Karbasi, Mohammad Mahmoody, Idan Mehalel, Shay Moran

Decomposable Non-Smooth Convex Optimization with Nearly-Linear Gradient Oracle Complexity

Sally Dong, Haotian Jiang, Yin Tat Lee, Swati Padmanabhan, Guanghao Ye

Instance-based Learning for Knowledge Base Completion

Wanyun Cui, Xingran Chen

Online Algorithms for the Santa Claus Problem

Max Springer, MohammadTaghi Hajiaghayi, Debmalya Panigrahi, Mohammad Khani

On the consistent estimation of optimal Receiver Operating Characteristic (ROC) curve

Renxiong Liu, Yunzhang Zhu

Information-Theoretic Safe Exploration with Gaussian Processes

Alessandro Bottero, Carlos Luis, Julia Vinogradska, Felix Berkenkamp, Jan R. Peters

Look where you look! Saliency-guided Q-networks for generalization in visual Reinforcement Learning

David Bertoin, Adil Zouitine, Mehdi Zouitine, Emmanuel Rachelson

On the Effect of Pre-training for Transformer in Different Modality on Offline Reinforcement Learning

Shiro Takagi

Don't Roll the Dice, Ask Twice: The Two-Query Distortion of Matching Problems and Beyond

Georgios Amanatidis, Georgios Birmpas, Aris Filos-Ratsikas, Alexandros Voudouris

Boosting the Performance of Generic Deep Neural Network Frameworks with Log-supermodular CRFs

Hao Xiong, Yangxiao Lu, Nicholas Ruozzi

A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization

Songtao Lu, Siliang Zeng, Xiaodong Cui, Mark Squillante, Lior Horesh

Learning Generalized Policy Automata for Relational Stochastic Shortest Path Problems

Rushang Karia, Rashmeet Kaur Nayyar, Siddharth Srivastava

Few-Shot Continual Active Learning by a Robot

Ali Ayub, Carter Fendley

Towards Robust Blind Face Restoration with Codebook Lookup Transformer

Shangchen Zhou, Kelvin Chan, Chongyi Li, Chen Change Loy

What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Shivam Garg, Dimitris Tsipras, Percy Liang, Gregory Valiant

DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations

Ximeng Sun, Ping Hu, Kate Saenko

Efficient Non-Parametric Optimizer Search for Diverse Tasks

Ruochen Wang, Yuanhao Xiong, Minhao Cheng, Cho-jui Hsieh

Trade-off between Payoff and Model Rewards in Shapley-Fair Collaborative Machine Learning

Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet

Training Spiking Neural Networks with Event-driven Backpropagation

Yaoyu Zhu, Zhaofei Yu, Wei Fang, Xiaodong Xie, Tiejun Huang

RNNs of RNNs: Recursive Construction of Stable Assemblies of Recurrent Neural Networks

Leo Kozachkov, Michaela Ennis, Jean-Jacques Slotine

Joint Learning of 2D-3D Weakly Supervised Semantic Segmentation

Hyeokjun Kweon, Kuk-Jin Yoon

Local Linear Convergence of Gradient Methods for Subspace Optimization via Strict Complementarity

Ron Fisher, Dan Garber

Personalized Federated Learning towards Communication Efficiency, Robustness and Fairness

Shiyun Lin, Yuze Han, Xiang Li, Zhihua Zhang

EZNAS: Evolving Zero-Cost Proxies For Neural Architecture Scoring

Yash Akhauri, Juan Munoz, Nilesh Jain, Ravishankar Iyer

Generalised Implicit Neural Representations

Daniele Grattarola, Pierre Vandergheynst

LECO: Learnable Episodic Count for Task-Specific Intrinsic Reward

Daejin Jo, Sungwoong Kim, Daniel Nam, Taehwan Kwon, Seungeun Rho

An Algorithm for Learning Switched Linear Dynamics from Data

Guillaume Berger, Monal Narasimhamurthy, Kandai Watanabe, Morteza Lahijanian, Sriram Sankaranarayanan

Scalable Multi-agent Covering Option Discovery based on Kronecker Graphs

Jiayu Chen, Jingdi Chen, Tian Lan, Vaneet Aggarwal

Michael Poli, Winnie Xu, Stefano Massaroli, Chenlin Meng, Kuno Kim

The Unreliability of Explanations in Few-shot Prompting for Textual Reasoning

Xi Ye, Greg Durrett

Spectral Bias Outside the Training Set for Deep Networks in the Kernel Regime

Benjamin Bowman, Guido F. Montufar

Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders

Kiarash Zahirnia, Oliver Schulte, Parmis Naddaf, Ke Li

Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks

Agustinus Kristiadi, Runa Eschenhagen, Philipp Hennig

GPT3.int8(): 8-bit Matrix Multiplication for Transformers at Scale

Tim Dettmers, Mike Lewis, Younes Belkada, Luke Zettlemoyer

Accelerating Sparse Convolution with Column Vector-Wise Sparsity

Yijun Tan, Kai Han, Kang Zhao, Xianzhi Yu, Zidong Du

Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations

Peng Jin, Jinfa Huang, Fenglin Liu, Xian Wu, Shen Ge

GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs

Zenan Li, Qitian Wu, Fan Nie, Junchi Yan

The Nature of Temporal Difference Errors in Multi-step Distributional Reinforcement Learning

Yunhao Tang, Rémi Munos, Mark Rowland, Bernardo Avila Pires, Will Dabney

Off-Policy Evaluation with Deficient Support Using Side Information

Nicolò Felicioni, Maurizio Ferrari Dacrema, Marcello Restelli, Paolo Cremonesi

Matryoshka Representation Learning

Aditya Kusupati, Gantavya Bhatt, Aniket Rege, Matthew Wallingford, Aditya Sinha

Graph Scattering beyond Wavelet Shackles

Christian Koke, Gitta Kutyniok

Prune and distill: similar reformatting of image information along rat visual cortex and deep neural networks

Paolo Muratore, Sina Tafazoli, Eugenio Piasini, Alessandro Laio, Davide Zoccolan

Tsetlin Machine for Solving Contextual Bandit Problems

Raihan Seraj, Jivitesh Sharma, Ole-Christoffer Granmo

Efficient Graph Similarity Computation with Alignment Regularization

Wei Zhuo, Guang Tan

Provably Adversarially Robust Detection of Out-of-Distribution Data (Almost) for Free

Alexander Meinke, Julian Bitterwolf, Matthias Hein

GENIE: Higher-Order Denoising Diffusion Solvers

Tim Dockhorn, Arash Vahdat, Karsten Kreis

Finite-Sample Maximum Likelihood Estimation of Location

Shivam Gupta, Jasper Lee, ecprice, Paul Valiant

Draft-and-Revise: Effective Image Generation with Contextual RQ-Transformer

Doyup Lee, Chiheon Kim, Saehoon Kim, Minsu Cho, WOOK SHIN HAN

When to Intervene: Learning Optimal Intervention Policies for Critical Events

Niranjan Damera Venkata, Chiranjib Bhattacharyya

Effects of Data Geometry in Early Deep Learning

Saket Tiwari, George Konidaris

Invariance Learning based on Label Hierarchy

Shoji Toyota, Kenji Fukumizu

A Theoretical View on Sparsely Activated Networks

Cenk Baykal, Nishanth Dikkala, Rina Panigrahy, Cyrus Rashtchian, Xin Wang

VoiceBlock: Privacy through Real-Time Adversarial Attacks with Audio-to-Audio Models

Patrick O'Reilly, Andreas Bugler, Keshav Bhandari, Max Morrison, Bryan Pardo

Characterizing Datapoints via Second-Split Forgetting

Pratyush Maini, Saurabh Garg, Zachary Lipton, J. Zico Kolter

Robust Imitation via Mirror Descent Inverse Reinforcement Learning

Dong-Sig Han, Hyunseo Kim, Hyundo Lee, JeHwan Ryu, Byoung-tak Zhang

An empirical analysis of compute-optimal large language model training

Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai

Learning-based Motion Planning in Dynamic Environments Using GNNs and Temporal Encoding

Ruipeng Zhang, Chenning Yu, Jingkai Chen, Chuchu Fan, Sicun Gao

Revisiting Injective Attacks on Recommender Systems

Haoyang Li, Shimin DI, Lei Chen

CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds

Haiyang Wang, Lihe Ding, Shaocong Dong, Shaoshuai Shi, Aoxue Li

Adapting to Online Label Shift with Provable Guarantees

Yong Bai, Yu-Jie Zhang, Peng Zhao, Masashi Sugiyama, Zhi-Hua Zhou

Semantic Probabilistic Layers for Neuro-Symbolic Learning

Kareem Ahmed, Stefano Teso, Kai-Wei Chang, Guy Van den Broeck, Antonio Vergari

DP-PCA: Statistically Optimal and Differentially Private PCA

Xiyang Liu, Weihao Kong, Prateek Jain, Sewoong Oh

Optimizing Data Collection for Machine Learning

Rafid Mahmood, James Lucas, Jose M. Alvarez, Sanja Fidler, Marc Law

BayesPCN: A Continually Learnable Predictive Coding Associative Memory

Jinsoo Yoo, Frank Wood

Global Convergence of Federated Learning for Mixed Regression

Lili Su, Jiaming Xu, Pengkun Yang

FETA: Towards Specializing Foundational Models for Expert Task Applications

Amit Alfassy, Assaf Arbelle, Oshri Halimi, Sivan Harary, Roei Herzig

Extra-Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods

Kimon Antonakopoulos, Ali Kavis, Volkan Cevher

Boosting the Transferability of Adversarial Attacks with Reverse Adversarial Perturbation

Zeyu Qin, Yanbo Fan, Yi Liu, Li Shen, Yong Zhang

Amplifying Membership Exposure via Data Poisoning

Yufei Chen, Chao Shen, Yun Shen, Cong Wang, Yang Zhang

Batch Bayesian optimisation via density-ratio estimation with guarantees

Rafael Oliveira, Louis Tiao, Fabio T Ramos

Myriad: a real-world testbed to bridge trajectory optimization and deep learning

Nikolaus Howe, Simon Dufort-Labbé, Nitarshan Rajkumar, Pierre-Luc Bacon

Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network

Ravinder Bhattoo, Sayan Ranu, N M Anoop Krishnan

A Benchmark for Compositional Visual Reasoning

Aimen Zerroug, Mohit Vaishnav, Julien Colin, Sebastian Musslick, Thomas Serre

Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks

Chenxiao Yang, Qitian Wu, Junchi Yan

An Investigation into Whitening Loss for Self-supervised Learning

Xi Weng, Lei Huang, lei zhao, Rao Anwer, Salman H Khan

Logical Activation Functions: Logit-space equivalents of Probabilistic Boolean Operators

Scott Lowe, Robert Earle, Jason d'Eon, Thomas P. Trappenberg, Sageev Oore

Depth is More Powerful than Width with Prediction Concatenation in Deep Forest

Shen-Huan Lyu, Yi-Xiao He, Zhi-Hua Zhou

Manifold Interpolating Optimal-Transport Flows for Trajectory Inference

Guillaume Huguet, Daniel Sumner Magruder, Alexander Tong, Oluwadamilola Fasina, Manik Kuchroo

Multi-Lingual Acquisition on Multimodal Pre-training for Cross-modal Retrieval

Liang Zhang, Anwen Hu, Qin Jin

FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction

Samiul Alam, Luyang Liu, Ming Yan, Mi Zhang

Dynamic Inverse Reinforcement Learning for Characterizing Animal Behavior

Zoe Ashwood, Aditi Jha, Jonathan W Pillow

Subsidiary Prototype Alignment for Universal Domain Adaptation

Jogendra Nath Kundu, Suvaansh Bhambri, Akshay R Kulkarni, Hiran Sarkar, Varun Jampani

A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation

Philip Amortila, Nan Jiang, Dhruv Madeka, Dean P. Foster

Mind Reader: Reconstructing complex images from brain activities

Sikun Lin, Thomas Sprague, Ambuj K Singh

Unsupervised Visual Representation Learning via Mutual Information Regularized Assignment

Sungik Choi, Hyunwoo J Kim, Sae-Young Chung, Donghoon Lee, Dong Hoon Lee

MCL-GAN: Generative Adversarial Networks with Multiple Specialized Discriminators

Jinyoung Choi, Bohyung Han

Class-Aware Adversarial Transformers for Medical Image Segmentation

Chenyu You, Ruihan Zhao, Fenglin Liu, Siyuan Dong, Sandeep Chinchali

Coresets for Vertical Federated Learning: Regularized Linear Regression and K-Means Clustering

Lingxiao Huang, Zhize Li, Jialin Sun, Haoyu Zhao

Multi-block Min-max Bilevel Optimization with Applications in Multi-task Deep AUC Maximization

Quanqi Hu, YONGJIAN ZHONG, Tianbao Yang

TUSK: Task-Agnostic Unsupervised Keypoints

Yuhe Jin, Weiwei Sun, Jan Hosang, Eduard Trulls, Kwang Moo Yi

GBA: A Tuning-free Approach to Switch between Synchronous and Asynchronous Training for Recommendation Models

Wenbo Su, Yuanxing Zhang, Yufeng Cai, Kaixu Ren, Pengjie Wang

Unified Optimal Transport Framework for Universal Domain Adaptation

Wanxing Chang, Ye Shi, Hoang Tuan, Jingya Wang

Meta-Complementing the Semantics of Short Texts in Neural Topic Models

Delvin Ce Zhang, Hady Lauw

Dual-Curriculum Contrastive Multi-Instance Learning for Cancer Prognosis Analysis with Whole Slide Images

CHAO TU, Yu Zhang, Zhenyuan Ning

Differentially Private Model Compression

FatemehSadat Mireshghallah, Arturs Backurs, Huseyin A. Inan, Lukas Wutschitz, Janardhan Kulkarni

Bidirectional Learning for Offline Infinite-width Model-based Optimization

Can Chen, Yingxueff Zhang, Jie Fu, Xue (Steve) Liu, Mark Coates

CLiMB: A Continual Learning Benchmark for Vision-and-Language Tasks

Tejas Srinivasan, Ting-Yun Chang, Leticia Pinto Alva, Georgios Chochlakis, Mohammad Rostami