NeurIPS 2022

2,834 papers

Exploiting Semantic Relations for Glass Surface Detection

Jiaying Lin, Yuen-Hei Yeung, Rynson Lau

Make an Omelette with Breaking Eggs: Zero-Shot Learning for Novel Attribute Synthesis

Yu-Hsuan Li, Tzu-Yin Chao, Ching-Chun Huang, Pin-Yu Chen, Wei-Chen Chiu

Ontologue: Declarative Benchmark Construction for Ontological Multi-Label Classification

Sean Yang, Bernease Herman, Bill Howe

FNeVR: Neural Volume Rendering for Face Animation

Bohan Zeng, Boyu Liu, Hong Li, Jianzhuang Liu, Dapeng Chen

Implicit Warping for Animation with Image Sets

Arun Mallya, Ting-Chun Wang, Ming-Yu Liu

Generative Visual Prompt: Unifying Distributional Control of Pre-Trained Generative Models

Chen Henry Wu, Saman Motamed, Shaunak Srivastava, Fernando D De la Torre

EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine

Jiayi Weng, Min Lin, Shengyi Huang, Bo Liu, Denys Makoviichuk

A general approximation lower bound in L^p norm, with applications to feed-forward neural networks

El Mehdi Achour, Armand Foucault, Sébastien Gerchinovitz, François Malgouyres

Training Uncertainty-Aware Classifiers with Conformalized Deep Learning

Bat-Sheva Einbinder, Yaniv Romano, Matteo Sesia, Yanfei Zhou

Uplifting Bandits

Yu-Guan Hsieh, Shiva P. Kasiviswanathan, Branislav Kveton

Active Learning Through a Covering Lens

Ofer Yehuda, Avihu Dekel, Guy Hacohen, Daphna Weinshall

On the inability of Gaussian process regression to optimally learn compositional functions

Matteo Giordano, Kolyan Ray, Johannes Schmidt-Hieber

Long Range Graph Benchmark

Vijay Prakash Dwivedi, Ladislav Rampášek, Michael Galkin, Ali Parviz, Guy Wolf

Efficient Phi-Regret Minimization in Extensive-Form Games via Online Mirror Descent

Yu Bai, Chi Jin, Song Mei, Ziang Song, Tiancheng Yu

Revisiting Neural Scaling Laws in Language and Vision

Ibrahim M Alabdulmohsin, Behnam Neyshabur, Xiaohua Zhai

One-shot Neural Backdoor Erasing via Adversarial Weight Masking

Shuwen Chai, Jinghui Chen

Meta-Reward-Net: Implicitly Differentiable Reward Learning for Preference-based Reinforcement Learning

Runze Liu, Fengshuo Bai, Yali Du, Yaodong Yang

Beyond Time-Average Convergence: Near-Optimal Uncoupled Online Learning via Clairvoyant Multiplicative Weights Update

Georgios Piliouras, Ryann Sim, Stratis Skoulakis

Meta-DMoE: Adapting to Domain Shift by Meta-Distillation from Mixture-of-Experts

Tao Zhong, Zhixiang Chi, Li Gu, Yang Wang, Yuanhao Yu

FiLM-Ensemble: Probabilistic Deep Learning via Feature-wise Linear Modulation

Mehmet Ozgur Turkoglu, Alexander Becker, Hüseyin Anil Gündüz, Mina Rezaei, Bernd Bischl

Trading off Utility, Informativeness, and Complexity in Emergent Communication

Mycal Tucker, Roger P. Levy, Julie A Shah, Noga Zaslavsky

Large Language Models are Zero-Shot Reasoners

Takeshi Kojima, Shixiang (Shane) Gu, Machel Reid, Yutaka Matsuo, Yusuke Iwasawa

A Combinatorial Perspective on the Optimization of Shallow ReLU Networks

Michael S Matena, Colin A Raffel

TA-MoE: Topology-Aware Large Scale Mixture-of-Expert Training

Chang Chen, Min Li, Zhihua Wu, Dianhai Yu, Chao Yang

Non-convex online learning via algorithmic equivalence

Udaya Ghai, Zhou Lu, Elad Hazan

To update or not to update? Neurons at equilibrium in deep models

Andrea Bragagnolo, Enzo Tartaglione, Marco Grangetto

Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs

Yongqiang Chen, Yonggang Zhang, Yatao Bian, Han Yang, MA Kaili

Unsupervised Representation Learning from Pre-trained Diffusion Probabilistic Models

Zijian Zhang, Zhou Zhao, Zhijie Lin

Finding Naturally Occurring Physical Backdoors in Image Datasets

Emily Wenger, Roma Bhattacharjee, Arjun Nitin Bhagoji, Josephine Passananti, Emilio Andere

SGAM: Building a Virtual 3D World through Simultaneous Generation and Mapping

Yuan Shen, Wei-Chiu Ma, Shenlong Wang

Gaussian Copula Embeddings

Chien Lu, Jaakko Peltonen

Probabilistic Missing Value Imputation for Mixed Categorical and Ordered Data

Yuxuan Zhao, Alex Townsend, Madeleine Udell

Coordinate Linear Variance Reduction for Generalized Linear Programming

Chaobing Song, Cheuk Yin Lin, Stephen Wright, Jelena Diakonikolas

Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach

Kaiwen Yang, Yanchao Sun, Jiahao Su, Fengxiang He, Xinmei Tian

Natural gradient enables fast sampling in spiking neural networks

Paul Masset, Jacob Zavatone-Veth, J. Patrick Connor, Venkatesh Murthy, Cengiz Pehlevan

Unsupervised Cross-Task Generalization via Retrieval Augmentation

Bill Yuchen Lin, Kangmin Tan, Chris Miller, Beiwen Tian, Xiang Ren

Panchromatic and Multispectral Image Fusion via Alternating Reverse Filtering Network

Keyu Yan, man zhou, Jie Huang, Feng Zhao, Chengjun Xie

ENS-10: A Dataset For Post-Processing Ensemble Weather Forecasts

Saleh Ashkboos, Langwen Huang, Nikoli Dryden, Tal Ben-Nun, Peter Dueben

Continual Learning In Environments With Polynomial Mixing Times

Matthew Riemer, Sharath Chandra Raparthy, Ignacio Cases, Gopeshh Subbaraj, Maximilian Puelma Touzel

Target alignment in truncated kernel ridge regression

Arash Amini, Richard Baumgartner, Dai Feng

Respecting Transfer Gap in Knowledge Distillation

Yulei Niu, Long Chen, Chang Zhou, Hanwang Zhang

METS-CoV: A Dataset of Medical Entity and Targeted Sentiment on COVID-19 Related Tweets

Peilin Zhou, Zeqiang Wang, Dading Chong, Zhijiang Guo, Yining Hua

C2FAR: Coarse-to-Fine Autoregressive Networks for Precise Probabilistic Forecasting

Shane Bergsma, Tim Zeyl, Javad Rahimipour Anaraki, Lei Guo

Policy Optimization for Markov Games: Unified Framework and Faster Convergence

Runyu Zhang, Qinghua Liu, Huan Wang, Caiming Xiong, Na Li

3DILG: Irregular Latent Grids for 3D Generative Modeling

Biao Zhang, Matthias Niessner, Peter Wonka

Last-Iterate Convergence of Optimistic Gradient Method for Monotone Variational Inequalities

Eduard Gorbunov, Adrien Taylor, Gauthier Gidel

Insights into Pre-training via Simpler Synthetic Tasks

Yuhuai Wu, Felix Li, Percy Liang

Transformer Memory as a Differentiable Search Index

Yi Tay, Vinh Tran, Mostafa Dehghani, Jianmo Ni, Dara Bahri

An In-depth Study of Stochastic Backpropagation

Jun Fang, Mingze Xu, Hao Chen, Bing Shuai, Zhuowen Tu

This is the way: designing and compiling LEPISZCZE, a comprehensive NLP benchmark for Polish

Lukasz Augustyniak, Kamil Tagowski, Albert Sawczyn, Denis Janiak, Roman Bartusiak

Aligning individual brains with fused unbalanced Gromov Wasserstein

Alexis Thual, Quang Huy TRAN, Tatiana Zemskova, Nicolas Courty, Rémi Flamary

Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox

Abdurakhmon Sadiev, Dmitry Kovalev, Peter Richtarik

One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement

Ning Xu, Congyu Qiao, Jiaqi Lv, Xin Geng, Min-ling Zhang

Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit

Boaz Barak, Benjamin Edelman, Surbhi Goel, Sham Kakade, Eran Malach

Diffusion Curvature for Estimating Local Curvature in High Dimensional Data

Dhananjay Bhaskar, Kincaid MacDonald, Oluwadamilola Fasina, Dawson Thomas, Bastian Rieck

Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling

Dmitry Kovalev, Alexander Gasnikov, Peter Richtarik

LISA: Learning Interpretable Skill Abstractions from Language

Divyansh Garg, Skanda Vaidyanath, Kuno Kim, Jiaming Song, Stefano Ermon

Decoupled Context Processing for Context Augmented Language Modeling

Zonglin Li, Ruiqi Guo, Sanjiv Kumar

Contrastive Adapters for Foundation Model Group Robustness

Michael Zhang, Christopher Re

SAPD+: An Accelerated Stochastic Method for Nonconvex-Concave Minimax Problems

Xuan Zhang, Necdet Serhat Aybat, Mert Gurbuzbalaban

Multi-fidelity Monte Carlo: a pseudo-marginal approach

Diana Cai, Ryan P. Adams

Meta-Learning Dynamics Forecasting Using Task Inference

Rui Wang, Robin Walters, Rose Yu

Bridging Central and Local Differential Privacy in Data Acquisition Mechanisms

Alireza Fallah, Ali Makhdoumi, azarakhsh malekian, Asuman Ozdaglar

Fair Wrapping for Black-box Predictions

Alexander Soen, Ibrahim M Alabdulmohsin, Sanmi Koyejo, Yishay Mansour, Nyalleng Moorosi

An Analysis of Ensemble Sampling

Chao Qin, Zheng Wen, Xiuyuan Lu, Benjamin Van Roy

Adaptive Multi-stage Density Ratio Estimation for Learning Latent Space Energy-based Model

Zhisheng Xiao, Tian Han

Pythae: Unifying Generative Autoencoders in Python - A Benchmarking Use Case

Clément Chadebec, Louis Vincent, Stéphanie ALLASSONNIERE

Exploring the Latent Space of Autoencoders with Interventional Assays

Felix Leeb, Stefan Bauer, Michel Besserve, Bernhard Schölkopf

A Contrastive Framework for Neural Text Generation

Yixuan Su, Tian Lan, Yan Wang, Dani Yogatama, Lingpeng Kong

Adaptation Accelerating Sampling-based Bayesian Inference in Attractor Neural Networks

Xingsi Dong, Zilong Ji, Tianhao Chu, Tiejun Huang, Wenhao Zhang

Non-Gaussian Tensor Programs

Eugene Golikov, Greg Yang

Entropy-Driven Mixed-Precision Quantization for Deep Network Design

Zhenhong Sun, Ce Ge, Junyan Wang, Ming Lin, Hesen Chen

PaCo: Parameter-Compositional Multi-task Reinforcement Learning

Lingfeng Sun, Haichao Zhang, Wei Xu, Masayoshi Tomizuka

Score-Based Diffusion meets Annealed Importance Sampling

Arnaud Doucet, Will Grathwohl, Alexander G Matthews, Heiko Strathmann

Stars: Tera-Scale Graph Building for Clustering and Learning

CJ Carey, Jonathan Halcrow, Rajesh Jayaram, Vahab Mirrokni, Warren Schudy

Quality Not Quantity: On the Interaction between Dataset Design and Robustness of CLIP

Thao Nguyen, Gabriel Ilharco, Mitchell Wortsman, Sewoong Oh, Ludwig Schmidt

Fine-Tuning Pre-Trained Language Models Effectively by Optimizing Subnetworks Adaptively

Haojie Zhang, Ge Li, Jia Li, Zhongjin Zhang, YUQI ZHU

Searching for Better Spatio-temporal Alignment in Few-Shot Action Recognition

Yichao Cao, Xiu Su, Qingfei Tang, Shan You, Xiaobo Lu

DENSE: Data-Free One-Shot Federated Learning

Jie Zhang, Chen Chen, Bo Li, Lingjuan Lyu, Shuang Wu

Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off

Mateo Espinosa Zarlenga, Pietro Barbiero, Gabriele Ciravegna, Giuseppe Marra, Francesco Giannini

Audio-Driven Co-Speech Gesture Video Generation

Xian Liu, Qianyi Wu, Hang Zhou, Yuanqi Du, Wayne Wu

UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANs

Philipp Oberdiek, Gernot Fink, Matthias Rottmann

MGNNI: Multiscale Graph Neural Networks with Implicit Layers

Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Xiaokui Xiao

Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization

Wenhao Gao, Tianfan Fu, Jimeng Sun, Connor Coley

Leveraging the Hints: Adaptive Bidding in Repeated First-Price Auctions

Wei Zhang, Yanjun Han, Zhengyuan Zhou, Aaron Flores, Tsachy Weissman

CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning

Hung Le, Yue Wang, Akhilesh Deepak Gotmare, Silvio Savarese, Steven Chu Hong Hoi

Towards Efficient 3D Object Detection with Knowledge Distillation

Jihan Yang, Shaoshuai Shi, Runyu Ding, Zhe Wang, Xiaojuan Qi

A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models

Lijia Zhou, Frederic Koehler, Pragya Sur, Danica J. Sutherland, Nati Srebro

Characterization of Excess Risk for Locally Strongly Convex Population Risk

Mingyang Yi, Ruoyu Wang, Zhi-ming Ma

Self-Supervised Learning of Brain Dynamics from Broad Neuroimaging Data

Armin Thomas, Christopher Re, Russell Poldrack

Masked Prediction: A Parameter Identifiability View

Bingbin Liu, Daniel J. Hsu, Andrej Risteski, Pradeep K Ravikumar, Pradeep K. Ravikumar

3DOS: Towards 3D Open Set Learning - Benchmarking and Understanding Semantic Novelty Detection on Point Clouds

Antonio Alliegro, Francesco Cappio Borlino, Tatiana Tommasi

GlanceNets: Interpretable, Leak-proof Concept-based Models

Emanuele Marconato, Andrea Passerini, Stefano Teso

Fixed-Distance Hamiltonian Monte Carlo

Hadi Mohasel Afshar, Sally Cripps

Learning Options via Compression

YiDing Jiang, Evan Liu, Benjamin Eysenbach, J. Zico Kolter, Chelsea Finn

Hierarchical Graph Transformer with Adaptive Node Sampling

ZAIXI ZHANG, Qi Liu, Qingyong Hu, Chee-Kong Lee

u-HuBERT: Unified Mixed-Modal Speech Pretraining And Zero-Shot Transfer to Unlabeled Modality

Wei-Ning Hsu, Bowen Shi

Evaluating Latent Space Robustness and Uncertainty of EEG-ML Models under Realistic Distribution Shifts

Neeraj Wagh, Jionghao Wei, Samarth Rawal, Brent M Berry, Yogatheesan Varatharajah

RSA: Reducing Semantic Shift from Aggressive Augmentations for Self-supervised Learning

Yingbin Bai, Erkun Yang, Zhaoqing Wang, Yuxuan Du, Bo Han

An Analytical Theory of Curriculum Learning in Teacher-Student Networks

Luca Saglietti, Stefano Mannelli, Andrew Saxe