NeurIPS 2023

3,540 papers

Symbolic Discovery of Optimization Algorithms

Xiangning Chen, Chen Liang, Da Huang, Esteban Real, Kaiyuan Wang

Time Series as Images: Vision Transformer for Irregularly Sampled Time Series

Zekun Li, Shiyang Li, Xifeng Yan

TD Convergence: An Optimization Perspective

Kavosh Asadi, Shoham Sabach, Yao Liu, Omer Gottesman, Rasool Fakoor

Training Transformers with 4-bit Integers

Haocheng Xi, ChangHao Li, Jianfei Chen, Jun Zhu

A Smooth Binary Mechanism for Efficient Private Continual Observation

Joel Daniel Andersson, Rasmus Pagh

Aligning Language Models with Human Preferences via a Bayesian Approach

Jiashuo WANG, Haozhao Wang, Shichao Sun, Wenjie Li

Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object Detection

Cheng-Ju Ho, Chen-Hsuan Tai, Yen-yu Lin, Ming-Hsuan Yang, Yi-Hsuan Tsai

Sequential Preference Ranking for Efficient Reinforcement Learning from Human Feedback

Minyoung Hwang, Gunmin Lee, Hogun Kee, Chan Woo Kim, Kyungjae Lee

An Inverse Scaling Law for CLIP Training

Xianhang Li, Zeyu Wang, Cihang Xie

Learning Transformer Programs

Dan Friedman, Alexander Wettig, Danqi Chen

RealTime QA: What's the Answer Right Now?

Jungo Kasai, Keisuke Sakaguchi, yoichi takahashi, Ronan Le Bras, Akari Asai

PETAL: Physics Emulation Through Averaged Linearizations for Solving Inverse Problems

Jihui Jin, Etienne Ollivier, Richard Touret, Matthew McKinley, Karim Sabra

Predicting mutational effects on protein-protein binding via a side-chain diffusion probabilistic model

Shiwei Liu, Tian Zhu, Milong Ren, Chungong Yu, Dongbo Bu

QuadAttacK: A Quadratic Programming Approach to Learning Ordered Top-K Adversarial Attacks

Thomas Paniagua, Ryan Grainger, Tianfu Wu

Global Update Tracking: A Decentralized Learning Algorithm for Heterogeneous Data

Sai Aparna Aketi, Abolfazl Hashemi, Kaushik Roy

Generalization bounds for neural ordinary differential equations and deep residual networks

Pierre Marion

Advancing Bayesian Optimization via Learning Correlated Latent Space

Seunghun Lee, Jaewon Chu, Sihyeon Kim, Juyeon Ko, Hyunwoo J Kim

Optimal Treatment Allocation for Efficient Policy Evaluation in Sequential Decision Making

ting li, Chengchun Shi, Jianing Wang, Fan Zhou, Hongtu Zhu

The Drunkard’s Odometry: Estimating Camera Motion in Deforming Scenes

David Recasens Lafuente, Martin R. Oswald, Marc Pollefeys, Javier Civera

Diff-Foley: Synchronized Video-to-Audio Synthesis with Latent Diffusion Models

Simian Luo, Chuanhao Yan, Chenxu Hu, Hang Zhao

A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm

Ilias Diakonikolas, Daniel Kane, Jasper Lee, Ankit Pensia, Thanasis Pittas

Fantastic Robustness Measures: The Secrets of Robust Generalization

Hoki Kim, Jinseong Park, Yujin Choi, Jaewook Lee

SLIBO-Net: Floorplan Reconstruction via Slicing Box Representation with Local Geometry Regularization

Jheng-Wei Su, Kuei-Yu Tung, Chi-Han Peng, Peter Wonka, Hung-Kuo (James) Chu

CLeAR: Continual Learning on Algorithmic Reasoning for Human-like Intelligence

Bong Gyun Kang, HyunGi Kim, Dahuin Jung, Sungroh Yoon

Meek Separators and Their Applications in Targeted Causal Discovery

Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler

ImageBrush: Learning Visual In-Context Instructions for Exemplar-Based Image Manipulation

ya sheng sun, Yifan Yang, Houwen Peng, Yifei Shen, Yuqing Yang

Learning Interpretable Low-dimensional Representation via Physical Symmetry

Xuanjie Liu, Daniel Chin, Yichen Huang, Gus Xia

Temporal Dynamic Quantization for Diffusion Models

Junhyuk So, Jungwon Lee, Daehyun Ahn, Hyungjun Kim, Eunhyeok Park

Hierarchical Gaussian Mixture based Task Generative Model for Robust Meta-Learning

Yizhou Zhang, Jingchao Ni, Wei Cheng, Zhengzhang Chen, Liang Tong

Dual Mean-Teacher: An Unbiased Semi-Supervised Framework for Audio-Visual Source Localization

Yuxin Guo, Shijie Ma, Hu Su, Zhiqing Wang, Yuhao Zhao

Nonparametric Identifiability of Causal Representations from Unknown Interventions

Julius von Kügelgen, Michel Besserve, Liang Wendong, Luigi Gresele, Armin Kekić

Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks

Minki Kang, Seanie Lee, Jinheon Baek, Kenji Kawaguchi, Sung Ju Hwang

Prefix-Tree Decoding for Predicting Mass Spectra from Molecules

Samuel Goldman, John Bradshaw, Jiayi Xin, Connor Coley

Provable Guarantees for Generative Behavior Cloning: Bridging Low-Level Stability and High-Level Behavior

Adam Block, Ali Jadbabaie, Daniel Pfrommer, Max Simchowitz, Russ Tedrake

Revisiting Scalarization in Multi-Task Learning: A Theoretical Perspective

Yuzheng Hu, Ruicheng Xian, Qilong Wu, Qiuling Fan, Lang Yin

Winner Takes It All: Training Performant RL Populations for Combinatorial Optimization

Nathan Grinsztajn, Daniel Furelos-Blanco, Shikha Surana, Clément Bonnet, Tom Barrett

Creating Multi-Level Skill Hierarchies in Reinforcement Learning

Joshua B. Evans, Ozgur Simsek

Kissing to Find a Match: Efficient Low-Rank Permutation Representation

Hannah Dröge, Zorah Lähner, Yuval Bahat, Onofre Martorell Nadal, Felix Heide

Annotator: A Generic Active Learning Baseline for LiDAR Semantic Segmentation

Binhui Xie, Shuang Li, Qingju Guo, Chi Liu, Xinjing Cheng

Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming

Gregory Dexter, Petros Drineas, David Woodruff, Taisuke Yasuda

A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning

Zitai Wang, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao

DropCompute: simple and more robust distributed synchronous training via compute variance reduction

Niv Giladi, Shahar Gottlieb, moran shkolnik, Asaf Karnieli, Ron Banner

StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners

Yonglong Tian, Lijie Fan, Phillip Isola, Huiwen Chang, Dilip Krishnan

Locality-Aware Generalizable Implicit Neural Representation

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

Max-Margin Token Selection in Attention Mechanism

Davoud Ataee Tarzanagh, Yingcong Li, Xuechen Zhang, Samet Oymak

Semantic segmentation of sparse irregular point clouds for leaf/wood discrimination

Yuchen BAI, Jean-Baptiste Durand, Grégoire Vincent, Florence Forbes

Imitation Learning from Vague Feedback

Xin-Qiang Cai, Yu-Jie Zhang, Chao-Kai Chiang, Masashi Sugiyama

On the choice of Perception Loss Function for Learned Video Compression

Sadaf Salehkalaibar, Truong Buu Phan, Jun Chen, Wei Yu, Ashish Khisti

TACO: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning

Ruijie Zheng, Xiyao Wang, Yanchao Sun, Shuang Ma, Jieyu Zhao

Noether Embedding: Efficient Learning of Temporal Regularities

Chi Gao, Zidong Zhou, Luping Shi

ARTIC3D: Learning Robust Articulated 3D Shapes from Noisy Web Image Collections

Chun-Han Yao, Amit Raj, Wei-Chih Hung, Michael Rubinstein, Yuanzhen Li

DiffPack: A Torsional Diffusion Model for Autoregressive Protein Side-Chain Packing

Yangtian Zhang, Zuobai Zhang, Bozitao Zhong, Sanchit Misra, Jian Tang

Online PCA in Converging Self-consistent Field Equations

Xihan Li, Xiang Chen, Rasul Tutunov, Haitham Bou Ammar, Lei Wang

Bypass Exponential Time Preprocessing: Fast Neural Network Training via Weight-Data Correlation Preprocessing

Josh Alman, 杰昊梁, Zhao Song, Ruizhe Zhang, Danyang Zhuo

No-regret Algorithms for Fair Resource Allocation

Abhishek Sinha, Ativ Joshi, Rajarshi Bhattacharjee, Cameron Musco, Mohammad Hajiesmaili

Unsupervised Optical Flow Estimation with Dynamic Timing Representation for Spike Camera

Lujie Xia, Ziluo Ding, Rui Zhao, Jiyuan Zhang, Lei Ma

Retaining Beneficial Information from Detrimental Data for Neural Network Repair

Long-Kai Huang, Peilin Zhao, Junzhou Huang, Sinno Pan

Reliable learning in challenging environments

Maria-Florina F Balcan, Steve Hanneke, Rattana Pukdee, Dravyansh Sharma

Pareto Frontiers in Deep Feature Learning: Data, Compute, Width, and Luck

Benjamin Edelman, Surbhi Goel, Sham Kakade, Eran Malach, Cyril Zhang

Unbiased Compression Saves Communication in Distributed Optimization: When and How Much?

Yutong He, Xinmeng Huang, Kun Yuan

On the Identifiability of Sparse ICA without Assuming Non-Gaussianity

Ignavier Ng, Yujia Zheng, Xinshuai Dong, Kun Zhang

Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors

Tom Hartvigsen, Swami Sankaranarayanan, Hamid Palangi, Yoon Kim, Marzyeh Ghassemi

AD-PT: Autonomous Driving Pre-Training with Large-scale Point Cloud Dataset

Jiakang Yuan, Bo Zhang, Xiangchao Yan, Botian Shi, Tao Chen

Online Performative Gradient Descent for Learning Nash Equilibria in Decision-Dependent Games

Zihan Zhu, Ethan Fang, Zhuoran Yang

Fast Exact Leverage Score Sampling from Khatri-Rao Products with Applications to Tensor Decomposition

Vivek Bharadwaj, Osman Asif Malik, Riley Murray, Laura Grigori, Aydin Buluc

Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees

Đorđe Žikelić, Mathias Lechner, Abhinav Verma, Krishnendu Chatterjee, Thomas Henzinger

Mechanic: A Learning Rate Tuner

Ashok Cutkosky, Aaron Defazio, Harsh Mehta

Multi-task Representation Learning for Pure Exploration in Bilinear Bandits

Subhojyoti Mukherjee, Qiaomin Xie, Josiah Hanna, Robert Nowak

Credal Marginal MAP

Radu Marinescu, Debarun Bhattacharjya, Junkyu Lee, Fabio Cozman, Alexander G. Gray

Understanding and Mitigating Copying in Diffusion Models

Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, Tom Goldstein

Transformers over Directed Acyclic Graphs

Yuankai Luo, Veronika Thost, Lei Shi

Debias Coarsely, Sample Conditionally: Statistical Downscaling through Optimal Transport and Probabilistic Diffusion Models

Zhong Yi Wan, Ricardo Baptista, Anudhyan Boral, John Anderson, Fei Sha

Optimal Treatment Regimes for Proximal Causal Learning

Tao Shen, Yifan Cui

Temporal Robustness against Data poisoning

Wenxiao Wang, Soheil Feizi

Simple and Controllable Music Generation

Jade Copet, Felix Kreuk, Itai Gat, Tal Remez, David Kant

Conformal Meta-learners for Predictive Inference of Individual Treatment Effects

Ahmed M. Alaa, Zaid Ahmad, Mark van der Laan

OpenAssistant Conversations - Democratizing Large Language Model Alignment

Andreas Kopf, Yannic Kilcher, Dimitri von Rütte, Sotiris Anagnostidis, Zhi Rui Tam

DELTA: Diverse Client Sampling for Fasting Federated Learning

Lin Wang, Yongxin Guo, Tao LIN, Xiaoying Tang

DeepPCR: Parallelizing Sequential Operations in Neural Networks

Federico Danieli, Miguel Sarabia, Xavier Suau Cuadros, Pau Rodriguez, Luca Zappella

Causal Fairness for Outcome Control

Drago Plecko, Elias Bareinboim

A Robust and Opponent-Aware League Training Method for StarCraft II

Ruozi Huang, Xipeng Wu, Hongsheng Yu, Zhong Fan, Haobo Fu

Scaling Laws for Hyperparameter Optimization

Arlind Kadra, Maciej Janowski, Martin Wistuba, Josif Grabocka

No Change, No Gain: Empowering Graph Neural Networks with Expected Model Change Maximization for Active Learning

Zixing Song, Yifei Zhang, Irwin King

Diffusion Hyperfeatures: Searching Through Time and Space for Semantic Correspondence

Grace Luo, Lisa Dunlap, Dong Huk Park, Aleksander Holynski, Trevor Darrell

Block Broyden's Methods for Solving Nonlinear Equations

Chengchang Liu, Cheng Chen, Luo Luo, John C.S. Lui

MathNAS: If Blocks Have a Role in Mathematical Architecture Design

Qinsi Wang, Jinghan Ke, Zhi Liang, Sihai Zhang

A^2CiD^2: Accelerating Asynchronous Communication in Decentralized Deep Learning

Adel Nabli, Eugene Belilovsky, Edouard Oyallon

Domain Agnostic Fourier Neural Operators

Ning Liu, Siavash Jafarzadeh, Yue Yu

Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds

Taira Tsuchiya, Shinji Ito, Junya Honda

Normalizing flow neural networks by JKO scheme

Chen Xu, Xiuyuan Cheng, Yao Xie

Assumption violations in causal discovery and the robustness of score matching

Francesco Montagna, Atalanti Mastakouri, Elias Eulig, Nicoletta Noceti, Lorenzo Rosasco

FOCAL: Contrastive Learning for Multimodal Time-Series Sensing Signals in Factorized Orthogonal Latent Space

Shengzhong Liu, Tomoyoshi Kimura, Dongxin Liu, Ruijie Wang, Jinyang Li

ContinuAR: Continuous Autoregression For Infinite-Fidelity Fusion

Wei Xing, Yuxin Wang, Zheng Xing

Unsupervised Learning for Solving the Travelling Salesman Problem

Yimeng Min, Yiwei Bai, Carla P. Gomes

Equivariant Single View Pose Prediction Via Induced and Restriction Representations

Owen Howell, David Klee, Ondrej Biza, Linfeng Zhao, Robin Walters

Generalizable One-shot 3D Neural Head Avatar

Xueting Li, Shalini De Mello, Sifei Liu, Koki Nagano, Umar Iqbal

Connecting Pre-trained Language Model and Downstream Task via Properties of Representation

Chenwei Wu, Holden Lee, Rong Ge

Differentiable Random Partition Models

Thomas Sutter, Alain Ryser, Joram Liebeskind, Julia Vogt

ContiFormer: Continuous-Time Transformer for Irregular Time Series Modeling

Yuqi Chen, Kan Ren, Yansen Wang, Yuchen Fang, Weiwei Sun

Propagating Knowledge Updates to LMs Through Distillation

Shankar Padmanabhan, Yasumasa Onoe, Michael Zhang, Greg Durrett, Eunsol Choi