NeurIPS

Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models

Thomas P. Zollo, Todd Morrill, Zhun Deng, Jake C. Snell, Toniann Pitassi, Richard Zemel

Comments 34 pages, 10 figures, published as conference paper at ICLR 2024, and accepted to the Socially Responsible Language Modelling Research (SoLaR) workshop at NeurIPS 2023

An optimal control perspective on diffusion-based generative modeling

Julius Berner, Lorenz Richter, Karen Ullrich

Comments Accepted for oral presentation at NeurIPS 2022 Workshop on Score-Based Methods

Journal ref Transactions on Machine Learning Research, 2024

Covariance-Aware Private Mean Estimation Without Private Covariance Estimation

Gavin Brown, Marco Gaboardi, Adam Smith, Jonathan Ullman, Lydia Zakynthinou

Comments 49 pages. Appeared in NeurIPS 2021. Updated version contains improved analysis of Tukey depth mechanism: robustness guarantees, tighter error analysis, and techniques for faster implementation

DISN: Deep Implicit Surface Network for High-quality Single-view 3D Reconstruction

Qiangeng Xu, Weiyue Wang, Duygu Ceylan, Radomir Mech, Ulrich Neumann

Comments This project was in part supported by the gift funding to the University of Southern California from Adobe Research

Journal ref 33rd Annual Conference on Neural Information Processing Systems (NeurIPS 2019)

The Hidden Linear Structure in Score-Based Models and its Application

Binxu Wang, John J. Vastola

Comments Accepted to Workshop on Diffusion Models in NeurIPS 2023. 24 pages, 8 figures. arXiv admin note: text overlap with arXiv:2311.10892

Bird's Eye View Based Pretrained World model for Visual Navigation

Kiran Lekkala, Chen Liu, Laurent Itti

Comments Under Review at the IROS 2024; Accepted at NeurIPS 2023, Robot Learning Workshop

Bootstrapped Training of Score-Conditioned Generator for Offline Design of Biological Sequences

Minsu Kim, Federico Berto, Sungsoo Ahn, Jinkyoo Park

Comments NeurIPS 2023, 19 pages, 5 figures

PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model

Yizhe Zhang, Jiatao Gu, Zhuofeng Wu, Shuangfei Zhai, Josh Susskind, Navdeep Jaitly

Comments Accepted by NeurIPS 2023, code at https://github.com/apple/ml-planner

A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning

Xidong Feng, Bo Liu, Jie Ren, Luo Mai, Rui Zhu, Haifeng Zhang, Jun Wang, Yaodong Yang

Comments NeurIPS 2022

Generalisable Agents for Neural Network Optimisation

Kale-ab Tessera, Callum Rhys Tilbury, Sasha Abramowitz, Ruan de Kock, Omayma Mahjoub, Benjamin Rosman, Sara Hooker, Arnu Pretorius

Comments Accepted at the Workshop on Advanced Neural Network Training (WANT) and Optimization for Machine Learning (OPT) at NeurIPS 2023

SoftPatch: Unsupervised Anomaly Detection with Noisy Data

Xi Jiang, Ying Chen, Qiang Nie, Yong Liu, Jianlin Liu, Bin-Bin Gao, Jun Liu, Chengjie Wang, Feng Zheng

Comments 36th Conference on Neural Information Processing Systems

Journal ref Advances in Neural Information Processing Systems 35, ISBN: 9781713871088, (2022)

RiskQ: Risk-sensitive Multi-Agent Reinforcement Learning Value Factorization

Siqi Shen, Chennan Ma, Chao Li, Weiquan Liu, Yongquan Fu, Songzhu Mei, Xinwang Liu, Cheng Wang

Comments Accepted at NeurIPS 2023

QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules

Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

Comments Accepted by NeurIPS 2023, Track on Datasets and Benchmarks

From Tempered to Benign Overfitting in ReLU Neural Networks

Guy Kornowski, Gilad Yehudai, Ohad Shamir

Comments NeurIPS 2023; fixed bug

Latent Field Discovery In Interacting Dynamical Systems With Neural Fields

Miltiadis Kofinas, Erik J. Bekkers, Naveen Shankar Nagaraja, Efstratios Gavves

Comments In NeurIPS 2023. Source code: https://github.com/mkofinas/aether

Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation

Shreyas Havaldar, Navodita Sharma, Shubhi Sareen, Karthikeyan Shanmugam, Aravindan Raghuveer

Comments Published as a conference paper at The Twelfth International Conference on Learning Representations (ICLR 2024) & Oral Presentation at Regulatable ML @ NeurIPS 2023

Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spaces

Leonard Papenmeier, Luigi Nardi, Matthias Poloczek

Comments 30 pages, 22 figures

Journal ref Advances in Neural Information Processing Systems 36 (NeurIPS 2023)

Jaccard Metric Losses: Optimizing the Jaccard Index with Soft Labels

Zifu Wang, Xuefei Ning, Matthew B. Blaschko

Comments NeurIPS 2023

Long N-step Surrogate Stage Reward to Reduce Variances of Deep Reinforcement Learning in Complex Problems

Junmin Zhong, Ruofan Wu, Jennie Si

Journal ref Advances in Neural Information Processing Systems 2023

Roto-translated Local Coordinate Frames For Interacting Dynamical Systems

Miltiadis Kofinas, Naveen Shankar Nagaraja, Efstratios Gavves

Comments In NeurIPS 2021. Source code: https://github.com/mkofinas/locs

TMT-VIS: Taxonomy-aware Multi-dataset Joint Training for Video Instance Segmentation

Rongkun Zheng, Lu Qi, Xi Chen, Yi Wang, Kun Wang, Yu Qiao, Hengshuang Zhao

Comments NeurIPS 2023

Proximity-Informed Calibration for Deep Neural Networks

Miao Xiong, Ailin Deng, Pang Wei Koh, Jiaying Wu, Shen Li, Jianqing Xu, Bryan Hooi

Comments The paper is accepted by NeurIPS 2023. The code is available at: https://github.com/MiaoXiong2320/ProximityBias-Calibration

Classification of Heavy-tailed Features in High Dimensions: a Superstatistical Approach

Urte Adomaityte, Gabriele Sicuro, Pierpaolo Vivo

Comments 25 pages, 8 figures

Journal ref Advances in Neural Information Processing Systems 36 (2024)

Provably Bounding Neural Network Preimages

Suhas Kotha, Christopher Brix, Zico Kolter, Krishnamurthy Dvijotham, Huan Zhang

Comments NeurIPS 2023 (Spotlight)

Generalized Munchausen Reinforcement Learning using Tsallis KL Divergence

Lingwei Zhu, Zheng Chen, Matthew Schlegel, Martha White

Comments Accepted by NeurIPS 2023

Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity

William de Vazelhes, Hualin Zhang, Huimin Wu, Xiao-Tong Yuan, Bin Gu

Comments Accepted for publication at NeurIPS 2022

Improving Fairness in Credit Lending Models using Subgroup Threshold Optimization

Cecilia Ying, Stephen Thomas

Comments Neural Information Processing Systems (NeurIPS) Workshop in Strategic ML

Energy Correction Model in the Feature Space for Out-of-Distribution Detection

Marc Lafon, Clément Rambour, Nicolas Thome

Comments NeurIPS ML Safety Workshop (2022)

xLP: Explainable Link Prediction for Master Data Management

Balaji Ganesan, Matheen Ahmed Pasha, Srinivasa Parkala, Neeraj R Singh, Gayatri Mishra, Sumit Bhatia, Hima Patel, Somashekar Naganna, Sameep Mehta

Comments 8 pages, 4 figures, NeurIPS 2020 Competition and Demonstration Track. arXiv admin note: text overlap with arXiv:2012.05516

Platypus: Quick, Cheap, and Powerful Refinement of LLMs

Ariel N. Lee, Cole J. Hunter, Nataniel Ruiz

Comments Workshop on Instruction Tuning and Instruction Following at NeurIPS 2023