NeurIPS

DELTA: Diverse Client Sampling for Fasting Federated Learning

Lin Wang, YongXin Guo, Tao Lin, Xiaoying Tang

Comments Accepted by Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023)

Distributionally Robust Bayesian Optimization with $φ$-divergences

Hisham Husain, Vu Nguyen, Anton van den Hengel

Comments NeurIPS 2023 camera ready paper

Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt

Yining Ma, Zhiguang Cao, Yeow Meng Chee

Comments Accepted at NeurIPS 2023

How Re-sampling Helps for Long-Tail Learning?

Jiang-Xin Shi, Tong Wei, Yuke Xiang, Yu-Feng Li

Comments Accepted by NeurIPS 2023

Sample Complexity Bounds for Score-Matching: Causal Discovery and Generative Modeling

Zhenyu Zhu, Francesco Locatello, Volkan Cevher

Comments Accepted in NeurIPS 2023

On kernel-based statistical learning in the mean field limit

Christian Fiedler, Michael Herty, Sebastian Trimpe

Comments NeurIPS 2023

Moral Responsibility for AI Systems

Sander Beckers

Comments Accepted at NeurIPS 2023

Closing the Gap Between the Upper Bound and the Lower Bound of Adam's Iteration Complexity

Bohan Wang, Jingwen Fu, Huishuai Zhang, Nanning Zheng, Wei Chen

Comments NeurIPS 2023 Accept

Diversifying Spatial-Temporal Perception for Video Domain Generalization

Kun-Yu Lin, Jia-Run Du, Yipeng Gao, Jiaming Zhou, Wei-Shi Zheng

Comments Accepted to NeurIPS 2023. Code is available at https://github.com/KunyuLin/STDN/

SmooSeg: Smoothness Prior for Unsupervised Semantic Segmentation

Mengcheng Lan, Xinjiang Wang, Yiping Ke, Jiaxing Xu, Litong Feng, Wayne Zhang

Comments Accepted by NeurIPS 2023. Code available: https://github.com/mc-lan/SmooSeg

Reproducibility in Multiple Instance Learning: A Case For Algorithmic Unit Tests

Edward Raff, James Holt

Comments To appear in the 37th Conference on Neural Information Processing Systems (NeurIPS 2023)

Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks

Ryan Sullivan, Akarsh Kumar, Shengyi Huang, John P. Dickerson, Joseph Suarez

Comments Accepted to NeurIPS 2023

A Dataset of Relighted 3D Interacting Hands

Gyeongsik Moon, Shunsuke Saito, Weipeng Xu, Rohan Joshi, Julia Buffalini, Harley Bellan, Nicholas Rosen, Jesse Richardson, Mallorie Mize, Philippe de Bree, Tomas Simon, Bo Peng, Shubham Garg, Kevyn McPhail, Takaaki Shiratori

Comments Accepted by NeurIPS 2023 (Datasets and Benchmarks Track)

SPA: A Graph Spectral Alignment Perspective for Domain Adaptation

Zhiqing Xiao, Haobo Wang, Ying Jin, Lei Feng, Gang Chen, Fei Huang, Junbo Zhao

Comments NeurIPS 2023 camera ready

Global Structure-Aware Diffusion Process for Low-Light Image Enhancement

Jinhui Hou, Zhiyu Zhu, Junhui Hou, Hui Liu, Huanqiang Zeng, Hui Yuan

Comments Accepted to NeurIPS 2023

Human-Guided Complexity-Controlled Abstractions

Andi Peng, Mycal Tucker, Eoin Kenny, Noga Zaslavsky, Pulkit Agrawal, Julie Shah

Comments NeurIPS 2023

Aberrant High-Order Dependencies in Schizophrenia Resting-State Functional MRI Networks

Qiang Li, Vince D. Calhoun, Adithya Ram Ballem, Shujian Yu, Jesus Malo, Armin Iraji

Comments 7 pages, 4 figures, Accepted to InfoCog@NeurIPS 2023 (https://sites.google.com/view/infocog-neurips-2023/home)

LightSpeed: Light and Fast Neural Light Fields on Mobile Devices

Aarush Gupta, Junli Cao, Chaoyang Wang, Ju Hu, Sergey Tulyakov, Jian Ren, László A Jeni

Comments Project Page: http://lightspeed-r2l.github.io/ . Add camera ready version

Journal ref NeurIPS 2023

Multi-scale Diffusion Denoised Smoothing

Jongheon Jeong, Jinwoo Shin

Comments Published as a conference paper at NeurIPS 2023; Code is available at https://github.com/jh-jeong/smoothing-multiscale

GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels

Xin Zheng, Miao Zhang, Chunyang Chen, Soheila Molaei, Chuan Zhou, Shirui Pan

Comments Accepted by NeurIPS 2023

Representation Learning via Consistent Assignment of Views over Random Partitions

Thalles Silva, Adín Ramírez Rivera

Comments To appear in NeurIPS 2023. Code available at https://github.com/sthalles/carp

Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games

Youbang Sun, Tao Liu, Ruida Zhou, P. R. Kumar, Shahin Shahrampour

Comments Will appear in NeurIPS 2023

Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction

Hanhan Zhou, Tian Lan, Guru Venkataramani, Wenbo Ding

Comments Accepted at NeurIPS 2023

Epidemic Learning: Boosting Decentralized Learning with Randomized Communication

Martijn de Vos, Sadegh Farhadkhani, Rachid Guerraoui, Anne-Marie Kermarrec, Rafael Pires, Rishi Sharma

Comments Accepted paper at NeurIPS 2023

Memory Efficient Optimizers with 4-bit States

Bingrui Li, Jianfei Chen, Jun Zhu

Comments v3: camera ready revisions for NeurIPS 2023

Towards Personalized Federated Learning via Heterogeneous Model Reassembly

Jiaqi Wang, Xingyi Yang, Suhan Cui, Liwei Che, Lingjuan Lyu, Dongkuan Xu, Fenglong Ma

Comments This paper has been accepted by NeurIPS 2023

Understanding the Latent Space of Diffusion Models through the Lens of Riemannian Geometry

Yong-Hyun Park, Mingi Kwon, Jaewoong Choi, Junghyo Jo, Youngjung Uh

Comments This paper has been accepted for NeurIPS 2023

HYTREL: Hypergraph-enhanced Tabular Data Representation Learning

Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis

Comments NeurIPS 2023 (spotlight)

Deep Contract Design via Discontinuous Networks

Tonghan Wang, Paul Dütting, Dmitry Ivanov, Inbal Talgam-Cohen, David C. Parkes

Journal ref NeurIPS 2023

Macro Placement by Wire-Mask-Guided Black-Box Optimization

Yunqi Shi, Ke Xue, Lei Song, Chao Qian

Comments Update NeurIPS'23 camera ready version