NeurIPS

Motion-X++: A Large-Scale Multimodal 3D Whole-body Human Motion Dataset

Yuhong Zhang, Jing Lin, Ailing Zeng, Guanlin Wu, Shunlin Lu, Yurong Fu, Yuanhao Cai, Ruimao Zhang, Haoqian Wang, Lei Zhang

Comments 17 pages, 14 figures, This work extends and enhances the research published in the NeurIPS 2023 paper, "Motion-X: A Large-scale 3D Expressive Whole-body Human Motion Dataset". arXiv admin note: substantial text overlap with arXiv:2307.00818

Most Influential Subset Selection: Challenges, Promises, and Beyond

Yuzheng Hu, Pingbang Hu, Han Zhao, Jiaqi W. Ma

Comments Accepted at the 38th Conference on Neural Information Processing Systems (NeurIPS 2024) Edit: Added discussion on a concurrent work

Convergence Analysis of Split Federated Learning on Heterogeneous Data

Pengchao Han, Chao Huang, Geng Tian, Ming Tang, Xin Liu

Comments Accepted by Conference on Neural Information Processing Systems (NeurIPS 2024)

Optimality of Message-Passing Architectures for Sparse Graphs

Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath

Comments 27 pages, 2 figures, published at NeurIPS 2023

Scalable Second-Order Optimization Algorithms for Minimizing Low-rank Functions

Edward Tansley, Coralia Cartis

Comments Accepted at NeurIPS 2024 Workshop OPT2024: Optimization for Machine Learning; fixed typo on page 5

Stylebreeder: Exploring and Democratizing Artistic Styles through Text-to-Image Models

Matthew Zheng, Enis Simsar, Hidir Yesiltepe, Federico Tombari, Joel Simon, Pinar Yanardag

Comments Accepted at NeurIPS 2024 D&B Track, Project page: https://stylebreeder.github.io HuggingFace DB Page: https://huggingface.co/datasets/stylebreeder/stylebreeder

Scaling-laws for Large Time-series Models

Thomas D. P. Edwards, James Alvey, Justin Alsing, Nam H. Nguyen, Benjamin D. Wandelt

Comments 4 main pages (16 total), 4 figures; Accepted for oral presentation in Time Series in the Age of Large Models (TSALM) Workshop at Neurips 2024

Energy-based Hopfield Boosting for Out-of-Distribution Detection

Claus Hofmann, Simon Schmid, Bernhard Lehner, Daniel Klotz, Sepp Hochreiter

Comments NeurIPS 2024

DNN-Based Topology Optimisation: Spatial Invariance and Neural Tangent Kernel

Benjamin Dupuis, Arthur Jacot

Journal ref Advances in Neural Information Processing Systems, 34:27659-27669, 2021

Statistical Uncertainty Quantification for Aggregate Performance Metrics in Machine Learning Benchmarks

Rachel Longjohn, Giri Gopalan, Emily Casleton

Comments LA-UR-24-25289; presented at the Workshop on Statistical Frontiers in LLMs and Foundation Models at NeurIPS 2024

Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity

Hanlin Gu, Win Kent Ong, Chee Seng Chan, Lixin Fan

Comments TLDR: The need for a "right to be forgotten" in Federated Learning has led to the development of the Ferrari framework, which efficiently unlearns sensitive features using a Lipschitz continuity-based metric, proven effective in extensive testing. Accepted at NeurIPS 2024

Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees

Sean Jaffe, Alexander Davydov, Deniz Lapsekili, Ambuj Singh, Francesco Bullo

Comments 9 pages, 3 figures. NeurIPS 2024

Preference-grounded Token-level Guidance for Language Model Fine-tuning

Shentao Yang, Shujian Zhang, Congying Xia, Yihao Feng, Caiming Xiong, Mingyuan Zhou

Comments v2: 37th Conference on Neural Information Processing Systems (NeurIPS 2023); v3: update on scaling up to PPO + LLMs

Deep Policy Iteration with Integer Programming for Inventory Management

Pavithra Harsha, Ashish Jagmohan, Jayant Kalagnanam, Brian Quanz, Divya Singhvi

Comments Prior shorter version accepted to NeurIPS 2021 Deep RL Workshop. Updated version to appear in MSOM journal. Authors are listed in alphabetical order

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes

Rasmus F. Ørsøe, Aske Rosted, GraphNeT Team

Comments Submitted and accepted to ML4PS @ NeurIPS

Vision Transformer Neural Architecture Search for Out-of-Distribution Generalization: Benchmark and Insights

Sy-Tuyen Ho, Tuan Van Vo, Somayeh Ebrahimkhani, Ngai-Man Cheung

Comments Accepted in NeurIPS 2024

Journal ref NeurIPS 2024

SALT: Sales Autocompletion Linked Business Tables Dataset

Tassilo Klein, Clemens Biehl, Margarida Costa, Andre Sres, Jonas Kolk, Johannes Hoffart

Comments Table Representation Learning Workshop at NeurIPS 2024

On the Adversarial Robustness of Benjamini Hochberg

Louis L Chen, Roberto Szechtman, Matan Seri

Comments 22 pages, 5 figures, NeurIPS 2024

Neural Network Prediction of Strong Lensing Systems with Domain Adaptation and Uncertainty Quantification

Shrihan Agarwal, Aleksandra Ćiprijanović, Brian D. Nord

Comments Accepted to the Machine Learning for Physical Sciences workshop at NeurIPS 2024; 24 pages, 2 figures, 4 tables

Abstracted Shapes as Tokens -- A Generalizable and Interpretable Model for Time-series Classification

Yunshi Wen, Tengfei Ma, Tsui-Wei Weng, Lam M. Nguyen, Anak Agung Julius

Comments Published in Neural Information Processing Systems (NeurIPS) 2024

Constrained Sampling with Primal-Dual Langevin Monte Carlo

Luiz F. O. Chamon, Mohammad Reza Karimi, Anna Korba

Comments 39 pages, 14 figures. Published at NeurIPS 2024

Robust Gaussian Processes via Relevance Pursuit

Sebastian Ament, Elizabeth Santorella, David Eriksson, Ben Letham, Maximilian Balandat, Eytan Bakshy

Comments NeurIPS 2024 Article (https://openreview.net/forum?id=5FATPIlWUJ)

Graph Learning for Numeric Planning

Dillon Z. Chen, Sylvie Thiébaux

Comments Extended version of NeurIPS 2024 paper

ControlMLLM: Training-Free Visual Prompt Learning for Multimodal Large Language Models

Mingrui Wu, Xinyue Cai, Jiayi Ji, Jiale Li, Oucheng Huang, Gen Luo, Hao Fei, Guannan Jiang, Xiaoshuai Sun, Rongrong Ji

Comments Accepted to NeurIPS 2024; Code:https://github.com/mrwu-mac/ControlMLLM

Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum

Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, Pavan Kumar Anasosalu Vasu, Cem Koc, Vaishaal Shankar, Oncel Tuzel

Comments NeurIPS 2024

Unity by Diversity: Improved Representation Learning in Multimodal VAEs

Thomas M. Sutter, Yang Meng, Andrea Agostini, Daphné Chopard, Norbert Fortin, Julia E. Vogt, Babak Shahbaba, Stephan Mandt

Comments Accepted at Neurips 2024

Mapping Housing Stock Characteristics from Drone Images for Climate Resilience in the Caribbean

Isabelle Tingzon, Nuala Margaret Cowan, Pierre Chrzanowski

Comments Tackling Climate Change with Machine Learning: Workshop at NeurIPS 2023

Journal ref Environ. Data Science 3 (2024) e29

HuRef: HUman-REadable Fingerprint for Large Language Models

Boyi Zeng, Lizheng Wang, Yuncong Hu, Yi Xu, Chenghu Zhou, Xinbing Wang, Yu Yu, Zhouhan Lin

Comments NeurIPS 2024

Unexpected Improvements to Expected Improvement for Bayesian Optimization

Sebastian Ament, Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy

Comments NeurIPS 2023 Spotlight (https://openreview.net/forum?id=QFgYOtOkDB)

Explicit and data-Efficient Encoding via Gradient Flow

Kyriakos Flouris, Anna Volokitin, Gustav Bredell, Ender Konukoglu

Comments Machine Learning and the Physical Sciences Workshop, NeurIPS 2024. arXiv admin note: text overlap with arXiv:2105.05031

Journal ref NeurIPS 2024 Machine Learning and the Physical Sciences