Papers
Orthogonal Bases for Equivariant Graph Learning with Provable k-WL Expressive Power
Jia He, Maggie Cheng
Optimal Experiment Design for Causal Effect Identification
Sina Akbari, Jalal Etesami, Negar Kiyavash
Mean Aggregator is More Robust than Robust Aggregators under Label Poisoning Attacks on Distributed Heterogeneous Data
Jie Peng, Weiyu Li, Stefan Vlaski et al.
The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond
Jiin Woo, Gauri Joshi, Yuejie Chi
depyf: Open the Opaque Box of PyTorch Compiler for Machine Learning Researchers
Kaichao You, Runsheng Bai, Meng Cao et al.
The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise
Shuze Daniel Liu, Shuhang Chen, Shangtong Zhang
Improving Graph Neural Networks on Multi-node Tasks with the Labeling Trick
Xiyuan Wang, Pan Li, Muhan Zhang
Directed Cyclic Graphs for Simultaneous Discovery of Time-Lagged and Instantaneous Causality from Longitudinal Data Using Instrumental Variables
Wei Jin, Yang Ni, Amanda B. Spence et al.
Bayesian Sparse Gaussian Mixture Model for Clustering in High Dimensions
Dapeng Yao, Fangzheng Xie, Yanxun Xu
Regularizing Hard Examples Improves Adversarial Robustness
Hyungyu Lee, Saehyung Lee, Ho Bae et al.
Random ReLU Neural Networks as Non-Gaussian Processes
Rahul Parhi, Pakshal Bohra, Ayoub El Biari et al.
Riemannian Bilevel Optimization
Jiaxiang Li, Shiqian Ma
Supervised Learning with Evolving Tasks and Performance Guarantees
Verónica Álvarez, Santiago Mazuelas, Jose A. Lozano
Error estimation and adaptive tuning for unregularized robust M-estimator
Pierre C. Bellec, Takuya Koriyama
From Sparse to Dense Functional Data in High Dimensions: Revisiting Phase Transitions from a Non-Asymptotic Perspective
Shaojun Guo, Dong Li, Xinghao Qiao et al.
Locally Private Causal Inference for Randomized Experiments
Yuki Ohnishi, Jordan Awan
Estimating Network-Mediated Causal Effects via Principal Components Network Regression
Alex Hayes, Mark M. Fredrickson, Keith Levin
Selective Inference with Distributed Data
Sifan Liu, Snigdha Panigrahi
Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization
Tianyi Lin, Chi Jin, Michael I. Jordan
An Axiomatic Definition of Hierarchical Clustering
Ery Arias-Castro, Elizabeth Coda
Test-Time Training on Video Streams
Renhao Wang, Yu Sun, Arnuv Tandon et al.
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback
Boxin Zhao, Lingxiao Wang, Ziqi Liu et al.
A Random Matrix Approach to Low-Multilinear-Rank Tensor Approximation
Hugo Lebeau, Florent Chatelain, Romain Couillet
Memory Gym: Towards Endless Tasks to Benchmark Memory Capabilities of Agents
Marco Pleines, Matthias Pallasch, Frank Zimmer et al.
Enhancing Graph Representation Learning with Localized Topological Features
Zuoyu Yan, Qi Zhao, Ze Ye et al.