Papers
4,025 papers found
Federated Asymptotics: a model to compare federated learning algorithms
Gary Cheng, Karan Chadha, John Duchi
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms
Vincent Plassier, Eric Moulines, Alain Durmus
Federated Learning for Data Streams
Othmane Marfoq, Giovanni Neglia, Laetitia Kameni et al.
Federated Learning under Distributed Concept Drift
Ellango Jothimurugesan, Kevin Hsieh, Jianyu Wang et al.
Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning
Ruitu Xu, Yifei Min, Tianhao Wang et al.
Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation
Gandharv Patil, Prashanth L.A., Dheeraj Nagaraj et al.
Fitting low-rank models on egocentrically sampled partial networks
Ga Ming Angus Chan, Tianxi Li
Fix-A-Step: Semi-supervised Learning From Uncurated Unlabeled Data
Zhe Huang, Mary-Joy Sidhom, Benjamin Wessler et al.
Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity
Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui et al.
Flexible and Efficient Contextual Bandits with Heterogeneous Treatment Effect Oracles
Aldo Gael Carranza, Sanath Kumar Krishnamurthy, Susan Athey
Flexible risk design using bi-directional dispersion
Matthew J. Holland
ForestPrune: Compact Depth-Pruned Tree Ensembles
Brian Liu, Rahul Mazumder
Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise
Haotian Ye, James Zou, Linjun Zhang
Frequentist Uncertainty Quantification in Semi-Structured Neural Networks
Emilio Dorigatti, Benjamin Schubert, Bernd Bischl et al.
From Shapley Values to Generalized Additive Models and back
Sebastian Bordt, Ulrike von Luxburg
Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits
Taira Tsuchiya, Shinji Ito, Junya Honda
Gaussian Processes on Distributions based on Regularized Optimal Transport
François Bachoc, Louis Béthune, Alberto Gonzalez-Sanz et al.
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion
Haotian Ju, Dongyue Li, Aneesh Sharma et al.
Generalized PTR: User-Friendly Recipes for Data-Adaptive Algorithms with Differential Privacy
Rachel Redberg, Yuqing Zhu, Yu-Xiang Wang
Generative Oversampling for Imbalanced Data via Majority-Guided VAE
Qingzhong Ai, Pengyun Wang, Lirong He et al.
Geometric Random Walk Graph Neural Networks via Implicit Layers
Giannis Nikolentzos, Michalis Vazirgiannis
Global Convergence of Over-parameterized Deep Equilibrium Models
Zenan Ling, Xingyu Xie, Qiuhao Wang et al.
Global-Local Regularization Via Distributional Robustness
Hoang Phan, Trung Le, Trung Phung et al.
Gradient-Informed Neural Network Statistical Robustness Estimation
Karim TIT, Teddy Furon, Mathias Rousset
Graph Alignment Kernels using Weisfeiler and Leman Hierarchies
Giannis Nikolentzos, Michalis Vazirgiannis