Papers
Generalization Bounds for Label Noise Stochastic Gradient Descent
Jung Eun Huh, Patrick Rebeschini
Generalization Bounds of Nonconvex-(Strongly)-Concave Stochastic Minimax Optimization
Siqi Zhang, Yifan Hu, Liang Zhang et al.
General Tail Bounds for Non-Smooth Stochastic Mirror Descent
Khaled Eldowa, Andrea Paudice
Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees
Alexia Jolicoeur-Martineau, Kilian Fatras, Tal Kachman
Generative Flow Networks as Entropy-Regularized RL
Daniil Tiapkin, Nikita Morozov, Alexey Naumov et al.
Gibbs-Based Information Criteria and the Over-Parameterized Regime
Haobo Chen, Gregory W Wornell, Yuheng Bu
GmGM: a fast multi-axis Gaussian graphical model
Ethan B. Andrew, David Westhead, Luisa Cutillo
Graph fission and cross-validation
James Leiner, Aaditya Ramdas
Graph Machine Learning through the Lens of Bilevel Optimization
Amber Yijia Zheng, Tong He, Yixuan Qiu et al.
Graph Partitioning with a Move Budget
Mina Dalirrooyfard, Elaheh Fata, Majid Behbahani et al.
Graph Pruning for Enumeration of Minimal Unsatisfiable Subsets
Panagiotis Lymperopoulos, Liping Liu
GRAWA: Gradient-based Weighted Averaging for Distributed Training of Deep Learning Models
Tolga Dimlioglu, Anna Choromanska
Hidden yet quantifiable: A lower bound for confounding strength using randomized trials
Piersilvio De Bartolomeis, Javier Abad Martinez, Konstantin Donhauser et al.
Hodge-Compositional Edge Gaussian Processes
Maosheng Yang, Viacheslav Borovitskiy, Elvin Isufi
Holographic Global Convolutional Networks for Long-Range Prediction Tasks in Malware Detection
Mohammad Mahmudul Alam, Edward Raff, Stella R Biderman et al.
Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation
Jiayi Huang, Han Zhong, Liwei Wang et al.
How does GPT-2 Predict Acronyms? Extracting and Understanding a Circuit via Mechanistic Interpretability
Jorge García-Carrasco, Alejandro Maté, Juan Carlos Trujillo
How Good is a Single Basin?
Kai Lion, Lorenzo Noci, Thomas Hofmann et al.
Identifiability of Product of Experts Models
Manav Kant, Eric Y Ma, Andrei Staicu et al.
Identifiable Feature Learning for Spatial Data with Nonlinear ICA
Hermanni Hälvä, Jonathan So, Richard E. Turner et al.
Identification and Estimation of “Causes of Effects” using Covariate-Mediator Information
Ryusei Shingaki, Manabu Kuroki
Identifying Confounding from Causal Mechanism Shifts
Sarah Mameche, Jilles Vreeken, David Kaltenpoth
Identifying Copeland Winners in Dueling Bandits with Indifferences
Viktor Bengs, Björn Haddenhorst, Eyke Hüllermeier
Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias
Yu Yang, Eric Gan, Gintare Karolina Dziugaite et al.