Papers
Frequentist Regret Bounds for Randomized Least-Squares Value Iteration
Andrea Zanette, David Brandfonbrener, Emma Brunskill et al.
Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs
Valentina Zantedeschi, Aurélien Bellet, Marc Tommasi
Functional Gradient Boosting for Learning Residual-like Networks with Statistical Guarantees
Atsushi Nitanda, Taiji Suzuki
Gain with no Pain: Efficiency of Kernel-PCA by Nyström Sampling
Nicholas Sterge, Bharath Sriperumbudur, Lorenzo Rosasco et al.
GAIT: A Geometric Approach to Information Theory
Jose Gallego Posada, Ankit Vani, Max Schwarzer et al.
Gaussianization Flows
Chenlin Meng, Yang Song, Jiaming Song et al.
Gaussian Sketching yields a J-L Lemma in RKHS
Samory Kpotufe, Bharath Sriperumbudur
Gaussian-Smoothed Optimal Transport: Metric Structure and Statistical Efficiency
Ziv Goldfeld, Kristjan Greenewald
General Identification of Dynamic Treatment Regimes Under Interference
Eli Sherman, David Arbour, Ilya Shpitser
GP-VAE: Deep Probabilistic Time Series Imputation
Vincent Fortuin, Dmitry Baranchuk, Gunnar Raetsch et al.
Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks
Mingchen Li, Mahdi Soltanolkotabi, Samet Oymak
Graph Coarsening with Preserved Spectral Properties
Yu Jin, Andreas Loukas, Joseph JaJa
Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative Filtering
Liwei Wu, Hsiang-Fu Yu, Nikhil Rao et al.
Greed Meets Sparsity: Understanding and Improving Greedy Coordinate Descent for Sparse Optimization
Huang Fang, Zhenan Fan, Yifan Sun et al.
Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis
Ryan Rogers, Aaron Roth, Adam Smith et al.
Hamiltonian Monte Carlo Swindles
Dan Piponi, Matthew Hoffman, Pavel Sountsov
Hermitian matrices for clustering directed graphs: insights and applications
Mihai Cucuringu, Huan Li, He Sun et al.
High Dimensional Robust Sparse Regression
Liu Liu, Yanyao Shen, Tianyang Li et al.
How fine can fine-tuning be? Learning efficient language models
Evani Radiya-Dixit, Xin Wang
How To Backdoor Federated Learning
Eugene Bagdasaryan, Andreas Veit, Yiqing Hua et al.
Hyperbolic Manifold Regression
Gian Marconi, Carlo Ciliberto, Lorenzo Rosasco
Hypothesis Testing Interpretations and Renyi Differential Privacy
Borja Balle, Gilles Barthe, Marco Gaboardi et al.
Identifying and Correcting Label Bias in Machine Learning
Heinrich Jiang, Ofir Nachum
Importance Sampling via Local Sensitivity
Anant Raj, Cameron Musco, Lester Mackey