Papers
Exploiting Equality Constraints in Causal Inference
Chi Zhang, Carlos Cinelli, Bryant Chen et al.
Explore the Context: Optimal Data Collection for Context-Conditional Dynamics Models
Jan Achterhold, Joerg Stueckler
Exponential Convergence Rates of Classification Errors on Learning with SGD and Random Features
Shingo Yashima, Atsushi Nitanda, Taiji Suzuki
Fair for All: Best-effort Fairness Guarantees for Classification
Anilesh Krishnaswamy, Zhihao Jiang, Kangning Wang et al.
False Discovery Rates in Biological Networks
Lu Yu, Tobias Kaufmann, Johannes Lederer
Fast Adaptation with Linearized Neural Networks
Wesley Maddox, Shuai Tang, Pablo Moreno et al.
Fast and Smooth Interpolation on Wasserstein Space
Sinho Chewi, Julien Clancy, Thibaut Le Gouic et al.
Faster Kernel Interpolation for Gaussian Processes
Mohit Yadav, Daniel Sheldon, Cameron Musco
Faster & More Reliable Tuning of Neural Networks: Bayesian Optimization with Importance Sampling
Setareh Ariafar, Zelda Mariet, Dana Brooks et al.
Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures
Fanghui Liu, Xiaolin Huang, Yingyi Chen et al.
Fast Statistical Leverage Score Approximation in Kernel Ridge Regression
Yifan Chen, Yun Yang
Federated f-Differential Privacy
Qinqing Zheng, Shuxiao Chen, Qi Long et al.
Federated Learning with Compression: Unified Analysis and Sharp Guarantees
Farzin Haddadpour, Mohammad Mahdi Kamani, Aryan Mokhtari et al.
Federated Multi-armed Bandits with Personalization
Chengshuai Shi, Cong Shen, Jing Yang
Feedback Coding for Active Learning
Gregory Canal, Matthieu Bloch, Christopher Rozell
Fenchel-Young Losses with Skewed Entropies for Class-posterior Probability Estimation
Han Bao, Masashi Sugiyama
Finding First-Order Nash Equilibria of Zero-Sum Games with the Regularized Nikaido-Isoda Function
Ioannis Tsaknakis, Mingyi Hong
Finite-Sample Regret Bound for Distributionally Robust Offline Tabular Reinforcement Learning
Zhengqing Zhou, Zhengyuan Zhou, Qinxun Bai et al.
Fisher Auto-Encoders
Khalil Elkhalil, Ali Hasan, Jie Ding et al.
Flow-based Alignment Approaches for Probability Measures in Different Spaces
Tam Le, Nhat Ho, Makoto Yamada
Follow Your Star: New Frameworks for Online Stochastic Matching with Known and Unknown Patience
Brian Brubach, Nathaniel Grammel, Will Ma et al.
Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings
Qipeng Guo, Zhijing Jin, Ziyu Wang et al.
Foundations of Bayesian Learning from Synthetic Data
Harrison Wilde, Jack Jewson, Sebastian Vollmer et al.
Fourier Bases for Solving Permutation Puzzles
Horace Pan, Risi Kondor
Fractional moment-preserving initialization schemes for training deep neural networks
Mert Gurbuzbalaban, Yuanhan Hu