Papers
TD-GEN: Graph Generation Using Tree Decomposition
Hamed Shirzad, Hossein Hajimirsadeghi, Amir H. Abdi et al.
Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies
Lenon Minorics, Caner Turkmen, David Kernert et al.
The Curse of Passive Data Collection in Batch Reinforcement Learning
Chenjun Xiao, Ilbin Lee, Bo Dai et al.
The Curse Revisited: When are Distances Informative for the Ground Truth in Noisy High-Dimensional Data?
Robin Vandaele, Bo Kang, Tijl De Bie et al.
The Fast Kernel Transform
John P. Ryan, Sebastian E. Ament, Carla P. Gomes et al.
The Importance of Future Information in Credit Card Fraud Detection
Van Bach Nguyen, Kanishka Ghosh Dastidar, Michael Granitzer et al.
The role of optimization geometry in single neuron learning
Nicholas Boffi, Stephen Tu, Jean-Jacques Slotine
The Tree Loss: Improving Generalization with Many Classes
Yujie Wang, Mike Izbicki
Thompson Sampling with a Mixture Prior
Joey Hong, Branislav Kveton, Manzil Zaheer et al.
Threading the Needle of On and Off-Manifold Value Functions for Shapley Explanations
Chih-Kuan Yeh, Kuan-Yun Lee, Frederick Liu et al.
Tight bounds for minimum $\ell_1$-norm interpolation of noisy data
Guillaume Wang, Konstantin Donhauser, Fanny Yang
Tile Networks: Learning Optimal Geometric Layout for Whole-page Recommendation
Shuai Xiao, Zaifan Jiang, Shuang Yang
Top K Ranking for Multi-Armed Bandit with Noisy Evaluations
Evrard Garcelon, Vashist Avadhanula, Alessandro Lazaric et al.
Towards an Understanding of Default Policies in Multitask Policy Optimization
Ted Moskovitz, Michael Arbel, Jack Parker-Holder et al.
Towards Federated Bayesian Network Structure Learning with Continuous Optimization
Ignavier Ng, Kun Zhang
Towards Return Parity in Markov Decision Processes
Jianfeng Chi, Jian Shen, Xinyi Dai et al.
Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent
Tongzheng Ren, Fuheng Cui, Alexia Atsidakou et al.
Towards Understanding Biased Client Selection in Federated Learning
Yae Jee Cho, Jianyu Wang, Gauri Joshi
Transductive Robust Learning Guarantees
Omar Montasser, Steve Hanneke, Nathan Srebro
Transfer Learning with Gaussian Processes for Bayesian Optimization
Petru Tighineanu, Kathrin Skubch, Paul Baireuther et al.
Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates
Nicholas J. Irons, Meyer Scetbon, Soumik Pal et al.
Triple-Q: A Model-Free Algorithm for Constrained Reinforcement Learning with Sublinear Regret and Zero Constraint Violation
Honghao Wei, Xin Liu, Lei Ying
Tuning-Free Generalized Hamiltonian Monte Carlo
Matthew D. Hoffman, Pavel Sountsov
Two-Sample Test with Kernel Projected Wasserstein Distance
Jie Wang, Rui Gao, Yao Xie