[1:00]
Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning
[1:15]
Faster Rates, Adaptive Algorithms, and Finite-Time Bounds for Linear Composition Optimization and Gradient TD Learning
[1:30]
A general class of surrogate functions for stable and efficient reinforcement learning
[1:45]
A Complete Characterisation of ReLU-Invariant Distributions