Pruning schemes have been widely used in practice to reduce the complexi...
We consider the sequential decision-making problem where the mean outcom...
The focus of this work is sample-efficient deep reinforcement learning (...
Data-driven machine learning models are being increasingly employed in
s...
Online imitation learning is the problem of how best to mimic expert
dem...
Distribution estimation under error-prone or non-ideal sampling modelled...
Labelled data often comes at a high cost as it may require recruiting hu...
We study the statistical limits of Imitation Learning (IL) in episodic M...
Estimation of missing mass with the popular Good-Turing (GT) estimator i...
Recent attacks on federated learning demonstrate that keeping the traini...
Imitation learning (IL) aims to mimic the behavior of an expert policy i...
Support size estimation and the related problem of unseen species estima...
A versatile scheduling problem to model a three-way tradeoff between
del...
The classical problem of maximizing a submodular function under a matroi...