160 citations · 1.5k across the 122 of their papers we have counts for
9 papers · 1 filter
Joint Learning of Linear Time-Invariant Dynamical Systems
Aditya Modi, Mohamad Kazem Shirani Faradonbeh, Ambuj Tewari +1
Linear time-invariant systems are very popular models in system theory and applications. A fundamental problem in system identification that remains rather unaddressed in extant li…
Balancing Adaptability and Non-exploitability in Repeated Games
Anthony DiGiovanni, Ambuj Tewari
We study the problem of guaranteeing low regret in repeated games against an opponent with unknown membership in one of several classes. We add the constraint that our algorithm is…
On the Statistical Benefits of Curriculum Learning
Ziping Xu, Ambuj Tewari
Curriculum learning (CL) is a commonly used machine learning training strategy. However, we still lack a clear theoretical understanding of CL's benefits. In this paper, we study t…
Learning in Online MDPs: Is there a Price for Handling the Communicating Case?
Gautam Chandrasekaran, Ambuj Tewari
It is a remarkable fact that the same regret rate can be achieved in both the Experts Problem and the Adversarial Multi-Armed Bandit problem albeit with a worse depen…
Bandit Algorithms for Precision Medicine
Yangyi Lu, Ziping Xu, Ambuj Tewari
The Oxford English Dictionary defines precision medicine as "medical care designed to optimize efficiency or therapeutic benefit for particular groups of patients, especially by us…
Weighted Gaussian Process Bandits for Non-stationary Environments
Yuntian Deng, Xingyu Zhou, Baekjin Kim +3
In this paper, we consider the Gaussian process (GP) bandit optimization problem in a non-stationary environment. To capture external changes, the black-box function is allowed to…