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Testing Symmetric Markov Chains from a Single Trajectory
We initiate the study of Markov chain testing, assuming access to a single trajectory of a Markov Chain.
Tight Lower Bounds for Multiplicative Weights Algorithmic Families
We study the fundamental problem of prediction with expert advice and develop regret lower bounds for a large family of algorithms for this problem.
Towards Optimal Algorithms for Prediction with Expert Advice
Further, we show that the optimal algorithm for $2$ and $3$ experts is a probability matching algorithm (analogous to Thompson sampling) against a particular randomized adversary.
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