16 citations · 58 across the 10 of their papers we have counts for
10 papers
Online Learning Algorithms for Stochastic Water-Filling
Yi Gai, Bhaskar Krishnamachari
Water-filling is the term for the classic solution to the problem of allocating constrained power to a set of parallel channels to maximize the total data-rate. It is used widely i…
Online Learning for Combinatorial Network Optimization with Restless Markovian Rewards
Yi Gai, Bhaskar Krishnamachari, Mingyan Liu
Combinatorial network optimization algorithms that compute optimal structures taking into account edge weights form the foundation for many network protocols. Examples include shor…
Efficient Online Learning for Opportunistic Spectrum Access
Wenhan Dai, Yi Gai, Bhaskar Krishnamachari
The problem of opportunistic spectrum access in cognitive radio networks has been recently formulated as a non-Bayesian restless multi-armed bandit problem. In this problem, there…
The Non-Bayesian Restless Multi-Armed Bandit: A Case of Near-Logarithmic Strict Regret
Wenhan Dai, Yi Gai, Bhaskar Krishnamachari +1
In the classic Bayesian restless multi-armed bandit (RMAB) problem, there are arms, with rewards on all arms evolving at each time as Markov chains with known parameters. A pla…
Funding Games: the Truth but not the Whole Truth
Amotz Bar-Noy, Yi Gai, Matthew P. Johnson +2
We introduce the Funding Game, in which identical resources are to be allocated among selfish agents. Each agent requests a number of resources and reports a valuatio…
A Packet Dropping Mechanism for Efficient Operation of M/M/1 Queues with Selfish Users
Yi Gai, Hua Liu, Bhaskar Krishnamachari
We consider a fundamental game theoretic problem concerning selfish users contributing packets to an M/M/1 queue. In this game, each user controls its own input rate so as to optim…