Qing Zhao

  1. Adaptive Shortest-Path Routing under Unknown and Stochastically Varying Link States.

    Authors: Qing Zhao, Keqin Liu
    Subjects: Networking and Internet Architecture
    Abstract

    We consider the adaptive shortest-path routing problem in wireless networks
    under unknown and stochastically varying link states. In this problem, we aim
    to optimize the quality of communication between a source and a destination
    through adaptive path selection. Due to the randomness and uncertainties in the
    network dynamics, the quality of each link varies over time according to a
    stochastic process with unknown distributions. After a path is selected for
    communication, the aggregated quality of all links on this path (e.g., total
    path delay) is observed.

  2. Extended UCB Policy for Multi-Armed Bandit with Light-Tailed Reward Distributions.

    Authors: Qing Zhao, Keqin Liu
    Subjects: Learning
    Abstract

    We consider the multi-armed bandit problems in which a player aims to accrue
    reward by sequentially playing a given set of arms with unknown reward
    statistics. In the classic work, policies were proposed to achieve the optimal
    logarithmic regret order for some special classes of light-tailed reward
    distributions, e.g., Auer et al.'s UCB1 index policy for reward distributions
    with finite support.

  3. Deterministic Sequencing of Exploration and Exploitation for Multi-Armed Bandit Problems.

    Authors: Qing Zhao, Keqin Liu
    Subjects: Optimization and Control
    Abstract

    In the Multi-Armed Bandit (MAB) problem, there are a given set of arms with
    unknown reward distributions. At each time, a player selects one arm to play,
    aiming to maximize the total expected reward over a horizon of length T. The
    essence of the problem is the tradeoff between exploration and exploitation:
    playing a less explored arm to learn its reward statistics for future benefit
    or playing the arm with the largest sample mean at the current time.

  4. A Note on: `Algorithms for Connected Set Cover Problem and Fault-Tolerant Connected Set Cover Problem'.

    Authors: Qing Zhao, Wei Ren
    Subjects: Data Structures and Algorithms
    Abstract

    A flaw in the greedy approximation algorithm proposed by Zhang et al. for
    minimum connected set cover problem is corrected, and a stronger result on the
    approximation ratio of the modified greedy algorithm is established. The
    results are now consistent with the existing results on connected dominating
    set problem which is a special case of the minimum connected set cover problem.

  5. Decentralized Restless Bandit with Multiple Players and Unknown Dynamics.

    Authors: Qing Zhao, Keqin Liu, Haoyang Liu
    Subjects: Optimization and Control
    Abstract

    We consider decentralized restless multi-armed bandit problems with unknown
    dynamics and multiple players. The reward state of each arm transits according
    to an unknown Markovian rule when it is played and evolves according to an
    arbitrary unknown random process when it is passive. Players activating the
    same arm at the same time collide and suffer from reward loss. The objective is
    to maximize the long-term reward by designing a decentralized arm selection
    policy to address unknown reward models and collisions among players.

  6. Learning in A Changing World: Non-Bayesian Restless Multi-Armed Bandit.

    Authors: Qing Zhao, Keqin Liu, Haoyang Liu
    Subjects: Optimization and Control
    Abstract

    We consider the restless multi-armed bandit (RMAB) problem with unknown
    dynamics. In this problem, at each time, a player chooses K out of N (N > K)
    arms to play. The state of each arm determines the reward when the arm is
    played and transits according to Markovian rules no matter the arm is engaged
    or passive. The Markovian dynamics of the arms are unknown to the player. The
    objective is to maximize the long-term reward by designing an optimal arm
    selection policy.

  7. The Non-Bayesian Restless Multi-Armed Bandit: a Case of Near-Logarithmic Regret.

    Authors: Qing Zhao, Yi Gai, Bhaskar Krishnamachari, Wenhan Dai
    Subjects: Optimization and Control
    Abstract

    In the classic Bayesian restless multi-armed bandit (RMAB) problem, there are
    $N$ arms, with rewards on all arms evolving at each time as Markov chains with
    known parameters. A player seeks to activate $K \geq 1$ arms at each time in
    order to maximize the expected total reward obtained over multiple plays. RMAB
    is a challenging problem that is known to be PSPACE-hard in general. We
    consider in this work the even harder non-Bayesian RMAB, in which the
    parameters of the Markov chain are assumed to be unknown \emph{a priori}.

  8. On the Connectivity and Multihop Delay of Ad Hoc Cognitive Radio Networks.

    Authors: Qing Zhao, Wei Ren, Ananthram Swami
    Subjects: Networking and Internet Architecture
    Abstract

    We analyze the multihop delay of ad hoc cognitive radio networks, where the
    transmission delay of each hop consists of the propagation delay and the
    waiting time for the availability of the communication channel (i.e., the
    occurrence of a spectrum opportunity at this hop). Using theories and
    techniques from continuum percolation and ergodicity, we establish the scaling
    law of the minimum multihop delay with respect to the source-destination
    distance in cognitive radio networks.

  9. Decentralized Multi-Armed Bandit with Multiple Distributed Players.

    Authors: Qing Zhao, Keqin Liu
    Subjects: Optimization and Control
    Abstract

    We consider multi-armed bandit with distributed players, where each player
    independently samples one of N stochastic processes with unknown parameters and
    accrues reward in each slot without information exchange. Users choosing the
    same arm collide, and none or only one receives reward depending on the
    collision model. This problem can be formulated as a decentralized multi-armed
    bandit problem.

  10. Decentralized Multi-Armed Bandit with Multiple Distributed Players.

    Authors: Qing Zhao, Keqin Liu
    Subjects: Optimization and Control
    Abstract

    We consider multi-armed bandit with distributed players, where each player
    independently samples one of N stochastic processes with unknown parameters and
    accrues reward in each slot without information exchange. Users choosing the
    same arm collide, and none or only one receives reward depending on the
    collision model. This problem can be formulated as a decentralized multi-armed
    bandit problem.

  11. Hopf Structures on Minimal Hopf Quivers.

    Authors: Hua-Lin Huang, Yu Ye, Qing Zhao
    Subjects: Quantum Algebra
    Abstract

    In this paper we investigate pointed Hopf algebras via quiver methods. We
    classify all possible Hopf structures arising from minimal Hopf quivers, namely
    basic cycles and the linear chain. This provides full local structure
    information for general pointed Hopf algebras.

  12. Hopf Structures on Minimal Hopf Quivers.

    Authors: Hua-Lin Huang, Yu Ye, Qing Zhao
    Subjects: Quantum Algebra
    Abstract

    In this paper we investigate pointed Hopf algebras via quiver methods. We
    classify all possible Hopf structures arising from minimal Hopf quivers, namely
    basic cycles and the linear chain. This provides full local structure
    information for general pointed Hopf algebras.

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