科學(xué)研究

【學(xué)術(shù)講座】Cost-aware Cascading Bandits

發(fā)布時間:2020-07-13

報告題目:Cost-aware Cascading Bandits

主講嘉賓:Cong Shen 教授 中國科學(xué)技術(shù)大學(xué)

邀請人:全智教授

時間:2018年 11月 23日(周 五)上午11:00

地點(diǎn):深圳大學(xué)南校區(qū)基礎(chǔ)實(shí)驗(yàn)樓北座信息工程學(xué)院N710會議室

報告摘要:

We will discuss a cost-aware cascading bandits mode that is motivated by many practical applications. This is a new variant of the multi-armed bandit model but incorporating the random cost of pulling arms and cascading feedback. In each step, the learning agent chooses an ordered list of items and examines them sequentially, until certain stopping condition is satisfied. Our objective is then to maximize the expected net reward in each step, i.e., the reward obtained in each step minus the total cost incurred in examining the items, by deciding the ordered list of items, as well as when to stop examination.

We study both the offline and online settings, depending on whether the state and cost statistics of the items are known beforehand. For the offline setting, we show that the Unit Cost Ranking with Threshold 1 (UCR-T1) policy is optimal. For the online setting, we propose a Cost-aware Cascading Upper Confidence Bound (CC-UCB) algorithm, and show that the cumulative regret scales in O(log T). We also provide a lower bound for all α-consistent policies, which scales in Ω(log T) and matches our upper bound. The performance of the CC-UCB algorithm is evaluated with real-world datasets.Joint work with R. Zhou (University of Science and Technology of China), C. Gan and J. Yang (Pennsylvania State University)

嘉賓簡介:

Cong Shen received his B.S. and M.S. degrees, in 2002 and 2004 respectively, from the Department of Electronic Engineering, Tsinghua University, China. He obtained the Ph.D. degree from the Electrical Engineering Department, UCLA, in 2009. From 2009 to 2014, He worked for Qualcomm Research in San Diego, CA. In 2015, he joined University of Science and Technology of China (USTC) as Professor in the School of Information Science and Technology. His research interests include machine learning, information theory, and wireless communications. He currently serves as an editor for the IEEE Transactions on Wireless Communications and an editor for the IEEE Wireless Communications

歡迎各位老師和同學(xué)參加。

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