8 papers
Efficient Multinomial Logistic Bandit via Frequent Directions
Linzhe He, Yu-Jie Zhang, Sifan Yang +1
This paper studies efficient online algorithms for multinomial logistic bandits (MLogB), where the feedback distribution over outcomes follows a multinomial logistic model of…
Distributed Online Convex Optimization with Compressed Communication: Optimal Regret and Applications
Sifan Yang, Dan-Yue Li, Lijun Zhang
Distributed online convex optimization (D-OCO) is a powerful paradigm for modeling distributed scenarios with streaming data. However, the communication cost between local learners…
Distributed Online Convex Optimization with Efficient Communication: Improved Algorithm and Lower bounds
Sifan Yang, Wenhao Yang, Wei Jiang +1
We investigate distributed online convex optimization with compressed communication, where learners connected by a network collaboratively minimize a sequence of global loss fu…
Online Nonsubmodular Optimization with Delayed Feedback in the Bandit Setting
Sifan Yang, Yuanyu Wan, Lijun Zhang
We investigate the online nonsubmodular optimization with delayed feedback in the bandit setting, where the loss function is -weakly DR-submodular and -weakly DR-supermodul…
Improved Analysis for Sign-based Methods with Momentum Updates
Wei Jiang, Dingzhi Yu, Sifan Yang +2
In this paper, we present enhanced analysis for sign-based optimization algorithms with momentum updates. Traditional sign-based methods, under the separable smoothness assumption,…
Discounted Online Convex Optimization: Uniform Regret Across a Continuous Interval
Wenhao Yang, Sifan Yang, Lijun Zhang
Reflecting the greater significance of recent history over the distant past in non-stationary environments, -discounted regret has been introduced in online convex optimization…