Semih Çaycı
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I am an NSF TRIPODS Postdoctoral Research Fellow at University of Illinois at Urbana-Champaign. My research interests include reinforcement learning, neural networks and stochastic control.

During my doctoral research, I worked on incorporating the continuous time dimension into the online learning and stochastic optimization framework, which is a fundamental problem in the optimal control of communication and computing systems among many other applications. Check out my Google Scholar profile for a list of my recent papers.
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News
  • "Group-Fair Online Learning", joint work with Swati Gupta and Atilla Eryilmaz, was published in the Proceedings of NeurIPS 2020. [link]

  • Does restarting a prolonged task expedite the completion and improve time-efficiency? How can you learn optimal restart strategies with bandit feedback? "Continuous-Time Multi-Armed Bandits with Controlled Restarts", joint work with Atilla Eryilmaz and R. Srikant, is now available. [link]

  • "Budget-Constrained Bandits over General Cost and Reward Distributions", joint work with Atilla Eryilmaz and R. Srikant, was published in the Proceedings of AISTATS 2020. [link][slides]
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