AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 2 of 87 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
We study the problem of recovering the ranking of a fixed set of items according to their unknown numerical utilities. At each interaction with the environment, a learner presents the item set to a human and receives comparative feedback of two types. Under full-ranking feedback, each interaction reveals a noisy rankin...
This work resolves the assumption-free adaptation problem for heavy-tailed bandits and characterize the price in the regret of not knowing the tail parameters and introduces a scheduled-exploration algorithm that requires no knowledge of $u$ and matches the resulting adaptation frontier up to logarithmic factors.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.