19 citations · 35 across the 19 of their papers we have counts for
4 papers · 1 filter
Preferences Evolve And So Should Your Bandits: Bandits with Evolving States for Online Platforms
Khashayar Khosravi, Renato Paes Leme, Chara Podimata +1
We propose a model for learning with bandit feedback while accounting for deterministically evolving and unobservable states that we call Bandits with Deterministically Evolving St…
Strategic Apple Tasting
Keegan Harris, Chara Podimata, Zhiwei Steven Wu
Algorithmic decision-making in high-stakes domains often involves assigning decisions to agents with incentives to strategically modify their input to the algorithm. In addition to…
Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents
Nika Haghtalab, Chara Podimata, Kunhe Yang
We introduce \emph{Calibrated Stackelberg Games (CSGs)}, a generalization of the standard Stackelberg Games (SGs) framework. In CSGs, a principal repeatedly interacts with an agent…
Recommending to Strategic Users
Andreas Haupt, Dylan Hadfield-Menell, Chara Podimata
Recommendation systems are pervasive in the digital economy. An important assumption in many deployed systems is that user consumption reflects user preferences in a static sense:…