125 citations · 148 across the 19 of their papers we have counts for
5 papers · 1 filter
Stable Matching with Ties: Approximation Ratios and Learning
Shiyun Lin, Simon Mauras, Nadav Merlis +1
We study matching markets with ties, where workers on one side of the market may have tied preferences over jobs, determined by their matching utilities. Unlike classical two-sided…
Improved Algorithms for Contextual Dynamic Pricing
Matilde Tullii, Solenne Gaucher, Nadav Merlis +1
In contextual dynamic pricing, a seller sequentially prices goods based on contextual information. Buyers will purchase products only if the prices are below their valuations. The…
Reinforcement Learning with Lookahead Information
Nadav Merlis
We study reinforcement learning (RL) problems in which agents observe the reward or transition realizations at their current state before deciding which action to take. Such observ…
On Bits and Bandits: Quantifying the Regret-Information Trade-off
Itai Shufaro, Nadav Merlis, Nir Weinberger +1
In many sequential decision problems, an agent performs a repeated task. He then suffers regret and obtains information that he may use in the following rounds. However, sometimes…
The Value of Reward Lookahead in Reinforcement Learning
Nadav Merlis, Dorian Baudry, Vianney Perchet
In reinforcement learning (RL), agents sequentially interact with changing environments while aiming to maximize the obtained rewards. Usually, rewards are observed only after acti…