37 citations · 90 across the 31 of their papers we have counts for
10 papers · 1 filter
Learning to Bid in Discriminatory Auctions with Budget Constraints
Negin Golrezaei, Sourav Sahoo
We study repeated bidding in multi-unit discriminatory (pay-as-bid) auctions for a single bidder with per-round utility equal to value minus times payment, where is…
Policy Regret for Embedding Model Routing: Contextual Bandits with Low-Rank Experts
Yan Dai, Negin Golrezaei, Patrick Jaillet
Modern recommendation systems increasingly rely on dynamically routing diverse queries to multiple embedding models. Despite its practical significance, this problem remains poorly…
Non-Stationary Bandits with Auto-Regressive Temporal Dependency
Qinyi Chen, Negin Golrezaei, Djallel Bouneffouf
Traditional multi-armed bandit (MAB) frameworks, predominantly examined under stochastic or adversarial settings, often overlook the temporal dynamics inherent in many real-world a…
Active Learning for Non-Parametric Choice Models
Fransisca Susan, Negin Golrezaei, Ehsan Emamjomeh-Zadeh +1
We study the problem of actively learning a non-parametric choice model based on consumers' decisions. We present a negative result showing that such choice models may not be ident…
Online Learning via Offline Greedy Algorithms: Applications in Market Design and Optimization
Rad Niazadeh, Negin Golrezaei, Joshua Wang +2
Motivated by online decision-making in time-varying combinatorial environments, we study the problem of transforming offline algorithms to their online counterparts. We focus on of…
Learning Product Rankings Robust to Fake Users
Negin Golrezaei, Vahideh Manshadi, Jon Schneider +1
In many online platforms, customers' decisions are substantially influenced by product rankings as most customers only examine a few top-ranked products. Concurrently, such platfor…
Optimal Learning for Structured Bandits
Bart P. G. Van Parys, Negin Golrezaei
We study structured multi-armed bandits, which is the problem of online decision-making under uncertainty in the presence of structural information. In this problem, the decision-m…
Dynamic Incentive-aware Learning: Robust Pricing in Contextual Auctions
Negin Golrezaei, Adel Javanmard, Vahab Mirrokni
Motivated by pricing in ad exchange markets, we consider the problem of robust learning of reserve prices against strategic buyers in repeated contextual second-price auctions. Buy…
Incentive-aware Contextual Pricing with Non-parametric Market Noise
Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang
We consider a dynamic pricing problem for repeated contextual second-price auctions with multiple strategic buyers who aim to maximize their long-term time discounted utility. The…
Contextual Bandits with Cross-learning
Santiago Balseiro, Negin Golrezaei, Mohammad Mahdian +2
In the classical contextual bandits problem, in each round , a learner observes some context , chooses some action to perform, and receives some reward . We c…