6 citations · 8 across the 8 of their papers we have counts for
8 papers
Non-Exclusive Notifications for Ride-Hailing at Lyft I: Single-Cycle Approximation Algorithms
Farbod Ekbatani, Rad Niazadeh, Shruti Penumatsa +11
Ride-hailing platforms increasingly rely on non-exclusive notifications--broadcasting a single request to multiple drivers simultaneously--to mitigate inefficiencies caused by unce…
Non-Exclusive Notifications for Ride-Hailing at Lyft II: Simulations and Marketplace Analysis
Farbod Ekbatani, Rad Niazadeh, Mehdi Golari +10
Ride-hailing platforms increasingly face uncertain driver acceptance, which makes traditional one-to-one \emph{exclusive dispatch} (ED) less efficient: rejections and timeouts forc…
Fair Active Learning in Low-Data Regimes
Romain Camilleri, Andrew Wagenmaker, Jamie Morgenstern +2
In critical machine learning applications, ensuring fairness is essential to avoid perpetuating social inequities. In this work, we address the challenges of reducing bias and impr…
A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity
Zhihan Xiong, Romain Camilleri, Maryam Fazel +2
We investigate the fixed-budget best-arm identification (BAI) problem for linear bandits in a potentially non-stationary environment. Given a finite arm set $\mathcal{X}\subset\mat…
Active Learning with Safety Constraints
Romain Camilleri, Andrew Wagenmaker, Jamie Morgenstern +2
Active learning methods have shown great promise in reducing the number of samples necessary for learning. As automated learning systems are adopted into real-time, real-world deci…
Nearly Optimal Algorithms for Level Set Estimation
Blake Mason, Romain Camilleri, Subhojyoti Mukherjee +3
The level set estimation problem seeks to find all points in a domain where the value of an unknown function exceeds a threshold .…
Selective Sampling for Online Best-arm Identification
Romain Camilleri, Zhihan Xiong, Maryam Fazel +2
This work considers the problem of selective-sampling for best-arm identification. Given a set of potential options , a learner aims to compute with…
High-Dimensional Experimental Design and Kernel Bandits
Romain Camilleri, Julian Katz-Samuels, Kevin Jamieson
In recent years methods from optimal linear experimental design have been leveraged to obtain state of the art results for linear bandits. A design returned from an objective such…