activity
20162022
most citedFinite Sample Prediction and Recovery Bounds for Ordinal Embedding

22 citations · 55 across the 9 of their papers we have counts for

collaborators

13 papers

cs.LG20221 cited

Adaptive Experimental Design and Counterfactual Inference

Tanner Fiez, Sergio Gamez, Arick Chen +2

Adaptive experimental design methods are increasingly being used in industry as a tool to boost testing throughput or reduce experimentation cost relative to traditional A/B/N test…

stat.ML2022

An Experimental Design Approach for Regret Minimization in Logistic Bandits

Blake Mason, Kwang-Sung Jun, Lalit Jain

In this work we consider the problem of regret minimization for logistic bandits. The main challenge of logistic bandits is reducing the dependence on a potentially large problem d…

stat.ML2021

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 .…

cs.LG20211 cited

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…

cs.LG2021

Improved Algorithms for Agnostic Pool-based Active Classification

Julian Katz-Samuels, Jifan Zhang, Lalit Jain +1

We consider active learning for binary classification in the agnostic pool-based setting. The vast majority of works in active learning in the agnostic setting are inspired by the…

stat.ML2020

A New Perspective on Pool-Based Active Classification and False-Discovery Control

Lalit Jain, Kevin Jamieson

In many scientific settings there is a need for adaptive experimental design to guide the process of identifying regions of the search space that contain as many true positives as…