12 citations · 18 across the 9 of their papers we have counts for
10 papers
Halve-Then-Greedy: Adaptive Sampling for Posterior Success with Near-Optimal Instance Dependence
Yinan Li, Kwang-Sung Jun, Kapilan Balagopalan +4
We study fixed-budget adaptive experimentation aimed at maximizing the probability of obtaining sufficient posterior evidence that a recommended design's mean performance exceeds a…
Fixed Budget is No Harder Than Fixed Confidence in Best-Arm Identification up to Logarithmic Factors
Kapilan Balagopalan, Yinan Li, Yao Zhao +4
The best-arm identification (BAI) problem is one of the most fundamental problems in interactive machine learning, which has two flavors: the fixed-budget setting (FB) and the fixe…
Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice
Tanner Fiez, Houssam Nassif, Yu-Cheng Chen +2
Adaptive experimental design (AED) methods are increasingly being used in industry as a tool to boost testing throughput or reduce experimentation cost relative to traditional A/B/…
Estimation of subsidiary performance metrics under optimal policies
Zhaoqi Li, Houssam Nassif, Alex Luedtke
In policy learning, the goal is typically to optimize a primary performance metric, but other subsidiary metrics often also warrant attention. This paper presents two strategies fo…
Experimental Designs for Heteroskedastic Variance
Justin Weltz, Tanner Fiez, Alexander Volfovsky +4
Most linear experimental design problems assume homogeneous variance although heteroskedastic noise is present in many realistic settings. Let a learner have access to a finite set…
A Data-Driven State Aggregation Approach for Dynamic Discrete Choice Models
Sinong Geng, Houssam Nassif, Carlos A. Manzanares
We study dynamic discrete choice models, where a commonly studied problem involves estimating parameters of agent reward functions (also known as "structural" parameters), using ag…
Neural Insights for Digital Marketing Content Design
Fanjie Kong, Yuan Li, Houssam Nassif +3
In digital marketing, experimenting with new website content is one of the key levers to improve customer engagement. However, creating successful marketing content is a manual and…
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…
Instance-optimal PAC Algorithms for Contextual Bandits
Zhaoqi Li, Lillian Ratliff, Houssam Nassif +2
In the stochastic contextual bandit setting, regret-minimizing algorithms have been extensively researched, but their instance-minimizing best-arm identification counterparts remai…
Improved Confidence Bounds for the Linear Logistic Model and Applications to Linear Bandits
Kwang-Sung Jun, Lalit Jain, Blake Mason +1
We propose improved fixed-design confidence bounds for the linear logistic model. Our bounds significantly improve upon the state-of-the-art bound by Li et al. (2017) via recent de…