activity
20182022
collaborators

5 papers

cs.HC2022

"I Want to Figure Things Out": Supporting Exploration in Navigation for People with Visual Impairments

Gaurav Jain, Yuanyang Teng, Dong Heon Cho +3

Navigation assistance systems (NASs) aim to help visually impaired people (VIPs) navigate unfamiliar environments. Most of today's NASs support VIPs via turn-by-turn navigation, bu…

stat.ML2019

On Multi-Armed Bandit Designs for Dose-Finding Clinical Trials

Maryam Aziz, Emilie Kaufmann, Marie-Karelle Riviere

We study the problem of finding the optimal dosage in early stage clinical trials through the multi-armed bandit lens. We advocate the use of the Thompson Sampling principle, a fle…

stat.ML2018

Pure-Exploration for Infinite-Armed Bandits with General Arm Reservoirs

Maryam Aziz, Kevin Jamieson, Javed Aslam

This paper considers a multi-armed bandit game where the number of arms is much larger than the maximum budget and is effectively infinite. We characterize necessary and sufficient…

cs.LG2018

Adaptively Pruning Features for Boosted Decision Trees

Maryam Aziz, Jesse Anderton, Javed Aslam

Boosted decision trees enjoy popularity in a variety of applications; however, for large-scale datasets, the cost of training a decision tree in each round can be prohibitively exp…

stat.ML2018

Pure Exploration in Infinitely-Armed Bandit Models with Fixed-Confidence

Maryam Aziz, Jesse Anderton, Emilie Kaufmann +1

We consider the problem of near-optimal arm identification in the fixed confidence setting of the infinitely armed bandit problem when nothing is known about the arm reservoir dist…