Sofia S. Villar

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 13

Top Topics

Multi Armed Bandit

Clinical Trials

Top Venues

Comput. Stat. Data Anal.

Publications

Harsh Kumar, Tong Li, Jiakai Shi, Ilya Musabirov, Rachel Kornfield, Jonah Meyerhoff, Ananya Bhattacharjee, Chris J. Karr, Theresa Nguyen, David C. Mohr, Anna N. Rafferty, Sofia S. Villar, Nina Deliu, Joseph Jay Williams
Using Adaptive Bandit Experiments to Increase and Investigate Engagement in Mental Health. AAAI (2024)
Harsh Kumar, Tong Li, Jiakai Shi, Ilya Musabirov, Rachel Kornfield, Jonah Meyerhoff, Ananya Bhattacharjee, Chris J. Karr, Theresa Nguyen, David C. Mohr, Anna N. Rafferty, Sofia S. Villar, Nina Deliu, Joseph Jay Williams
Using Adaptive Bandit Experiments to Increase and Investigate Engagement in Mental Health. CoRR (2023)
James K. He, Sofia S. Villar, Lida Mavrogonatou
Computing the Performance of A New Adaptive Sampling Algorithm Based on The Gittins Index in Experiments with Exponential Rewards. CoRR (2023)
Lida Mavrogonatou, Yuxuan Sun, David S. Robertson, Sofia S. Villar
A comparison of allocation strategies for optimising clinical trial designs under variance heterogeneity. Comput. Stat. Data Anal. 176 (2022)
Isabel Chien, Nina Deliu, Richard E. Turner, Adrian Weller, Sofia S. Villar, Niki Kilbertus
Multi-disciplinary fairness considerations in machine learning for clinical trials. CoRR (2022)
Xijin Chen, Kim May Lee, Sofia S. Villar, David S. Robertson
Some performance considerations when using multi-armed bandit algorithms in the presence of missing data. CoRR (2022)
Isabel Chien, Nina Deliu, Richard Turner, Adrian Weller, Sofia S. Villar, Niki Kilbertus
Multi-disciplinary fairness considerations in machine learning for clinical trials. FAccT (2022)
Nina Deliu, Joseph Jay Williams, Sofia S. Villar
Efficient Inference Without Trading-off Regret in Bandits: An Allocation Probability Test for Thompson Sampling. CoRR (2021)
Jacob Nogas, Tong Li, Fernando J. Yanez, Arghavan Modiri, Nina Deliu, Ben Prystawski, Sofia S. Villar, Anna N. Rafferty, Joseph Jay Williams
Algorithms for Adaptive Experiments that Trade-off Statistical Analysis with Reward: Combining Uniform Random Assignment and Reward Maximization. CoRR (2021)
Joseph Jay Williams, Jacob Nogas, Nina Deliu, Hammad Shaikh, Sofia S. Villar, Audrey Durand, Anna N. Rafferty
Challenges in Statistical Analysis of Data Collected by a Bandit Algorithm: An Empirical Exploration in Applications to Adaptively Randomized Experiments. CoRR (2021)
Cong Shen, Zhiyang Wang, Sofia S. Villar, Mihaela van der Schaar
Learning for Dose Allocation in Adaptive Clinical Trials with Safety Constraints. ICML (2020)
Cong Shen, Zhiyang Wang, Sofia S. Villar, Mihaela van der Schaar
Learning for Dose Allocation in Adaptive Clinical Trials with Safety Constraints. CoRR (2020)
S. Faye Williamson, Peter Jacko, Sofia S. Villar, Thomas Jaki
A Bayesian adaptive design for clinical trials in rare diseases. Comput. Stat. Data Anal. 113 (2017)
Peter Jacko, Sofia S. Villar
Opportunistic schedulers for optimal scheduling of flows in wireless systems with ARQ feedback. International Teletraffic Congress (2012)
José Niño-Mora, Sofia S. Villar
Sensor scheduling for hunting elusive hiding targets via whittle's restless bandit index policy. NetGCoop (2011)
José Niño-Mora, Sofia S. Villar
Multitarget tracking via restless bandit marginal productivity indices and Kalman filter in discrete time. CDC (2009)