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Sofia S. Villar
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2020 – today
- 2024
- [c6]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: 22906-22912 - 2023
- [i8]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 abs/2301.01107 (2023) - [i7]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 abs/2310.18326 (2023) - 2022
- [j2]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: 107559 (2022) - [c5]Isabel Chien, Nina Deliu
, Richard E. Turner, Adrian Weller, Sofia S. Villar, Niki Kilbertus:
Multi-disciplinary fairness considerations in machine learning for clinical trials. FAccT 2022: 906-924 - [i6]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 abs/2205.03820 (2022) - [i5]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 abs/2205.08875 (2022) - 2021
- [i4]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 abs/2103.12198 (2021) - [i3]Nina Deliu, Joseph Jay Williams, Sofia S. Villar:
Efficient Inference Without Trading-off Regret in Bandits: An Allocation Probability Test for Thompson Sampling. CoRR abs/2111.00137 (2021) - [i2]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 abs/2112.08507 (2021) - 2020
- [c4]Cong Shen, Zhiyang Wang, Sofia S. Villar, Mihaela van der Schaar:
Learning for Dose Allocation in Adaptive Clinical Trials with Safety Constraints. ICML 2020: 8730-8740 - [i1]Cong Shen, Zhiyang Wang, Sofia S. Villar, Mihaela van der Schaar:
Learning for Dose Allocation in Adaptive Clinical Trials with Safety Constraints. CoRR abs/2006.05026 (2020)
2010 – 2019
- 2017
- [j1]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: 136-153 (2017) - 2012
- [c3]Peter Jacko, Sofia S. Villar:
Opportunistic schedulers for optimal scheduling of flows in wireless systems with ARQ feedback. ITC 2012: 1-8 - 2011
- [c2]José Niño-Mora, Sofia S. Villar:
Sensor scheduling for hunting elusive hiding targets via whittle's restless bandit index policy. NetGCoop 2011: 1-8
2000 – 2009
- 2009
- [c1]José Niño-Mora
, Sofia S. Villar:
Multitarget tracking via restless bandit marginal productivity indices and Kalman filter in discrete time. CDC 2009: 2905-2910
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last updated on 2024-05-08 21:02 CEST by the dblp team
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