no code implementations • 4 May 2023 • Vivek F. Farias, Hao Li, Tianyi Peng, Xinyuyang Ren, Huawei Zhang, Andrew Zheng
We formalize the problem of inference in such experiments as one of policy evaluation.
no code implementations • 21 Mar 2023 • Jackie Baek, Justin J. Boutilier, Vivek F. Farias, Jonas Oddur Jonasson, Erez Yoeli
DecompPI is simple and easy to implement for organizations aiming to improve long-term behavior through targeted interventions, and this paper demonstrates its strong performance both theoretically and empirically.
no code implementations • 6 Jun 2022 • Vivek F. Farias, Andrew A. Li, Tianyi Peng, Andrew Zheng
We consider experiments in dynamical systems where interventions on some experimental units impact other units through a limiting constraint (such as a limited inventory).
no code implementations • 22 Oct 2021 • Vivek F. Farias, Andrew A. Li, Tianyi Peng
The problem of low-rank matrix completion with heterogeneous and sub-exponential (as opposed to homogeneous and Gaussian) noise is particularly relevant to a number of applications in modern commerce.
1 code implementation • NeurIPS 2021 • Vivek F. Farias, Andrew A. Li, Tianyi Peng
The problem of causal inference with panel data is a central econometric question.
no code implementations • NeurIPS 2021 • Jackie Baek, Vivek F. Farias
When patients are associated with natural groups on the basis of, say, race or age, it is natural to ask whether the cost of exploration borne by any single group is 'fair'.
no code implementations • 17 Nov 2020 • Vivek F. Farias, Andrew A. Li, Deeksha Sinha
Personalization and recommendations are now accepted as core competencies in just about every online setting, ranging from media platforms to e-commerce to social networks.
no code implementations • 23 Jun 2020 • Vivek F. Farias, Andrew A. Li, Tianyi Peng
Using synthetic data and real data from a consumer goods retailer, we show that our approach provides up to a 10x cost reduction over incumbent approaches to anomaly detection.
no code implementations • 11 Jun 2020 • Jackie Baek, Vivek F. Farias
The key algorithmic task for Thompson sampling is drawing a sample from the posterior of the optimal action.
no code implementations • 11 Jun 2020 • Jackie Baek, Vivek F. Farias, Andreea Georgescu, Retsef Levi, Tianyi Peng, Deeksha Sinha, Joshua Wilde, Andrew Zheng
In a similar vein, our results imply that in the case of an SIR model, one cannot hope to predict the eventual number of infections until one is approximately two-thirds of the way to the time at which the infection rate has peaked.