Alexander Volfovsky

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 29

Top Topics

Experimental Designs

Gaussian Mixture

Observational Data

Top Venues

J. Mach. Learn. Res.

Publications

Harsh Parikh, Quinn Lanners, Zade Akras, Sahar Zafar, M. Brandon Westover, Cynthia Rudin, Alexander Volfovsky
Safe and Interpretable Estimation of Optimal Treatment Regimes. AISTATS (2024)
Travis Seale-Carlisle, Saksham Jain, Courtney Lee, Caroline Levenson, Swathi Ramprasad, Brandon Garrett, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
Evaluating Pre-trial Programs Using Interpretable Machine Learning Matching Algorithms for Causal Inference. AAAI (2024)
Srikar Katta, Harsh Parikh, Cynthia Rudin, Alexander Volfovsky
Interpretable Causal Inference for Analyzing Wearable, Sensor, and Distributional Data. AISTATS (2024)
Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, David Page
From Feature Importance to Distance Metric: An Almost Exact Matching Approach for Causal Inference. CoRR (2023)
Harsh Parikh, Quinn Lanners, Zade Akras, Sahar F. Zafar, M. Brandon Westover, Cynthia Rudin, Alexander Volfovsky
Estimating Trustworthy and Safe Optimal Treatment Regimes. CoRR (2023)
Marco Morucci, Vittorio Orlandi, Harsh Parikh, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
A Double Machine Learning Approach to Combining Experimental and Observational Data. CoRR (2023)
Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, David Page
Variable importance matching for causal inference. UAI (2023)
Srikar Katta, Harsh Parikh, Cynthia Rudin, Alexander Volfovsky
Interpretable Causal Inference for Analyzing Wearable, Sensor, and Distributional Data. CoRR (2023)
Justin Weltz, Tanner Fiez, Alexander Volfovsky, Eric Laber, Blake Mason, Houssam Nassif, Lalit Jain
Experimental Designs for Heteroskedastic Variance. NeurIPS (2023)
Harsh Parikh, Kentaro Hoffman, Haoqi Sun, Wendong Ge, Jin Jing, Rajesh Amerineni, Lin Liu, Jimeng Sun, Sahar Zafar, Aaron Struck, Alexander Volfovsky, Cynthia Rudin, M. Brandon Westover
Why Interpretable Causal Inference is Important for High-Stakes Decision Making for Critically Ill Patients and How To Do It. CoRR (2022)
Harsh Parikh, Cynthia Rudin, Alexander Volfovsky
MALTS: Matching After Learning to Stretch. J. Mach. Learn. Res. 23 (2022)
Alexandre Belloni, Fei Fang, Alexander Volfovsky
Neighborhood Adaptive Estimators for Causal Inference under Network Interference. CoRR (2022)
Tianyu Wang, Marco Morucci, M. Usaid Awan, Yameng Liu, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference. J. Mach. Learn. Res. 22 (2021)
Neha R. Gupta, Vittorio Orlandi, Chia-Rui Chang, Tianyu Wang, Marco Morucci, Pritam Dey, Thomas J. Howell, Xian Sun, Angikar Ghosal, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
dame-flame: A Python Library Providing Fast Interpretable Matching for Causal Inference. CoRR (2021)
Graham Tierney, Christopher Bail, Alexander Volfovsky
Author Clustering and Topic Estimation for Short Texts. CoRR (2021)
M. Usaid Awan, Marco Morucci, Vittorio Orlandi, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
Almost-Matching-Exactly for Treatment Effect Estimation under Network Interference. CoRR (2020)
Marco Morucci, Vittorio Orlandi, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation. CoRR (2020)
Marco Morucci, Vittorio Orlandi, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation. UAI (2020)
M. Usaid Awan, Marco Morucci, Vittorio Orlandi, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
Almost-Matching-Exactly for Treatment Effect Estimation under Network Interference. AISTATS (2020)
M. Usaid Awan, Yameng Liu, Marco Morucci, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
Interpretable Almost-Matching-Exactly With Instrumental Variables. CoRR (2019)
Galen Reeves, Vaishakhi Mayya, Alexander Volfovsky
The Geometry of Community Detection via the MMSE Matrix. CoRR (2019)
Fan Bu, Sonia Xu, Katherine Heller, Alexander Volfovsky
SMOGS: Social Network Metrics of Game Success. AISTATS (2019)
Galen Reeves, Vaishakhi Mayya, Alexander Volfovsky
The Geometry of Community Detection via the MMSE Matrix. ISIT (2019)
M. Usaid Awan, Yameng Liu, Marco Morucci, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
Interpretable Almost Matching Exactly With Instrumental Variables. UAI (2019)
Awa Dieng, Yameng Liu, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
Interpretable Almost-Exact Matching for Causal Inference. AISTATS (2019)
Heather Mathews, Vaishakhi Mayya, Alexander Volfovsky, Galen Reeves
Gaussian Mixture Models for Stochastic Block Models with Non-Vanishing Noise. CAMSAP (2019)
Harsh Parikh, Cynthia Rudin, Alexander Volfovsky
MALTS: Matching After Learning to Stretch. CoRR (2018)
Awa Dieng, Yameng Liu, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
Collapsing-Fast-Large-Almost-Matching-Exactly: A Matching Method for Causal Inference. CoRR (2018)
Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky, Tianyu Wang
FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference. CoRR (2017)