Alexander Volfovsky

According to our database, Alexander Volfovsky authored at least 25 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Safe and Interpretable Estimation of Optimal Treatment Regimes.

Harsh Parikh, Quinn Lanners, Zade Akras, Sahar Zafar, M. Brandon Westover, Cynthia Rudin, Alexander Volfovsky

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Interpretable Causal Inference for Analyzing Wearable, Sensor, and Distributional Data.

Srikar Katta, Harsh Parikh, Cynthia Rudin, Alexander Volfovsky

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Evaluating Pre-trial Programs Using Interpretable Machine Learning Matching Algorithms for Causal Inference.

Travis Seale-Carlisle, Saksham Jain, Courtney Lee, Caroline Levenson, Swathi Ramprasad, Brandon Garrett, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Estimating Trustworthy and Safe Optimal Treatment Regimes.

Harsh Parikh, Quinn Lanners, Zade Akras, Sahar F. Zafar, M. Brandon Westover, Cynthia Rudin, Alexander Volfovsky

CoRR, 2023

A Double Machine Learning Approach to Combining Experimental and Observational Data.

Marco Morucci, Vittorio Orlandi, Harsh Parikh, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky

CoRR, 2023

From Feature Importance to Distance Metric: An Almost Exact Matching Approach for Causal Inference.

Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, David Page

CoRR, 2023

Variable importance matching for causal inference.

Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, David Page

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Experimental Designs for Heteroskedastic Variance.

Justin Weltz, Tanner Fiez, Alexander Volfovsky, Eric Laber, Blake Mason, Houssam Nassif, Lalit Jain

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

MALTS: Matching After Learning to Stretch.

Harsh Parikh, Cynthia Rudin, Alexander Volfovsky

J. Mach. Learn. Res., 2022

Neighborhood Adaptive Estimators for Causal Inference under Network Interference.

Alexandre Belloni, Fei Fang, Alexander Volfovsky

CoRR, 2022

Why Interpretable Causal Inference is Important for High-Stakes Decision Making for Critically Ill Patients and How To Do It.

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

CoRR, 2022

2021

FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference.

Tianyu Wang, Marco Morucci, M. Usaid Awan, Yameng Liu, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky

J. Mach. Learn. Res., 2021

Author Clustering and Topic Estimation for Short Texts.

Graham Tierney, Christopher Bail, Alexander Volfovsky

CoRR, 2021

dame-flame: A Python Library Providing Fast Interpretable Matching for Causal Inference.

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

CoRR, 2021

2020

Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation.

Marco Morucci, Vittorio Orlandi, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Almost-Matching-Exactly for Treatment Effect Estimation under Network Interference.

M. Usaid Awan, Marco Morucci, Vittorio Orlandi, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Interpretable Almost Matching Exactly With Instrumental Variables.

M. Usaid Awan, Yameng Liu, Marco Morucci, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

The Geometry of Community Detection via the MMSE Matrix.

Galen Reeves, Vaishakhi Mayya, Alexander Volfovsky

Proceedings of the IEEE International Symposium on Information Theory, 2019

Gaussian Mixture Models for Stochastic Block Models with Non-Vanishing Noise.

Heather Mathews, Vaishakhi Mayya, Alexander Volfovsky, Galen Reeves

Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

Interpretable Almost-Exact Matching for Causal Inference.

Awa Dieng, Yameng Liu, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

SMOGS: Social Network Metrics of Game Success.

Fan Bu, Sonia Xu, Katherine A. Heller, Alexander Volfovsky

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Collapsing-Fast-Large-Almost-Matching-Exactly: A Matching Method for Causal Inference.

Awa Dieng, Yameng Liu, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky

CoRR, 2018

2017

FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference.

Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky, Tianyu Wang

CoRR, 2017

2016

Networks.

Elizabeth L. Ogburn, Alexander Volfovsky

Proceedings of the Handbook of Big Data., 2016

2013

Likelihoods for fixed rank nomination networks.

Peter Hoff, Bailey K. Fosdick, Alexander Volfovsky, Katherine Stovel

Netw. Sci., 2013