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Alexander Volfovsky
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2020 – today
- 2024
- [c12]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: 22331-22340 - [c11]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: 2134-2142 - [c10]Srikar Katta, Harsh Parikh, Cynthia Rudin, Alexander Volfovsky:
Interpretable Causal Inference for Analyzing Wearable, Sensor, and Distributional Data. AISTATS 2024: 3340-3348 - 2023
- [c9]Justin Weltz, Tanner Fiez, Alexander Volfovsky, Eric Laber, Blake Mason, Houssam Nassif, Lalit Jain:
Experimental Designs for Heteroskedastic Variance. NeurIPS 2023 - [c8]Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, David Page:
Variable importance matching for causal inference. UAI 2023: 1174-1184 - [i15]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 abs/2302.11715 (2023) - [i14]Marco Morucci, Vittorio Orlandi, Harsh Parikh, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky:
A Double Machine Learning Approach to Combining Experimental and Observational Data. CoRR abs/2307.01449 (2023) - [i13]Harsh Parikh, Quinn Lanners, Zade Akras, Sahar F. Zafar, M. Brandon Westover, Cynthia Rudin, Alexander Volfovsky:
Estimating Trustworthy and Safe Optimal Treatment Regimes. CoRR abs/2310.15333 (2023) - [i12]Srikar Katta, Harsh Parikh, Cynthia Rudin, Alexander Volfovsky:
Interpretable Causal Inference for Analyzing Wearable, Sensor, and Distributional Data. CoRR abs/2312.10569 (2023) - 2022
- [j3]Harsh Parikh, Cynthia Rudin, Alexander Volfovsky:
MALTS: Matching After Learning to Stretch. J. Mach. Learn. Res. 23: 240:1-240:42 (2022) - [i11]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 abs/2203.04920 (2022) - [i10]Alexandre Belloni, Fei Fang, Alexander Volfovsky:
Neighborhood Adaptive Estimators for Causal Inference under Network Interference. CoRR abs/2212.03683 (2022) - 2021
- [j2]Tianyu Wang
FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference. J. Mach. Learn. Res. 22: 31:1-31:41 (2021) - [i9]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 abs/2101.01867 (2021) - [i8]Graham Tierney, Christopher Bail, Alexander Volfovsky:
Author Clustering and Topic Estimation for Short Texts. CoRR abs/2106.09533 (2021) - 2020
- [c7]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: 3252-3262 - [c6]Marco Morucci, Vittorio Orlandi, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky:
Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation. UAI 2020: 1089-1098 - [i7]M. Usaid Awan, Marco Morucci, Vittorio Orlandi, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky:
Almost-Matching-Exactly for Treatment Effect Estimation under Network Interference. CoRR abs/2003.00964 (2020) - [i6]Marco Morucci, Vittorio Orlandi, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky:
Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation. CoRR abs/2003.01805 (2020)
2010 – 2019
- 2019
- [c5]Fan Bu, Sonia Xu, Katherine A. Heller, Alexander Volfovsky:
SMOGS: Social Network Metrics of Game Success. AISTATS 2019: 2406-2414 - [c4]Awa Dieng, Yameng Liu, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky:
Interpretable Almost-Exact Matching for Causal Inference. AISTATS 2019: 2445-2453 - [c3]Heather Mathews, Vaishakhi Mayya, Alexander Volfovsky, Galen Reeves:
Gaussian Mixture Models for Stochastic Block Models with Non-Vanishing Noise. CAMSAP 2019: 699-703 - [c2]Galen Reeves, Vaishakhi Mayya, Alexander Volfovsky:
The Geometry of Community Detection via the MMSE Matrix. ISIT 2019: 400-404 - [c1]M. Usaid Awan, Yameng Liu, Marco Morucci, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky:
Interpretable Almost Matching Exactly With Instrumental Variables. UAI 2019: 1116-1126 - [i5]M. Usaid Awan, Yameng Liu, Marco Morucci, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky:
Interpretable Almost-Matching-Exactly With Instrumental Variables. CoRR abs/1906.11658 (2019) - [i4]Galen Reeves, Vaishakhi Mayya, Alexander Volfovsky:
The Geometry of Community Detection via the MMSE Matrix. CoRR abs/1907.02496 (2019) - 2018
- [i3]Awa Dieng, Yameng Liu, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky:
Collapsing-Fast-Large-Almost-Matching-Exactly: A Matching Method for Causal Inference. CoRR abs/1806.06802 (2018) - [i2]Harsh Parikh, Cynthia Rudin, Alexander Volfovsky:
MALTS: Matching After Learning to Stretch. CoRR abs/1811.07415 (2018) - 2017
- [i1]Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky, Tianyu Wang:
FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference. CoRR abs/1707.06315 (2017) - 2016
- [p1]Elizabeth L. Ogburn, Alexander Volfovsky:
Networks. Handbook of Big Data 2016: 171-190 - 2013
- [j1]Peter Hoff, Bailey K. Fosdick
Likelihoods for fixed rank nomination networks. Netw. Sci. 1(3): 253-277 (2013)
Coauthor Index
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