Steve Yadlowsky

According to our database, Steve Yadlowsky authored at least 18 papers between 2014 and 2024.

Collaborative distances:

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

2024

Choosing a Proxy Metric from Past Experiments.

Nilesh Tripuraneni, Lee Richardson, Alexander D'Amour, Jacopo Soriano, Steve Yadlowsky

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

2023

Pretraining Data Mixtures Enable Narrow Model Selection Capabilities in Transformer Models.

Steve Yadlowsky, Lyric Doshi, Nilesh Tripuraneni

CoRR, 2023

Diagnosing Model Performance Under Distribution Shift.

Tiffany Tianhui Cai, Hongseok Namkoong, Steve Yadlowsky

CoRR, 2023

2022

Underspecification Presents Challenges for Credibility in Modern Machine Learning.

Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley

J. Mach. Learn. Res., 2022

Boosting the interpretability of clinical risk scores with intervention predictions.

Eric Loreaux, Ke Yu, Jonas Kemp, Martin Seneviratne, Christina Chen, Subhrajit Roy, Ivan Protsyuk, Natalie Harris, Alexander D'Amour, Steve Yadlowsky, Mingjun Chen

CoRR, 2022

The MultiBERTs: BERT Reproductions for Robustness Analysis.

Thibault Sellam, Steve Yadlowsky, Ian Tenney, Jason Wei, Naomi Saphra, Alexander D'Amour, Tal Linzen, Jasmijn Bastings, Iulia Raluca Turc, Jacob Eisenstein, Dipanjan Das, Ellie Pavlick

Proceedings of the Tenth International Conference on Learning Representations, 2022

Calibration Error for Heterogeneous Treatment Effects.

Yizhe Xu, Steve Yadlowsky

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Counterfactual Invariance to Spurious Correlations: Why and How to Pass Stress Tests.

Victor Veitch, Alexander D'Amour, Steve Yadlowsky, Jacob Eisenstein

CoRR, 2021

SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression.

Steve Yadlowsky, Taedong Yun, Cory Y. McLean, Alexander D'Amour

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Counterfactual Invariance to Spurious Correlations in Text Classification.

Victor Veitch, Alexander D'Amour, Steve Yadlowsky, Jacob Eisenstein

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Deep Cox Mixtures for Survival Regression.

Chirag Nagpal, Steve Yadlowsky, Negar Rostamzadeh, Katherine A. Heller

Proceedings of the Machine Learning for Healthcare Conference, 2021

2020

Measure what matters: Counts of hospitalized patients are a better metric for health system capacity planning for a reopening.

Sehj Kashyap, Saurabh Gombar, Steve Yadlowsky, Alison Callahan, Jason A. Fries, Benjamin A. Pinsky, Nigam H. Shah

J. Am. Medical Informatics Assoc., 2020

Off-policy Policy Evaluation For Sequential Decisions Under Unobserved Confounding.

Hongseok Namkoong, Ramtin Keramati, Steve Yadlowsky, Emma Brunskill

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Estimation and Validation of a Class of Conditional Average Treatment Effects Using Observational Data.

Steve Yadlowsky, Fabio Pellegrini, Federica Lionetto, Stefan Braune, Lu Tian

CoRR, 2019

A Calibration Metric for Risk Scores with Survival Data.

Steve Yadlowsky, Sanjay Basu, Lu Tian

Proceedings of the Machine Learning for Healthcare Conference, 2019

2018

Derivative Free Optimization Via Repeated Classification.

Tatsunori Hashimoto, Steve Yadlowsky, John C. Duchi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Adaptive Sampling Probabilities for Non-Smooth Optimization.

Hongseok Namkoong, Aman Sinha, Steve Yadlowsky, John C. Duchi

Proceedings of the 34th International Conference on Machine Learning, 2017

2014

Iterative Hard Thresholding for Keyword Extraction from Large Text Corpora.

Steve Yadlowsky, Preetum Nakkarin, Jingyan Wang, Rishi Sharma, Laurent El Ghaoui

Proceedings of the 13th International Conference on Machine Learning and Applications, 2014