Steve Yadlowsky

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 24

Top Topics

Model Selection

Statistical Inference

Top Venues

Publications

Nilesh Tripuraneni, Lee Richardson, Alexander D'Amour, Jacopo Soriano, Steve Yadlowsky
Choosing a Proxy Metric from Past Experiments. KDD (2024)
Nilesh Tripuraneni, Lee Richardson, Alexander D'Amour, Jacopo Soriano, Steve Yadlowsky
Choosing a Proxy Metric from Past Experiments. CoRR (2023)
Steve Yadlowsky, Lyric Doshi, Nilesh Tripuraneni
Pretraining Data Mixtures Enable Narrow Model Selection Capabilities in Transformer Models. CoRR (2023)
Tiffany Cai, Hongseok Namkoong, Steve Yadlowsky
Diagnosing Model Performance Under Distribution Shift. CoRR (2023)
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
Underspecification Presents Challenges for Credibility in Modern Machine Learning. J. Mach. Learn. Res. 23 (2022)
Eric Loreaux, Ke Yu, Jonas Kemp, Martin Seneviratne, Christina Chen, Subhrajit Roy, Ivan Protsyuk, Natalie Harris, Alexander D'Amour, Steve Yadlowsky, Mingjun Chen
Boosting the interpretability of clinical risk scores with intervention predictions. CoRR (2022)
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
The MultiBERTs: BERT Reproductions for Robustness Analysis. ICLR (2022)
Yizhe Xu, Steve Yadlowsky
Calibration Error for Heterogeneous Treatment Effects. AISTATS (2022)
Victor Veitch, Alexander D'Amour, Steve Yadlowsky, Jacob Eisenstein
Counterfactual Invariance to Spurious Correlations in Text Classification. NeurIPS (2021)
Chirag Nagpal, Steve Yadlowsky, Negar Rostamzadeh, Katherine A. Heller
Deep Cox Mixtures for Survival Regression. MLHC (2021)
Steve Yadlowsky, Taedong Yun, Cory Y. McLean, Alexander D'Amour
SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression. NeurIPS (2021)
Chirag Nagpal, Steve Yadlowsky, Negar Rostamzadeh, Katherine A. Heller
Deep Cox Mixtures for Survival Regression. CoRR (2021)
Steve Yadlowsky, Taedong Yun, Cory Y. McLean, Alexander D'Amour
SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression. CoRR (2021)
Thibault Sellam, Steve Yadlowsky, Jason Wei, Naomi Saphra, Alexander D'Amour, Tal Linzen, Jasmijn Bastings, Iulia Turc, Jacob Eisenstein, Dipanjan Das, Ian Tenney, Ellie Pavlick
The MultiBERTs: BERT Reproductions for Robustness Analysis. CoRR (2021)
Victor Veitch, Alexander D'Amour, Steve Yadlowsky, Jacob Eisenstein
Counterfactual Invariance to Spurious Correlations: Why and How to Pass Stress Tests. CoRR (2021)
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
Underspecification Presents Challenges for Credibility in Modern Machine Learning. CoRR (2020)
Hongseok Namkoong, Ramtin Keramati, Steve Yadlowsky, Emma Brunskill
Off-policy Policy Evaluation For Sequential Decisions Under Unobserved Confounding. NeurIPS (2020)
Sehj Kashyap, Saurabh Gombar, Steve Yadlowsky, Alison Callahan, Jason A. Fries, Benjamin A. Pinsky, Nigam H. Shah
Measure what matters: Counts of hospitalized patients are a better metric for health system capacity planning for a reopening. J. Am. Medical Informatics Assoc. 27 (7) (2020)
Hongseok Namkoong, Ramtin Keramati, Steve Yadlowsky, Emma Brunskill
Off-policy Policy Evaluation For Sequential Decisions Under Unobserved Confounding. CoRR (2020)
Steve Yadlowsky, Fabio Pellegrini, Federica Lionetto, Stefan Braune, Lu Tian
Estimation and Validation of a Class of Conditional Average Treatment Effects Using Observational Data. CoRR (2019)
Steve Yadlowsky, Sanjay Basu, Lu Tian
A Calibration Metric for Risk Scores with Survival Data. MLHC (2019)
Tatsunori B. Hashimoto, Steve Yadlowsky, John C. Duchi
Derivative free optimization via repeated classification. CoRR (2018)
Tatsunori Hashimoto, Steve Yadlowsky, John C. Duchi
Derivative Free Optimization Via Repeated Classification. AISTATS (2018)
Hongseok Namkoong, Aman Sinha, Steve Yadlowsky, John C. Duchi
Adaptive Sampling Probabilities for Non-Smooth Optimization. ICML (2017)
Steve Yadlowsky, Preetum Nakkarin, Jingyan Wang, Rishi Sharma, Laurent El Ghaoui
Iterative Hard Thresholding for Keyword Extraction from Large Text Corpora. ICMLA (2014)