KerJEPA: Kernel Discrepancies for Euclidean Self-Supervised Learning
Eric Zimmermann, Eric Zimmermann, Harley Wiltzer, Justin Szeto, David Alvarez-Melis, Lester Mackey
December 2025
出版物
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-
-
Informed Correctors for Discrete Diffusion Models
Yixiu Zhao, Jiaxin Shi, Lester Mackey, Scott W. Linderman
NeurIPS 2025 | September 2025
-
It’s Hard to Be Normal: The Impact of Noise on Structure-agnostic Estimation
Jikai Jin, Lester Mackey, Vasilis Syrgkanis
NeurIPS 2025 | July 2025
-
Causal integration of chemical structures improves representations of microscopy images for morphological profiling
Yemin Yu, Neil Tenenholtz, Lester Mackey, Ying Wei, David Alvarez-Melis, Ava P. Amini, Alex Lu
April 2025
-
Cheap Permutation Testing
Carles Domingo-Enrich, Raaz Dwivedi, Lester Mackey
March 2025
-
Low-Rank Thinning
A. M. Carrell, Albert Gong, Abhishek Shetty, Raaz Dwivedi, Lester Mackey
ICML 2025 | February 2025
-
-
-
SureMap: Simultaneous mean estimation for single-task and multi-task disaggregated evaluation
Lester Mackey, Miro Dudík, Alex Chouldechova
October 2024
-
Debiased Distribution Compression
Lingxiao Li, Raaz Dwivedi, Lester Mackey
ICML 2024 | April 2024
-
-
-
A Finite-Particle Convergence Rate for Stein Variational Gradient Descent
Jiaxin Shi, Lester Mackey
NeurIPS 2023 | December 2023
-
SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery
Konstantin Klemmer, Esther Rolf, Caleb Robinson, Lester Mackey, M. Rußwurm
November 2023
-
Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation
E. Zelikman, Eliana Lorch, Lester Mackey, Adam Tauman Kalai
October 2023
-
Evaluation of Dependency Structure for Multivariate Weather Predictors using Copulas
Samuel Chege Maina, Dorcas Mwigereri, Jonathan Weyn, Lester Mackey, Millicent Ochieng
ACM Journal on Computing and Sustainable Societies | September 2023, 巻1(2): pp. 1-23
-
Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations
Hammaad Adam, Fan Yin, Mary Hu, Neil Tenenholtz, Lorin Crawford, Lester Mackey, Allison Koenecke
NeurIPS 2023 | June 2023
-
Adaptive Bias Correction for Improved Subseasonal Forecasting
Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Judah Cohen, Miruna Oprescu, Ernest Fraenkel, Lester Mackey
Nature Communications | June 2023
-
Learning Rate Free Bayesian Inference in Constrained Domains
Lester Mackey, Louis Sharrock, Christopher Nemeth
NeurIPS 2023 | May 2023
-
-
-
Gradient Estimation with Discrete Stein Operators
Jiaxin Shi, Yuhao Zhou, Jessica Hwang, Michalis Titsias, Lester Mackey
NeurIPS 2022 | November 2022
Outstanding Paper
-
Scalable Spike-and-Slab
Niloy Biswas, Lester Mackey, Xiao-Li Meng
ICML 2022 | July 2022
-
Distribution Compression in Near-Linear Time
Abhishek Shetty, Raaz Dwivedi, Lester Mackey
ICLR 2022 | April 2022
-
Generalized Kernel Thinning
ICLR 2022 | April 2022
-
Sampling with Mirrored Stein Operators
Jiaxin Shi, Chang Liu, Lester Mackey
ICLR 2022 | April 2022
-
-
-
Learned Benchmarks for Subseasonal Forecasting
Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Miruna Oprescu, Judah Cohen, Franklyn Wang, Sean Knight, Maria Geogdzhayeva, Sam Levang, Ernest Fraenkel, Lester Mackey
September 2021
Preprint
-
Independent Finite Approximations For Bayesian Nonparametric Inference
Tin D. Nguyen, Jonathan Huggins, Lorenzo Masoero, Lester Mackey, Tamara Broderick
July 2021
-
Online Learning with Optimism and Delay
Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey
2021 International Conference on Machine Learning | July 2021
-
Kernel Thinning
Raaz Dwivedi, Lester Mackey
COLT 2021 | May 2021
-
Initialization and Regularization of Factorized Neural Layers
Mikhail Khodak, Neil Tenenholtz, Lester Mackey, Nicolo Fusi
2021 International Conference on Learning Representations | May 2021
-
Knowledge Distillation as Semiparametric Inference
Tri Dao, Govinda M Kamath, Vasilis Syrgkanis, Lester Mackey
April 2021
-
-
-
Stochastic Stein Discrepancies
Jackson Gorham, Anant Raj, Lester Mackey
NeurIPS | December 2020
-
Cross-validation Confidence Intervals for Test Error
Pierre Bayle, Alexandre Bayle, Lucas Janson, Lester Mackey
July 2020
-
Opportunities and Challenges for Analyzing Cancer Data at the Inter- and Intra-Institutional Levels
Julie Wu, Jordan Bryan, Samuel M. Rubinstein, Lucy Wang, Michele Lenoue-Newton, Raed Zuhour, Mia Levy, Christine Micheel, Yaomin Xu, Suresh K. Bhavnani, Lester Mackey, Jeremy L. Warner
JCO Precision Oncology | July 2020
-
Single Point Transductive Prediction
Nilesh Tripuraneni, Lester Mackey
ICML 2020 | July 2020
-
Minimax Estimation of Conditional Moment Models
Nishanth Dikkala, Greg Lewis, Lester Mackey, Vasilis Syrgkanis
NeurIPS 2020 | June 2020
-
Bayesian seismic inversion: Measuring Langevin MCMC sample quality with kernels
Muhammad Izzatullah, Ricardo Baptista, Lester Mackey, Youssef M Marzouk
June 2020
-
Optimal Thinning of MCMC Output
Marina Riabiz, Wilson Chen, Jon Cockayne, Pawel Swietach, Steven A. Niederer, Lester Mackey, Chris. J. Oates
May 2020
-
Weighted Meta-Learning
Diana Cai, Rishit Sheth, Lester Mackey, Nicolo Fusi
March 2020
-
Approximate Cross-Validation: Guarantees For Model Assessment And Selection
Ashia Wilson, Maximilian Kasy, Lester Mackey
Proceedings of the 23rdInternational Conference on Artificial Intelligence and Statistics (AISTATS) 2020 | March 2020
-
-
-
Multifactorial Model to Predict Response to PD-(L)1 Blockade in Patients with High PD-L1 Metastatic Non-Small Cell Lung Cancer
K. Arbour, Miruna Oprescu, J. Hakim, H. Rizvi, M. Leiserson, M. Ginsburg, A. Plodkowski, J. Sauter, I. Preeshagul, Sharon Gillett, Philip Rosenfield, Lester Mackey, Miro Dudík, M. Hellmann
Journal of Thoracic Oncology | October 2019, 巻14(10): pp. S290
-
Improving Subseasonal Forecasting in the Western U.S. with Machine Learning
Jessica Hwang, Paulo Orenstein, Judah Cohen, Karl Pfeiffer, Lester Mackey
2019 Knowledge Discovery and Data Mining | July 2019
Sub-Seasonal Climate Forecast Rodeo challenge winner
-
A Kernel Stein Test For Comparing Latent Variable Models
Heishiro Kanagawa, Wittawat Jitkrittum, Lester Mackey, Kenji Fukumizu, Arthur Gretton
July 2019
ArXiv preprint
-
Measuring Sample Quality with Kernels
Jackson Gorham, Lester Mackey
International Conference on Machine Learning (ICML) | April 2019
-
Stratification of amyotrophic lateral sclerosis patients: a crowdsourcing approach
Robert Kueffner, Neta Zach, Maya Bronfeld, Raquel Norel, Nazem Atassi, Venkat Balagurusamy, Barbara DiCamillo, Adriano Chio, Merit Cudkowicz, Donna Dillenberger, Orla Hardiman, Bruce Hoff, Joshua Knight, Melanie L. Leitner, Guang Li, Lara Mangravite, Thea Norman, Liuxia Wang, The ALS Stratification Consortium (including Lester Mackey), Jinfeng Xiao, Wen-Chieh Fang, Jian Peng, Chen Yang, Huan-Jui Chang, Gustavo Stolovitzky, Lester Mackey
Scientific Reports | April 2019
-
-
-
A Multifactorial Model of T Cell Expansion and Durable Clinical Benefit in Response to a PD-L1 Inhibitor
Mark DM Leiserson, Vasilis Syrgkanis, Amy Gilson, Miroslav Dudik, Sharon Gillett, Jennifer Chayes, Christian Borgs, Dean F. Bajorin, Jonathan Rosenberg, Samuel Funt, Alexandra Snyder, Lester Mackey
PLOS ONE | December 2018, 巻13(12): pp. 1-11
-
S2S reboot: An argument for greater inclusion of machine learning in subseasonal to seasonal forecasts
Judah Cohen, Dim Coumou, Jessica Hwang, Lester Mackey, Paulo Orenstein, Sonja Totz
WIREs Climate Change | December 2018
-
Model Compression with Generative Adversarial Networks
Ruishan Liu, Nicolo Fusi, Lester Mackey
December 2018
-
Global Non-convex Optimization with Discretized Diffusions
Murat A. Erdogdu, Lester Mackey, Ohad Shamir
Advances in Neural Information Processing Systems (NeurIPS) | December 2018
-
Random Feature Stein Discrepancies
Jonathan Huggins, Lester Mackey
Advances in Neural Information Processing Systems (NeurIPS) | December 2018
-
Measuring Sample Quality with Diffusions
Jackson Gorham, Andrew B. Duncan, Sebastian J. Vollmer, Lester Mackey
November 2018
-
Stein Points
Wilson Ye Chen, Lester Mackey, Jackson Gorham, Francois-Xavier Briol, Chris J. Oates
International Conference on Machine Learning (ICML) | July 2018
-
Expert identification of visual primitives used by CNNs during mammogram classification
Jimmy Wu, Diondra Peck, Scott Hsieh, Vandana Dialani, Constance D. Lehman, Bolei Zhou, Vasilis Syrgkanis, Lester Mackey, Genevieve Patterson
Medical Imaging 2018: Computer-Aided Diagnosis, Proc. of SPIE Vol. 10575, 105752T | February 2018
-
-
-
Orthogonal Machine Learning: Power and Limitations
Lester Mackey, Vasilis Syrgkanis, Ilias Zadik
International Conference on Machine Learning | December 2017
-
Accurate Inference for Adaptive Linear Models
Yash Deshpande, Lester Mackey, Vasilis Syrgkanis, Matt Taddy
International Conference on Machine Learning (ICML) | December 2017
-
Empirical Bayesian Analysis of Simultaneous Changepoints in Multiple Data Sequences
Zhou Fan, Lester Mackey
Annals of Applied Statistics | December 2017
-
Improving Gibbs Sampler Scan Quality with DoGS
IOANNIS MITLIAGKAS, Lester Mackey
International Conference on Machine Learning (ICML) | August 2017
-
-
-
KerJEPA: Kernel Discrepancies for Euclidean Self-Supervised Learning
Eric Zimmermann, Eric Zimmermann, Harley Wiltzer, Justin Szeto, David Alvarez-Melis, Lester Mackey
December 2025
-
Informed Correctors for Discrete Diffusion Models
Yixiu Zhao, Jiaxin Shi, Lester Mackey, Scott W. Linderman
NeurIPS 2025 | September 2025
-
It’s Hard to Be Normal: The Impact of Noise on Structure-agnostic Estimation
Jikai Jin, Lester Mackey, Vasilis Syrgkanis
NeurIPS 2025 | July 2025
-
Causal integration of chemical structures improves representations of microscopy images for morphological profiling
Yemin Yu, Neil Tenenholtz, Lester Mackey, Ying Wei, David Alvarez-Melis, Ava P. Amini, Alex Lu
April 2025
-
Cheap Permutation Testing
Carles Domingo-Enrich, Raaz Dwivedi, Lester Mackey
March 2025
-
Low-Rank Thinning
A. M. Carrell, Albert Gong, Abhishek Shetty, Raaz Dwivedi, Lester Mackey
ICML 2025 | February 2025
-
SureMap: Simultaneous mean estimation for single-task and multi-task disaggregated evaluation
Lester Mackey, Miro Dudík, Alex Chouldechova
October 2024
-
Debiased Distribution Compression
Lingxiao Li, Raaz Dwivedi, Lester Mackey
ICML 2024 | April 2024
-
A Finite-Particle Convergence Rate for Stein Variational Gradient Descent
Jiaxin Shi, Lester Mackey
NeurIPS 2023 | December 2023
-
SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery
Konstantin Klemmer, Esther Rolf, Caleb Robinson, Lester Mackey, M. Rußwurm
November 2023
-
Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation
E. Zelikman, Eliana Lorch, Lester Mackey, Adam Tauman Kalai
October 2023
-
Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations
Hammaad Adam, Fan Yin, Mary Hu, Neil Tenenholtz, Lorin Crawford, Lester Mackey, Allison Koenecke
NeurIPS 2023 | June 2023
-
Adaptive Bias Correction for Improved Subseasonal Forecasting
Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Judah Cohen, Miruna Oprescu, Ernest Fraenkel, Lester Mackey
Nature Communications | June 2023
-
Learning Rate Free Bayesian Inference in Constrained Domains
Lester Mackey, Louis Sharrock, Christopher Nemeth
NeurIPS 2023 | May 2023
-
Gradient Estimation with Discrete Stein Operators
Jiaxin Shi, Yuhao Zhou, Jessica Hwang, Michalis Titsias, Lester Mackey
NeurIPS 2022 | November 2022
Outstanding Paper
-
Scalable Spike-and-Slab
Niloy Biswas, Lester Mackey, Xiao-Li Meng
ICML 2022 | July 2022
-
Generalized Kernel Thinning
ICLR 2022 | April 2022
-
Distribution Compression in Near-Linear Time
Abhishek Shetty, Raaz Dwivedi, Lester Mackey
ICLR 2022 | April 2022
-
Sampling with Mirrored Stein Operators
Jiaxin Shi, Chang Liu, Lester Mackey
ICLR 2022 | April 2022
-
Learned Benchmarks for Subseasonal Forecasting
Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Miruna Oprescu, Judah Cohen, Franklyn Wang, Sean Knight, Maria Geogdzhayeva, Sam Levang, Ernest Fraenkel, Lester Mackey
September 2021
Preprint
-
Independent Finite Approximations For Bayesian Nonparametric Inference
Tin D. Nguyen, Jonathan Huggins, Lorenzo Masoero, Lester Mackey, Tamara Broderick
July 2021
-
Online Learning with Optimism and Delay
Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey
2021 International Conference on Machine Learning | July 2021
-
Kernel Thinning
Raaz Dwivedi, Lester Mackey
COLT 2021 | May 2021
-
Initialization and Regularization of Factorized Neural Layers
Mikhail Khodak, Neil Tenenholtz, Lester Mackey, Nicolo Fusi
2021 International Conference on Learning Representations | May 2021
-
Knowledge Distillation as Semiparametric Inference
Tri Dao, Govinda M Kamath, Vasilis Syrgkanis, Lester Mackey
April 2021
-
Stochastic Stein Discrepancies
Jackson Gorham, Anant Raj, Lester Mackey
NeurIPS | December 2020
-
Single Point Transductive Prediction
Nilesh Tripuraneni, Lester Mackey
ICML 2020 | July 2020
-
Minimax Estimation of Conditional Moment Models
Nishanth Dikkala, Greg Lewis, Lester Mackey, Vasilis Syrgkanis
NeurIPS 2020 | June 2020
-
Optimal Thinning of MCMC Output
Marina Riabiz, Wilson Chen, Jon Cockayne, Pawel Swietach, Steven A. Niederer, Lester Mackey, Chris. J. Oates
May 2020
-
Weighted Meta-Learning
Diana Cai, Rishit Sheth, Lester Mackey, Nicolo Fusi
March 2020
-
Approximate Cross-Validation: Guarantees For Model Assessment And Selection
Ashia Wilson, Maximilian Kasy, Lester Mackey
Proceedings of the 23rdInternational Conference on Artificial Intelligence and Statistics (AISTATS) 2020 | March 2020
-
A Kernel Stein Test For Comparing Latent Variable Models
Heishiro Kanagawa, Wittawat Jitkrittum, Lester Mackey, Kenji Fukumizu, Arthur Gretton
July 2019
ArXiv preprint
-
Measuring Sample Quality with Kernels
Jackson Gorham, Lester Mackey
International Conference on Machine Learning (ICML) | April 2019
-
S2S reboot: An argument for greater inclusion of machine learning in subseasonal to seasonal forecasts
Judah Cohen, Dim Coumou, Jessica Hwang, Lester Mackey, Paulo Orenstein, Sonja Totz
WIREs Climate Change | December 2018
-
Model Compression with Generative Adversarial Networks
Ruishan Liu, Nicolo Fusi, Lester Mackey
December 2018
-
Random Feature Stein Discrepancies
Jonathan Huggins, Lester Mackey
Advances in Neural Information Processing Systems (NeurIPS) | December 2018
-
Global Non-convex Optimization with Discretized Diffusions
Murat A. Erdogdu, Lester Mackey, Ohad Shamir
Advances in Neural Information Processing Systems (NeurIPS) | December 2018
-
Measuring Sample Quality with Diffusions
Jackson Gorham, Andrew B. Duncan, Sebastian J. Vollmer, Lester Mackey
November 2018
-
Stein Points
Wilson Ye Chen, Lester Mackey, Jackson Gorham, Francois-Xavier Briol, Chris J. Oates
International Conference on Machine Learning (ICML) | July 2018
-
Accurate Inference for Adaptive Linear Models
Yash Deshpande, Lester Mackey, Vasilis Syrgkanis, Matt Taddy
International Conference on Machine Learning (ICML) | December 2017
-
Improving Gibbs Sampler Scan Quality with DoGS
IOANNIS MITLIAGKAS, Lester Mackey
International Conference on Machine Learning (ICML) | August 2017
-
-
-
Causal integration of chemical structures improves representations of microscopy images for morphological profiling
Yemin Yu, Neil Tenenholtz, Lester Mackey, Ying Wei, David Alvarez-Melis, Ava P. Amini, Alex Lu
April 2025
-
Opportunities and Challenges for Analyzing Cancer Data at the Inter- and Intra-Institutional Levels
Julie Wu, Jordan Bryan, Samuel M. Rubinstein, Lucy Wang, Michele Lenoue-Newton, Raed Zuhour, Mia Levy, Christine Micheel, Yaomin Xu, Suresh K. Bhavnani, Lester Mackey, Jeremy L. Warner
JCO Precision Oncology | July 2020
-
Multifactorial Model to Predict Response to PD-(L)1 Blockade in Patients with High PD-L1 Metastatic Non-Small Cell Lung Cancer
K. Arbour, Miruna Oprescu, J. Hakim, H. Rizvi, M. Leiserson, M. Ginsburg, A. Plodkowski, J. Sauter, I. Preeshagul, Sharon Gillett, Philip Rosenfield, Lester Mackey, Miro Dudík, M. Hellmann
Journal of Thoracic Oncology | October 2019, 巻14(10): pp. S290
-
Stratification of amyotrophic lateral sclerosis patients: a crowdsourcing approach
Robert Kueffner, Neta Zach, Maya Bronfeld, Raquel Norel, Nazem Atassi, Venkat Balagurusamy, Barbara DiCamillo, Adriano Chio, Merit Cudkowicz, Donna Dillenberger, Orla Hardiman, Bruce Hoff, Joshua Knight, Melanie L. Leitner, Guang Li, Lara Mangravite, Thea Norman, Liuxia Wang, The ALS Stratification Consortium (including Lester Mackey), Jinfeng Xiao, Wen-Chieh Fang, Jian Peng, Chen Yang, Huan-Jui Chang, Gustavo Stolovitzky, Lester Mackey
Scientific Reports | April 2019
-
A Multifactorial Model of T Cell Expansion and Durable Clinical Benefit in Response to a PD-L1 Inhibitor
Mark DM Leiserson, Vasilis Syrgkanis, Amy Gilson, Miroslav Dudik, Sharon Gillett, Jennifer Chayes, Christian Borgs, Dean F. Bajorin, Jonathan Rosenberg, Samuel Funt, Alexandra Snyder, Lester Mackey
PLOS ONE | December 2018, 巻13(12): pp. 1-11
-
Expert identification of visual primitives used by CNNs during mammogram classification
Jimmy Wu, Diondra Peck, Scott Hsieh, Vandana Dialani, Constance D. Lehman, Bolei Zhou, Vasilis Syrgkanis, Lester Mackey, Genevieve Patterson
Medical Imaging 2018: Computer-Aided Diagnosis, Proc. of SPIE Vol. 10575, 105752T | February 2018
-
Empirical Bayesian Analysis of Simultaneous Changepoints in Multiple Data Sequences
Zhou Fan, Lester Mackey
Annals of Applied Statistics | December 2017
-
-
-
SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery
Konstantin Klemmer, Esther Rolf, Caleb Robinson, Lester Mackey, M. Rußwurm
November 2023
-
Expert identification of visual primitives used by CNNs during mammogram classification
Jimmy Wu, Diondra Peck, Scott Hsieh, Vandana Dialani, Constance D. Lehman, Bolei Zhou, Vasilis Syrgkanis, Lester Mackey, Genevieve Patterson
Medical Imaging 2018: Computer-Aided Diagnosis, Proc. of SPIE Vol. 10575, 105752T | February 2018
-
-
-
Evaluation of Dependency Structure for Multivariate Weather Predictors using Copulas
Samuel Chege Maina, Dorcas Mwigereri, Jonathan Weyn, Lester Mackey, Millicent Ochieng
ACM Journal on Computing and Sustainable Societies | September 2023, 巻1(2): pp. 1-23
-
Adaptive Bias Correction for Improved Subseasonal Forecasting
Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Judah Cohen, Miruna Oprescu, Ernest Fraenkel, Lester Mackey
Nature Communications | June 2023
-
Learned Benchmarks for Subseasonal Forecasting
Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Miruna Oprescu, Judah Cohen, Franklyn Wang, Sean Knight, Maria Geogdzhayeva, Sam Levang, Ernest Fraenkel, Lester Mackey
September 2021
Preprint
-
Improving Subseasonal Forecasting in the Western U.S. with Machine Learning
Jessica Hwang, Paulo Orenstein, Judah Cohen, Karl Pfeiffer, Lester Mackey
2019 Knowledge Discovery and Data Mining | July 2019
Sub-Seasonal Climate Forecast Rodeo challenge winner
-
-
-
Evaluation of Dependency Structure for Multivariate Weather Predictors using Copulas
Samuel Chege Maina, Dorcas Mwigereri, Jonathan Weyn, Lester Mackey, Millicent Ochieng
ACM Journal on Computing and Sustainable Societies | September 2023, 巻1(2): pp. 1-23
-
Stein Points
Wilson Ye Chen, Lester Mackey, Jackson Gorham, Francois-Xavier Briol, Chris J. Oates
International Conference on Machine Learning (ICML) | July 2018
-
-
-
Initialization and Regularization of Factorized Neural Layers
Mikhail Khodak, Neil Tenenholtz, Lester Mackey, Nicolo Fusi
2021 International Conference on Learning Representations | May 2021
-
Knowledge Distillation as Semiparametric Inference
Tri Dao, Govinda M Kamath, Vasilis Syrgkanis, Lester Mackey
April 2021
-
Stochastic Stein Discrepancies
Jackson Gorham, Anant Raj, Lester Mackey
NeurIPS | December 2020
-
Cross-validation Confidence Intervals for Test Error
Pierre Bayle, Alexandre Bayle, Lucas Janson, Lester Mackey
July 2020
-
Bayesian seismic inversion: Measuring Langevin MCMC sample quality with kernels
Muhammad Izzatullah, Ricardo Baptista, Lester Mackey, Youssef M Marzouk
June 2020
-
Improving Subseasonal Forecasting in the Western U.S. with Machine Learning
Jessica Hwang, Paulo Orenstein, Judah Cohen, Karl Pfeiffer, Lester Mackey
2019 Knowledge Discovery and Data Mining | July 2019
Sub-Seasonal Climate Forecast Rodeo challenge winner
-
-
-
Empirical Bayesian Analysis of Simultaneous Changepoints in Multiple Data Sequences
Zhou Fan, Lester Mackey
Annals of Applied Statistics | December 2017
-
-
-
Orthogonal Machine Learning: Power and Limitations
Lester Mackey, Vasilis Syrgkanis, Ilias Zadik
International Conference on Machine Learning | December 2017
-
-
-
KerJEPA: Kernel Discrepancies for Euclidean Self-Supervised Learning
Eric Zimmermann, Eric Zimmermann, Harley Wiltzer, Justin Szeto, David Alvarez-Melis, Lester Mackey
December 2025
-
Causal integration of chemical structures improves representations of microscopy images for morphological profiling
Yemin Yu, Neil Tenenholtz, Lester Mackey, Ying Wei, David Alvarez-Melis, Ava P. Amini, Alex Lu
April 2025
-
Cheap Permutation Testing
Carles Domingo-Enrich, Raaz Dwivedi, Lester Mackey
March 2025
-
SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery
Konstantin Klemmer, Esther Rolf, Caleb Robinson, Lester Mackey, M. Rußwurm
November 2023
-
Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation
E. Zelikman, Eliana Lorch, Lester Mackey, Adam Tauman Kalai
October 2023
-
Independent Finite Approximations For Bayesian Nonparametric Inference
Tin D. Nguyen, Jonathan Huggins, Lorenzo Masoero, Lester Mackey, Tamara Broderick
July 2021
-
Knowledge Distillation as Semiparametric Inference
Tri Dao, Govinda M Kamath, Vasilis Syrgkanis, Lester Mackey
April 2021
-
Cross-validation Confidence Intervals for Test Error
Pierre Bayle, Alexandre Bayle, Lucas Janson, Lester Mackey
July 2020
-
Bayesian seismic inversion: Measuring Langevin MCMC sample quality with kernels
Muhammad Izzatullah, Ricardo Baptista, Lester Mackey, Youssef M Marzouk
June 2020
-
Optimal Thinning of MCMC Output
Marina Riabiz, Wilson Chen, Jon Cockayne, Pawel Swietach, Steven A. Niederer, Lester Mackey, Chris. J. Oates
May 2020
-
Weighted Meta-Learning
Diana Cai, Rishit Sheth, Lester Mackey, Nicolo Fusi
March 2020
-
Model Compression with Generative Adversarial Networks
Ruishan Liu, Nicolo Fusi, Lester Mackey
December 2018
-
Measuring Sample Quality with Diffusions
Jackson Gorham, Andrew B. Duncan, Sebastian J. Vollmer, Lester Mackey
November 2018
-
-
-
Informed Correctors for Discrete Diffusion Models
Yixiu Zhao, Jiaxin Shi, Lester Mackey, Scott W. Linderman
NeurIPS 2025 | September 2025
-
It’s Hard to Be Normal: The Impact of Noise on Structure-agnostic Estimation
Jikai Jin, Lester Mackey, Vasilis Syrgkanis
NeurIPS 2025 | July 2025
-
Low-Rank Thinning
A. M. Carrell, Albert Gong, Abhishek Shetty, Raaz Dwivedi, Lester Mackey
ICML 2025 | February 2025
-
Debiased Distribution Compression
Lingxiao Li, Raaz Dwivedi, Lester Mackey
ICML 2024 | April 2024
-
A Finite-Particle Convergence Rate for Stein Variational Gradient Descent
Jiaxin Shi, Lester Mackey
NeurIPS 2023 | December 2023
-
Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations
Hammaad Adam, Fan Yin, Mary Hu, Neil Tenenholtz, Lorin Crawford, Lester Mackey, Allison Koenecke
NeurIPS 2023 | June 2023
-
Learning Rate Free Bayesian Inference in Constrained Domains
Lester Mackey, Louis Sharrock, Christopher Nemeth
NeurIPS 2023 | May 2023
-
Gradient Estimation with Discrete Stein Operators
Jiaxin Shi, Yuhao Zhou, Jessica Hwang, Michalis Titsias, Lester Mackey
NeurIPS 2022 | November 2022
Outstanding Paper
-
Scalable Spike-and-Slab
Niloy Biswas, Lester Mackey, Xiao-Li Meng
ICML 2022 | July 2022
-
Generalized Kernel Thinning
ICLR 2022 | April 2022
-
Distribution Compression in Near-Linear Time
Abhishek Shetty, Raaz Dwivedi, Lester Mackey
ICLR 2022 | April 2022
-
Sampling with Mirrored Stein Operators
Jiaxin Shi, Chang Liu, Lester Mackey
ICLR 2022 | April 2022
-
Online Learning with Optimism and Delay
Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey
2021 International Conference on Machine Learning | July 2021
-
Kernel Thinning
Raaz Dwivedi, Lester Mackey
COLT 2021 | May 2021
-
Initialization and Regularization of Factorized Neural Layers
Mikhail Khodak, Neil Tenenholtz, Lester Mackey, Nicolo Fusi
2021 International Conference on Learning Representations | May 2021
-
Stochastic Stein Discrepancies
Jackson Gorham, Anant Raj, Lester Mackey
NeurIPS | December 2020
-
Single Point Transductive Prediction
Nilesh Tripuraneni, Lester Mackey
ICML 2020 | July 2020
-
Minimax Estimation of Conditional Moment Models
Nishanth Dikkala, Greg Lewis, Lester Mackey, Vasilis Syrgkanis
NeurIPS 2020 | June 2020
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Approximate Cross-Validation: Guarantees For Model Assessment And Selection
Ashia Wilson, Maximilian Kasy, Lester Mackey
Proceedings of the 23rdInternational Conference on Artificial Intelligence and Statistics (AISTATS) 2020 | March 2020
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Improving Subseasonal Forecasting in the Western U.S. with Machine Learning
Jessica Hwang, Paulo Orenstein, Judah Cohen, Karl Pfeiffer, Lester Mackey
2019 Knowledge Discovery and Data Mining | July 2019
Sub-Seasonal Climate Forecast Rodeo challenge winner
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Measuring Sample Quality with Kernels
Jackson Gorham, Lester Mackey
International Conference on Machine Learning (ICML) | April 2019
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Random Feature Stein Discrepancies
Jonathan Huggins, Lester Mackey
Advances in Neural Information Processing Systems (NeurIPS) | December 2018
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Global Non-convex Optimization with Discretized Diffusions
Murat A. Erdogdu, Lester Mackey, Ohad Shamir
Advances in Neural Information Processing Systems (NeurIPS) | December 2018
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Stein Points
Wilson Ye Chen, Lester Mackey, Jackson Gorham, Francois-Xavier Briol, Chris J. Oates
International Conference on Machine Learning (ICML) | July 2018
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Orthogonal Machine Learning: Power and Limitations
Lester Mackey, Vasilis Syrgkanis, Ilias Zadik
International Conference on Machine Learning | December 2017
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Accurate Inference for Adaptive Linear Models
Yash Deshpande, Lester Mackey, Vasilis Syrgkanis, Matt Taddy
International Conference on Machine Learning (ICML) | December 2017
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Improving Gibbs Sampler Scan Quality with DoGS
IOANNIS MITLIAGKAS, Lester Mackey
International Conference on Machine Learning (ICML) | August 2017
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SureMap: Simultaneous mean estimation for single-task and multi-task disaggregated evaluation
Lester Mackey, Miro Dudík, Alex Chouldechova
October 2024
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Learned Benchmarks for Subseasonal Forecasting
Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Miruna Oprescu, Judah Cohen, Franklyn Wang, Sean Knight, Maria Geogdzhayeva, Sam Levang, Ernest Fraenkel, Lester Mackey
September 2021
Preprint
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A Kernel Stein Test For Comparing Latent Variable Models
Heishiro Kanagawa, Wittawat Jitkrittum, Lester Mackey, Kenji Fukumizu, Arthur Gretton
July 2019
ArXiv preprint
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Evaluation of Dependency Structure for Multivariate Weather Predictors using Copulas
Samuel Chege Maina, Dorcas Mwigereri, Jonathan Weyn, Lester Mackey, Millicent Ochieng
ACM Journal on Computing and Sustainable Societies | September 2023, 巻1(2): pp. 1-23
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Adaptive Bias Correction for Improved Subseasonal Forecasting
Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Judah Cohen, Miruna Oprescu, Ernest Fraenkel, Lester Mackey
Nature Communications | June 2023
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Opportunities and Challenges for Analyzing Cancer Data at the Inter- and Intra-Institutional Levels
Julie Wu, Jordan Bryan, Samuel M. Rubinstein, Lucy Wang, Michele Lenoue-Newton, Raed Zuhour, Mia Levy, Christine Micheel, Yaomin Xu, Suresh K. Bhavnani, Lester Mackey, Jeremy L. Warner
JCO Precision Oncology | July 2020
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Multifactorial Model to Predict Response to PD-(L)1 Blockade in Patients with High PD-L1 Metastatic Non-Small Cell Lung Cancer
K. Arbour, Miruna Oprescu, J. Hakim, H. Rizvi, M. Leiserson, M. Ginsburg, A. Plodkowski, J. Sauter, I. Preeshagul, Sharon Gillett, Philip Rosenfield, Lester Mackey, Miro Dudík, M. Hellmann
Journal of Thoracic Oncology | October 2019, 巻14(10): pp. S290
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Stratification of amyotrophic lateral sclerosis patients: a crowdsourcing approach
Robert Kueffner, Neta Zach, Maya Bronfeld, Raquel Norel, Nazem Atassi, Venkat Balagurusamy, Barbara DiCamillo, Adriano Chio, Merit Cudkowicz, Donna Dillenberger, Orla Hardiman, Bruce Hoff, Joshua Knight, Melanie L. Leitner, Guang Li, Lara Mangravite, Thea Norman, Liuxia Wang, The ALS Stratification Consortium (including Lester Mackey), Jinfeng Xiao, Wen-Chieh Fang, Jian Peng, Chen Yang, Huan-Jui Chang, Gustavo Stolovitzky, Lester Mackey
Scientific Reports | April 2019
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A Multifactorial Model of T Cell Expansion and Durable Clinical Benefit in Response to a PD-L1 Inhibitor
Mark DM Leiserson, Vasilis Syrgkanis, Amy Gilson, Miroslav Dudik, Sharon Gillett, Jennifer Chayes, Christian Borgs, Dean F. Bajorin, Jonathan Rosenberg, Samuel Funt, Alexandra Snyder, Lester Mackey
PLOS ONE | December 2018, 巻13(12): pp. 1-11
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S2S reboot: An argument for greater inclusion of machine learning in subseasonal to seasonal forecasts
Judah Cohen, Dim Coumou, Jessica Hwang, Lester Mackey, Paulo Orenstein, Sonja Totz
WIREs Climate Change | December 2018
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Expert identification of visual primitives used by CNNs during mammogram classification
Jimmy Wu, Diondra Peck, Scott Hsieh, Vandana Dialani, Constance D. Lehman, Bolei Zhou, Vasilis Syrgkanis, Lester Mackey, Genevieve Patterson
Medical Imaging 2018: Computer-Aided Diagnosis, Proc. of SPIE Vol. 10575, 105752T | February 2018
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Empirical Bayesian Analysis of Simultaneous Changepoints in Multiple Data Sequences
Zhou Fan, Lester Mackey
Annals of Applied Statistics | December 2017
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