Debiased Distribution Compression
Lingxiao Li, Raaz Dwivedi, Lester Mackey
ICML 2024 | April 2024
Lester Mackey
Principal Researcher
Publications
Publications by Year
-
-
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, Vol 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, Vol 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, Vol 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
Publications by Research Area
-
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
-
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, Vol 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, Vol 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
-
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, Vol 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, Vol 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
-
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
Publications by Type
-
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
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
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
Measuring Sample Quality with Kernels
Jackson Gorham, Lester Mackey
International Conference on Machine Learning (ICML) | April 2019
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
Stein Points
Wilson Ye Chen, Lester Mackey, Jackson Gorham, Francois-Xavier Briol, Chris J. Oates
International Conference on Machine Learning (ICML) | July 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
Improving Gibbs Sampler Scan Quality with DoGS
IOANNIS MITLIAGKAS, Lester Mackey
International Conference on Machine Learning (ICML) | August 2017
-
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
-
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, Vol 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
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, Vol 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, Vol 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
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
-
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
A Kernel Stein Test For Comparing Latent Variable Models
Heishiro Kanagawa, Wittawat Jitkrittum, Lester Mackey, Kenji Fukumizu, Arthur Gretton
July 2019
ArXiv preprint