Lester Mackey

According to our database, Lester Mackey authored at least 81 papers between 2006 and 2024.

Collaborative distances:

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

2024

Do Language Models Know When They're Hallucinating References?

Ayush Agrawal, Mirac Suzgun, Lester Mackey, Adam Kalai

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2024, 2024

2023

Social norm bias: residual harms of fairness-aware algorithms.

Myra Cheng, Maria De-Arteaga, Lester Mackey, Adam Tauman Kalai

Data Min. Knowl. Discov., September, 2023

Metrizing Weak Convergence with Maximum Mean Discrepancies.

Carl-Johann Simon-Gabriel, Alessandro Barp, Bernhard Schölkopf, Lester Mackey

J. Mach. Learn. Res., 2023

SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery.

Konstantin Klemmer, Esther Rolf, Caleb Robinson, Lester Mackey, Marc Rußwurm

CoRR, 2023

Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation.

Eric Zelikman, Eliana Lorch, Lester Mackey, Adam Tauman Kalai

CoRR, 2023

Reflections from the Workshop on AI-Assisted Decision Making for Conservation.

Lily Xu, Esther Rolf, Sara Beery, Joseph R. Bennett, Tanya Y. Berger-Wolf, Tanya Birch, Elizabeth Bondi-Kelly, Justin Brashares, Melissa S. Chapman, Anthony Corso, Andrew Davies, Nikhil Garg, Angela Gaylard, Robert Heilmayr, Hannah Kerner, Konstantin Klemmer, Vipin Kumar, Lester Mackey, Claire Monteleoni, Paul Moorcroft, Jonathan Palmer, Andrew Perrault, David Thau, Milind Tambe

CoRR, 2023

Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations.

Hammaad Adam, Fan Yin, Mary Hu, Neil A. Tenenholtz, Lorin Crawford, Lester Mackey, Allison Koenecke

CoRR, 2023

Do Language Models Know When They're Hallucinating References?

Ayush Agrawal, Lester Mackey, Adam Tauman Kalai

CoRR, 2023

A Finite-Particle Convergence Rate for Stein Variational Gradient Descent.

Jiaxin Shi, Lester Mackey

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Rate Free Bayesian Inference in Constrained Domains.

Louis Sharrock, Lester Mackey, Christopher Nemeth

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

SubseasonalClimateUSA: A Dataset for Subseasonal Forecasting and Benchmarking.

Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Miruna Oprescu, Judah Cohen, Franklyn Wang, Sean Knight, Maria Geogdzhayeva, Sam Levang, Ernest Fraenkel, Lester Mackey

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations.

Hammaad Adam, Fan Yin, Huibin Hu, Neil A. Tenenholtz, Lorin Crawford, Lester Mackey, Allison Koenecke

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Compress Then Test: Powerful Kernel Testing in Near-linear Time.

Carles Domingo-Enrich, Raaz Dwivedi, Lester Mackey

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Controlling Moments with Kernel Stein Discrepancies.

Heishiro Kanagawa, Arthur Gretton, Lester Mackey

CoRR, 2022

Budget-Constrained Bounds for Mini-Batch Estimation of Optimal Transport.

David Alvarez-Melis, Nicolò Fusi, Lester Mackey, Tal Wagner

CoRR, 2022

Targeted Separation and Convergence with Kernel Discrepancies.

Alessandro Barp, Carl-Johann Simon-Gabriel, Mark Girolami, Lester Mackey

CoRR, 2022

Adaptive Bias Correction for Improved Subseasonal Forecasting.

Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Judah Cohen, Miruna Oprescu, Ernest Fraenkel, Lester Mackey

CoRR, 2022

Gradient Estimation with Discrete Stein Operators.

Jiaxin Shi, Yuhao Zhou, Jessica Hwang, Michalis K. Titsias, Lester Mackey

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Scalable Spike-and-Slab.

Niloy Biswas, Lester Mackey, Xiao-Li Meng

Proceedings of the International Conference on Machine Learning, 2022

Sampling with Mirrored Stein Operators.

Jiaxin Shi, Chang Liu, Lester Mackey

Proceedings of the Tenth International Conference on Learning Representations, 2022

Distribution Compression in Near-Linear Time.

Abhishek Shetty, Raaz Dwivedi, Lester Mackey

Proceedings of the Tenth International Conference on Learning Representations, 2022

Generalized Kernel Thinning.

Raaz Dwivedi, Lester Mackey

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Bounding Wasserstein distance with couplings.

Niloy Biswas, Lester Mackey

CoRR, 2021

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

CoRR, 2021

Near-optimal inference in adaptive linear regression.

Koulik Khamaru, Yash Deshpande, Lester Mackey, Martin J. Wainwright

CoRR, 2021

Online Learning with Optimism and Delay.

Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey

Proceedings of the 38th International Conference on Machine Learning, 2021

Initialization and Regularization of Factorized Neural Layers.

Mikhail Khodak, Neil A. Tenenholtz, Lester Mackey, Nicolò Fusi

Proceedings of the 9th International Conference on Learning Representations, 2021

Knowledge Distillation as Semiparametric Inference.

Tri Dao, Govinda M. Kamath, Vasilis Syrgkanis, Lester Mackey

Proceedings of the 9th International Conference on Learning Representations, 2021

Kernel Thinning.

Raaz Dwivedi, Lester Mackey

Proceedings of the Conference on Learning Theory, 2021

2020

Model-specific Data Subsampling with Influence Functions.

Anant Raj, Cameron Musco, Lester Mackey, Nicoló Fusi

CoRR, 2020

Metrizing Weak Convergence with Maximum Mean Discrepancies.

Carl-Johann Simon-Gabriel, Alessandro Barp, Lester Mackey

CoRR, 2020

Weighted Meta-Learning.

Diana Cai, Rishit Sheth, Lester Mackey, Nicoló Fusi

CoRR, 2020

Stochastic Stein Discrepancies.

Jackson Gorham, Anant Raj, Lester Mackey

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

Minimax Estimation of Conditional Moment Models.

Nishanth Dikkala, Greg Lewis, Lester Mackey, Vasilis Syrgkanis

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

Cross-validation Confidence Intervals for Test Error.

Pierre Bayle, Alexandre Bayle, Lucas Janson, Lester Mackey

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

Single Point Transductive Prediction.

Nilesh Tripuraneni, Lester Mackey

Proceedings of the 37th International Conference on Machine Learning, 2020

Approximate Cross-validation: Guarantees for Model Assessment and Selection.

Ashia C. Wilson, Maximilian Kasy, Lester Mackey

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Importance Sampling via Local Sensitivity.

Anant Raj, Cameron Musco, Lester Mackey

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Debiasing Linear Prediction.

Nilesh Tripuraneni, Lester Mackey

CoRR, 2019

A Kernel Stein Test for Comparing Latent Variable Models.

Heishiro Kanagawa, Wittawat Jitkrittum, Lester Mackey, Kenji Fukumizu, Arthur Gretton

CoRR, 2019

Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond.

Xuechen Li, Denny Wu, Lester Mackey, Murat A. Erdogdu

CoRR, 2019

Accelerating Rescaled Gradient Descent: Fast Optimization of Smooth Functions.

Ashia C. Wilson, Lester Mackey, Andre Wibisono

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond.

Xuechen Li, Yi Wu, Lester Mackey

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Minimum Stein Discrepancy Estimators.

Alessandro Barp, François-Xavier Briol, Andrew B. Duncan, Mark A. Girolami, Lester W. Mackey

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Improving Subseasonal Forecasting in the Western U.S. with Machine Learning.

Jessica Hwang, Paulo Orenstein, Judah Cohen, Karl Pfeiffer, Lester Mackey

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Stein Point Markov Chain Monte Carlo.

Wilson Ye Chen, Alessandro Barp, François-Xavier Briol, Jackson Gorham, Mark A. Girolami, Lester W. Mackey, Chris J. Oates

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Model Compression with Generative Adversarial Networks.

Ruishan Liu, Nicoló Fusi, Lester Mackey

CoRR, 2018

DeepMiner: Discovering Interpretable Representations for Mammogram Classification and Explanation.

Jimmy Wu, Bolei Zhou, Diondra Peck, Scott Hsieh, Vandana Dialani, Lester W. Mackey, Genevieve Patterson

CoRR, 2018

Random Feature Stein Discrepancies.

Jonathan H. Huggins, Lester Mackey

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Global Non-convex Optimization with Discretized Diffusions.

Murat A. Erdogdu, Lester Mackey, Ohad Shamir

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 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 W. Mackey, Genevieve Patterson

Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

Orthogonal Machine Learning: Power and Limitations.

Ilias Zadik, Lester W. Mackey, Vasilis Syrgkanis

Proceedings of the 35th International Conference on Machine Learning, 2018

Accurate Inference for Adaptive Linear Models.

Yash Deshpande, Lester W. Mackey, Vasilis Syrgkanis, Matt Taddy

Proceedings of the 35th International Conference on Machine Learning, 2018

Stein Points.

Wilson Ye Chen, Lester W. Mackey, Jackson Gorham, François-Xavier Briol, Chris J. Oates

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Predicting inpatient clinical order patterns with probabilistic topic models vs conventional order sets.

Jonathan H. Chen, Mary K. Goldstein, Steven M. Asch, Lester W. Mackey, Russ B. Altman

J. Am. Medical Informatics Assoc., 2017

Improving Gibbs Sampler Scan Quality with DoGS.

Ioannis Mitliagkas, Lester W. Mackey

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

Measuring Sample Quality with Kernels.

Jackson Gorham, Lester W. Mackey

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

2016

Measuring Sample Quality with Diffusions.

Jack Gorham, Andrew B. Duncan, Sebastian J. Vollmer, Lester W. Mackey

CoRR, 2016

Automated Organization of Electronic Health Record Data by Probabilistic Topic Modeling to Inform Clinical Decision Making.

Jonathan H. Chen, Mary K. Goldstein, Steven M. Asch, Lester W. Mackey, Russ B. Altman

Proceedings of the Summit on Clinical Research Informatics, 2016

2015

Combinatorial Clustering and the Beta Negative Binomial Process.

Tamara Broderick, Lester W. Mackey, John W. Paisley, Michael I. Jordan

IEEE Trans. Pattern Anal. Mach. Intell., 2015

Distributed matrix completion and robust factorization.

Lester W. Mackey, Ameet Talwalkar, Michael I. Jordan

J. Mach. Learn. Res., 2015

Measuring Sample Quality with Stein's Method.

Jackson Gorham, Lester W. Mackey

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Mixed Membership Matrix Factorization.

Lester W. Mackey, David J. Weiss, Michael I. Jordan

Proceedings of the Handbook of Mixed Membership Models and Their Applications., 2014

Corrupted Sensing: Novel Guarantees for Separating Structured Signals.

Rina Foygel, Lester W. Mackey

IEEE Trans. Inf. Theory, 2014

Joint Link Prediction and Attribute Inference Using a Social-Attribute Network.

Neil Zhenqiang Gong, Ameet Talwalkar, Lester W. Mackey, Ling Huang, Eui Chul Richard Shin, Emil Stefanov, Elaine Shi, Dawn Song

ACM Trans. Intell. Syst. Technol., 2014

Weighted Classification Cascades for Optimizing Discovery Significance in the HiggsML Challenge.

Lester W. Mackey, Jordan Bryan

CoRR, 2014

Weighted Classification Cascades for Optimizing Discovery Significance in the HiggsML Challenge.

Lester W. Mackey, Jordan Bryan, Man Yue Mo

Proceedings of the Workshop on High-energy Physics and Machine Learning, 2014

2013

Divide-and-Conquer Subspace Segmentation

Ameet Talwalkar, Lester W. Mackey, Yadong Mu, Shih-Fu Chang, Michael I. Jordan

CoRR, 2013

Distributed Low-Rank Subspace Segmentation.

Ameet Talwalkar, Lester W. Mackey, Yadong Mu, Shih-Fu Chang, Michael I. Jordan

Proceedings of the IEEE International Conference on Computer Vision, 2013

2012

Matrix Factorization and Matrix Concentration.

Lester Mackey

PhD thesis, 2012

The Asymptotics of Ranking Algorithms

John C. Duchi, Lester W. Mackey, Michael I. Jordan

CoRR, 2012

2011

Predicting Links and Inferring Attributes using a Social-Attribute Network (SAN)

Neil Zhenqiang Gong, Ameet Talwalkar, Lester W. Mackey, Ling Huang, Eui Chul Richard Shin, Emil Stefanov, Elaine Shi, Dawn Song

CoRR, 2011

Divide-and-Conquer Matrix Factorization.

Lester W. Mackey, Ameet Talwalkar, Michael I. Jordan

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Visually Relating Gene Expression and in vivo DNA Binding Data.

Min-Yu Huang, Lester W. Mackey, Soile V. E. Keränen, Gunther H. Weber, Michael I. Jordan, David W. Knowles, Mark D. Biggin, Bernd Hamann

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2011

2010

Mixed Membership Matrix Factorization.

Lester W. Mackey, David J. Weiss, Michael I. Jordan

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

On the Consistency of Ranking Algorithms.

John C. Duchi, Lester W. Mackey, Michael I. Jordan

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

2009

Feature-Weighted Linear Stacking

Joseph Sill, Gábor Takács, Lester W. Mackey, David Lin

CoRR, 2009

2008

Deflation Methods for Sparse PCA.

Lester W. Mackey

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007

Fault-tolerant typed assembly language.

Frances Perry, Lester W. Mackey, George A. Reis, Jay Ligatti, David I. August, David Walker

Proceedings of the ACM SIGPLAN 2007 Conference on Programming Language Design and Implementation, 2007

2006

Static typing for a faulty lambda calculus.

David Walker, Lester W. Mackey, Jay Ligatti, George A. Reis, David I. August

Proceedings of the 11th ACM SIGPLAN International Conference on Functional Programming, 2006

Participatory design with proxies: developing a desktop-PDA system to support people with aphasia.

Jordan L. Boyd-Graber, Sonya S. Nikolova, Karyn Moffatt, Kenrick C. Kin, Joshua Y. Lee, Lester W. Mackey, Marilyn Tremaine, Maria M. Klawe

Proceedings of the 2006 Conference on Human Factors in Computing Systems, 2006