Mackey, Lester

46 publications

NeurIPS 2025 Informed Correctors for Discrete Diffusion Models Yixiu Zhao, Jiaxin Shi, Feng Chen, Shaul Druckmann, Lester Mackey, Scott Linderman

NeurIPS 2025 It’s Hard to Be Normal: The Impact of Noise on Structure-Agnostic Estimation Jikai Jin, Lester Mackey, Vasilis Syrgkanis

ICML 2025 Low-Rank Thinning Annabelle Michael Carrell, Albert Gong, Abhishek Shetty, Raaz Dwivedi, Lester Mackey

AAAI 2025 SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery Konstantin Klemmer, Esther Rolf, Caleb Robinson, Lester Mackey, Marc Rußwurm

NeurIPSW 2024 Adapting Language Models via Token Translation Zhili Feng, Tanya Marwah, Nicolo Fusi, David Alvarez-Melis, Lester Mackey

NeurIPSW 2024 Adapting Language Models via Token Translation Zhili Feng, Tanya Marwah, Lester Mackey, David Alvarez-Melis, Nicolo Fusi

NeurIPSW 2024 Adapting Language Models via Token Translation Zhili Feng, Tanya Marwah, Nicolo Fusi, David Alvarez-Melis, Lester Mackey

ICML 2024 Debiased Distribution Compression Lingxiao Li, Raaz Dwivedi, Lester Mackey

JMLR 2024 Kernel Thinning Raaz Dwivedi, Lester Mackey

NeurIPS 2024 SureMap: Simultaneous Mean Estimation for Single-Task and Multi-Task Disaggregated Evaluation Mikhail Khodak, Lester Mackey, Alexandra Chouldechova, Miroslav Dudík

JMLR 2024 Targeted Separation and Convergence with Kernel Discrepancies Alessandro Barp, Carl-Johann Simon-Gabriel, Mark Girolami, Lester Mackey

ICMLW 2023 Adaptive Bias Correction for Improved Subseasonal Forecasting Soukayna Mouatadid, Paulo Orenstein, Genevieve Elaine Flaspohler, Judah Cohen, Miruna Oprescu, Ernest Fraenkel, Lester Mackey

AISTATS 2023 Compress Then Test: Powerful Kernel Testing in Near-Linear Time Carles Domingo-Enrich, Raaz Dwivedi, Lester Mackey

NeurIPSW 2023 Do Language Models Know When They're Hallucinating References? Ayush Agrawal, Mirac Suzgun, Lester Mackey, Adam Kalai

JMLR 2023 Metrizing Weak Convergence with Maximum Mean Discrepancies Carl-Johann Simon-Gabriel, Alessandro Barp, Bernhard Schölkopf, Lester Mackey

NeurIPSW 2023 Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation Eric Zelikman, Eliana Lorch, Lester Mackey, Adam Tauman Kalai

NeurIPSW 2023 Towards Global, General-Purpose Pretrained Geographic Location Encoders Konstantin Klemmer, Esther Rolf, Caleb Robinson, Lester Mackey, Marc Rußwurm

NeurIPSW 2022 A Finite-Particle Convergence Rate for Stein Variational Gradient Descent Jiaxin Shi, Lester Mackey

NeurIPSW 2022 Adaptive Bias Correction for Improved Subseasonal Forecast Soukayna Mouatadid, Paulo Orenstein, Genevieve Elaine Flaspohler, Judah Cohen, Miruna Oprescu, Ernest Fraenkel, Lester Mackey

ICLR 2022 Distribution Compression in Near-Linear Time Abhishek Shetty, Raaz Dwivedi, Lester Mackey

ICLR 2022 Generalized Kernel Thinning Raaz Dwivedi, Lester Mackey

ICLR 2022 Sampling with Mirrored Stein Operators Jiaxin Shi, Chang Liu, Lester Mackey

ICML 2022 Scalable Spike-and-Slab Niloy Biswas, Lester Mackey, Xiao-Li Meng

NeurIPSW 2022 Targeted Separation and Convergence with Kernel Discrepancies Alessandro Barp, Carl-Johann Simon-Gabriel, Mark Girolami, Lester Mackey

ICLR 2021 Initialization and Regularization of Factorized Neural Layers Mikhail Khodak, Neil A. Tenenholtz, Lester Mackey, Nicolo Fusi

COLT 2021 Kernel Thinning Raaz Dwivedi, Lester Mackey

ICLR 2021 Knowledge Distillation as Semiparametric Inference Tri Dao, Govinda M Kamath, Vasilis Syrgkanis, Lester Mackey

ICML 2021 Online Learning with Optimism and Delay Genevieve E Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey

AISTATS 2020 Approximate Cross-Validation: Guarantees for Model Assessment and Selection Ashia Wilson, Maximilian Kasy, Lester Mackey

AISTATS 2020 Importance Sampling via Local Sensitivity Anant Raj, Cameron Musco, Lester Mackey

NeurIPSW 2020 Independent Versus Truncated Finite Approximations for Bayesian Nonparametric Inference Tin D. Nguyen, Jonathan H. Huggins, Lorenzo Masoero, Lester Mackey, Tamara Broderick

ICML 2020 Single Point Transductive Prediction Nilesh Tripuraneni, Lester Mackey

NeurIPS 2019 Accelerating Rescaled Gradient Descent: Fast Optimization of Smooth Functions Ashia C Wilson, Lester Mackey, Andre Wibisono

NeurIPS 2019 Minimum Stein Discrepancy Estimators Alessandro Barp, Francois-Xavier Briol, Andrew Duncan, Mark Girolami, Lester Mackey

ICML 2019 Stein Point Markov Chain Monte Carlo Wilson Ye Chen, Alessandro Barp, Francois-Xavier Briol, Jackson Gorham, Mark Girolami, Lester Mackey, Chris Oates

NeurIPS 2019 Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond Xuechen Li, Yi Wu, Lester Mackey, Murat A Erdogdu

ICML 2018 Accurate Inference for Adaptive Linear Models Yash Deshpande, Lester Mackey, Vasilis Syrgkanis, Matt Taddy

NeurIPS 2018 Global Non-Convex Optimization with Discretized Diffusions Murat A Erdogdu, Lester Mackey, Ohad Shamir

ICML 2018 Orthogonal Machine Learning: Power and Limitations Lester Mackey, Vasilis Syrgkanis, Ilias Zadik

NeurIPS 2018 Random Feature Stein Discrepancies Jonathan Huggins, Lester Mackey

ICML 2018 Stein Points Wilson Ye Chen, Lester Mackey, Jackson Gorham, Francois-Xavier Briol, Chris Oates

ICML 2017 Improving Gibbs Sampler Scan Quality with DoGS Ioannis Mitliagkas, Lester Mackey

ICML 2017 Measuring Sample Quality with Kernels Jackson Gorham, Lester Mackey

JMLR 2015 Distributed Matrix Completion and Robust Factorization Lester Mackey, Ameet Talwalkar, Michael I. Jordan

NeurIPS 2015 Measuring Sample Quality with Stein's Method Jackson Gorham, Lester Mackey

ICCV 2013 Distributed Low-Rank Subspace Segmentation Ameet Talwalkar, Lester Mackey, Yadong Mu, Shih-Fu Chang, Michael I. Jordan