Lester Mackey
34 papers · 2013–2025 · 9 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (12) π Conference Polyglot (9) π Interdisciplinary Bridge π§ Keyword Pioneer π£ Hot Topic Early Bird
π
Academic Marathon
(12)
π§
Keyword Pioneer
π
Conference Polyglot
(9)
π
Keyword Champion
(2)
π
Grand Slam
ποΈ
Keyword Collector
(131)
β‘
Prolific Year
(5)
π
Conference Pioneer
π
Century Club
(34)
π₯
Unstoppable
(9)
π
Trend Setter
β
The Questioner
Conferences
ICML (11)
NIPS (7)
ICLR (5)
JMLR (4)
AISTATS (3)
AAAI (1)
COLT (1)
EACL (1)
ICCV (1)
Top co-authors
Research topics
Keywords
markov chain monte carlo
(8)
kernel methods
(5)
stein discrepancy
(5)
maximum mean discrepancy
(5)
weak convergence
(3)
stein method
(3)
kernel stein discrepancy
(3)
reproducing kernel hilbert space
(3)
matrix factorization
(2)
convex optimization
(2)
sample quality
(2)
convergence rate
(2)
non-convex optimization
(2)
integration error
(2)
gibbs sampling
(2)
importance sampling
(2)
reproducing kernel
(2)
posterior inference
(2)
distributed computing
(2)
quasi-monte carlo
(2)
Papers
SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery
AAAI 2025
Low-Rank Thinning
ICML 2025
Kernel Thinning
JMLR 2024
Debiased Distribution Compression
ICML 2024
SureMap: Simultaneous mean estimation for single-task and multi-task disaggregated evaluation
NIPS 2024
Do Language Models Know When Theyβre Hallucinating References?
EACL 2024
Targeted Separation and Convergence with Kernel Discrepancies
JMLR 2024
Metrizing Weak Convergence with Maximum Mean Discrepancies
JMLR 2023
Compress Then Test: Powerful Kernel Testing in Near-linear Time
AISTATS 2023
Generalized Kernel Thinning
ICLR 2022
Distribution Compression in Near-Linear Time
ICLR 2022
Sampling with Mirrored Stein Operators
ICLR 2022
Scalable Spike-and-Slab
ICML 2022
Online Learning with Optimism and Delay
ICML 2021
Knowledge Distillation as Semiparametric Inference
ICLR 2021
Kernel Thinning
COLT 2021
Initialization and Regularization of Factorized Neural Layers
ICLR 2021
Importance Sampling via Local Sensitivity
AISTATS 2020
Approximate Cross-validation: Guarantees for Model Assessment and Selection
AISTATS 2020
Single Point Transductive Prediction
ICML 2020
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond
NIPS 2019
Minimum Stein Discrepancy Estimators
NIPS 2019
Accelerating Rescaled Gradient Descent: Fast Optimization of Smooth Functions
NIPS 2019
Stein Point Markov Chain Monte Carlo
ICML 2019
Orthogonal Machine Learning: Power and Limitations
ICML 2018
Global Non-convex Optimization with Discretized Diffusions
NIPS 2018
Stein Points
ICML 2018
Accurate Inference for Adaptive Linear Models
ICML 2018
Random Feature Stein Discrepancies
NIPS 2018
Improving Gibbs Sampler Scan Quality with DoGS
ICML 2017
Measuring Sample Quality with Kernels
ICML 2017
Distributed Matrix Completion and Robust Factorization
JMLR 2015
Measuring Sample Quality with Stein's Method
NIPS 2015
Distributed Low-Rank Subspace Segmentation
ICCV 2013