Lester Mackey - RankMe

90 papers A* 27A 3Journal 58Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Probabilistic Inference and Learning with Stein's Method. CoRR Qiang Liu, Lester Mackey, Chris J. Oates
2026	J	`jnl`	WildCat: Near-Linear Attention in Theory and Practice. CoRR Tobias Schröder, Lester Mackey
2025	J	`jnl`	Causal integration of chemical structures improves representations of microscopy images for morphological profiling. CoRR Yemin Yu, Neil A. Tenenholtz, Lester Mackey, Ying Wei, David Alvarez-Melis, Ava P. Amini, Alex X. Lu
2025	J	`jnl`	Coevolutionary Continuous Discrete Diffusion: Make Your Diffusion Language Model a Latent Reasoner. CoRR Cai Zhou, Chenxiao Yang, Yi Hu, Chenyu Wang, Chubin Zhang, Muhan Zhang, Lester Mackey, Tommi S. Jaakkola, Stephen Bates, Dinghuai Zhang
2025	J	`jnl`	Estimating Treatment Effects with Independent Component Analysis. CoRR Patrik Reizinger, Lester Mackey, Wieland Brendel, Rahul Krishnan
2025	J	`jnl`	It's Hard to Be Normal: The Impact of Noise on Structure-agnostic Estimation. CoRR Jikai Jin, Lester Mackey, Vasilis Syrgkanis
2025	J	`jnl`	KerJEPA: Kernel Discrepancies for Euclidean Self-Supervised Learning. CoRR Eric Zimmermann, Harley Wiltzer, Justin Szeto, David Alvarez-Melis, Lester Mackey
2025	A*	`conf`	Low-Rank Thinning. ICML Annabelle Michael Carrell, Albert Gong, Abhishek Shetty, Raaz Dwivedi, Lester Mackey
2025	J	`jnl`	Low-Rank Thinning. CoRR Annabelle Michael Carrell, Albert Gong, Abhishek Shetty, Raaz Dwivedi, Lester Mackey
2025	A*	`conf`	SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery. AAAI Konstantin Klemmer, Esther Rolf, Caleb Robinson, Lester Mackey, Marc Rußwurm
2025	J	`jnl`	The Relative Instability of Model Comparison with Cross-validation. CoRR Alexandre Bayle, Lucas Janson, Lester Mackey
2024	J	`jnl`	Adapting Language Models via Token Translation. CoRR Zhili Feng, Tanya Marwah, Nicolò Fusi, David Alvarez-Melis, Lester Mackey
2024	A*	`ed.`	Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver, BC, Canada, December 10 - 15, 2024. NeurIPS Amir Globersons, Lester Mackey, Danielle Belgrave, Angela Fan, Ulrich Paquet, Jakub M. Tomczak, Cheng Zhang
2024	A*	`conf`	Debiased Distribution Compression. ICML Lingxiao Li, Raaz Dwivedi, Lester Mackey
2024	J	`jnl`	Debiased Distribution Compression. CoRR Lingxiao Li, Raaz Dwivedi, Lester Mackey
2024	—	`conf`	Do Language Models Know When They're Hallucinating References? EACL (Findings) Ayush Agrawal, Mirac Suzgun, Lester Mackey, Adam Kalai
2024	J	`jnl`	Informed Correctors for Discrete Diffusion Models. CoRR Yixiu Zhao, Jiaxin Shi, Lester Mackey, Scott W. Linderman
2024	J	`jnl`	Kernel Thinning. J. Mach. Learn. Res. Raaz Dwivedi, Lester Mackey
2024	J	`jnl`	SureMap: Simultaneous Mean Estimation for Single-Task and Multi-Task Disaggregated Evaluation. CoRR Mikhail Khodak, Lester Mackey, Alexandra Chouldechova, Miroslav Dudík
2024	A*	`conf`	SureMap: Simultaneous mean estimation for single-task and multi-task disaggregated evaluation. NeurIPS Misha Khodak, Lester Mackey, Alexandra Chouldechova, Miro Dudík
2024	J	`jnl`	Targeted Separation and Convergence with Kernel Discrepancies. J. Mach. Learn. Res. Alessandro Barp, Carl-Johann Simon-Gabriel, Mark Girolami, Lester Mackey
2023	A*	`conf`	A Finite-Particle Convergence Rate for Stein Variational Gradient Descent. NeurIPS Jiaxin Shi, Lester Mackey
2023	A	`conf`	Compress Then Test: Powerful Kernel Testing in Near-linear Time. AISTATS Carles Domingo-Enrich, Raaz Dwivedi, Lester Mackey
2023	J	`jnl`	Compress Then Test: Powerful Kernel Testing in Near-linear Time. CoRR Carles Domingo-Enrich, Raaz Dwivedi, Lester Mackey
2023	J	`jnl`	Do Language Models Know When They're Hallucinating References? CoRR Ayush Agrawal, Lester Mackey, Adam Tauman Kalai
2023	J	`jnl`	Evaluation of Dependency Structure for Multivariate Weather Predictors Using Copulas. ACM J. Comput. Sustain. Soc. Samuel C. Maina, Dorcas Gicuku Mwigereri, Jonathan A. Weyn, Lester Mackey, Millicent Ochieng
2023	A*	`conf`	Learning Rate Free Bayesian Inference in Constrained Domains. NeurIPS Louis Sharrock, Lester Mackey, Christopher Nemeth
2023	J	`jnl`	Learning Rate Free Bayesian Inference in Constrained Domains. CoRR Louis Sharrock, Lester Mackey, Christopher Nemeth
2023	J	`jnl`	Metrizing Weak Convergence with Maximum Mean Discrepancies. J. Mach. Learn. Res. Carl-Johann Simon-Gabriel, Alessandro Barp, Bernhard Schölkopf, Lester Mackey
2023	J	`jnl`	Reflections from the Workshop on AI-Assisted Decision Making for Conservation. CoRR 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
2023	J	`jnl`	SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery. CoRR Konstantin Klemmer, Esther Rolf, Caleb Robinson, Lester Mackey, Marc Rußwurm
2023	J	`jnl`	Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation. CoRR Eric Zelikman, Eliana Lorch, Lester Mackey, Adam Tauman Kalai
2023	A*	`conf`	Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations. NeurIPS Hammaad Adam, Fan Yin, Huibin Hu, Neil A. Tenenholtz, Lorin Crawford, Lester Mackey, Allison Koenecke
2023	J	`jnl`	Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations. CoRR Hammaad Adam, Fan Yin, Mary Hu, Neil A. Tenenholtz, Lorin Crawford, Lester Mackey, Allison Koenecke
2023	J	`jnl`	Social norm bias: residual harms of fairness-aware algorithms. Data Min. Knowl. Discov. Myra Cheng, Maria De-Arteaga, Lester Mackey, Adam Tauman Kalai
2023	A*	`conf`	SubseasonalClimateUSA: A Dataset for Subseasonal Forecasting and Benchmarking. NeurIPS Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Miruna Oprescu, Judah Cohen, Franklyn Wang, Sean Knight, Maria Geogdzhayeva, Sam Levang, Ernest Fraenkel, Lester Mackey
2022	J	`jnl`	A Finite-Particle Convergence Rate for Stein Variational Gradient Descent. CoRR Jiaxin Shi, Lester Mackey
2022	J	`jnl`	Adaptive Bias Correction for Improved Subseasonal Forecasting. CoRR Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Judah Cohen, Miruna Oprescu, Ernest Fraenkel, Lester Mackey
2022	J	`jnl`	Budget-Constrained Bounds for Mini-Batch Estimation of Optimal Transport. CoRR David Alvarez-Melis, Nicolò Fusi, Lester Mackey, Tal Wagner
2022	J	`jnl`	Controlling Moments with Kernel Stein Discrepancies. CoRR Heishiro Kanagawa, Arthur Gretton, Lester Mackey
2022	A*	`conf`	Distribution Compression in Near-Linear Time. ICLR Abhishek Shetty, Raaz Dwivedi, Lester Mackey
2022	A*	`conf`	Generalized Kernel Thinning. ICLR Raaz Dwivedi, Lester Mackey
2022	A*	`conf`	Gradient Estimation with Discrete Stein Operators. NeurIPS Jiaxin Shi, Yuhao Zhou, Jessica Hwang, Michalis K. Titsias, Lester Mackey
2022	J	`jnl`	Gradient Estimation with Discrete Stein Operators. CoRR Jiaxin Shi, Yuhao Zhou, Jessica Hwang, Michalis K. Titsias, Lester Mackey
2022	A*	`conf`	Sampling with Mirrored Stein Operators. ICLR Jiaxin Shi, Chang Liu, Lester Mackey
2022	A*	`conf`	Scalable Spike-and-Slab. ICML Niloy Biswas, Lester Mackey, Xiao-Li Meng
2022	J	`jnl`	Scalable Spike-and-Slab. CoRR Niloy Biswas, Lester Mackey, Xiao-Li Meng
2022	J	`jnl`	Targeted Separation and Convergence with Kernel Discrepancies. CoRR Alessandro Barp, Carl-Johann Simon-Gabriel, Mark Girolami, Lester Mackey
2021	J	`jnl`	Bounding Wasserstein distance with couplings. CoRR Niloy Biswas, Lester Mackey
2021	J	`jnl`	Distribution Compression in Near-linear Time. CoRR Abhishek Shetty, Raaz Dwivedi, Lester Mackey
2021	J	`jnl`	Generalized Kernel Thinning. CoRR Raaz Dwivedi, Lester Mackey
2021	A*	`conf`	Initialization and Regularization of Factorized Neural Layers. ICLR Mikhail Khodak, Neil A. Tenenholtz, Lester Mackey, Nicolò Fusi
2021	J	`jnl`	Initialization and Regularization of Factorized Neural Layers. CoRR Mikhail Khodak, Neil A. Tenenholtz, Lester Mackey, Nicolò Fusi
2021	A*	`conf`	Kernel Thinning. COLT Raaz Dwivedi, Lester Mackey
2021	J	`jnl`	Kernel Thinning. CoRR Raaz Dwivedi, Lester Mackey
2021	A*	`conf`	Knowledge Distillation as Semiparametric Inference. ICLR Tri Dao, Govinda M. Kamath, Vasilis Syrgkanis, Lester Mackey
2021	J	`jnl`	Knowledge Distillation as Semiparametric Inference. CoRR Tri Dao, Govinda M. Kamath, Vasilis Syrgkanis, Lester Mackey
2021	J	`jnl`	Learned Benchmarks for Subseasonal Forecasting. CoRR Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Miruna Oprescu, Judah Cohen, Franklyn Wang, Sean Knight, Maria Geogdzhayeva, Sam Levang, Ernest Fraenkel, Lester Mackey
2021	J	`jnl`	Near-optimal inference in adaptive linear regression. CoRR Koulik Khamaru, Yash Deshpande, Lester Mackey, Martin J. Wainwright
2021	A*	`conf`	Online Learning with Optimism and Delay. ICML Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey
2021	J	`jnl`	Online Learning with Optimism and Delay. CoRR Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey
2021	J	`jnl`	Sampling with Mirrored Stein Operators. CoRR Jiaxin Shi, Chang Liu, Lester Mackey
2021	J	`jnl`	Social Norm Bias: Residual Harms of Fairness-Aware Algorithms. CoRR Myra Cheng, Maria De-Arteaga, Lester Mackey, Adam Tauman Kalai
2020	A	`conf`	Approximate Cross-validation: Guarantees for Model Assessment and Selection. AISTATS Ashia C. Wilson, Maximilian Kasy, Lester Mackey
2020	J	`jnl`	Approximate Cross-validation: Guarantees for Model Assessment and Selection. CoRR Ashia C. Wilson, Maximilian Kasy, Lester Mackey
2020	A*	`conf`	Cross-validation Confidence Intervals for Test Error. NeurIPS Pierre Bayle, Alexandre Bayle, Lucas Janson, Lester Mackey
2020	J	`jnl`	Cross-validation Confidence Intervals for Test Error. CoRR Pierre Bayle, Alexandre Bayle, Lucas Janson, Lester Mackey
2020	A	`conf`	Importance Sampling via Local Sensitivity. AISTATS Anant Raj, Cameron Musco, Lester Mackey
2020	J	`jnl`	Metrizing Weak Convergence with Maximum Mean Discrepancies. CoRR Carl-Johann Simon-Gabriel, Alessandro Barp, Lester Mackey
2020	A*	`conf`	Minimax Estimation of Conditional Moment Models. NeurIPS Nishanth Dikkala, Greg Lewis, Lester Mackey, Vasilis Syrgkanis
2020	J	`jnl`	Minimax Estimation of Conditional Moment Models. CoRR Nishanth Dikkala, Greg Lewis, Lester Mackey, Vasilis Syrgkanis
2020	J	`jnl`	Model-specific Data Subsampling with Influence Functions. CoRR Anant Raj, Cameron Musco, Lester Mackey, Nicoló Fusi
2020	A*	`conf`	Single Point Transductive Prediction. ICML Nilesh Tripuraneni, Lester Mackey
2020	A*	`conf`	Stochastic Stein Discrepancies. NeurIPS Jackson Gorham, Anant Raj, Lester Mackey
2020	J	`jnl`	Stochastic Stein Discrepancies. CoRR Jackson Gorham, Anant Raj, Lester Mackey
2020	J	`jnl`	Weighted Meta-Learning. CoRR Diana Cai, Rishit Sheth, Lester Mackey, Nicoló Fusi
2019	J	`jnl`	A Kernel Stein Test for Comparing Latent Variable Models. CoRR Heishiro Kanagawa, Wittawat Jitkrittum, Lester Mackey, Kenji Fukumizu, Arthur Gretton
2019	A*	`conf`	Accelerating Rescaled Gradient Descent: Fast Optimization of Smooth Functions. NeurIPS Ashia C. Wilson, Lester Mackey, Andre Wibisono
2019	J	`jnl`	Debiasing Linear Prediction. CoRR Nilesh Tripuraneni, Lester Mackey
2019	J	`jnl`	Importance Sampling via Local Sensitivity. CoRR Anant Raj, Cameron Musco, Lester Mackey
2019	A*	`conf`	Improving Subseasonal Forecasting in the Western U.S. with Machine Learning. KDD Jessica Hwang, Paulo Orenstein, Judah Cohen, Karl Pfeiffer, Lester Mackey
2019	A*	`conf`	Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond. NeurIPS Xuechen Li, Yi Wu, Lester Mackey
2019	J	`jnl`	Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond. CoRR Xuechen Li, Denny Wu, Lester Mackey, Murat A. Erdogdu
2018	A*	`conf`	Global Non-convex Optimization with Discretized Diffusions. NeurIPS Murat A. Erdogdu, Lester Mackey, Ohad Shamir
2018	J	`jnl`	Global Non-convex Optimization with Discretized Diffusions. CoRR Murat A. Erdogdu, Lester Mackey, Ohad Shamir
2018	J	`jnl`	Improving Subseasonal Forecasting in the Western U.S. with Machine Learning. CoRR Jessica Hwang, Paulo Orenstein, Karl Pfeiffer, Judah Cohen, Lester Mackey
2018	J	`jnl`	Model Compression with Generative Adversarial Networks. CoRR Ruishan Liu, Nicoló Fusi, Lester Mackey
2018	A*	`conf`	Random Feature Stein Discrepancies. NeurIPS Jonathan H. Huggins, Lester Mackey
2018	J	`jnl`	Random Feature Stein Discrepancies. CoRR Jonathan H. Huggins, Lester Mackey
2012	—	`—`	Matrix Factorization and Matrix Concentration. Lester Mackey