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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd">
<html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en" lang="en">
<head>
<meta http-equiv="content-type" content="text/html; charset=iso-8859-1" />
<title>Lester Mackey: Talks</title>
<meta name="keywords" content="lester mackey, computer science, machine learning, statistical, research, stanford" />
<meta name="description" content="Lester Mackey's website" />
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<h1>Lester Mackey</h1>
<h2>lwmackey@gmail.com</h2>
<!--<h2>Personal homepage</h2>-->
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<ul>
<li><a href="index.html">Home</a></li>
<li><a href="research.html">Research</a></li>
<li><a href="talks.html" class="active">Talks</a></li>
<li><a href="teaching.html">Teaching</a></li>
<li><a href="dinosaurplanet.html">Netflix Prize</a></li>
<li><a href="alsprize4life.html">ALS Prize4Life</a></li>
<li><a href="forecastrodeo.html">Forecast Rodeo</a></li>
<li><a href="aiweatherquest.html">AI Weather Quest</a></li>
<li><a href="contact.html">Contact</a></li>
<li><a href="bio.html">Bio</a></li>
<li><a href="papers/Lester_Mackey-CV.pdf">CV</a></li>
</ul>
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<div id="content">
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<!--
<h4>Research Interests</h4>
<div class="contentarea">
<ul class="normal">
<li><b>Statistical machine learning</b></li>
<li><b>Scalable algorithms</b></li>
<li><b>High-dimensional statistics</b></li>
<li><b>Approximate inference</b></li>
<li><b>Probability</b></li>
</ul>
</div>
<div class="divider1"></div>
-->
<h4>Invited Talks</h4>
<div class="contentarea">
<ul class="normal">
<li><b>Compressed Attention. (<a href="papers/attention-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'attention-slides.pdf']);">slides</a>)</b>
<ul class="normal">
<li>Aspen Meeting on Foundation Models, Aspen, Oct. 2026.</li>
</ul>
</li>
<br />
<li><b>Compressing Uncertainty in Artificial Intelligence. (<a href="papers/compress-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'compress-slides.pdf']);">slides</a>)</b>
<ul class="normal">
<li>Keynote - Conference on Uncertainty in Artificial Intelligence (UAI), Amsterdam, Aug. 2026.</li>
</ul>
</li>
<br />
<li><b>Better-than-i.i.d. Sampling. (<a href="papers/better-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'better-slides.pdf']);">slides</a>)</b>
<ul class="normal">
<li>MSR Workshop on Generative Modeling and Sampling, Microsoft Research New England, Aug. 2026.</li>
<li>IMS Medallion Lecture, Joint Statistical Meetings, Boston, Aug. 2026.</li>
</ul>
</li>
<br />
<li><b>Stein's Method, Learning, and Inference. (<a href="papers/gsd_ksd-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'gsd_ksd-slides.pdf']);">slides</a>, <a href="https://www.youtube.com/watch?v=XnaHuB9SGms">video</a>)</b>
<ul class="normal">
<li>Keynote - IMSS Annual Lecture, University College London, Apr. 2026.</li>
<li>American Mathematical Society von Neumann Lecture, Joint Mathematics Meetings, Jan. 2025.</li>
<li>Plenary - SIAM Conference on Mathematics of Data Science (MDS), Sep. 2022.</li>
<li>Tutorial - Stein's Method: The Golden Anniversary, IMS, Jun. 2022.</li>
<li>Beyond iid Learning Seminar, ETH Zurich, Dec. 2021.</li>
<li>Your Model Is Wrong Workshop, NeurIPS, Dec. 2021.</li>
<li>Plenary - International Conference on Monte Carlo Methods and Applications (MCM), Aug. 2021.</li>
<li>ISI World Statistics Conference, Jul. 2021.</li>
<li>Probability for Machine Learning Seminar, University of Oxford, Dec. 2020.</li>
<li>Econometrics and Statistics Colloquium Workshop, U. Chicago, Nov. 2020.</li>
<li>Joint Statistics and Machine Learning Seminar, Carnegie Mellon University, Nov. 2020.</li>
<li>Statistics Colloquium, Penn State, Sep. 2020.</li>
<li>Oberwolfach Uncertainty Quantification Workshop, Oberwolfach, Germany, Mar. 2019.</li>
<li>Keynote - Data, Learning, and Inference Workshop (DALI), George, South Africa, Jan. 2019.</li>
<li>Charles Stein Memorial Session, Joint Statistical Meetings, Vancouver, Canada, Jul. 2018.</li>
</ul>
</li>
<br />
<li><b>Advances in Distribution Compression / Kernel Thinning and Stein Thinning. (<a href="papers/thinning-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'thinning-slides.pdf']);">slides</a>)</b>
<ul class="normal">
<li>CAARMS: Conference for African American Researchers in the Mathematical Sciences, Cornell University, June 2025.</li>
<li>Statistics Seminar, Harvard University, October 2024.</li>
<li>Stochastics and Statistics Seminar, MIT, December 2023.</li>
<li>IMSI Workshop on Permutations and Causal Inference, Chicago, August 2023.</li>
<li>COPSS Leadership Academy Seminar, Joint Statistical Meetings, Toronto, August 2023.</li>
<li>Ethel Newbold Prize Seminar, World Statistics Congress, Ottawa, July 2023.</li>
<li>Semi-plenary - Journees de Statistique, French Statistical Society, Brussels, July 2023.</li>
<li>GRAMSIA: Graphical Models, Statistical Inference, and Algorithms Workshop, Harvard University, May 2023.</li>
<li>Probability and Statistics Seminar, Boston University, Mar. 2023.</li>
<li>Information Systems Laboratory Colloquium, Stanford University, Mar. 2023.</li>
<li>Statistics Seminar, UW Madison, Dec. 2022.</li>
<li>Data Science Seminar, London School of Economics, May 2022.</li>
<li>StatML CDT, Imperial College London and University of Oxford, March 2022.</li>
<li>Symposium on Advances in Approximate Bayesian Inference, February 2022.</li>
<li>Statistics Seminar, University of Michigan, December 2021.</li>
<li>Statistics and Data Science Seminar, Yale University, November 2021.</li>
<li>ML Advances and Applications Seminar, Vector Institute & Fields Institute, November 2021.</li>
<li>ML Theory Seminar, Harvard University, November 2021.</li>
<li>Computational Bayesian Statistics Journal Club, Flatiron Institute, November 2021.</li>
<li>Applied Math Colloquium, Cornell University, October 2021.</li>
<li>Bayesian Data Analysis Webinar, October 2021.</li>
<li>Statistics Seminar, Cambridge University, October 2021.</li>
<li>Statistics Colloquium, Columbia University, September 2021.</li>
</ul>
</li>
<br />
<li><b>Knowledge Distillation as Semiparametric Inference. (<a href="papers/enhanced_kd_gantsc-slides.pdf">slides</a>, <a href="https://www.youtube.com/watch?v=dEE3-g_8dWo">video</a>)</b>
<ul class="normal">
<li>Bridging the Gap Between Practice and Theory in Deep Learning Workshop, ICLR, May 2024.</li>
<li>Directions in ML Speaker Series, Microsoft Research, Apr. 2021.</li>
</ul>
</li>
<br />
<li><b>Doing Some Good with Machine Learning. (<a href="papers/doing_some_good-slides.pdf">slides</a>, <!--<a href="https://icml.cc/virtual/2020/invited%20talk/6855">video</a>)</b>--><a href="https://slideslive.com/38930520">video</a>)</b>
<ul class="normal">
<li>AI for Social Impact Seminar, Harvard University, Apr. 2024.</li>
<li>AI and ML Community Seminar, Microsoft, Feb. 2024.</li>
<li>Data Science for Social Change Seminar, Cornell University, Feb. 2023.</li>
<li>Computer Science Tea, Carleton College, Feb. 2023.</li>
<li>Keynote - Data Science Week, Purdue University Fort Wayne, Nov. 2022.</li>
<li>Mathematical Sciences Colloquium, Appalachian State University, Sep. 2022.</li>
<li>Research Science Institute, Distinguished Guest Lecture, July 2022.</li>
<li>CIFAR Deep Learning+Reinforcement Learning Summer School, July 2021.</li>
<li>Data Science for Social Good, Stanford University, July 2021.</li>
<li>Statistics Seminar, Luxembourg Statistical Society, June 2021.</li>
<li>AI Seminar, University of Alberta, May 2021.</li>
<li>Neyman Seminar, U.C. Berkeley, Dec. 2020.</li>
<li>Keynote - International Conference on Machine Learning (ICML), July 2020.</li>
</ul>
</li>
<br />
<li><b>Adaptive Bias Correction for Improved Subseasonal Forecasting. (<a href="papers/abc-slides.pdf">slides</a>)</b>
<ul class="normal">
<li>Workshop on AI-Assisted Decision-Making for Conservation, Harvard CRCS, Oct. 2022.</li>
</ul>
</li>
<br />
<li><b>Cross-validation Confidence Intervals for Test Error. (<a href="papers/cvci-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'cvci-slides.pdf']);">slides</a>)</b>
<ul class="normal">
<li>Inference and Interpretability in a Model-Free Setting, Joint Statistical Meetings, Aug. 2021.</li>
</ul>
</li>
<br />
<li><b>Online Learning with Optimism and Delay. (<a href="papers/poold-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'poold-slides.pdf']);">slides</a>, <a href="https://youtu.be/udfOa2ekTK4">video</a>)</b>
<ul class="normal">
<li>ICML Time Series Workshop, July 2021.</li>
</ul>
</li>
<br />
<li><b>Improving Subseasonal Forecasting in the Western U.S. with Machine Learning. (<a href="papers/rodeo-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'rodeo-slides.pdf']);">slides</a>, <a href="https://www.youtube.com/watch?v=DbTn9vUYR_c">video</a>)</b>
<ul class="normal">
<li>ICLR Climate Change AI Workshop, Apr. 2020.</li>
<li>Keynote - Open Data Science Conference, Apr. 2020.</li>
<li>NeurIPS Workshop on Tackling Climate Change with Machine Learning, Dec. 2019.</li>
<li>Statistics & Data Science Conference (SDSCon), MIT, Apr. 2019.</li>
<li>Computer Science Colloquium, Cornell University, Nov. 2018.</li>
</ul>
</li>
<br />
<li><b>Orthogonal Machine Learning: Power and Limitations. (<a href="papers/orthogonalml-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'orthogonalml-slides.pdf']);">slides</a>, <a href="https://simons.berkeley.edu/talks/orthogonal-machine-learning-power-limitations">video</a>)</b>
<ul class="normal">
<li>Robust and High-Dimensional Statistics Workshop, Simons Institute for the Theory of Computing, Oct. 2018.</li>
</ul>
</li>
<br />
<li><b>Measuring Sample Quality with Kernels. (<a href="papers/ksd-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'ksd-slides.pdf']);">slides</a>)</b>
<ul class="normal">
<li>Bayes, Machine Learning, and Deep Learning Invited Session, International Society for Bayesian Analysis (ISBA) World Meeting, June 2018.</li>
<li>Harvard / MIT Econometrics Workshop, MIT, Mar. 2018.</li>
<li>SAMSI Workshop on Trends and Advances in Monte Carlo Sampling Algorithms, Duke University, Dec. 2017.</li>
<li>SAMSI Workshop on Quasi-Monte Carlo and High-Dimensional Sampling Methods, Duke University, Aug. 2017.</li>
<li>Borchard Colloquium on Concentration Inequalities, High Dimensional Statistics, and Stein's Method, Missilac, France, July 2017.</li>
<li>New England Machine Learning Day, Cambridge, MA, May 2017.</li>
<li>Machine Learning Seminar, MIT, Mar. 2017.</li>
</ul>
</li>
<br />
<li><b>Measuring Sample Quality with Stein's Method. (<a href="papers/steindiscrepancy-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'steindiscrepancy-slides.pdf']);">slides</a>)</b>
<ul class="normal">
<li>Gatsby Unit Seminar, University College London, Oct. 2016.</li>
<li>Seminar, University of Liege, Sep. 2016.</li>
<li>Quetelet Seminar, Ghent University, Sep. 2016.</li>
<li>International Conference on Monte Carlo and Quasi-Monte Carlo Methods (MCQMC), Stanford, CA, Aug. 2016.</li>
<li>Statistics Seminar, Columbia University, Feb. 2016.</li>
<li>Quasi-Monte Carlo Invited Session, IMS-ISBA Joint Meeting (MCMSki V), Jan. 2016.</li>
<li>Wharton Statistics Seminar, University of Pennsylvania, Dec. 2015.</li>
<li>Neyman Seminar, UC Berkeley, Sep. 2015.</li>
<li>IMS-Microsoft Research Workshop: Foundations of Data Science, Cambridge, MA, June 2015.</li>
<li>Stochastics and Statistics Seminar, MIT, May 2015.</li>
<li>Statistics Seminar, Stanford University, May 2015.</li>
</ul>
</li>
<br />
<li><b>Statistics for Social Good</b>
<ul class="normal">
<li>AI Now Symposium on the Social and Economic Impact of Artificial Intelligence Technologies, MIT, July 2017.</li>
<li>Data Science @ Stanford Seminar, Stanford, June 2016.</li>
</ul>
</li>
<br />
<li><b>Matrix Completion and Matrix Concentration. (<a href="papers/mc2-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'mc2-slides.pdf']);">slides</a>)</b>
<ul class="normal">
<li>IDSS Special Seminar, MIT, Feb. 2016.</li>
<li>Statistics Seminar, Harvard University, Nov. 2014.</li>
<li>Blackwell-Tapia Conference, Los Angeles, CA, Nov. 2014.</li>
<li>Information Systems Laboratory Colloquium, Stanford University, April 2013.</li>
<li>Statistics Seminar, Yale University, April 2013.</li>
<li>Statistics Seminar, Columbia University, April 2013.</li>
<li>Computer Science Seminar, University of Southern California, May 2012.</li>
<li>Statistics Seminar, Stanford University, Jan. 2012.</li>
</ul>
</li>
<br />
<li><b>Divide-and-Conquer Matrix Factorization. (<a href="papers/dfc-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'dfc-slides.pdf']);">slides</a>)</b>
<ul class="normal">
<li>CS Department Colloquium, Princeton University, Dec. 2015.</li>
<li>Workshop on Big Data: Theoretical and Practical Challenges, Paris, France, May 2013.</li>
<li>Kaggle, San Francisco, CA, Feb. 2013.</li>
<li>Statistical Science Seminar Series, Duke University, Jan. 2012.</li>
<li>CMS Seminar, Caltech, Jan. 2012.</li>
<li>San Francisco Bay Area Machine Learning Meetup, San Francisco, CA, Nov. 2011.</li>
</ul>
</li>
<br />
<li><b>Predicting ALS Disease Progression with Bayesian Additive Regression Trees. (<a href="papers/alsprize4life-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'alsprize4life-slides.pdf']);">slides</a>)</b>
<ul class="normal">
<li>Big Data in Biomedicine Conference, Stanford University, May 2015.</li>
<li>Guest Lecture, Stats 202, Stanford University, Nov. 2013.</li>
<li>Statistics Seminar, Stanford University, April 2013.</li>
<li>RECOMB Conference on Regulatory and Systems Genomics, San Francisco, CA, Nov. 2012.</li>
</ul>
</li>
<br />
<li><b>Weighted Classification Cascades for Optimizing Discovery Significance. (<a href="papers/cascades-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'cascades-slides.pdf']);">slides</a>)</b>
<ul class="normal">
<li>NeurIPS Workshop on High-energy particle physics, machine learning, and the HiggsML data challenge (HEPML), December 2014.</li>
</ul>
</li>
<br />
<li><b>Ranking, Aggregation, and You. (<a href="papers/rankasymptotics-10_5_14-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'rankasymptotics-slides.pdf']);">slides</a>)</b>
<ul class="normal">
<li>Statistics Seminar, University of Chicago, Oct. 2014</li>
<li>Yale MacMillan-CSAP Workshop on Quantitative Research Methods, Yale University, Sep. 2014.</li>
<li>Wharton Statistics Seminar, University of Pennsylvania, Sep. 2014.</li>
<li>Statistics Seminar, Carnegie Mellon University, Sep. 2014.</li>
<li>Western Section Meeting, American Mathematical Society, Nov. 2013.</li>
<li>Statistics Seminar, Stanford University, Sep. 2013.</li>
<li>Stanford Statistics/Machine Learning Reading Group, Stanford University, Nov. 2012.</li>
</ul>
</li>
<br />
<li><b>Dividing, Conquering, and Mixing Matrix Factorizations. (<a href="papers/dfc_m3f-6_5_13-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'dfc_m3f-6_5_13-slides.pdf']);">slides</a>)</b>
<ul class="normal">
<li>Technicolor, Palo Alto, CA, June 2013.</li>
</ul>
</li>
<br />
<li><b>Stein's Method for Matrix Concentration. (<a href="papers/matstein-12_10_12-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'matstein-slides.pdf']);">slides</a>)</b>
<ul class="normal">
<li>Institut National de Recherche en Informatique et en Automatique (INRIA), Dec. 2012.</li>
<li>Berkeley Probability Seminar, University of California, Berkeley, May 2012.</li>
</ul>
</li>
<br />
<li><b>Build a Better Netflix, Win a Million Dollars? </b>
<ul class="normal">
<li>SPARC Camp, Aug. 2014. (<a href="papers/netflix-8_10_14-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'netflix-8_10_14-slides.pdf']);">slides</a>)</li>
<li>USA Science and Engineering Festival, Washington, DC, Apr. 2012. (<a href="papers/netflix-usa_sef12-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'netflix-usa_sef12-slides.pdf']);">slides</a>)</li>
</ul>
</li>
<br />
<li><b>The Story of the Netflix Prize: An Ensembler's Tale. (<a href="papers/netflix_story-nas11-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'netflix_story-nas11-slides.pdf']);">slides</a>, <a href="http://vimeo.com/62347587" onClick="_gaq.push(['_trackEvent', 'Talk', 'Link', 'http://vimeo.com/62347587']);">video</a>)</b>
<ul class="normal">
<li>National Academies' Seminar, Washington, DC, Nov. 2011.</li>
</ul>
</li>
<br />
<li><b>Mixed Membership Matrix Factorization. (<a href="papers/m3f-jsm11-slides.pdf" onClick="_gaq.push(['_trackEvent', 'Slides', 'Download', 'm3f-jsm11-slides.pdf']);">slides</a>)</b>
<ul class="normal">
<li>Joint Statistical Meetings, Miami Beach, FL, July 2011.</li>
</ul>
</li>
<br />
<li><b>False Event Identification and Beyond: A Machine Learning Approach.</b>
<ul class="normal">
<li>Comprehensive Test Ban Treaty Organization Technical Meeting on Data Mining, Vienna, Austria, Nov. 2009, presented with Ariel Kleiner.</li>
</ul>
</li>
<br />
<li><b>The Dinosaur Planet Approach to the Netflix Prize.</b>
<ul class="normal">
<li>LIDS Seminar Series, MIT, Nov. 2008, presented with David Weiss.</li>
<li>Guest Lecture, Stat 157, U.C. Berkeley, Sept. 2008.</li>
<li>Process Driven Trading Group, Morgan Stanley, April 2008, presented with David Lin and David Weiss.</li>
</ul>
</li>
</ul>
</div>
<div class="divider1"></div>
<h4>Panels and Presentations</h4>
<div class="contentarea">
<ul class="normal">
<li><b>The Future of Trustworthy AI.</b>
<ul class="normal">
<li>Computing Research Association Trustworthy AI Fellowship Field School, Aug. 2025.</li>
</ul>
</li><br />
<li><b>Frontiers of Statistics in Industry.</b>
<ul class="normal">
<li>National Academies of Sciences, Engineering, and Medicine, Apr. 2025.</li>
</ul>
</li><br />
<li><b>Ask Me Anything.</b>
<ul class="normal">
<li>Learning Theory Mentorship Workshop, Conference on Algorithmic Learning Theory (ALT), Mar. 2021.</li>
</ul>
</li><br />
<li><b>Climate Change: A Grand Challenge for Machine Learning.</b>
<ul class="normal">
<li>NeurIPS Workshop on Tackling Climate Change with Machine Learning, Dec. 2019.</li>
</ul>
</li><br />
<li><b>A Multifactorial Model of T Cell Expansion and Durable Clinical Benefit in Response to a PD-L1 Inhibitor.</b>
<ul class="normal">
<li>American Association for Cancer Research (AACR) Annual Meeting, Chicago, IL, Apr. 2018.</li>
</ul>
</li><br />
<li><b>Post hoc analysis using PRO-ACT database to evaluate Repository Corticotropin Injection (H.P. Acthar® Gel) as potential treatment for ALS.</b>
<ul class="normal">
<li>American Academy of Neurology 70th Annual Meeting, Los Angeles, CA, Apr. 2018.</li>
</ul>
</li><br />
<li><b>Divide and Conquer Subspace Segmentation.</b>
<ul class="normal">
<li>NeurIPS Workshop on Big Learning, Lake Tahoe, NV, Dec. 2012.</li>
</ul>
</li><br />
<li><b>Improved Automated Seismic Event Extraction Using Machine Learning.</b>
<ul class="normal">
<li>American Geophysical Union Fall Meeting, San Francisco, CA, Dec. 2009.</li>
</ul>
</li><br />
<li><b>Machine Learning for Improved Automated Seismic Event Extraction.</b>
<ul class="normal">
<li>International Scientific Studies Conference, Vienna, Austria, June 2009.</li>
</ul>
</li>
</ul>
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