Lester Mackey @LesterMackey
Machine learning researcher @MSFTResearch (@MSRNE); adjunct professor @Stanford web.stanford.edu/~lmackey/ Joined November 2010-
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Lester Mackey retweeted
Beyond humbled to be on this year's #TIME100AI AI can be an asset for climate & energy - but only if its development is guided by actual climate needs & planetary limits. Shoutout to those in the community working to shape a responsible, equitable, climate-aligned AI future 🌍💪
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Lester Mackey retweeted
Lester Mackey retweeted
In 1965, Margaret Dayhoff published the Atlas of Protein Sequence and Structure, which collated the 65 proteins whose amino acid sequences were then known. Inspired by that Atlas, today we are releasing the Dayhoff Atlas of protein sequence data and protein language models.
Lester Mackey retweeted
thrilled to share The Dayhoff Atlas of protein language data and models 🚀 protein biology in the age of AI! aka.ms/dayhoff/prepri… we built + open source the largest natural protein dataset, w/ 3.3 billion seqs & a first-in-class dataset of structure-based synthetic proteins
Lester Mackey retweeted
So you want to skip our thinning proofs—but you’d still like our out-of-the-box attention speedups? I’ll be presenting the Thinformer in two ICML workshop posters tomorrow! Catch me at Es-FoMo (1-2:30, East hall A) and at LCFM (10:45-11:30 & 3:30-4:30, West 202-204)
So you want to skip our thinning proofs—but you’d still like our out-of-the-box attention speedups? I’ll be presenting the Thinformer in two ICML workshop posters tomorrow! Catch me at Es-FoMo (1-2:30, East hall A) and at LCFM (10:45-11:30 & 3:30-4:30, West 202-204)
Lester Mackey retweeted
If you’re not at ICML, don’t worry! You can still read our work. Our new theoretically principled algorithms beat recent baselines across multiple tasks—including Transformer approximation! arxiv.org/abs/2502.12063
Lester Mackey retweeted
Your data is low-rank, so stop wasting compute! In our new paper on low-rank thinning, we share one weird trick to speed up Transformer inference, SGD training, and hypothesis testing at scale. Come by ICML poster W-1012 Tuesday at 4:30!
Your data is low-rank, so stop wasting compute! In our new paper on low-rank thinning, we share one weird trick to speed up Transformer inference, SGD training, and hypothesis testing at scale. Come by ICML poster W-1012 Tuesday at 4:30!
Lester Mackey retweeted
At ICML this week? Check out @annabelle_cs's paper in collaboration with @LesterMackey and colleagues on Low-Rank Thinning! ⏰ Tue 15 Jul 4:30 - 7 p.m. PDT New theory, dataset compression, efficient attention and more: icml.cc/virtual/2025/p…
Lester Mackey retweeted
It's Hard to Be Normal: The Impact of Noise on Structure-agnostic Estimation ift.tt/RcE5Hby
Lester Mackey retweeted
Low-Rank Thinning ift.tt/F3OINvD
Lester Mackey retweeted
Causal integration of chemical structures improves representations of microscopy images for morphological profiling. arxiv.org/abs/2504.09544
Lester Mackey retweeted
Exciting news in the global statistics community! Grace Wahba was awarded the prestigious 2025 International Prize in Statistics for her groundbreaking work on smoothing splines, which revolutionized data analysis and machine learning. https://www. statprize.org/index.cfm
Lester Mackey retweeted
We are pleased to announce that the Ethel Newbold Prize 2025 has been awarded to Po-Ling Loh from the Department of Pure Mathematics and Mathematical Statistics (DPMMS), University of Cambridge. CONGRATULATIONS!
Lester Mackey retweeted
CONGRATULATIONS!
Lester Mackey retweeted
Congratulations to the winners of the inaugural David Cox Medal for Statistics, Prof Eric Tchetgen Tchetgen (University of Pennsylvania), Prof Nancy Zhang (University of Pennsylvania) and Prof Richard Samworth (University of Cambridge)!
Lester Mackey retweeted
Low-Rank Thinning ift.tt/78hU9om
Lester Mackey retweeted
Interested in learning about Kernel Discrepancies❓ Maximum Mean Discrepancy Hilbert-Schmidt Independence Criterion Kernel Stein Discrepancy 🧐 Don't know where to begin? 👀 Check out my Practical Introduction to Kernel Discrepancies: MMD, HSIC & KSD! arxiv.org/abs/2503.04820
Lester Mackey retweeted
Great to see our paper presenting recall, a framework which calibrates clustering for the impact of data "double-dipping" in single-cell studies, out today in AJHG! Congratulations, @AlanDenadel and co-authors!
Great to see our paper presenting recall, a framework which calibrates clustering for the impact of data "double-dipping" in single-cell studies, out today in AJHG! Congratulations, @AlanDenadel and co-authors!
Lester Mackey retweeted
Please join us in congratulating this year's winners! You can read more about the winners and the awards on our website: community.amstat.org/copss/home
Lester Mackey retweeted
NeurIPS 2025 is soliciting self-nominations for reviewers and ACs. Please read our blog post for details on eligibility criteria, and process to self-nominate: blog.neurips.cc/2025/03/10/sel…
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