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Workshop
High-energy particle physics, machine learning, and the HiggsML data challenge (HEPML)
Glen Cowan · Balázs Kégl · Kyle Cranmer · Gábor Melis · Tim Salimans · Vladimir Vava Gligorov · Daniel Whiteson · Lester Mackey · Wojciech Kotlowski · Roberto Díaz Morales · Pierre Baldi · Cecile Germain · David Rousseau · Isabelle Guyon · Tianqi Chen

Sat Dec 13 05:30 AM -- 03:30 PM (PST) @ Level 5, room 511 c

Author Information

Glen Cowan (Royal Holloway, University of London)
Balázs Kégl (Université Paris Saclay/CNRS)
Kyle Cranmer (New York University)
Gábor Melis (Google Deepmind)
Tim Salimans (Algoritmica)
Vladimir Vava Gligorov (CERN)
Daniel Whiteson (University of California Irvine)
Lester Mackey (Microsoft Research)
Wojciech Kotlowski (Poznan University of Technology, Poland)
Roberto Díaz Morales (University Carlos III de Madrid)
Pierre Baldi (UC Irvine)
Cecile Germain (Universite Paris Sud)
David Rousseau (LAL-Orsay)

Particle physicist, studying the Higgs Boson on the ATLAS experiment at the LHC at CERN, passionate about applying ML algorithms to fundamental research. Organized the HiggsML challenge in 2014 and now the [TrackML challenge] (https://sites.google.com/site/trackmlparticle/home)

Isabelle Guyon (U. Paris-Saclay & ChaLearn)

Isabelle Guyon recently joined Google Brain as a research scientist. She is also professor of artificial intelligence at Université Paris-Saclay (Orsay). Her areas of expertise include computer vision, bioinformatics, and power systems. She is best known for being a co-inventor of Support Vector Machines. Her recent interests are in automated machine learning, meta-learning, and data-centric AI. She has been a strong promoter of challenges and benchmarks, and is president of ChaLearn, a non-profit dedicated to organizing machine learning challenges. She is community lead of Codalab competitions, a challenge platform used both in academia and industry. She co-organized the “Challenges in Machine Learning Workshop” @ NeurIPS between 2014 and 2019, launched the "NeurIPS challenge track" in 2017 while she was general chair, and pushed the creation of the "NeurIPS datasets and benchmark track" in 2021, as a NeurIPS board member.

Tianqi Chen (OctoML)

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