Videos

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The Tree Evaluation Problem: Context and Recent Results Thumbnail

The Tree Evaluation Problem: Context and Recent Results

Presenter
  • Ian Mertz
January 29, 2024
IAS
Randomization, Neutrality, and Fairness: "Fairness in Algorithmic Decisions via Social Choice" Thumbnail

Randomization, Neutrality, and Fairness: "Fairness in Algorithmic Decisions via Social Choice"

Presenter
  • Nisarg Shah
October 24, 2023
SLMath
Randomization, Neutrality, and Fairness: Characterizing General Top Trading Cycles Mechanisms Thumbnail

Randomization, Neutrality, and Fairness: Characterizing General Top Trading Cycles Mechanisms

Presenter
  • Bettina Klaus
October 23, 2023
SLMath
Marika Maria Kieferova - Generating Approx. Ground State of Molecules Using Quantum Machine Learning Thumbnail

Marika Maria Kieferova - Generating Approx. Ground State of Molecules Using Quantum Machine Learning

Presenter
  • Marika Kieferova
October 18, 2023
IPAM
Yu Tong - Recent progress in Hamiltonian learning - IPAM at UCLA Thumbnail

Yu Tong - Recent progress in Hamiltonian learning - IPAM at UCLA

Presenter
  • Yu Tong
October 2, 2023
IPAM
Introductory Workshop: Algorithms, Fairness, and Equity: "Manipulation-Robust Citizens' Assembly Selection" Thumbnail

Introductory Workshop: Algorithms, Fairness, and Equity: "Manipulation-Robust Citizens' Assembly Selection"

Presenter
  • Bailey Flanigan
August 31, 2023
SLMath
Introductory Workshop: Algorithms, Fairness, and Equity: "Geometry of Deep Learning and Explainable ML" Thumbnail

Introductory Workshop: Algorithms, Fairness, and Equity: "Geometry of Deep Learning and Explainable ML"

Presenter
  • Anders Karlsson
August 30, 2023
SLMath
Introductory Workshop: Algorithms, Fairness, and Equity: "Thinking Critically About Fair Clustering: Past, Present, and Future" Thumbnail

Introductory Workshop: Algorithms, Fairness, and Equity: "Thinking Critically About Fair Clustering: Past, Present, and Future"

Presenter
  • Brian Brubach
August 29, 2023
SLMath
Introductory Workshop: Algorithms, Fairness, and Equity: "Pretrial Risk Assessment on the Ground- Lessons from New Mexico" Thumbnail

Introductory Workshop: Algorithms, Fairness, and Equity: "Pretrial Risk Assessment on the Ground- Lessons from New Mexico"

Presenters
  • Cristopher Moore
  • Cristopher Moore
August 28, 2023
SLMath

Reduced label complexity for tight linear regression

Presenter
  • Alex Gittens
June 29, 2023
ICERM

Signed Cumulative Distribution Transform for Machine Learning

Presenter
  • Sumati Thareja
May 8, 2023
ICERM
Michele Ceriotti - Machine learning for atomic-scale modeling - potentials and beyond - IPAM at UCLA Thumbnail

Michele Ceriotti - Machine learning for atomic-scale modeling - potentials and beyond - IPAM at UCLA

Presenter
  • Michele Ceriotti
May 3, 2023
IPAM