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This is the first part of an oral history interview on the lifelong involvement of Joel Lebowitz in the development of statistical mechanics. Here the covered topics include the formative years, which overlapped the tragic period of Nazi…

History and Philosophy of Physics · Physics 2017-04-26 Joel Lebowitz , Luisa Bonolis

These are lecture notes that are based on the lectures from a class I taught on the topic of Spectral Graph Methods at UC Berkeley during the Spring 2015 semester.

Data Structures and Algorithms · Computer Science 2016-08-18 Michael W. Mahoney

I developed the lecture notes based on my ``Linear Model'' course at the University of California, Berkeley over the past ten years. This book provides an intermediate-level introduction to the linear model. It balances rigorous proofs and…

Methodology · Statistics 2025-06-23 Peng Ding

I published an interview of Leo Breiman in Statistical Science [Olshen (2001)], and also the solution to a problem concerning almost sure convergence of binary tree-structured estimators in regression [Olshen (2007)]. The former summarized…

Applications · Statistics 2011-01-06 Richard A. Olshen

This article focuses on training work carried out in artificial intelligence (AI) at the National Center for Supercomputing Applications (NCSA) at the University of Illinois Urbana-Champaign via a research experience for undergraduates…

Artificial Intelligence · Computer Science 2024-06-24 Daniel S. Katz , Volodymyr Kindratenko , Olena Kindratenko , Priyam Mazumdar

This special issue is a product of the First Interdisciplinary Symposium on Statistical Challenges and Opportunities in Electronic Commerce Research, which took place on May 22--23, 2005, at the Robert H. Smith School of Business,…

Statistics Theory · Mathematics 2007-06-13 Wolfgang Jank , Galit Shmueli

Breiman challenged statisticians to think more broadly, to step into the unknown, model-free learning world, with him paving the way forward. Statistics community responded with slight optimism, some skepticism, and plenty of disbelief.…

Machine Learning · Statistics 2021-03-23 Jelena Bradic , Yinchu Zhu

Random forests are a learning algorithm proposed by Breiman [Mach. Learn. 45 (2001) 5--32] that combines several randomized decision trees and aggregates their predictions by averaging. Despite its wide usage and outstanding practical…

Statistics Theory · Mathematics 2015-08-11 Erwan Scornet , Gérard Biau , Jean-Philippe Vert

The undergraduate data science curriculum at the University of California, Berkeley is anchored in five new courses that emphasize computational thinking, inferential thinking, and working on real-world problems. We believe that…

Computers and Society · Computer Science 2021-03-18 Ani Adhikari , John DeNero , Michael I. Jordan

Beginning in the 1970s, Alexander Philip Dawid has been a leading contributor to the foundations of statistics and especially to the development and application of Bayesian statistics. He is also known for his work on causality, especially…

Other Statistics · Statistics 2025-11-26 Vladimir Vovk , Glenn Shafer

Eugenio Regazzini was born on August 12, 1946 in Cremona (Italy), and took his degree in 1969 at the University "L. Bocconi" of Milano. He has held positions at the universities of Torino, Bologna and Milano, and at the University "L.…

Other Statistics · Statistics 2012-05-23 Antonio Lijoi , Igor Prünster

These notes were originally prepared as additional material for the lessons I have given at the summer school Gamma-ray Astrophysics and Multifrequency: Data analysis and astroparticle problems, organized by the Department of Physics of the…

Instrumentation and Methods for Astrophysics · Physics 2009-10-13 Luigi Foschini

This material complements David Chandler's Introduction to Modern Statistical Mechanics (Oxford University Press, 1987) in a graduate-level, one-semester course I teach in the Department of Chemistry at Duke University. Students enter this…

Statistical Mechanics · Physics 2017-05-22 Patrick Charbonneau

These notes were originally written for the Stochastic Analysis Seminar in the Department of Operations Research and Financial Engineering at Princeton University, in February of 2011. The seminar was attended and supported by members of…

Mathematical Finance · Quantitative Finance 2016-10-04 Andrew Papanicolaou

We discuss important aspects of HCI research regarding Research Data Management (RDM) to achieve better publication processes and higher reuse of HCI research results. Various context elements of RDM for HCI are discussed, including…

Human-Computer Interaction · Computer Science 2025-02-03 David Goedicke , Mark Colley , Sebastian S. Feger , Michael Goedicke , Bastian Pfleging , Wendy Ju

This manuscript is based on the Summary and Overview talk given at the "The International Conference of Strongly Correlated Electronic Systems" (SCES '04), July 26-30, at Karlsruhe, Germany. After highlighting some of the principal new…

Strongly Correlated Electrons · Physics 2009-11-10 C. M. Varma

These notes were compiled as lecture notes for a course developed and taught at the University of the Southern California. They should be accessible to a typical engineering graduate student with a strong background in Applied Mathematics.…

Machine Learning · Computer Science 2023-01-04 Deep Ray , Orazio Pinti , Assad A. Oberai

Large particle physics projects funded by the U.S. Government require an evaluation and mitigation of each project's potential impacts on the local communities. However, beyond meeting governmental requirements, particle physics projects…

High Energy Physics - Experiment · Physics 2022-03-16 R. Zens , M. Headley , D. Wolf , A. Markovitz , F. Dukes , J. Tang , K. Bloom , V. Boisvert

The dynamics of simple two-alternative forced-choice (2AFC) decisions are well-modeled by a class of random walk models (e.g. Laming, 1968; Ratcliff, 1978; Usher & McClelland, 2001; Bogacz et al., 2006). However, in real-life, even simple…

Neurons and Cognition · Quantitative Biology 2026-03-31 Michael Shvartsman , Vaibhav Srivastava , Narayanan Sundaram , Jonathan D. Cohen

Despite the success of large-scale empirical risk minimization (ERM) at achieving high accuracy across a variety of machine learning tasks, fair ERM is hindered by the incompatibility of fairness constraints with stochastic optimization. We…

Machine Learning · Computer Science 2023-01-13 Andrew Lowy , Sina Baharlouei , Rakesh Pavan , Meisam Razaviyayn , Ahmad Beirami