Michael Mahoney


Boundary thickness and robustness in learning models

ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning

PyHessian: Neural networks through the lens of the Hessian

Hessian-based Analysis of Large Batch Training and Robustness to Adversaries

Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging

A Berkeley View of Systems Challenges for AI

Blog Posts

RISELab and UC Berkeley’s new Foundations of Data Analysis (FODA) Institute

Michael Mahoney News

We are pleased to announce the involvement of RISELab faculty with the new Foundations of Data Analysis (FODA) Institute. The FODA Institute is funded as part of the NSF TRIPODS program, and it is designed to bring together core research communities in theoretical statistics, applied mathematics, and theoretical computer science to address foundational questions at the heart of data science. In addition to RISELab faculty Michael Mahoney and Mike Jordan, also involved with this FODA/TRIPODS effort are statistics faculty Bin Yu and Fernando Perez and EECS/Simons faculty Dick Karp. We look forward to the fruitful interactions between theory, implementations, and real-time applications.   For more details, here is the link to the press release: https://data.berkeley.edu/news/berkeley-defining-next-academic-frontier-two-nsf-awards-uc-berkeley-set-stage-new-era-data