6 citations · 7 across the 6 of their papers we have counts for
Showing 2025Show all
3 papers · 1 filter
cs.LG2025
Accelerating scientific discovery with the common task framework
J. Nathan Kutz, Peter Battaglia, Michael Brenner +12
Machine learning (ML) and artificial intelligence (AI) algorithms are transforming and empowering the characterization and control of dynamic systems in the engineering, physical,…
stat.ML2025
Random Matrix Theory for Deep Learning: Beyond Eigenvalues of Linear Models
Zhenyu Liao, Michael W. Mahoney
Modern Machine Learning (ML) and Deep Neural Networks (DNNs) often operate on high-dimensional data and rely on overparameterized models, where classical low-dimensional intuitions…
math.NA2025
Fundamental Bias in Inverting Random Sampling Matrices with Application to Sub-sampled Newton
Chengmei Niu, Zhenyu Liao, Zenan Ling +1
A substantial body of work in machine learning (ML) and randomized numerical linear algebra (RandNLA) has exploited various sorts of random sketching methodologies, including rando…