activity
20222026
most citedBeyond the broken tetrahedron

1 citations · 1 across the 7 of their papers we have counts for

collaborators

8 papers

math.PR2026

Free-Probabilistic State Evolution and Random Matrix Discrepancy

August Y. Chen, Ahmed El Alaoui

Let be independent real symmetric Gaussian random matrices, and consider the linear operator , $x\in \mathbb{R}^n…

math.ST2026

How abundant are good interpolators?

August Y. Chen, Ahmed El Alaoui

Let be the set of unit norm linear classifiers which correctly classify every point of a labeled dataset , , $y_i \…

cs.LG2026

On the Robustness of Langevin Dynamics to Score Function Error

Daniel Yiming Cao, August Y. Chen, Karthik Sridharan +1

We consider the robustness of score-based generative modeling to errors in the estimate of the score function. In particular, we show that Langevin dynamics is not robust to the $L…

cs.LG2026

Statistical Learning from Attribution Sets

Lorne Applebaum, Robert Busa-Fekete, August Y. Chen +3

We address the problem of training conversion prediction models in advertising domains under privacy constraints, where direct links between ad clicks and conversions are unavailab…

math.OC2025

Efficiently Escaping Saddle Points under Generalized Smoothness via Self-Bounding Regularity

Daniel Yiming Cao, August Y. Chen, Karthik Sridharan +1

We study the optimization of non-convex functions that are not necessarily smooth (gradient and/or Hessian are Lipschitz) using first order methods. Smoothness is a restrictive ass…

stat.ML2024

Optimization, Isoperimetric Inequalities, and Sampling via Lyapunov Potentials

August Y. Chen, Karthik Sridharan

In this paper, we prove that optimizability of any function F using Gradient Flow from all initializations implies a Poincaré Inequality for Gibbs measures mu_{beta} = e^{-beta F}/…

cs.LG2024

Langevin Dynamics: A Unified Perspective on Optimization via Lyapunov Potentials

August Y. Chen, Ayush Sekhari, Karthik Sridharan

We study the problem of non-convex optimization using Stochastic Gradient Langevin Dynamics (SGLD). SGLD is a natural and popular variation of stochastic gradient descent where at…

math.CO2022★ 1 cited

Beyond the broken tetrahedron

August Y. Chen, Bjarne Schülke

Here we consider the hypergraph Turán problem in uniformly dense hypergraphs as was suggested by Erdős and Sós. Given a -graph , the uniform Turán density of is…