12 citations · 17 across the 8 of their papers we have counts for
9 papers
Neural Algorithmic Reasoning for Graph Saddle Point Problems
Samantha Chen, Jesse He, Coleman Clougherty +2
Neural algorithmic reasoning, or aligning a neural network with an algorithmic paradigm, has emerged as an approach to solving polynomial-time-solvable and computationally harder c…
Revisiting Meta-Learning with Noisy Labels: Reweighting Dynamics and Theoretical Guarantees
Yiming Zhang, Chester Holtz, Gal Mishne +1
Learning with noisy labels remains challenging because over-parameterized networks memorize corrupted supervision. Meta-learning-based sample reweighting mitigates this by using a…
Robust Graph-Based Semi-Supervised Learning via -Conductances
Sawyer Jack Robertson, Chester Holtz, Zhengchao Wan +2
We study the problem of semi-supervised learning on graphs in the regime where data labels are scarce or possibly corrupted. We propose an approach called -conductance learning…
Robust boundary detection and density estimation using doubly stochastic scaling of the Gaussian kernel
Dhruv Kohli, Jesse He, Chester Holtz +2
This paper addresses the problem of detecting boundary points and estimating the sampling density of a dataset derived from a compact manifold with boundary, potentially in the pre…
Learning Sample Reweighting for Accuracy and Adversarial Robustness
Chester Holtz, Tsui-Wei Weng, Gal Mishne
There has been great interest in enhancing the robustness of neural network classifiers to defend against adversarial perturbations through adversarial training, while balancing th…
Evaluating Disentanglement in Generative Models Without Knowledge of Latent Factors
Chester Holtz, Gal Mishne, Alexander Cloninger
Probabilistic generative models provide a flexible and systematic framework for learning the underlying geometry of data. However, model selection in this setting is challenging, p…
Online Adversarial Purification based on Self-Supervision
Changhao Shi, Chester Holtz, Gal Mishne
Deep neural networks are known to be vulnerable to adversarial examples, where a perturbation in the input space leads to an amplified shift in the latent network representation. I…
Comparative Analysis of Classic Garbage-Collection Algorithms for a Lisp-like Language
Tyler Hannan, Chester Holtz, Jonathan Liao
In this paper, we demonstrate the effectiveness of Cheney's Copy Algorithm for a Lisp-like system and experimentally show the infeasability of developing an optimal garbage collect…
A Refutation of the Clique-Based P=NP Proofs of LaPlante and Tamta-Pande-Dhami
Hector A. Cardenas, Chester Holtz, Maria Janczak +2
In this work, we critique two papers, "A Polynomial-Time Solution to the Clique Problem" by Tamta, Pande, and Dhami, and "A Polynomial-Time Algorithm For Solving Clique Problems" b…