A Refutation of the Clique-Based P=NP Proofs of LaPlante and Tamta-Pande-Dhami. - Hector A. Cardenas; Chester Holtz; Maria Janczak; Philip Meyers; Nathaniel S. Potrepka (CoRR, 2015)

Comparative Analysis of Classic Garbage-Collection Algorithms for a Lisp-like Language. - Tyler Hannan; Chester Holtz; Jonathan Liao (CoRR, 2015)

University of Rochester WMT 2017 NMT System Submission. - Chester Holtz; Chuyang Ke; Daniel Gildea (WMT, 2017)

Autism spectrum disorder detection from semi-structured and unstructured medical data. - Jianbo Yuan; Chester Holtz; Tristram H. Smith; Jiebo Luo 001 (EURASIP J. Bioinform. Syst. Biol., 2017)

A Comparison of Machine Learning Tools for Early Prediction of Sepsis from ICU Data. - Po-Ya Hsu; Chester Holtz (CinC, 2019)

Tslearn, A Machine Learning Toolkit for Time Series Data. - Romain Tavenard; Johann Faouzi; Gilles Vandewiele; Felix Divo; Guillaume Androz; Chester Holtz; Marie Payne; Roman Yurchak; Marc Rußwurm; Kushal Kolar; Eli Woods (J. Mach. Learn. Res., 2020)

Grid-Based Framework for Routability Analysis and Diagnosis With Conditional Design Rules. - Dongwon Park; Daeyeal Lee; Ilgweon Kang; Chester Holtz; Sicun Gao; Bill Lin 001; Chung-Kuan Cheng (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2020)

A Unified Printed Circuit Board Routing Algorithm With Complicated Constraints and Differential Pairs. - Ting-Chou Lin; Devon J. Merrill; Yen-Yi Wu; Chester Holtz; Chung-Kuan Cheng (ASP-DAC, 2021)

Online Adversarial Purification based on Self-supervised Learning. - Changhao Shi; Chester Holtz; Gal Mishne (ICLR, 2021)

Design and System Technology Co-Optimization Sensitivity Prediction for VLSI Technology Development using Machine Learning. - Chung-Kuan Cheng; Chia-Tung Ho; Chester Holtz; Bill Lin 001 (SLIP, 2021)

Online Adversarial Purification based on Self-Supervision. - Changhao Shi; Chester Holtz; Gal Mishne (CoRR, 2021)

Net Separation-Oriented Printed Circuit Board Placement via Margin Maximization. - Chung-Kuan Cheng; Chia-Tung Ho; Chester Holtz (ASP-DAC, 2022)

Placement initialization via a projected eigenvector algorithm: late breaking results. - Pengwen Chen; Chung-Kuan Cheng; Albert Chern; Chester Holtz; Aoxi Li; Yucheng Wang (DAC, 2022)

Evaluating Disentanglement in Generative Models Without Knowledge of Latent Factors. - Chester Holtz; Gal Mishne; Alexander Cloninger (TAG-ML, 2022)

Learning Sample Reweighting for Accuracy and Adversarial Robustness. - Chester Holtz; Tsui-Wei Weng; Gal Mishne (CoRR, 2022)

Machine Learning Prediction for Design and System Technology Co-Optimization Sensitivity Analysis. - Chung-Kuan Cheng; Chia-Tung Ho; Chester Holtz; Daeyeal Lee; Bill Lin 001 (IEEE Trans. Very Large Scale Integr. Syst., 2022)

Placement Initialization via Sequential Subspace Optimization with Sphere Constraints. - Pengwen Chen; Chung-Kuan Cheng; Albert Chern; Chester Holtz; Aoxi Li; Yucheng Wang (ISPD, 2023)

Semi-Supervised Laplacian Learning on Stiefel Manifolds. - Chester Holtz; Pengwen Chen; Alexander Cloninger; Chung-Kuan Cheng; Gal Mishne (CoRR, 2023)

Graph Embedding via Subspace Minimization with Applications to Chip Placement and Semi-Supervised Learning - Chester Holtz (2023)

DAGSizer: A Directed Graph Convolutional Network Approach to Discrete Gate Sizing of VLSI Graphs. - Chung-Kuan Cheng; Chester Holtz; Andrew B. Kahng; Bill Lin 001; Uday Mallappa (ACM Trans. Design Autom. Electr. Syst., 2023)

Continuous Partitioning for Graph-Based Semi-Supervised Learning. - Chester Holtz; Pengwen Chen; Zhengchao Wan; Chung-Kuan Cheng; Gal Mishne (NeurIPS, 2024)

On Robustness and Generalization of ML-Based Congestion Predictors to Valid and Imperceptible Perturbations. - Chester Holtz; Yucheng Wang; Chung-Kuan Cheng; Bill Lin 001 (CoRR, 2024)

Robust Graph-Based Semi-Supervised Learning via p-Conductances. - Sawyer Jack Robertson; Chester Holtz; Zhengchao Wan; Gal Mishne; Alexander Cloninger (CoRR, 2025)