10 papers
Cofilling Shattering: A Syndrome-Support Hierarchy for Check Erasures
Joshua Steier
Let be a binary linear map with fixed coordinate bases, let , and let be the minimum Hamming weight of a preimage of the sy…
Ergodic Deviation-Robust Equilibrium under Mirror Descent Learning in Finite Games
Joshua Steier
We introduce Ergodic Deviation-Robust Equilibrium (EDRE), a dynamics-relative equilibrium concept for repeated finite games in which agents learn via entropic mirror descent (EMD).…
Adjacency Spectral Radius Under Laplacian Sparsification: Deterministic and Probabilistic Bounds
Joshua Steier
Spielman-Srivastava spectral sparsification preserves Laplacian quadratic forms to within (1 +/- epsilon), but does not directly control the adjacency spectral radius lambda_1, whi…
Information Routing in Atomistic Foundation Models: How Task Alignment and Equivariance Shape Linear Disentanglement
Joshua Steier
What determines whether a molecular property prediction model organizes its representations so that geometric and compositional information can be cleanly separated? We introduce C…
PAC Guarantees for Reinforcement Learning: Sample Complexity, Coverage, and Structure
Joshua Steier
When data is scarce or mistakes are costly, average-case metrics fall short. What a practitioner needs is a guarantee: with probability at least , the learned policy is $\vare…
When Does Margin Clamping Affect Training Variance? Dataset-Dependent Effects in Contrastive Forward-Forward Learning
Joshua Steier
Contrastive Forward-Forward (CFF) learning trains Vision Transformers layer by layer against supervised contrastive objectives. CFF training can be sensitive to random seed, but th…
PyHealth 2.0: A Comprehensive Open-Source Toolkit for Accessible and Reproducible Clinical Deep Learning
John Wu, Yongda Fan, Zhenbang Wu +14
Difficulty replicating baselines, high computational costs, and required domain expertise create persistent barriers to clinical AI research. To address these challenges, we introd…
Spectral and Homological Bounds on k-Component Edge Connectivity
Joshua Steier
We present a novel theoretical framework connecting k-component edge connectivity with spectral graph theory and homology theory to pro vide new insights into the resilience of rea…
On the Degree Sequences of Multigraphs with Edge Additions and Deletions
Joshua Steier
The degree sequence of a graph is a numerical method to characterize the properties of graphs. Generalized forms of degree sequences exist for complete graphs and complete graphs.…
A Characterization of Distance Matrices of Positive Weighted Kneser Graphs and Generalized Petersen Graphs
Joshua Steier, Luis Monterroso
Rubei et. al., established results for the distance matrix of positive weighted Petersen graphs. Focusing on the properties of the distance matrix, we generalized positive weighted…