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Learning Goal-Reaching Quasimetric Geometry From Finite-Time Reachability
Daisuke Yamada, Travis Pence, Vikas Singh
In goal-conditioned reinforcement learning (GCRL), quasimetric learning models goal-reaching costs as quasimetric distances, connecting local constraints to global value geometry.…
Tree-Structured Orthonormal Decomposition of the Aitchison Simplex
Daisuke Yamada, Qijun Zhang, Travis Pence +3
Compositional data -- vectors encoding relative proportions -- arise across scientific domains, including ecology, geochemistry, and genomics. The features in these data often come…
Recursive Binding on a Budget: Subspace Carving in Order-p Tensor Memories
Travis Pence, Daisuke Yamada, Vikas Singh
Tensor Product Representations provide the structural fidelity required for symbolic reasoning in models but suffer from exponential dimensionality growth when encoding deep recurs…
Composing Linear Layers from Irreducibles
Travis Pence, Daisuke Yamada, Vikas Singh
Contemporary large models often exhibit behaviors suggesting the presence of low-level primitives that compose into modules with richer functionality, but these fundamental buildin…
ASAT: Adaptive Scoring and Thresholding with Human Feedback for Robust Out-of-Distribution Detection
Daisuke Yamada, Harit Vishwakarma, Ramya Korlakai Vinayak
Machine Learning (ML) models are trained on in-distribution (ID) data but often encounter out-of-distribution (OOD) inputs during deployment---posing serious risks in safety-critic…