12 papers
Determinantal Point Process Approximation under Positive and Negative Dependence
So Anzai, Hideitsu Hino
Determinantal point processes (DPPs) are widely used as probabilistic models for diverse random subsets, but their approximation error under model misspecification has not been ful…
Projective Maximum Entropy: Universality and Acceptance-Region Calibration
Hideitsu Hino
Maximum-entropy reference distributions are usually constructed on the normalized probability simplex. This formulation is less natural for unnormalized statistical models, in whic…
LIG: Layer-wise Integrated Gradients for Within-Layer Flow Analysis in Transformers
Eight Suzuki, Hideitsu Hino, Noboru Murata
Transformers achieve strong performance, but their internal computations remain opaque. We view each Transformer layer as a dynamic graph whose nodes are token representations and…
An -accurate level set estimation with a stopping criterion
Hideaki Ishibashi, Kota Matsui, Kentaro Kutsukake +1
The level set estimation problem seeks to identify regions within a set of candidate points where an unknown and costly to evaluate function's value exceeds a specified threshold,…
From DPPs to -DPPs: identifiability analysis via spectral decomposition
Hideitsu Hino, Keisuke Yano
We study the geometry of determinantal point processes (DPPs) through the spectral decomposition . The spectrum governs the cardinality distribution via element…
Sobolev--Ricci Curvature
Kyoichi Iwasaki, Tam Le, Hideitsu Hino
Ricci curvature is a fundamental concept in differential geometry for encoding local geometric structure, and its graph-based analogues have recently gained prominence as practical…