Tsukasa Yoshida

collaborators

2 papers

cs.IR2026

What Limits Does Quantization Place on Dense Top- $k$ Retrieval? A Theoretical Study

Koki Okajima, Tsukasa Yoshida

We establish conditions for embedding a corpus of $N$ documents as $d$ -dimensional vectors such that every $k$ -subset $S \subseteq [N]$ is realizable as a result of top- $k$ retriev…

math.ST2025

Empirical Bayes Estimation for Lasso-Type Regularizers: Analysis of Automatic Relevance Determination

Tsukasa Yoshida, Kazuho Watanabe

This paper focuses on linear regression models with non-conjugate sparsity-inducing regularizers such as lasso and group lasso. Although the empirical Bayes approach enables us to…

What Limits Does Quantization Place on Dense Top-k Retrieval? A Theoretical Study

Empirical Bayes Estimation for Lasso-Type Regularizers: Analysis of Automatic Relevance Determination

What Limits Does Quantization Place on Dense Top- $k$ Retrieval? A Theoretical Study