Kabashima, Yoshiyuki

16 publications

ACML 2024 Diffusion Model Based Posterior Sampling for Noisy Linear Inverse Problems Xiangming Meng, Yoshiyuki Kabashima

AAAI 2024 QCS-SGM+: Improved Quantized Compressed Sensing with Score-Based Generative Models Xiangming Meng, Yoshiyuki Kabashima

AISTATS 2023 Average Case Analysis of Lasso Under Ultra Sparse Conditions Koki Okajima, Xiangming Meng, Takashi Takahashi, Yoshiyuki Kabashima

AISTATS 2023 On Model Selection Consistency of Lasso for High-Dimensional Ising Models Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima

ICLR 2023 Quantized Compressed Sensing with Score-Based Generative Models Xiangming Meng, Yoshiyuki Kabashima

NeurIPS 2021 Ising Model Selection Using $\ell_{1}$-Regularized Linear Regression: A Statistical Mechanics Analysis Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima

JMLR 2019 Semi-Analytic Resampling in Lasso Tomoyuki Obuchi, Yoshiyuki Kabashima

JMLR 2018 Accelerating Cross-Validation in Multinomial Logistic Regression with $\ell_1$-Regularization Tomoyuki Obuchi, Yoshiyuki Kabashima

NeurIPS 2018 Objective and Efficient Inference for Couplings in Neuronal Networks Yu Terada, Tomoyuki Obuchi, Takuya Isomura, Yoshiyuki Kabashima

ALT 2004 A BP-Based Algorithm for Performing Bayesian Inference in Large Perceptron-Type Networks Yoshiyuki Kabashima, Shinsuke Uda

NeurIPS 2000 Error-Correcting Codes on a Bethe-like Lattice Renato Vicente, David Saad, Yoshiyuki Kabashima

NeurIPS 1999 Regular and Irregular Gallager-Zype Error-Correcting Codes Yoshiyuki Kabashima, Tatsuto Murayama, David Saad, Renato Vicente

NeurIPS 1998 The Belief in TAP Yoshiyuki Kabashima, David Saad

NeCo 1995 Learning a Decision Boundary from Stochastic Examples: Incremental Algorithms with and Without Queries Yoshiyuki Kabashima, Shigeru Shinomoto

COLT 1993 Acceleration of Learning in Binary Choice Problems Yoshiyuki Kabashima, Shigeru Shinomoto

NeCo 1992 Learning Curves for Error Minimum and Maximum Likelihood Algorithms Yoshiyuki Kabashima, Shigeru Shinomoto