Learning Curves for Error Minimum and Maximum Likelihood Algorithms. - Yoshiyuki Kabashima; Shigeru Shinomoto (Neural Comput., 1992)

Acceleration of Learning in Binary Choice Problems. - Yoshiyuki Kabashima; Shigeru Shinomoto (COLT, 1993)

Learning a Decision Boundary from Stochastic Examples: Incremental Algorithms with and without Queries. - Yoshiyuki Kabashima; Shigeru Shinomoto (Neural Comput., 1995)

The Belief in TAP. - Yoshiyuki Kabashima; David Saad (NIPS, 1998)

Regular and Irregular Gallager-zype Error-Correcting Codes. - Yoshiyuki Kabashima; Tatsuto Murayama; David Saad; Renato Vicente (NIPS, 1999)

Error-correcting Codes on a Bethe-like Lattice. - Renato Vicente; David Saad; Yoshiyuki Kabashima (NIPS, 2000)

Weight vs. Magnetization Enumerator for Gallager Codes. - Jort van Mourik; David Saad; Yoshiyuki Kabashima (IMACC, 2001)

Statistical Physics of Low Density Parity Check Error Correcting Codes. - David Saad; Yoshiyuki Kabashima; Tatsuto Murayama; Renato Vicente (IMACC, 2001)

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

Statistical mechanical evaluation of error exponents for lossy data compression. - Tadaaki Hosaka; Yoshiyuki Kabashima (ISIT, 2004)

An LDPCC decoding algorithm based on bowman-levin approximation -comparison with bp and CCCP-. - Masato Inoue; Miho Komiya; Yoshiyuki Kabashima (ISIT, 2005)

A CDMA multiuser detection algorithm based on survey propagation - Yoshiyuki Kabashima (CoRR, 2005)

Statistical Mechanical Approach to Lossy Data Compression:Theory and Practice - Tadaaki Hosaka; Yoshiyuki Kabashima (CoRR, 2005)

Survey propagation for the cascading Sourlas code - Jonathan Paul Lewis Hatchett; Yoshiyuki Kabashima (CoRR, 2006)

Analysis of CDMA systems that are characterized by eigenvalue spectrum - Koujin Takeda; Shinsuke Uda; Yoshiyuki Kabashima (CoRR, 2006)

Statistical Mechanics of Communication and Computation. - Yoshiyuki Kabashima (New Gener. Comput., 2006)

Statistical mechanical analysis of the linear vector channel in digital communication - Koujin Takeda; Atsushi Hatabu; Yoshiyuki Kabashima (CoRR, 2007)

Inference from correlated patterns: a unified theory for perceptron learning and linear vector channels - Yoshiyuki Kabashima (CoRR, 2007)

An integral formula for large random rectangular matrices and its application to analysis of linear vector channels. - Yoshiyuki Kabashima (WiOpt, 2008)

How could the replica method improve accuracy of performance assessment of channel coding? - Yoshiyuki Kabashima (CoRR, 2008)

Typical reconstruction limit of compressed sensing based on Lp-norm minimization - Yoshiyuki Kabashima; Tadashi Wadayama; Toshiyuki Tanaka (CoRR, 2009)

Statistical mechanical analysis of the Kronecker channel model for MIMO wireless communication - Atsushi Hatabu; Koujin Takeda; Yoshiyuki Kabashima (CoRR, 2009)

Decoding Algorithm of Low-density Parity-check Codes based on Bowman-Levin Approximation. - Ken-ichi Tamura; Miho Komiya; Masato Inoue; Yoshiyuki Kabashima (New Gener. Comput., 2009)

Statistical mechanical analysis of a typical reconstruction limit of compressed sensing. - Yoshiyuki Kabashima; Tadashi Wadayama; Toshiyuki Tanaka (ISIT, 2010)

Statistical mechanical analysis of compressed sensing utilizing correlated compression matrix. - Koujin Takeda; Yoshiyuki Kabashima (ISIT, 2010)

Statistical Mechanical Assessment of a Reconstruction Limit of Compressed Sensing: Toward Theoretical Analysis of Correlated Signals - Koujin Takeda; Yoshiyuki Kabashima (CoRR, 2010)

Average error exponent of undetected error probability of binary matrix ensembles. - Kazushi Mimura; Tadashi Wadayama; Toshiyuki Tanaka; Yoshiyuki Kabashima (ISIT, 2011)

A signal recovery algorithm for sparse matrix based compressed sensing - Yoshiyuki Kabashima; Tadashi Wadayama (CoRR, 2011)

Spectral Analysis of Random Sparse Matrices. - Tomonori Ando; Yoshiyuki Kabashima; Hisanao Takahashi; Osamu Watanabe 001; Masaki Yamamoto 001 (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2011)

Compressed sensing with sparse, structured matrices. - Maria Chiara Angelini; Federico Ricci-Tersenghi; Yoshiyuki Kabashima (Allerton Conference, 2012)

Sparse-matrix-based compressed sensing for spectrum sensing in Flexible Wireless System. - Doohwan Lee; Yoshiyuki Kabashima; Koujin Takeda; Takayuki Yamada; Kazunori Akabane; Kazuhiro Uehara (APCC, 2012)

A study of the universal threshold in the ℓ1 recovery by statistical mechanics. - Koujin Takeda; Yoshiyuki Kabashima (CISS, 2012)

Statistical Mechanical Analysis of Semantic Orientations on Lexical Network. - Takuma Goto; Yoshiyuki Kabashima; Hiroya Takamura (COLING, 2012)

Average growth rate of low-density generator-matrix codes ensembles. - Kazushi Mimura; Tadashi Wadayama; Yoshiyuki Kabashima (ISITA, 2012)

Analysis of sparse representations using bi-orthogonal dictionaries. - Mikko Vehkaperä; Yoshiyuki Kabashima; Saikat Chatterjee; Erik Aurell; Mikael Skoglund; Lars K. Rasmussen (ITW, 2012)

Statistical Mechanics of Dictionary Learning - Ayaka Sakata; Yoshiyuki Kabashima (CoRR, 2012)

A Mean-field Approach for an Intercarrier Interference Canceller for OFDM - Ayaka Sakata; Yoshiyuki Kabashima; Yitzhak Peleg (CoRR, 2012)

Typical l1-recovery limit of sparse vectors represented by concatenations of random orthogonal matrices - Yoshiyuki Kabashima; Mikko Vehkaperä; Saikat Chatterjee (CoRR, 2012)

Statistical mechanics approach to sparse noise denoising. - Mikko Vehkaperä; Yoshiyuki Kabashima; Saikat Chatterjee (EUSIPCO, 2013)

Sample complexity of Bayesian optimal dictionary learning. - Ayaka Sakata; Yoshiyuki Kabashima (ISIT, 2013)

Reconstruction algorithm in compressed sensing based on maximum a posteriori estimation. - Koujin Takeda; Yoshiyuki Kabashima (CoRR, 2013)

Statistical mechanics approach to 1-bit compressed sensing - Yingying Xu; Yoshiyuki Kabashima (CoRR, 2013)

Entropy landscape of solutions in the binary perceptron problem - Haiping Huang; K. Y. Michael Wong; Yoshiyuki Kabashima (CoRR, 2013)

Signal recovery using expectation consistent approximation for linear observations. - Yoshiyuki Kabashima; Mikko Vehkaperä (ISIT, 2014)

Origin of the computational hardness for learning with binary synapses. - Haiping Huang; Yoshiyuki Kabashima (CoRR, 2014)

Bayesian signal reconstruction for 1-bit compressed sensing. - Yingying Xu; Yoshiyuki Kabashima; Lenka Zdeborová (CoRR, 2014)

Replica symmetric bound for restricted isometry constant. - Ayaka Sakata; Yoshiyuki Kabashima (ISIT, 2015)

Limitations in the spectral method for graph partitioning: detectability threshold and localization of eigenvectors. - Tatsuro Kawamoto; Yoshiyuki Kabashima (CoRR, 2015)

Detectability of the spectral method for sparse graph partitioning. - Tatsuro Kawamoto; Yoshiyuki Kabashima (CoRR, 2015)

Dimensionality reduction based on an overcomplete basis. - Yoshinori Nakanishi-Ohno; Tomoyuki Obuchi; Masato Okada; Yoshiyuki Kabashima (CoRR, 2015)

Online compressed sensing. - Paulo V. Rossi; Yoshiyuki Kabashima; Jun-ichi Inoue (CoRR, 2015)

Approximate cross-validation formula for Bayesian linear regression. - Yoshiyuki Kabashima; Tomoyuki Obuchi; Makoto Uemura (Allerton, 2016)

Sampling approach to sparse approximation problem: Determining degrees of freedom by simulated annealing. - Tomoyuki Obuchi; Yoshiyuki Kabashima (EUSIPCO, 2016)

Cross-validation model assessment for modular networks. - Tatsuro Kawamoto; Yoshiyuki Kabashima (CoRR, 2016)

Comparative analysis of model assessment in community detection. - Tatsuro Kawamoto; Yoshiyuki Kabashima (CoRR, 2016)

Detectability thresholds of general modular graphs. - Tatsuro Kawamoto; Yoshiyuki Kabashima (CoRR, 2016)

Cross validation in LASSO and its acceleration. - Tomoyuki Obuchi; Yoshiyuki Kabashima (CoRR, 2016)

Sparse approximation problem: how rapid simulated annealing succeeds and fails. - Tomoyuki Obuchi; Yoshiyuki Kabashima (CoRR, 2016)

Statistical mechanics analysis of thresholding 1-bit compressed sensing. - Yingying Xu; Yoshiyuki Kabashima (CoRR, 2016)

Phase Transitions and Sample Complexity in Bayes-Optimal Matrix Factorization. - Yoshiyuki Kabashima; Florent Krzakala; Marc Mézard; Ayaka Sakata; Lenka Zdeborová (IEEE Trans. Inf. Theory, 2016)

Analysis of Regularized LS Reconstruction and Random Matrix Ensembles in Compressed Sensing. - Mikko Vehkaperä; Yoshiyuki Kabashima; Saikat Chatterjee (IEEE Trans. Inf. Theory, 2016)

Objective and efficient inference for couplings in neuronal networks. - Yu Terada; Tomoyuki Obuchi; Takuya Isomura; Yoshiyuki Kabashima (NeurIPS, 2018)

Statistical mechanical analysis of sparse linear regression as a variable selection problem. - Tomoyuki Obuchi; Yoshinori Nakanishi-Ohno; Masato Okada; Yoshiyuki Kabashima (CoRR, 2018)

Counting the number of metastable states in the modularity landscape: Algorithmic detectability limit of greedy algorithms in community detection. - Tatsuro Kawamoto; Yoshiyuki Kabashima (CoRR, 2018)

Accelerating Cross-Validation in Multinomial Logistic Regression with $ ell_1$-Regularization. - Tomoyuki Obuchi; Yoshiyuki Kabashima (J. Mach. Learn. Res., 2018)

Replicated Vector Approximate Message Passing For Resampling Problem. - Takashi Takahashi; Yoshiyuki Kabashima (CoRR, 2019)

Approximate matrix completion based on cavity method. - Chihiro Noguchi; Yoshiyuki Kabashima (CoRR, 2019)

Learning performance in inverse Ising problems with sparse teacher couplings. - Alia Abbara; Yoshiyuki Kabashima; Tomoyuki Obuchi; Yingying Xu (CoRR, 2019)

Semi-Analytic Resampling in Lasso. - Tomoyuki Obuchi; Yoshiyuki Kabashima (J. Mach. Learn. Res., 2019)

Macroscopic Analysis of Vector Approximate Message Passing in a Model Mismatch Setting. - Takashi Takahashi; Yoshiyuki Kabashima (ISIT, 2020)

Semi-analytic approximate stability selection for correlated data in generalized linear models. - Takashi Takahashi; Yoshiyuki Kabashima (CoRR, 2020)

Perfect Reconstruction of Sparse Signals via Greedy Monte-Carlo Search. - Kao Hayashi; Tomoyuki Obuchi; Yoshiyuki Kabashima (CoRR, 2020)

Structure Learning in Inverse Ising Problems Using 𝓁2-Regularized Linear Estimator. - Xiangming Meng; Tomoyuki Obuchi; Yoshiyuki Kabashima (CoRR, 2020)

High-dimensional structure learning of binary pairwise Markov networks: A comparative numerical study. - Johan Pensar; Yingying Xu; Santeri Puranen; Maiju Pesonen; Yoshiyuki Kabashima; Jukka Corander (Comput. Stat. Data Anal., 2020)

Inferring Neuronal Couplings From Spiking Data Using a Systematic Procedure With a Statistical Criterion. - Yu Terada; Tomoyuki Obuchi; Takuya Isomura; Yoshiyuki Kabashima (Neural Comput., 2020)

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

Ising Model Selection Using 𝓁1-Regularized Linear Regression. - Xiangming Meng; Tomoyuki Obuchi; Yoshiyuki Kabashima (CoRR, 2021)

Matrix completion based on Gaussian belief propagation. - Koki Okajima; Yoshiyuki Kabashima (CoRR, 2021)

On Model Selection Consistency of Lasso for High-Dimensional Ising Models on Tree-like Graphs. - Xiangming Meng; Tomoyuki Obuchi; Yoshiyuki Kabashima (CoRR, 2021)

Macroscopic Analysis of Vector Approximate Message Passing in a Model-Mismatched Setting. - Takashi Takahashi; Yoshiyuki Kabashima (IEEE Trans. Inf. Theory, 2022)

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

Average case analysis of Lasso under ultra sparse conditions. - Koki Okajima; Xiangming Meng; Takashi Takahashi; Yoshiyuki Kabashima (AISTATS, 2023)

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

QCM-SGM+: Improved Quantized Compressed Sensing With Score-Based Generative Models for General Sensing Matrices. - Xiangming Meng; Yoshiyuki Kabashima (CoRR, 2023)

Generating gradients in the energy landscape using rectified linear type cost functions for efficiently solving 0/1 matrix factorization in Simulated Annealing. - Makiko Konoshima; Hirotaka Tamura; Yoshiyuki Kabashima (CoRR, 2023)

Compressed Sensing Radar Detectors Under the Row-Orthogonal Design Model: A Statistical Mechanics Perspective. - Siqi Na; Tianyao Huang; Yimin Liu; Takashi Takahashi; Yoshiyuki Kabashima; Xiqin Wang (IEEE Trans. Signal Process., 2023)

Decision Theoretic Cutoff and ROC Analysis for Bayesian Optimal Group Testing. - Ayaka Sakata; Yoshiyuki Kabashima (IEEE Trans. Inf. Theory, 2023)

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

Diffusion Model Based Posterior Sampling for Noisy Linear Inverse Problems. - Xiangming Meng; Yoshiyuki Kabashima (ACML, 2024)

Improving Decoupled Posterior Sampling for Inverse Problems using Data Consistency Constraint. - Zhi Qi; Shihong Yuan; Yuyin Yuan; Linling Kuang; Yoshiyuki Kabashima; Xiangming Meng (CoRR, 2024)