Hiroto Saigo

发表

gBoost: a mathematical programming approach to graph classification and regression

Sebastian Nowozin, Taku Kudo, Koji Tsuda, 2009, Machine Learning.

Extracting Sets of Chemical Substructures and Protein Domains Governing Drug-Target Interactions

Yoshihiro Yamanishi, Hiroto Saigo, Edouard Pauwels, 2011, J. Chem. Inf. Model..

Entire Regularization Path for Sparse Nonnegative Interaction Model

Yasuo Tabei, Hiroto Saigo, Mirai Takayanagi, 2018, 2018 IEEE International Conference on Data Mining (ICDM).

RF-NR: Random Forest Based Approach for Improved Classification of Nuclear Receptors

Hiroto Saigo, Hamid D. Ismail, Dukka B KC, 2018, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

DeepRMethylSite: a deep learning based approach for prediction of arginine methylation sites in proteins.

Hiroto Saigo, Kaushik Roy, Niraj Thapa, 2020, Molecular omics.

Reaction graph kernels predict EC numbers of unknown enzymatic reactions in plant secondary metabolism

Hisashi Kashima, Koji Tsuda, Hiroto Saigo, 2010, BMC Bioinformatics.

Protein Clustering on a Grassmann Manifold

Hiroto Saigo, Kazuhiro Fukui, Chendra Hadi Suryanto, 2012, PRIB.

Mathematical Programming Methods for Learning from Structured Data: Applications to Molecular QSAR Analysis, HIV Drug Resistance Prediction, and Image Categorisation

Takeaki Uno, Taku Kudo, Koji Tsuda, 2007 .

Comparison of SVM-Based Methods for Remote Homology Detection

Tatsuya Akutsu, Jean-Philippe Vert, Hiroto Saigo, 2002 .

Context-Aware Latent Dirichlet Allocation for Topic Segmentation

Tetsu Matsukawa, Einoshin Suzuki, Hiroto Saigo, 2020, PAKDD.

KDSNP: A kernel-based approach to detecting high-order SNP interactions

Hiroto Saigo, Kento Kodama, Hiroto Saigo, 2016, J. Bioinform. Comput. Biol..

Large‐scale prediction of disulphide bridges using kernel methods, two‐dimensional recursive neural networks, and weighted graph matching

Pierre Baldi, Jianlin Cheng, Hiroto Saigo, 2005, Proteins.

Matrix Decomposition-based Dimensionality Reduction on Graph Data

Koji Tsuda, Hiroto Saigo, Hiroto Saigo, 2011, Graph Data Management.

Scalable Partial Least Squares Regression on Grammar-Compressed Data Matrices

Yasuo Tabei, Yoshihiro Yamanishi, Simon J. Puglisi, 2016, KDD.

Reaction graph kernels for discovering missing enzymes in the plant secondary metabolism

Koji Tsuda, Hiroto Saigo, Masahiro Hattori, 2007, NIPS 2007.

Regression with interval output values

Hisashi Kashima, Hiroto Saigo, Akihiro Inokuchi, 2008, 2008 19th International Conference on Pattern Recognition.

A Bayesian Approach to Graphy Regression with Relevant Subgraph Selection

Koji Tsuda, Hiroto Saigo, Silvia Chiappa, 2009, SDM.

Iterative Subgraph Mining for Principal Component Analysis

Koji Tsuda, Hiroto Saigo, Hiroto Saigo, 2008, 2008 Eighth IEEE International Conference on Data Mining.

Graph Classification

Koji Tsuda, Hiroto Saigo, Hiroto Saigo, 2010, Managing and Mining Graph Data.

CNN-BLPred: a Convolutional neural network based predictor for β-Lactamases (BL) and their classes

Hiroto Saigo, Hamid D. Ismail, Dukka B Kc, 2017, BMC Bioinformatics.

Fast Iterative Mining Using Sparsity-Inducing Loss Functions

Hisashi Kashima, Koji Tsuda, Hiroto Saigo, 2013, IEICE Trans. Inf. Syst..

Protein homology detection using string alignment kernels

Tatsuya Akutsu, Jean-Philippe Vert, Hiroto Saigo, 2004, Bioinform..

Partial least squares regression for graph mining

Nicole Krämer, Koji Tsuda, Hiroto Saigo, 2008, KDD.

Mining complex genotypic features for predicting HIV-1 drug resistance

Takeaki Uno, Koji Tsuda, Hiroto Saigo, 2007, Bioinform..

Graph boosting for molecular QSAR analysis

Koji Tsuda, Hiroto Saigo, Kudo T Kadowaki T, 2006, NIPS 2006.

Mining Discriminative Patterns from Graph Data with Multiple Labels and Its Application to Quantitative Structure-Activity Relationship (QSAR) Models

Yoshihiro Yamanishi, Zheng Shao, Hiroto Saigo, 2015, J. Chem. Inf. Model..

Graph kernels for chemical informatics

Pierre Baldi, Sanjay Joshua Swamidass, Hiroto Saigo, 2005, Neural Networks.

Functional census of mutation sequence spaces: the example of p53 cancer rescue mutants

Pierre Baldi, Ray Luo, Sanjay Joshua Swamidass, 2006, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Optimizing amino acid substitution matrices with a local alignment kernel

Tatsuya Akutsu, Jean-Philippe Vert, Hiroto Saigo, 2006, BMC Bioinformatics.

Topic modeling for sequential documents based on hybrid inter-document topic dependency

Einoshin Suzuki, Bin Tong, Hiroto Saigo, 2021, Journal of Intelligent Information Systems.

Sparse Nonnegative Interaction Models

Yasuo Tabei, Einoshin Suzuki, Hiroto Saigo, 2021, IEEE Access.

Automatically mining Relevant Variable Interactions Via Sparse Bayesian Learning

Yasuo Tabei, Hiroto Saigo, Mirai Takayanagi, 2021, 2020 25th International Conference on Pattern Recognition (ICPR).

Structural Class Classification of 3D Protein Structure Based on Multi-View 2D Images

Hiroto Saigo, Kazuhiro Fukui, Chendra Hadi Suryanto, 2018, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

RF-GlutarySite: a random forest based predictor for glutarylation sites.

Hiroto Saigo, Robert H Newman, Dukka B Kc, 2019, Molecular omics.

Graph Mining in Chemoinformatics

Koji Tsuda, Hiroto Saigo, Hiroto Saigo, 2010 .