Ichigaku Takigawa

According to our database, Ichigaku Takigawa authored at least 44 papers between 2004 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2023

Machine learning refinement of in situ images acquired by low electron dose LC-TEM.

Hiroyasu Katsuno, Yuki Kimura, Tomoya Yamazaki, Ichigaku Takigawa

CoRR, 2023

2022

Interval-Memoized Backtracking on ZDDs for Fast Enumeration of All Lower Cost Solutions.

Shin-ichi Minato, Mutsunori Banbara, Takashi Horiyama, Jun Kawahara, Ichigaku Takigawa, Yutaro Yamaguchi

CoRR, 2022

2021

Minor-embedding heuristics for large-scale annealing processors with sparse hardware graphs of up to 102, 400 nodes.

Yuya Sugie, Yuki Yoshida, Normann Mertig, Takashi Takemoto, Hiroshi Teramoto, Atsuyoshi Nakamura, Ichigaku Takigawa, Shin-ichi Minato, Masanao Yamaoka, Tamiki Komatsuzaki

Soft Comput., 2021

Fast improvement of TEM image with low-dose electrons by deep learning.

Hiroyasu Katsuno, Yuki Kimura, Tomoya Yamazaki, Ichigaku Takigawa

CoRR, 2021

2020

Dual graph convolutional neural network for predicting chemical networks.

Shonosuke Harada, Hirotaka Akita, Masashi Tsubaki, Yukino Baba, Ichigaku Takigawa, Yoshihiro Yamanishi, Hisashi Kashima

BMC Bioinform., April, 2020

Efficiently Enumerating Substrings with Statistically Significant Frequencies of Locally Optimal Occurrences in Gigantic String.

Atsuyoshi Nakamura, Ichigaku Takigawa, Hiroshi Mamitsuka

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Learning Relevant Molecular Representations via Self-Attentive Graph Neural Networks.

Shoma Kikuchi, Ichigaku Takigawa, Satoshi Oyama, Masahito Kurihara

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Dual Convolutional Neural Network for Graph of Graphs Link Prediction.

Shonosuke Harada, Hirotaka Akita, Masashi Tsubaki, Yukino Baba, Ichigaku Takigawa, Yoshihiro Yamanishi, Hisashi Kashima

CoRR, 2018

Jointly learning relevant subgraph patterns and nonlinear models of their indicators.

Ryo Shirakawa, Yusei Yokoyama, Fumiya Okazaki, Ichigaku Takigawa

CoRR, 2018

Graph Minors from Simulated Annealing for Annealing Machines with Sparse Connectivity.

Yuya Sugie, Yuki Yoshida, Normann Mertig, Takashi Takemoto, Hiroshi Teramoto, Atsuyoshi Nakamura, Ichigaku Takigawa, Shin-ichi Minato, Masanao Yamaoka, Tamiki Komatsuzaki

Proceedings of the Theory and Practice of Natural Computing - 7th International Conference, 2018

FPGA-Based QBoost with Large-Scale Annealing Processor and Accelerated Hyperparameter Search.

Takashi Takemoto, Normann Mertig, Masato Hayashi, Saki Susa-Tanaka, Hiroshi Teramoto, Atsuyoshi Nakamura, Ichigaku Takigawa, Shin-ichi Minato, Tamiki Komatsuzaki, Masanao Yamaoka

Proceedings of the 2018 International Conference on ReConFigurable Computing and FPGAs, 2018

2017

Generalized Sparse Learning of Linear Models Over the Complete Subgraph Feature Set.

Ichigaku Takigawa, Hiroshi Mamitsuka

IEEE Trans. Pattern Anal. Mach. Intell., 2017

An Online Self-Constructive Normalized Gaussian Network with Localized Forgetting.

Jana Backhus, Ichigaku Takigawa, Hideyuki Imai, Mineichi Kudo, Masanori Sugimoto

IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2017

Exploring phenotype patterns of breast cancer within somatic mutations: a modicum in the intrinsic code.

Sohiya Yotsukura, Masayuki Karasuyama, Ichigaku Takigawa, Hiroshi Mamitsuka

Briefings Bioinform., 2017

2016

Dense core model for cohesive subgraph discovery.

Sadamori Koujaku, Ichigaku Takigawa, Mineichi Kudo, Hideyuki Imai

Soc. Networks, 2016

Mining approximate patterns with frequent locally optimal occurrences.

Atsuyoshi Nakamura, Ichigaku Takigawa, Hisashi Tosaka, Mineichi Kudo, Hiroshi Mamitsuka

Discret. Appl. Math., 2016

Online EM for the Normalized Gaussian Network with Weight-Time-Dependent Updates.

Jana Backhus, Ichigaku Takigawa, Hideyuki Imai, Mineichi Kudo, Masanori Sugimoto

Proceedings of the Neural Information Processing - 23rd International Conference, 2016

Reducing Redundancy with Unit Merging for Self-constructive Normalized Gaussian Networks.

Jana Backhus, Ichigaku Takigawa, Hideyuki Imai, Mineichi Kudo, Masanori Sugimoto

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2016, 2016

2015

Ensemble and Multiple Kernel Regressors: Which Is Better?

Akira Tanaka, Hirofumi Takebayashi, Ichigaku Takigawa, Hideyuki Imai, Mineichi Kudo

IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2015

Community Change Detection in Dynamic Networks in Noisy Environment.

Sadamori Koujaku, Mineichi Kudo, Ichigaku Takigawa, Hideyuki Imai

Proceedings of the 24th International Conference on World Wide Web Companion, 2015

2014

Similarity-based machine learning methods for predicting drug-target interactions: a brief review.

Hao Ding, Ichigaku Takigawa, Hiroshi Mamitsuka, Shanfeng Zhu

Briefings Bioinform., 2014

Analyses on Generalization Error of Ensemble Kernel Regressors.

Akira Tanaka, Ichigaku Takigawa, Hideyuki Imai, Mineichi Kudo

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2014

Theoretical Analyses on Ensemble and Multiple Kernel Regressors.

Akira Tanaka, Ichigaku Takigawa, Hideyuki Imai, Mineichi Kudo

Proceedings of the Sixth Asian Conference on Machine Learning, 2014

2013

Fast algorithms for finding a minimum repetition representation of strings and trees.

Atsuyoshi Nakamura, Tomoya Saito, Ichigaku Takigawa, Mineichi Kudo, Hiroshi Mamitsuka

Discret. Appl. Math., 2013

2012

Extended Analyses for an Optimal Kernel in a Class of Kernels with an Invariant Metric.

Akira Tanaka, Ichigaku Takigawa, Hideyuki Imai, Mineichi Kudo

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2012

2011

A spectral approach to clustering numerical vectors as nodes in a network.

Motoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka

Pattern Recognit., 2011

Efficiently mining <i>δ</i>-tolerance closed frequent subgraphs.

Ichigaku Takigawa, Hiroshi Mamitsuka

Mach. Learn., 2011

2010

Mining metabolic pathways through gene expression.

Timothy Hancock, Ichigaku Takigawa, Hiroshi Mamitsuka

Bioinform., 2010

Algorithms for Finding a Minimum Repetition Representation of a String.

Atsuyoshi Nakamura, Tomoya Saito, Ichigaku Takigawa, Hiroshi Mamitsuka, Mineichi Kudo

Proceedings of the String Processing and Information Retrieval, 2010

2009

Field independent probabilistic model for clustering multi-field documents.

Shanfeng Zhu, Ichigaku Takigawa, Jia Zeng, Hiroshi Mamitsuka

Inf. Process. Manag., 2009

Convex sets as prototypes for classifying patterns.

Ichigaku Takigawa, Mineichi Kudo, Atsuyoshi Nakamura

Eng. Appl. Artif. Intell., 2009

Efficiently finding genome-wide three-way gene interactions from transcript- and genotype-data.

Mitsunori Kayano, Ichigaku Takigawa, Motoki Shiga, Koji Tsuda, Hiroshi Mamitsuka

Bioinform., 2009

2008

Probabilistic path ranking based on adjacent pairwise coexpression for metabolic transcripts analysis.

Ichigaku Takigawa, Hiroshi Mamitsuka

Bioinform., 2008

Classification by reflective convex hulls.

Mineichi Kudo, Atsuyoshi Nakamura, Ichigaku Takigawa

Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008

Mining significant tree patterns in carbohydrate sugar chains.

Kosuke Hashimoto, Ichigaku Takigawa, Motoki Shiga, Minoru Kanehisa, Hiroshi Mamitsuka

Proceedings of the ECCB'08 Proceedings, 2008

2007

A spectral clustering approach to optimally combining numericalvectors with a modular network.

Motoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka

Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

Annotating gene function by combining expression data with a modular gene network.

Motoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka

Proceedings of the Proceedings 15th International Conference on Intelligent Systems for Molecular Biology (ISMB) & 6th European Conference on Computational Biology (ECCB), 2007

A Probabilistic Model for Clustering Text Documents with Multiple Fields.

Shanfeng Zhu, Ichigaku Takigawa, Shuqin Zhang, Hiroshi Mamitsuka

Proceedings of the Advances in Information Retrieval, 2007

2006

Applying Gaussian Distribution-Dependent Criteria to Decision Trees for High-Dimensional Microarray Data.

Raymond Wan, Ichigaku Takigawa, Hiroshi Mamitsuka

Proceedings of the Data Mining and Bioinformatics, First International Workshop, 2006

Combining Vector-Space and Word-Based Aspect Models for Passage Retrieval.

Raymond Wan, Ichigaku Takigawa, Hiroshi Mamitsuka, Vo Ngoc Anh

Proceedings of the Fifteenth Text REtrieval Conference, 2006

2005

The Convex Subclass Method: Combinatorial Classifier Based on a Family of Convex Sets.

Ichigaku Takigawa, Mineichi Kudo, Atsuyoshi Nakamura

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2005

2004

Performance analysis of minimum ℓ₁-norm solutions for underdetermined source separation.

Ichigaku Takigawa, Mineichi Kudo, Jun Toyama

IEEE Trans. Signal Process., 2004

Projection Learning Based Kernel Machine Design Using Series of Monotone Increasing Reproducing Kernel Hilbert Spaces.

Akira Tanaka, Ichigaku Takigawa, Hideyuki Imai, Mineichi Kudo, Masaaki Miyakoshi

Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2004

On the Minimum l₁-Norm Signal Recovery in Underdetermined Source Separation.

Ichigaku Takigawa, Mineichi Kudo, Atsuyoshi Nakamura, Jun Toyama

Proceedings of the Independent Component Analysis and Blind Signal Separation, 2004