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Koji Tsuda
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2020 – today
- 2024
- [i19]Zetian Mao, Jiawen Li, Chen Liang, Diptesh Das, Masato Sumita, Koji Tsuda:
Molecule Graph Networks with Many-body Equivariant Interactions. CoRR abs/2406.13265 (2024) - [i18]Zhang Haishan, Diptesh Das, Koji Tsuda:
Preference-Optimized Pareto Set Learning for Blackbox Optimization. CoRR abs/2408.09976 (2024) - 2023
- [j55]Jiawen Li, Masato Sumita, Ryo Tamura, Koji Tsuda:
Interpretable Fragment-Based Molecule Design with Self-Learning Entropic Population Annealing. Adv. Intell. Syst. 5(10) (2023) - [j54]Francois Berenger, Koji Tsuda:
3D-Sensitive Encoding of Pharmacophore Features. J. Chem. Inf. Model. 63(8): 2360-2369 (2023) - [j53]Weilin Yuan, Yusuke Hibi, Ryo Tamura, Masato Sumita, Yasuyuki Nakamura, Masanobu Naito, Koji Tsuda:
Revealing factors influencing polymer degradation with rank-based machine learning. Patterns 4(12): 100846 (2023) - [j52]Takumi Yoshida, Hiroyuki Hanada, Kazuya Nakagawa, Kouichi Taji, Koji Tsuda, Ichiro Takeuchi:
Efficient model selection for predictive pattern mining model by safe pattern pruning. Patterns 4(12): 100890 (2023) - [j51]Dai Hai Nguyen, Koji Tsuda:
On a linear fused Gromov-Wasserstein distance for graph structured data. Pattern Recognit. 138: 109351 (2023) - [i17]Ryo Tamura, Koji Tsuda, Shoichi Matsuda:
NIMS-OS: An automation software to implement a closed loop between artificial intelligence and robotic experiments in materials science. CoRR abs/2304.13927 (2023) - [i16]Takumi Yoshida, Hiroyuki Hanada, Kazuya Nakagawa, Kouichi Taji, Koji Tsuda, Ichiro Takeuchi:
Efficient Model Selection for Predictive Pattern Mining Model by Safe Pattern Pruning. CoRR abs/2306.13561 (2023) - [i15]Chao Huang, Diptesh Das, Koji Tsuda:
Feature Importance Measurement based on Decision Tree Sampling. CoRR abs/2307.13333 (2023) - 2022
- [j50]Yuichi Motoyama, Ryo Tamura, Kazuyoshi Yoshimi, Kei Terayama, Tsuyoshi Ueno, Koji Tsuda:
Bayesian optimization package: PHYSBO. Comput. Phys. Commun. 278: 108405 (2022) - [j49]Masato Sumita, Kei Terayama, Ryo Tamura, Koji Tsuda:
QCforever: A Quantum Chemistry Wrapper for Everyone to Use in Black-Box Optimization. J. Chem. Inf. Model. 62(18): 4427-4434 (2022) - [c59]Diptesh Das, Vo Nguyen Le Duy, Hiroyuki Hanada, Koji Tsuda, Ichiro Takeuchi:
Fast and More Powerful Selective Inference for Sparse High-Order Interaction Model. AAAI 2022: 9999-10007 - [i14]Dai Hai Nguyen, Koji Tsuda:
On a linear fused Gromov-Wasserstein distance for graph structured data. CoRR abs/2203.04711 (2022) - 2021
- [j48]Francois Berenger, Koji Tsuda:
Molecular generation by Fast Assembly of (Deep)SMILES fragments. J. Cheminformatics 13(1): 88 (2021) - [i13]Syun Izawa, Koki Kitai, Shu Tanaka, Ryo Tamura, Koji Tsuda:
Continuous black-box optimization with quantum annealing and random subspace coding. CoRR abs/2104.14778 (2021) - [i12]Dai Hai Nguyen, Koji Tsuda:
A generative model for molecule generation based on chemical reaction trees. CoRR abs/2106.03394 (2021) - [i11]Diptesh Das, Vo Nguyen Le Duy, Hiroyuki Hanada, Koji Tsuda, Ichiro Takeuchi:
Fast and More Powerful Selective Inference for Sparse High-order Interaction Model. CoRR abs/2106.04929 (2021) - 2020
- [j47]Ryosuke Shibukawa, Shoichi Ishida, Kazuki Yoshizoe, Kunihiro Wasa, Kiyosei Takasu, Yasushi Okuno, Kei Terayama, Koji Tsuda:
CompRet: a comprehensive recommendation framework for chemical synthesis planning with algorithmic enumeration. J. Cheminformatics 12(1): 52 (2020) - [j46]Jianbin Qin, Chuan Xiao, Sheng Hu, Jie Zhang, Wei Wang, Yoshiharu Ishikawa, Koji Tsuda, Kunihiko Sadakane:
Efficient query autocompletion with edit distance-based error tolerance. VLDB J. 29(4): 919-943 (2020)
2010 – 2019
- 2019
- [i10]Xiaolin Sun, Zhufeng Hou, Masato Sumita, Shinsuke Ishihara, Ryo Tamura, Koji Tsuda:
Leveraging Legacy Data to Accelerate Materials Design via Preference Learning. CoRR abs/1910.11516 (2019) - 2018
- [j45]Shuhei Denzumi, Jun Kawahara, Koji Tsuda, Hiroki Arimura, Shin-ichi Minato, Kunihiko Sadakane:
DenseZDD: A Compact and Fast Index for Families of Sets. Algorithms 11(8): 128 (2018) - [j44]Kei Terayama, Hiroaki Iwata, Mitsugu Araki, Yasushi Okuno, Koji Tsuda:
Machine learning accelerates MD-based binding pose prediction between ligands and proteins. Bioinform. 34(5): 770-778 (2018) - [j43]Kazuki Yoshizoe, Aika Terada, Koji Tsuda:
MP-LAMP: parallel detection of statistically significant multi-loci markers on cloud platforms. Bioinform. 34(17): 3047-3049 (2018) - [j42]Mitsugu Araki, Hiroaki Iwata, Biao Ma, Atsuto Fujita, Kei Terayama, Yukari Sagae, Fumie Ono, Koji Tsuda, Narutoshi Kamiya, Yasushi Okuno:
Improving the Accuracy of Protein-Ligand Binding Mode Prediction Using a Molecular Dynamics-Based Pocket Generation Approach. J. Comput. Chem. 39(32): 2679-2689 (2018) - [c58]Mahito Sugiyama, Hiroyuki Nakahara, Koji Tsuda:
Legendre Decomposition for Tensors. NeurIPS 2018: 8825-8835 - [i9]Mahito Sugiyama, Hiroyuki Nakahara, Koji Tsuda:
Legendre Tensor Decomposition. CoRR abs/1802.04502 (2018) - [i8]Mahito Sugiyama, Koji Tsuda, Hiroyuki Nakahara:
Transductive Boltzmann Machines. CoRR abs/1805.07938 (2018) - 2017
- [j41]Xiufeng Yang, Kazuki Yoshizoe, Akito Taneda, Koji Tsuda:
RNA inverse folding using Monte Carlo tree search. BMC Bioinform. 18(1): 468 (2017) - [c57]Mahito Sugiyama, Hiroyuki Nakahara, Koji Tsuda:
Tensor Balancing on Statistical Manifold. ICML 2017: 3270-3279 - [c56]Shinya Suzumura, Kazuya Nakagawa, Yuta Umezu, Koji Tsuda, Ichiro Takeuchi:
Selective Inference for Sparse High-Order Interaction Models. ICML 2017: 3338-3347 - [i7]Mahito Sugiyama, Hiroyuki Nakahara, Koji Tsuda:
Tensor Balancing on Statistical Manifold. CoRR abs/1702.08142 (2017) - [i6]Xiufeng Yang, Jinzhe Zhang, Kazuki Yoshizoe, Kei Terayama, Koji Tsuda:
ChemTS: An Efficient Python Library for de novo Molecular Generation. CoRR abs/1710.00616 (2017) - 2016
- [j40]Aika Terada, Ryo Yamada, Koji Tsuda, Jun Sese:
LAMPLINK: detection of statistically significant SNP combinations from GWAS data. Bioinform. 32(22): 3513-3515 (2016) - [j39]David A. duVerle, Sohiya Yotsukura, Seitaro Nomura, Hiroyuki Aburatani, Koji Tsuda:
CellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data. BMC Bioinform. 17: 363 (2016) - [c55]Mahito Sugiyama, Hiroyuki Nakahara, Koji Tsuda:
Information decomposition on structured space. ISIT 2016: 575-579 - [c54]Kazuya Nakagawa, Shinya Suzumura, Masayuki Karasuyama, Koji Tsuda, Ichiro Takeuchi:
Safe Pattern Pruning: An Efficient Approach for Predictive Pattern Mining. KDD 2016: 1785-1794 - [c53]Aika Terada, David duVerle, Koji Tsuda:
Significant Pattern Mining with Confounding Variables. PAKDD (1) 2016: 277-289 - [i5]Mahito Sugiyama, Hiroyuki Nakahara, Koji Tsuda:
Information Decomposition on Structured Space. CoRR abs/1601.05533 (2016) - 2015
- [j38]Kana Shimizu, Koji Nuida, Hiromi Arai, Shigeo Mitsunari, Nuttapong Attrapadung, Michiaki Hamada, Koji Tsuda, Takatsugu Hirokawa, Jun Sakuma, Goichiro Hanaoka, Kiyoshi Asai:
Privacy-preserving search for chemical compound databases. BMC Bioinform. 16(S18): S6 (2015) - [c52]Yukino Baba, Hisashi Kashima, Yasunobu Nohara, Eiko Kai, Partha Pratim Ghosh, Rafiqul Islam Maruf, Ashir Ahmed, Masahiro Kuroda, Sozo Inoue, Tatsuo Hiramatsu, Michio Kimura, Shuji Shimizu, Kunihisa Kobayashi, Koji Tsuda, Masashi Sugiyama, Mathieu Blondel, Naonori Ueda, Masaru Kitsuregawa, Naoki Nakashima:
Predictive Approaches for Low-Cost Preventive Medicine Program in Developing Countries. KDD 2015: 1681-1690 - [c51]Takahisa Toda, Koji Tsuda:
BDD construction for all solutions SAT and efficient caching mechanism. SAC 2015: 1880-1886 - [c50]David A. duVerle, Shohei Kawasaki, Yoshiji Yamada, Jun Sakuma, Koji Tsuda:
Privacy-Preserving Statistical Analysis by Exact Logistic Regression. IEEE Symposium on Security and Privacy Workshops 2015: 7-16 - [c49]Takahisa Toda, Shogo Takeuchi, Koji Tsuda, Shin-ichi Minato:
Superset Generation on Decision Diagrams. WALCOM 2015: 317-322 - [i4]Kazuki Yoshizoe, Aika Terada, Koji Tsuda:
Redesigning pattern mining algorithms for supercomputers. CoRR abs/1510.07787 (2015) - 2014
- [j37]Takeru Inoue, Keiji Takano, Takayuki Watanabe, Jun Kawahara, Ryo Yoshinaka, Akihiro Kishimoto, Koji Tsuda, Shin-ichi Minato, Yasuhiro Hayashi:
Distribution Loss Minimization With Guaranteed Error Bound. IEEE Trans. Smart Grid 5(1): 102-111 (2014) - [c48]Ken-ichiro Moridomi, Kohei Hatano, Eiji Takimoto, Koji Tsuda:
Online matrix prediction for sparse loss matrices. ACML 2014 - [c47]Jun Sese, Aika Terada, Yuki Saito, Koji Tsuda:
Statistically significant subgraphs for genome-wide association study. SSDM@ECML/PKDD 2014: 29-36 - [c46]Shin-ichi Minato, Takeaki Uno, Koji Tsuda, Aika Terada, Jun Sese:
A Fast Method of Statistical Assessment for Combinatorial Hypotheses Based on Frequent Itemset Enumeration. ECML/PKDD (2) 2014: 422-436 - [c45]Shuhei Denzumi, Jun Kawahara, Koji Tsuda, Hiroki Arimura, Shin-ichi Minato, Kunihiko Sadakane:
DenseZDD: A Compact and Fast Index for Families of Sets. SEA 2014: 187-198 - [c44]Hirohito Sasakawa, Hiroki Harada, David duVerle, Hiroki Arimura, Koji Tsuda, Jun Sakuma:
Oblivious Evaluation of Non-deterministic Finite Automata with Application to Privacy-Preserving Virus Genome Detection. WPES 2014: 21-30 - 2013
- [j36]David duVerle, Ichiro Takeuchi, Yuko Murakami-Tonami, Kenji Kadomatsu, Koji Tsuda:
Discovering combinatorial interactions in survival data. Bioinform. 29(23): 3053-3059 (2013) - [j35]Hiroto Saigo, Hisashi Kashima, Koji Tsuda:
Fast Iterative Mining Using Sparsity-Inducing Loss Functions. IEICE Trans. Inf. Syst. 96-D(8): 1766-1773 (2013) - [j34]Chuan Xiao, Jianbin Qin, Wei Wang, Yoshiharu Ishikawa, Koji Tsuda, Kunihiko Sadakane:
Efficient Error-tolerant Query Autocompletion. Proc. VLDB Endow. 6(6): 373-384 (2013) - [c43]Aika Terada, Koji Tsuda, Jun Sese:
Fast Westfall-Young permutation procedure for combinatorial regulation discovery. BIBM 2013: 153-158 - [c42]Shuhei Denzumi, Koji Tsuda, Hiroki Arimura, Shin-ichi Minato:
Compact Complete Inverted Files for Texts and Directed Acyclic Graphs Based on Sequence Binary Decision Diagrams . Stringology 2013: 157-167 - 2012
- [j33]Koji Tsuda:
Data Mining for Biologists. Int. J. Knowl. Discov. Bioinform. 3(4): 1-14 (2012) - [j32]Jun-Ichi Ito, Yasuo Tabei, Kana Shimizu, Koji Tsuda, Kentaro Tomii:
PoSSuM: a database of similar protein-ligand binding and putative pockets. Nucleic Acids Res. 40(Database-Issue): 541-548 (2012) - 2011
- [j31]Kana Shimizu, Koji Tsuda:
SlideSort: all pairs similarity search for short reads. Bioinform. 27(4): 464-470 (2011) - [j30]Elisabeth Georgii, Koji Tsuda, Bernhard Schölkopf:
Multi-way set enumeration in weight tensors. Mach. Learn. 82(2): 123-155 (2011) - [c41]Koji Tsuda, Shin-ichi Minato:
Second Workshop on Algorithms for Large-Scale Information Processing in Knowledge Discovery (ALSIP). JSAI-isAI Workshops 2011: 184-185 - [c40]Yasuo Tabei, Daisuke Okanohara, Shuichi Hirose, Koji Tsuda:
LGM: Mining Frequent Subgraphs from Linear Graphs. PAKDD (2) 2011: 26-37 - [c39]Yasuo Tabei, Koji Tsuda:
Kernel-based Similarity Search in Massive Graph Databases with Wavelet Trees. SDM 2011: 154-163 - [p4]Koji Tsuda:
Graph Classification Methods in Chemoinformatics. Handbook of Statistical Bioinformatics 2011: 335-351 - [p3]Hiroto Saigo, Koji Tsuda:
Matrix Decomposition-based Dimensionality Reduction on Graph Data. Graph Data Management 2011: 260-284 - [i3]Yasuo Tabei, Daisuke Okanohara, Shuichi Hirose, Koji Tsuda:
LGM: Mining Frequent Subgraphs from Linear Graphs. CoRR abs/1102.4480 (2011) - 2010
- [j29]Hiroto Saigo, Masahiro Hattori, Hisashi Kashima, Koji Tsuda:
Reaction graph kernels predict EC numbers of unknown enzymatic reactions in plant secondary metabolism. BMC Bioinform. 11(S-1): 31 (2010) - [j28]Hisashi Kashima, Satoshi Oyama, Yoshihiro Yamanishi, Koji Tsuda:
Cartesian Kernel: An Efficient Alternative to the Pairwise Kernel. IEICE Trans. Inf. Syst. 93-D(10): 2672-2679 (2010) - [c38]Yasuo Tabei, Takeaki Uno, Masashi Sugiyama, Koji Tsuda:
Single versus Multiple Sorting in All Pairs Similarity Search. ACML 2010: 145-160 - [p2]Koji Tsuda, Hiroto Saigo:
Graph Classification. Managing and Mining Graph Data 2010: 337-363
2000 – 2009
- 2009
- [j27]Sabine Dietmann, Elisabeth Georgii, Alexey V. Antonov, Koji Tsuda, Hans-Werner Mewes:
The DICS repository: module-assisted analysis of disease-related gene lists. Bioinform. 25(6): 830-831 (2009) - [j26]Elisabeth Georgii, Sabine Dietmann, Takeaki Uno, Philipp Pagel, Koji Tsuda:
Enumeration of condition-dependent dense modules in protein interaction networks. Bioinform. 25(7): 933-940 (2009) - [j25]Mitsunori Kayano, Ichigaku Takigawa, Motoki Shiga, Koji Tsuda, Hiroshi Mamitsuka:
Efficiently finding genome-wide three-way gene interactions from transcript- and genotype-data. Bioinform. 25(21): 2735-2743 (2009) - [j24]Hisashi Kashima, Yoshihiro Yamanishi, Tsuyoshi Kato, Masashi Sugiyama, Koji Tsuda:
Simultaneous inference of biological networks of multiple species from genome-wide data and evolutionary information: a semi-supervised approach. Bioinform. 25(22): 2962-2968 (2009) - [j23]Hyunjung Shin, Koji Tsuda, Bernhard Schölkopf:
Protein functional class prediction with a combined graph. Expert Syst. Appl. 36(2): 3284-3292 (2009) - [j22]Hiroto Saigo, Sebastian Nowozin, Tadashi Kadowaki, Taku Kudo, Koji Tsuda:
gBoost: a mathematical programming approach to graph classification and regression. Mach. Learn. 75(1): 69-89 (2009) - [c37]Elisabeth Georgii, Koji Tsuda, Bernhard Schölkopf:
Multi-way set enumeration in real-valued tensors. KDD Workshop on Data Mining using Matrices and Tensors 2009 - [c36]Yoshinobu Kawahara, Kiyohito Nagano, Koji Tsuda, Jeff A. Bilmes:
Submodularity Cuts and Applications. NIPS 2009: 916-924 - [c35]Hisashi Kashima, Satoshi Oyama, Yoshihiro Yamanishi, Koji Tsuda:
On Pairwise Kernels: An Efficient Alternative and Generalization Analysis. PAKDD 2009: 1030-1037 - [c34]Silvia Chiappa, Hiroto Saigo, Koji Tsuda:
A Bayesian Approach to Graphy Regression with Relevant Subgraph Selection. SDM 2009: 295-304 - [c33]Hisashi Kashima, Tsuyoshi Kato, Yoshihiro Yamanishi, Masashi Sugiyama, Koji Tsuda:
Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction. SDM 2009: 1100-1111 - [i2]Takeaki Uno, Masashi Sugiyama, Koji Tsuda:
Efficient Construction of Neighborhood Graphs by the Multiple Sorting Method. CoRR abs/0904.3151 (2009) - 2008
- [c32]Sebastian Nowozin, Koji Tsuda:
Frequent Subgraph Retrieval in Geometric Graph Databases. ICDM 2008: 953-958 - [c31]Hiroto Saigo, Koji Tsuda:
Iterative Subgraph Mining for Principal Component Analysis. ICDM 2008: 1007-1012 - [c30]Hiroto Saigo, Nicole Krämer, Koji Tsuda:
Partial least squares regression for graph mining. KDD 2008: 578-586 - [c29]Koji Tsuda, Kenichi Kurihara:
Graph Mining with Variational Dirichlet Process Mixture Models. SDM 2008: 432-442 - 2007
- [j21]Hiroto Saigo, Takeaki Uno, Koji Tsuda:
Mining complex genotypic features for predicting HIV-1 drug resistance. Bioinform. 23(18): 2455-2462 (2007) - [j20]Gal Chechik, Christina S. Leslie, William Stafford Noble, Gunnar Rätsch, Quaid Morris, Koji Tsuda:
NIPS workshop on New Problems and Methods in Computational Biology. BMC Bioinform. 8(S-10) (2007) - [j19]Elisabeth Georgii, Sabine Dietmann, Takeaki Uno, Philipp Pagel, Koji Tsuda:
Mining expression-dependent modules in the human interaction network. BMC Bioinform. 8(S-8) (2007) - [j18]Florian Steinke, Matthias W. Seeger, Koji Tsuda:
Experimental design for efficient identification of gene regulatory networks using sparse Bayesian models. BMC Syst. Biol. 1: 51 (2007) - [c28]Sebastian Nowozin, Koji Tsuda, Takeaki Uno, Taku Kudo, Gökhan H. Bakir:
Weighted Substructure Mining for Image Analysis. CVPR 2007 - [c27]Sebastian Nowozin, Gökhan H. Bakir, Koji Tsuda:
Discriminative Subsequence Mining for Action Classification. ICCV 2007: 1-8 - [c26]Koji Tsuda:
Entire regularization paths for graph data. ICML 2007: 919-926 - [c25]Sebastian Nowozin, Koji Tsuda, Takeaki Uno, Taku Kudo, Gökhan H. Bakir:
Weighted Substructure Mining for Image Analysis. MLG 2007 - [c24]Tsuyoshi Idé, Koji Tsuda:
Change-Point Detection using Krylov Subspace Learning. SDM 2007: 515-520 - [c23]Matthias W. Seeger, Florian Steinke, Koji Tsuda:
Bayesian Inference and Optimal Design in the Sparse Linear Model. AISTATS 2007: 444-451 - [e1]Paolo Frasconi, Kristian Kersting, Koji Tsuda:
Mining and Learning with Graphs, MLG 2007, Firence, Italy, August 1-3, 2007, Proceedings. 2007 [contents] - 2006
- [j17]Yasuo Tabei, Koji Tsuda, Taishin Kin, Kiyoshi Asai:
SCARNA: fast and accurate structural alignment of RNA sequences by matching fixed-length stem fragments. Bioinform. 22(14): 1723-1729 (2006) - [j16]Michiaki Hamada, Koji Tsuda, Taku Kudo, Taishin Kin, Kiyoshi Asai:
Mining frequent stem patterns from unaligned RNA sequences. Bioinform. 22(20): 2480-2487 (2006) - [j15]Tsuyoshi Kato, Yukio Murata, Koh Miura, Kiyoshi Asai, Paul Horton, Koji Tsuda, Wataru Fujibuchi:
Network-based de-noising improves prediction from microarray data. BMC Bioinform. 7(S-1) (2006) - [c22]Koji Tsuda, Taku Kudo:
Clustering graphs by weighted substructure mining. ICML 2006: 953-960 - [p1]Hyunjung Shin, Koji Tsuda:
Prediction of Protein Function from Networks. Semi-Supervised Learning 2006: 361-375 - 2005
- [j14]Tsuyoshi Kato, Koji Tsuda, Kiyoshi Asai:
Selective integration of multiple biological data for supervised network inference. Bioinform. 21(10): 2488-2495 (2005) - [j13]Koji Tsuda, Gunnar Rätsch, Manfred K. Warmuth:
Matrix Exponentiated Gradient Updates for On-line Learning and Bregman Projection. J. Mach. Learn. Res. 6: 995-1018 (2005) - [j12]Koji Tsuda, Gunnar Rätsch:
Image reconstruction by linear programming. IEEE Trans. Image Process. 14(6): 737-744 (2005) - [c21]Koji Tsuda, Hyunjung Shin, Bernhard Schölkopf:
Fast protein classification with multiple networks. ECCB/JBI 2005: 65 - [c20]Koji Tsuda:
Propagating distributions on a hypergraph by dual information regularization. ICML 2005: 920-927 - 2004
- [j11]Koji Tsuda, Shotaro Akaho, Motoaki Kawanabe, Klaus-Robert Müller:
Asymptotic Properties of the Fisher Kernel. Neural Comput. 16(1): 115-137 (2004) - [j10]Koji Tsuda, Shinsuke Uda, Taishin Kin, Kiyoshi Asai:
Minimizing the Cross Validation Error to Mix Kernel Matrices of Heterogeneous Biological Data. Neural Process. Lett. 19(1): 63-72 (2004) - [c19]Gökhan H. Bakir, Alexander Zien, Koji Tsuda:
Learning to Find Graph Pre-images. DAGM-Symposium 2004: 253-261 - [c18]Koji Tsuda, William Stafford Noble:
Learning kernels from biological networks by maximizing entropy. ISMB/ECCB (Supplement of Bioinformatics) 2004: 326-333 - [c17]Koji Tsuda, Gunnar Rätsch, Manfred K. Warmuth:
Matrix Exponential Gradient Updates for On-line Learning and Bregman Projection. NIPS 2004: 1425-1432 - [c16]Tsuyoshi Kato, Koji Tsuda, Kentaro Tomii, Kiyoshi Asai:
A New Variational Framework for Rigid-Body Alignment. SSPR/SPR 2004: 171-179 - 2003
- [j9]Koji Tsuda, Shotaro Akaho, Kiyoshi Asai:
The em Algorithm for Kernel Matrix Completion with Auxiliary Data. J. Mach. Learn. Res. 4: 67-81 (2003) - [c15]Hisashi Kashima, Koji Tsuda, Akihiro Inokuchi:
Marginalized Kernels Between Labeled Graphs. ICML 2003: 321-328 - [c14]Koji Tsuda, Gunnar Rätsch:
Image Reconstruction by Linear Programming. NIPS 2003: 57-64 - 2002
- [j8]Koji Tsuda, Motoaki Kawanabe, Gunnar Rätsch, Sören Sonnenburg, Klaus-Robert Müller:
A New Discriminative Kernel from Probabilistic Models. Neural Comput. 14(10): 2397-2414 (2002) - [j7]Koji Tsuda, Masashi Sugiyama, Klaus-Robert Müller:
Subspace information criterion for nonquadratic regularizers-Model selection for sparse regressors. IEEE Trans. Neural Networks 13(1): 70-80 (2002) - [c13]Masanori Arita, Koji Tsuda, Kiyoshi Asai:
Modeling splicing sites with pairwise correlations. ECCB 2002: 27-34 - [c12]Koji Tsuda, Motoaki Kawanabe:
The Leave-One-Out Kernel. ICANN 2002: 727-732 - [c11]