Hiroshi Mamitsuka Papers on DiSC'04 Mining Biologically Active Patterns in Metabolic Pathways using Microarray Expression Profiles Publications Note: Links lead to the DBLP on the Web. Hiroshi Mamitsuka Hiroshi Mamitsuka: Empirical Evaluation of Ensemble Feature Subset Selection Methods for Learning from a High-Dimensional Database in Drug Desig. BIBE 2003 : 253-257 Hiroshi Mamitsuka: Detecting Experimental Noises in Protein-Protein Interactions with Iterative Sampling and Model-Based Clustering. BIBE 2003 : 385-392 Hiroshi Mamitsuka: Efficient Mining from Heterogeneous Data Sets for Predicting Protein-Protein Interactions. DEXA Workshops 2003 : 32-36 Hiroshi Mamitsuka: Hierarchical Latent Knowledge Analysis for Co-occurrence Data. ICML 2003 : 504-511 Hiroshi Mamitsuka: Selective Sampling with a Hierarchical Latent Variable Model. IDA 2003 : 352-363 Atsuko Yamaguchi , Hiroshi Mamitsuka: Finding the Maximum Common Subgraph of a Partial k-Tree and a Graph with a Polynomially Bounded Number of Spanning Trees. ISAAC 2003 : 58-67 Hiroshi Mamitsuka: Efficient Unsupervised Mining from Noisy Data Sets: Application to Clustering Co-occurrence Data. SDM 2003 Hiroshi Mamitsuka: Iteratively Selecting Feature Subsets for Mining from High-Dimensional Databases. PKDD 2002 : 361-372 Hiroshi Mamitsuka, Naoki Abe : Efficient Data Mining by Active Learning. Progress in Discovery Science 2002 : 258-267 Hiroshi Mamitsuka, Naoki Abe : Efficient Mining from Large Databases by Query Learning. ICML 2000 : 575-582 Naoki Abe , Hiroshi Mamitsuka, Atsuyoshi Nakamura : Empirical Comparison of Competing Query Learning Methods. Discovery Science 1998 : 387-388 Naoki Abe , Hiroshi Mamitsuka: Query Learning Strategies Using Boosting and Bagging. ICML 1998 : 1-9 Hiroshi Mamitsuka: Supervised learning of hidden Markov models for sequence discrimination. RECOMB 1997 : 202-208 Naoki Abe , Hiroshi Mamitsuka: Predicting Protein Secondary Structure Using Stochastic Tree Grammars. Machine Learning 29 (2-3): 275-301 (1997) Hiroshi Mamitsuka: A Learning Method of Hidden Markov Models for Sequence Discrimination. Journal of Computational Biology 3 (3): 361-374 (1996) Hiroshi Mamitsuka, Kenji Yamanishi : alpha-Helix region prediction with stochastic rule learning. Computer Applications in the Biosciences 11 (4): 399-411 (1995) Hiroshi Mamitsuka: Representing inter-residue dependencies in protein sequences with probabilistic networks. Computer Applications in the Biosciences 11 (4): 413-422 (1995) Naoki Abe , Hiroshi Mamitsuka: A New Method for Predicting Protein Secondary Structures Based on Stochastic Tree Grammars. ICML 1994 : 3-11 Hiroshi Mamitsuka, Naoki Abe : Predicting Location and Structure Of beta-Sheet Regions Using Stochastic Tree Grammars. ISMB 1994 : 276-284 Hiroshi Mamitsuka, Kenji Yamanishi : Protein Secondary Structure Prediction Based on Stochastic-Rule Learning. ALT 1992 : 240-251 1 [ 2 ] [ 3 ] [ 7 ] [ 9 ] [ 10 ] [ 11 ] [ 12 ] 2 [ 10 ] 3 [ 15 ] 4 [ 1 ] [ 5 ] ©2004 Association for Computing Machinery