Atsuyoshi Nakamura

Atsuyoshi Nakamura, Tomoya Saito, Ichigaku Takigawa, Mineichi Kudo, Hiroshi Mamitsuka: Fast algorithms for finding a minimum repetition representation of strings and trees. Discrete Applied Mathematics 161(10-11): 1556-1575 (2013)

Koji Tabata, Atsuyoshi Nakamura, Mineichi Kudo: Fast Approximation Algorithm for the 1-Median Problem. Discovery Science 2012: 169-183

Takashi Saso, Kojiro Kobayashi, Atsuyoshi Nakamura: On the possible patterns of inputs for block sorting in the Burrows-Wheeler transformation. Inf. Process. Lett. 111(12): 595-599 (2011)

Tetsuji Takahashi, Mineichi Kudo, Atsuyoshi Nakamura: Construction of convex hull classifiers in high dimensions. Pattern Recognition Letters 32(16): 2224-2230 (2011)

Hiroyuki Hanada, Atsuyoshi Nakamura, Mineichi Kudo: A practical comparison of edit distance approximation algorithms. GrC 2011: 231-236

Koji Ouchi, Atsuyoshi Nakamura, Mineichi Kudo: Efficient construction and usefulness of hyper-rectangle greedy covers. GrC 2011: 533-538

Atsuyoshi Nakamura, Mineichi Kudo: Packing Alignment: Alignment for Sequences of Various Length Events. PAKDD (2) 2011: 234-245

Taishi Uchiya, Atsuyoshi Nakamura, Mineichi Kudo: Algorithms for Adversarial Bandit Problems with Multiple Plays. ALT 2010: 375-389

Atsuyoshi Nakamura, Tomoya Saito, Ichigaku Takigawa, Hiroshi Mamitsuka, Mineichi Kudo: Algorithms for Finding a Minimum Repetition Representation of a String. SPIRE 2010: 185-190

Ichigaku Takigawa, Mineichi Kudo, Atsuyoshi Nakamura: Convex sets as prototypes for classifying patterns. Eng. Appl. of AI 22(1): 101-108 (2009)

Tetsuji Takahashi, Mineichi Kudo, Atsuyoshi Nakamura: Classifier Selection in a Family of Polyhedron Classifiers. CIARP 2009: 441-448

Satoshi Shirai, Mineichi Kudo, Atsuyoshi Nakamura: Comparison of Bagging and Boosting Algorithms on Sample and Feature Weighting. MCS 2009: 22-31

Yohji Shidara, Mineichi Kudo, Atsuyoshi Nakamura: Classification Based on Consistent Itemset Rules. Trans. MLDM 1(1): 17-30 (2008)

Atsuyoshi Nakamura, Mineichi Kudo: What Sperner Family Concept Class is Easy to Be Enumerated? ICDM 2008: 482-491

Mineichi Kudo, Atsuyoshi Nakamura, Ichigaku Takigawa: Classification by reflective convex hulls. ICPR 2008: 1-4

Yohji Shidara, Mineichi Kudo, Atsuyoshi Nakamura: Classification by bagged consistent itemset rules. ICPR 2008: 1-4

Satoshi Shirai, Mineichi Kudo, Atsuyoshi Nakamura: Bagging, Random Subspace Method and Biding. SSPR/SPR 2008: 801-810

Hisashi Tosaka, Atsuyoshi Nakamura, Mineichi Kudo: Mining Subtrees with Frequent Occurrence of Similar Subtrees. Discovery Science 2007: 286-290

Yohji Shidara, Atsuyoshi Nakamura, Mineichi Kudo: CCIC: Consistent Common Itemsets Classifier. MLDM 2007: 490-498

Atsuyoshi Nakamura: Learning-Related Complexity of Linear Ranking Functions. ALT 2006: 378-392

Atsuyoshi Nakamura, Naoki Abe: Improvements to the Linear Programming Based Scheduling of Web Advertisements. Electronic Commerce Research 5(1): 75-98 (2005)

Atsuyoshi Nakamura: An efficient query learning algorithm for ordered binary decision diagrams. Inf. Comput. 201(2): 178-198 (2005)

Atsuyoshi Nakamura, Michael Schmitt, Niels Schmitt, Hans-Ulrich Simon: Inner Product Spaces for Bayesian Networks. Journal of Machine Learning Research 6: 1383-1403 (2005)

Mineichi Kudo, Atsuyoshi Nakamura: Specific-Purpose Web Searches on the Basis of Structure and Contents. Federation over the Web 2005: 79-96

Hidehiko Ino, Mineichi Kudo, Atsuyoshi Nakamura: A Comparative Study of Algorithms for Finding Web Communities. ICDE Workshops 2005: 1257

Hiroyuki Hasegawa, Mineichi Kudo, Atsuyoshi Nakamura: Empirical Study on Usefulness of Algorithm SACwRApper for Reputation Extraction from the WWW. KES (4) 2005: 668-674

Ichigaku Takigawa, Mineichi Kudo, Atsuyoshi Nakamura: The Convex Subclass Method: Combinatorial Classifier Based on a Family of Convex Sets. MLDM 2005: 90-99

Atsuyoshi Nakamura, Mineichi Kudo: Mining Frequent Trees with Node-Inclusion Constraints. PAKDD 2005: 850-860

Hidehiko Ino, Mineichi Kudo, Atsuyoshi Nakamura: Partitioning of Web graphs by community topology. WWW 2005: 661-669

Yohji Shidara, Mineichi Kudo, Atsuyoshi Nakamura: Extraction of Generalized Rules with Automated Attribute Abstraction. Foundations of Data Mining and knowledge Discovery 2005: 161-170

Atsuyoshi Nakamura, Michael Schmitt, Niels Schmitt, Hans-Ulrich Simon: Bayesian Networks and Inner Product Spaces. COLT 2004: 518-533

Ichigaku Takigawa, Mineichi Kudo, Atsuyoshi Nakamura, Jun Toyama: On the Minimum l₁-Norm Signal Recovery in Underdetermined Source Separation. ICA 2004: 193-200

Atsuyoshi Nakamura, Mineichi Kudo, Akira Tanaka, Kazuhiko Tanabe: Collaborative Filtering Using Projective Restoration Operators. Discovery Science 2003: 393-401

Atsuyoshi Nakamura, Mineichi Kudo, Akira Tanaka: Collaborative Filtering Using Restoration Operators. PKDD 2003: 339-349

Atsuyoshi Nakamura, Naoki Abe: Online Learning of Binary and n-ary Relations over Clustered Domains. J. Comput. Syst. Sci. 65(2): 224-256 (2002)

Atsuyoshi Nakamura: Improvements in practical aspects of optimally scheduling web advertising. WWW 2002: 536-541

Atsuyoshi Nakamura: Query learning of bounded-width OBDDs. Theor. Comput. Sci. 241(1-2): 83-114 (2000)

Atsuyoshi Nakamura, Naoki Abe, Hiroshi Matoba, Katsuhiro Ochiai: Automatic recording agent for digital video server. ACM Multimedia 2000: 57-66

Marc Langheinrich, Atsuyoshi Nakamura, Naoki Abe, Tomonari Kamba, Yoshiyuki Koseki: Unintrusive Customization Techniques for Web Advertising. Computer Networks 31(11-16): 1259-1272 (1999)

Atsuyoshi Nakamura: Learning Specialist Decision Lists. COLT 1999: 215-225

Naoki Abe, Atsuyoshi Nakamura: Learning to Optimally Schedule Internet Banner Advertisements. ICML 1999: 12-21

Atsuyoshi Nakamura, Jun-ichi Takeuchi, Naoki Abe: Efficient Distribution-Free Population Learning of Simple Concepts. Ann. Math. Artif. Intell. 23(1-2): 53-82 (1998)

Naoki Abe, Hiroshi Mamitsuka, Atsuyoshi Nakamura: Empirical Comparison of Competing Query Learning Methods. Discovery Science 1998: 387-388

Atsuyoshi Nakamura, Naoki Abe: Collaborative Filtering Using Weighted Majority Prediction Algorithms. ICML 1998: 395-403

Atsuyoshi Nakamura: An Efficient Exact Learning Algorithm for Ordered Binary Decision Diagrams. ALT 1997: 307-322

Atsuyoshi Nakamura: Query Learning of Bounded-Width OBDDs. ALT 1996: 37-50

Atsuyoshi Nakamura, Naoki Abe: Exact Learning of Linear Combinations of Monotone Terms from Function Value Queries. Theor. Comput. Sci. 137(1): 159-176 (1995)

Atsuyoshi Nakamura, Shinji Miura: Learning Sparse Linear Combinations of Basis Functions over a Finite Domain. ALT 1995: 138-150

Atsuyoshi Nakamura, Naoki Abe: On-line Learning of Binary and n-ary Relations over Multi-dimensional Clusters. COLT 1995: 214-221

Naoki Abe, Hang Li, Atsuyoshi Nakamura: On-line Learning of Binary Lexical Relations Using Two-dimensional Weighted Majority Algorithms. ICML 1995: 3-11

Naoki Abe, Hang Li, Atsuyoshi Nakamura: On-line Learning of Binary Lexical Relations Using Two-dimensional Weighted Majority Algorithms. CoRR abs/cmp-lg/9507010 (1995)

Atsuyoshi Nakamura, Naoki Abe, Jun-ichi Takeuchi: Efficient Distribution-free Population Learning of Simple Concepts. AII/ALT 1994: 500-515

Atsuyoshi Nakamura, Naoki Abe: Exact Learning of Linear Combinations of Monotone Terms from Function Value Queries. ALT 1993: 300-313