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Note: Links lead to the DBLP on the Web. Naoki Abe Naoki Abe, Roni Khardon : Foreword. Theor. Comput. Sci. 313 (2): 173-174 (2004) Bianca Zadrozny , John Langford , Naoki Abe: Cost-Sensitive Learning by Cost-Proportionate Example Weighting. ICDM 2003 : 435- Naoki Abe, Edwin P. D. Pednault , Haixun Wang , Bianca Zadrozny , Wei Fan , Chidanand Apté : Empirical Comparison of Various Reinforcement Learning Strategies for Sequential Targeted Marketing. ICDM 2002 : 3-10 Edwin P. D. Pednault , Naoki Abe, Bianca Zadrozny : Sequential cost-sensitive decision making with reinforcement learning. KDD 2002 : 259-268 Hiroshi Mamitsuka , Naoki Abe: Efficient Data Mining by Active Learning. Progress in Discovery Science 2002 : 258-267 Atsuyoshi Nakamura , Naoki Abe: Online Learning of Binary and n-ary Relations over Clustered Domains. J. Comput. Syst. Sci. 65 (2): 224-256 (2002) Naoki Abe, Roni Khardon , Thomas Zeugmann : Algorithmic Learning Theory, 12th International Conference, ALT 2001, Washington, DC, USA, November 25-28, 2001, Proceedings Springer 2001 Naoki Abe, Roni Khardon , Thomas Zeugmann : Editors' Introduction. ALT 2001 : 1-8 Atsuyoshi Nakamura , Naoki Abe, Hiroshi Matoba , Katsuhiro Ochiai : Automatic recording agent for digital video server. ACM Multimedia 2000 : 57-66 Hiroshi Mamitsuka , Naoki Abe: Efficient Mining from Large Databases by Query Learning. ICML 2000 : 575-582 Naoki Abe, Tomonari Kamba : A Web marketing system with automatic pricing. Computer Networks 33 (1-6): 775-788 (2000) Jun-ichi Takeuchi , Naoki Abe, Shun-ichi Amari : The Lob-Pass Problem. J. Comput. Syst. Sci. 61 (3): 523-557 (2000) Naoki Abe, Atsuyoshi Nakamura : Learning to Optimally Schedule Internet Banner Advertisements. ICML 1999 : 12-21 Naoki Abe, Philip M. Long : Associative Reinforcement Learning using Linear Probabilistic Concepts. ICML 1999 : 3-11 Hang Li , Naoki Abe: Learning Dependencies between Case Frame Slots. Computational Linguistics 25 (2): 283-291 (1999) Marc Langheinrich , Atsuyoshi Nakamura , Naoki Abe, Tomonari Kamba , Yoshiyuki Koseki : Unintrusive Customization Techniques for Web Advertising. Computer Networks 31 (11-16): 1259-1272 (1999) Hang Li , Naoki Abe: Word Clustering and Disambiguation Based on Co-occurence Data. COLING-ACL 1998 : 749-755 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 Atsuyoshi Nakamura , Naoki Abe: Collaborative Filtering Using Weighted Majority Prediction Algorithms. ICML 1998 : 395-403 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) Hang Li , Naoki Abe: Generalizing Case Frames Using a Thesaurus and the MDL Principle. Computational Linguistics 24 (2): 217-244 (1998) Naoki Abe, Hiroshi Mamitsuka : Predicting Protein Secondary Structure Using Stochastic Tree Grammars. Machine Learning 29 (2-3): 275-301 (1997) Naoki Abe: Towards Realistic Theories of Learning. New Generation Comput. 15 (1): 3-25 (1997) Hang Li , Naoki Abe: Learning Dependencies between Case Frame Slots. COLING 1996 : 10-15 Hang Li , Naoki Abe: Clustering Words with the MDL Principle. COLING 1996 : 4-9 Naoki Abe, Hang Li : Learning Word Association Norms Using Tree Cut Pair Models. ICML 1996 : 3-11 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: Characterizing PAC-Learnability of Semilinear Sets Inf. Comput. 116 (1): 81-102 (1995) Atsuyoshi Nakamura , Naoki Abe: Exact Learning of Linear Combinations of Monotone Terms from Function Value Queries. Theor. Comput. Sci. 137 (1): 159-176 (1995) Naoki Abe: Towards Realistic Theories of Learning. AII/ALT 1994 : 187-209 Atsuyoshi Nakamura , Naoki Abe, Jun-ichi Takeuchi : Efficient Distribution-free Population Learning of Simple Concepts. AII/ALT 1994 : 500-515 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 Atsuyoshi Nakamura , Naoki Abe: Exact Learning of Linear Combinations of Monotone Terms from Function Value Queries. ALT 1993 : 300-313 Naoki Abe, Jun-ichi Takeuchi : The "lob-pass" Problem and an On-line Learning Model of Rational Choice. COLT 1993 : 422-428 Naoki Abe, Manfred K. Warmuth : On the Computational Complexity of Approximating Distributions by Probabilistic Automata. Machine Learning 9 : 205-260 (1992) Naoki Abe, Manfred K. Warmuth , Jun-ichi Takeuchi : Polynomial Learnability of Probabilistic Concepts with Respect to the Kullback-Leibler Divergence. COLT 1991 : 277-289 Naoki Abe: On the Sample Complexity of Various Learning Strategies in the Probabilistic PAC Learning Paradigms. Nonmonotonic and Inductive Logic 1991 : 89-106 Naoki Abe: Learning Commutative Deterministic Finite State Automata in Polynomial Time. New Generation Comput. 8 (4): 319- (1991) Naoki Abe: Learning Commutative Deterministic Finite State Automata in Polynomial Time. ALT 1990 : 223-235 Naoki Abe, Manfred K. Warmuth : On the Computational Complexity of Approximating Distributions by Probabilistic Automata. COLT 1990 : 52-66 Naoki Abe: Polynomial Learnability of Semilinear Sets. COLT 1989 : 25-40 Naoki Abe: Polynominal Learnability and Locality of Formal Grammars. ACL 1988 : 225-232 Naoki Abe: Feasible learnability of formal grammars and the theory of natural language acquisition. COLING 1988 : 1-6 1 [ 35 ] 2 [ 44 ] 3 [ 44 ] 4 [ 31 ] [ 36 ] 5 [ 39 ] [ 40 ] [ 46 ] 6 [ 31 ] 7 [ 45 ] 8 [ 31 ] 9 [ 18 ] [ 20 ] [ 21 ] [ 22 ] [ 25 ] [ 30 ] [ 32 ] 10 [ 33 ] 11 [ 12 ] [ 13 ] [ 24 ] [ 28 ] [ 29 ] [ 37 ] [ 42 ] 12 [ 38 ] 13 [ 11 ] [ 14 ] [ 16 ] [ 18 ] [ 19 ] [ 26 ] [ 27 ] [ 29 ] [ 31 ] [ 34 ] [ 38 ] [ 41 ] 14 [ 38 ] 15 [ 43 ] [ 44 ] 16 [ 8 ] [ 10 ] [ 14 ] [ 26 ] [ 35 ] 17 [ 44 ] 18 [ 4 ] [ 8 ] [ 9 ] 19 [ 43 ] [ 44 ] [ 45 ] 20 [ 39 ] [ 40 ]  ©2004 Association for Computing Machinery |
