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Taisuke Sato
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2020 – today
- 2023
- [j27]Taisuke Sato, Katsumi Inoue:
Differentiable learning of matricized DNFs and its application to Boolean networks. Mach. Learn. 112(8): 2821-2843 (2023) - [i15]Taisuke Sato, Akihiro Takemura, Katsumi Inoue:
Towards end-to-end ASP computation. CoRR abs/2306.06821 (2023) - 2021
- [j26]Chiaki Sakama, Katsumi Inoue, Taisuke Sato:
Logic programming in tensor spaces. Ann. Math. Artif. Intell. 89(12): 1133-1153 (2021) - [j25]Hien D. Nguyen, Chiaki Sakama, Taisuke Sato, Katsumi Inoue:
An efficient reasoning method on logic programming using partial evaluation in vector spaces. J. Log. Comput. 31(5): 1298-1316 (2021) - [j24]Takaki Kobayashi, Akiomi Ushida, Taisuke Sato:
Pseudo-Laminarization of Mixed Microbubble Water and Complex Fluids in Capillary Flows. Symmetry 13(7): 1141 (2021) - [c68]Taisuke Sato, Ryosuke Kojima:
Boolean Network Learning in Vector Spaces for Genome-wide Network Analysis. KR 2021: 560-569 - [i14]Taisuke Sato, Ryosuke Kojima:
MatSat: a matrix-based differentiable SAT solver. CoRR abs/2108.06481 (2021) - 2020
- [c67]Taisuke Sato, Chiaki Sakama, Katsumi Inoue:
From 3-valued Semantics to Supported Model Computation for Logic Programs in Vector Spaces. ICAART (2) 2020: 758-765
2010 – 2019
- 2019
- [c66]Taisuke Sato, Ryosuke Kojima:
Logical Inference as Cost Minimization in Vector Spaces. IJCAI 2019: 239-255 - [c65]Ryosuke Kojima, Taisuke Sato:
T-PRISM: A tensorized logic programming language for data modelling. NeSy@IJCAI 2019 - [i13]Ryosuke Kojima, Taisuke Sato:
A tensorized logic programming language for large-scale data. CoRR abs/1901.08548 (2019) - 2018
- [j23]Ryosuke Kojima, Taisuke Sato:
Learning to rank in PRISM. Int. J. Approx. Reason. 93: 561-577 (2018) - [c64]Taisuke Sato, Katsumi Inoue, Chiaki Sakama:
Abducing Relations in Continuous Spaces. IJCAI 2018: 1956-1962 - [c63]Hien D. Nguyen, Chiaki Sakama, Taisuke Sato, Katsumi Inoue:
Computing Logic Programming Semantics in Linear Algebra. MIWAI 2018: 32-48 - [i12]Chiaki Sakama, Hien D. Nguyen, Taisuke Sato, Katsumi Inoue:
Partial Evaluation of Logic Programs in Vector Spaces. CoRR abs/1811.11435 (2018) - 2017
- [j22]Taisuke Sato:
A linear algebraic approach to datalog evaluation. Theory Pract. Log. Program. 17(3): 244-265 (2017) - [c62]Taisuke Sato:
Embedding Tarskian Semantics in Vector Spaces. AAAI Workshops 2017 - [c61]Taisuke Sato:
Learning probability by comparison. AMBN 2017: 5 - [c60]Chiaki Sakama, Katsumi Inoue, Taisuke Sato:
Linear Algebraic Characterization of Logic Programs. KSEM 2017: 520-533 - [i11]Taisuke Sato:
Embedding Tarskian Semantics in Vector Spaces. CoRR abs/1703.03193 (2017) - 2016
- [j21]Nicolas Schwind, Morgan Magnin, Katsumi Inoue, Tenda Okimoto, Taisuke Sato, Kazuhiro Minami, Hiroshi Maruyama:
Formalization of resilience for constraint-based dynamic systems. J. Reliab. Intell. Environ. 2(1): 17-35 (2016) - [i10]Taisuke Sato:
A Linear Algebraic Approach to Datalog Evaluation. CoRR abs/1608.00139 (2016) - 2015
- [j20]James Cussens, Luc De Raedt, Angelika Kimmig, Taisuke Sato:
Introduction to the special issue on probability, logic and learning. Theory Pract. Log. Program. 15(2): 145-146 (2015) - [j19]Taisuke Sato, Keiichi Kubota:
Viterbi training in PRISM. Theory Pract. Log. Program. 15(2): 147-168 (2015) - [c59]Yuki Sato, Taisuke Sato, Jin Mitsugi:
Boxcan: A platform realizing fast retrieval of parent-child tree of containers and inner objects over EPCIS events. APCC 2015: 692-696 - 2014
- [j18]Yoshitaka Kameya, Takashi Mori, Taisuke Sato:
Using WFSTs for Efficient EM Learning of Probabilistic CFGs and Their Extensions. Inf. Media Technol. 9(4): 517-556 (2014) - [j17]Taisuke Sato, Philipp J. Meyer:
Infinite probability computation by cyclic explanation graphs. Theory Pract. Log. Program. 14(6): 909-937 (2014) - [c58]Ryosuke Kojima, Taisuke Sato:
Goal and Plan Recognition via Parse Trees Using Prefix and Infix Probability Computation. ILP 2014: 76-91 - [i9]Taisuke Sato, Keiichi Kubota, Yoshitaka Kameya:
A Logic-based Approach to Generatively Defined Discriminative Modeling. CoRR abs/1410.3935 (2014) - 2013
- [i8]Taisuke Sato, Keiichi Kubota:
Viterbi training in PRISM. CoRR abs/1303.5659 (2013) - [i7]Taisuke Sato, Philipp J. Meyer:
Infinite probability computation by cyclic explanation graphs. CoRR abs/1309.0339 (2013) - 2012
- [c57]Taisuke Sato, Philipp J. Meyer:
Tabling for infinite probability computation. ICLP (Technical Communications) 2012: 348-358 - [c56]Yoshitaka Kameya, Taisuke Sato:
RP-growth: Top-k Mining of Relevant Patterns with Minimum Support Raising. SDM 2012: 816-827 - 2011
- [j16]Taisuke Sato, Masakazu Ishihata, Katsumi Inoue:
Constraint-based probabilistic modeling for statistical abduction. Mach. Learn. 83(2): 241-264 (2011) - [c55]Masakazu Ishihata, Taisuke Sato, Shin-ichi Minato:
Compiling Bayesian Networks for Parameter Learning Based on Shared BDDs. Australasian Conference on Artificial Intelligence 2011: 203-212 - [c54]Gabriel Synnaeve, Katsumi Inoue, Andrei Doncescu, Hidetomo Nabeshima, Yoshitaka Kameya, Masakazu Ishihata, Taisuke Sato:
Kinetic Models and Qualitative Abstraction for Relational Learning in Systems Biology. BIOINFORMATICS 2011: 47-54 - [c53]Gabriel Synnaeve, Katsumi Inoue, Andrei Doncescu, Hidetomo Nabeshima, Yoshitaka Kameya, Masakazu Ishihata, Taisuke Sato:
Discretized Kinetic Models for Abductive Reasoning in Systems Biology. BIOSTEC (Selected Papers) 2011: 141-154 - [c52]Yoshitaka Kameya, Satoru Nakamura, Tatsuya Iwasaki, Taisuke Sato:
Verbal Characterization of Probabilistic Clusters Using Minimal Discriminative Propositions. ICTAI 2011: 873-875 - [c51]Taisuke Sato:
A General MCMC Method for Bayesian Inference in Logic-Based Probabilistic Modeling. IJCAI 2011: 1472-1477 - [c50]Masakazu Ishihata, Yoshitaka Kameya, Taisuke Sato:
Variational Bayes Inference for Logic-Based Probabilistic Models on BDDs. ILP 2011: 189-203 - [c49]Masakazu Ishihata, Taisuke Sato:
Bayesian inference for statistical abduction using Markov chain Monte Carlo. ACML 2011: 81-96 - [i6]Yoshitaka Kameya, Taisuke Sato:
Parameter Learning of Logic Programs for Symbolic-Statistical Modeling. CoRR abs/1106.1797 (2011) - [i5]Yoshitaka Kameya, Satoru Nakamura, Tatsuya Iwasaki, Taisuke Sato:
Verbal Characterization of Probabilistic Clusters using Minimal Discriminative Propositions. CoRR abs/1108.5002 (2011) - 2010
- [j15]Jon Sneyers, Wannes Meert, Joost Vennekens, Yoshitaka Kameya, Taisuke Sato:
CHR(PRISM)-based probabilistic logic learning. Theory Pract. Log. Program. 10(4-6): 433-447 (2010) - [c48]Neng-Fa Zhou, Yoshitaka Kameya, Taisuke Sato:
Mode-Directed Tabling for Dynamic Programming, Machine Learning, and Constraint Solving. ICTAI (2) 2010: 213-218 - [c47]Masakazu Ishihata, Yoshitaka Kameya, Taisuke Sato, Shin-ichi Minato:
An EM Algorithm on BDDs with Order Encoding for Logic-based Probabilistic Models. ACML 2010: 161-176 - [i4]Jon Sneyers, Wannes Meert, Joost Vennekens, Yoshitaka Kameya, Taisuke Sato:
CHR(PRISM)-based Probabilistic Logic Learning. CoRR abs/1007.3858 (2010)
2000 – 2009
- 2009
- [c46]Taisuke Sato:
Generative Modeling by PRISM. ICLP 2009: 24-35 - [c45]Katsumi Inoue, Taisuke Sato, Masakazu Ishihata, Yoshitaka Kameya, Hidetomo Nabeshima:
Evaluating Abductive Hypotheses using an EM Algorithm on BDDs. IJCAI 2009: 810-815 - [c44]Taisuke Sato:
Statistical Learning of Probabilistic BDDs. SAGA 2009: 15 - [c43]Taisuke Sato:
Logic-Based Probabilistic Modeling. WoLLIC 2009: 61-71 - 2008
- [j14]Taisuke Sato, Yoshitaka Kameya, Kenichi Kurihara:
Variational Bayes via propositionalized probability computation in PRISM. Ann. Math. Artif. Intell. 54(1-3): 135-158 (2008) - [j13]Taisuke Sato:
A glimpse of symbolic-statistical modeling by PRISM. J. Intell. Inf. Syst. 31(2): 161-176 (2008) - [j12]Neng-Fa Zhou, Taisuke Sato, Yi-Dong Shen:
Linear tabling strategies and optimizations. Theory Pract. Log. Program. 8(1): 81-109 (2008) - [c42]Kenichi Kurihara, Tsuyoshi Murata, Taisuke Sato:
Identification of MCMC Samples for Clustering. LKR 2008: 27-37 - [p1]Taisuke Sato, Yoshitaka Kameya:
New Advances in Logic-Based Probabilistic Modeling by PRISM. Probabilistic Inductive Logic Programming 2008: 118-155 - 2007
- [j11]Kenichi Kurihara, Yoshitaka Kameya, Taisuke Sato:
Discovering Concepts from Word Co-occurrences with a Relational Model. Inf. Media Technol. 2(1): 317-325 (2007) - [j10]Humikazu Mitomi, Fuyuki Fujiwara, Masanobu Yamamoto, Taisuke Sato:
Bayesian classification of a human custom based on stochastic context-free grammar. Syst. Comput. Jpn. 38(9): 52-62 (2007) - [c41]Shin-ichi Minato, Ken Satoh, Taisuke Sato:
Compiling Bayesian Networks by Symbolic Probability Calculation Based on Zero-Suppressed BDDs. IJCAI 2007: 2550-2555 - [c40]Taisuke Sato:
Inside-Outside Probability Computation for Belief Propagation. IJCAI 2007: 2605-2610 - [i3]Taisuke Sato, Yoshitaka Kameya, Kenichi Kurihara:
Variational Bayes via Propositionalization. Probabilistic, Logical and Relational Learning - A Further Synthesis 2007 - [i2]Neng-Fa Zhou, Taisuke Sato, Yi-Dong Shen:
Linear Tabling Strategies and Optimizations. CoRR abs/0705.3468 (2007) - 2006
- [c39]Masanobu Yamamoto, Humikazu Mitomi, Fuyuki Fujiwara, Taisuke Sato:
Bayesian Classification of Task-Oriented Actions Based on Stochastic Context-Free Grammar. FGR 2006: 317-323 - [c38]Kenichi Kurihara, Taisuke Sato:
Variational Bayesian Grammar Induction for Natural Language. ICGI 2006: 84-96 - 2005
- [c37]Taisuke Sato, Yoshitaka Kameya, Neng-Fa Zhou:
Generative Modeling with Failure in PRISM. IJCAI 2005: 847-852 - [i1]Taisuke Sato, Yoshitaka Kameya:
Learning through failure. Probabilistic, Logical and Relational Learning 2005 - 2004
- [c36]Yoshitaka Kameya, Taisuke Sato, Neng-Fa Zhou:
Yet More Efficient EM Learning for Parameterized Logic Programs by Inter-Goal Sharing. ECAI 2004: 490-494 - [c35]Taisuke Sato, Yoshitaka Kameya:
Negation Elimination for Finite PCFGs. LOPSTR 2004: 117-132 - [c34]Neng-Fa Zhou, Yi-Dong Shen, Taisuke Sato:
Semi-naive evaluation in linear tabling. PPDP 2004: 90-97 - 2003
- [c33]Neng-Fa Zhou, Taisuke Sato:
Efficient fixpoint computation in linear tabling. PPDP 2003: 275-283 - 2002
- [c32]Taisuke Sato, Yoshitaka Kameya:
Statistical Abduction with Tabulation. Computational Logic: Logic Programming and Beyond 2002: 567-587 - [c31]Taisuke Sato:
EM Learning for Symbolic-Statistical Models in Statistical Abduction. Progress in Discovery Science 2002: 189-200 - 2001
- [j9]Taisuke Sato, Yoshitaka Kameya:
Parameter Learning of Logic Programs for Symbolic-Statistical Modeling. J. Artif. Intell. Res. 15: 391-454 (2001) - [j8]Masayuki Numao, Taisuke Sato:
Tutorial Series on Web-computing - Preface. New Gener. Comput. 19(2): 193 (2001) - [c30]Nobuhisa Ueda, Taisuke Sato:
Simplified Training Algorithms for Hierarchical Hidden Markov Models. Discovery Science 2001: 401-415 - [c29]Taisuke Sato:
Parameterized Logic Programs where Computing Meets Learning. FLOPS 2001: 40-60 - [c28]Taisuke Sato, Shigeru Abe, Yoshitaka Kameya, Kiyoaki Shirai:
A Separate-and-Learn Approach to EM Learning of PCFGs. NLPRS 2001: 255-262 - 2000
- [c27]Yoshitaka Kameya, Taisuke Sato:
Efficient EM Learning with Tabulation for Parameterized Logic Programs. Computational Logic 2000: 269-284
1990 – 1999
- 1999
- [c26]Yoshitaka Kameya, Nobuhisa Ueda, Taisuke Sato:
A Graphical Method for Parameter Learning of Symbolic-Statistical Models. Discovery Science 1999: 264-276 - [c25]Taisuke Sato, Satoshi Funada:
Reactive Logic Programming by Reinforcement Learning. ICLP 1999: 617 - [e2]Aart Middeldorp, Taisuke Sato:
Functional and Logic Programming, 4th Fuji International Symposium, FLOPS'99, Tsukuba, Japan, November 11-13, 1999, Proceedings. Lecture Notes in Computer Science 1722, Springer 1999, ISBN 3-540-66677-X [contents] - 1998
- [c24]Yoshitaka Kameya, Taisuke Sato:
Abstracting a Human's Decision Process by PRISM. Discovery Science 1998: 389-390 - 1997
- [c23]Taisuke Sato, Yoshitaka Kameya:
PRISM: A Language for Symbolic-Statistical Modeling. IJCAI 1997: 1330-1339 - 1995
- [j7]Hitoshi Iba, Hugo de Garis, Taisuke Sato:
A Numerical Approach to Genetic Programming for System Identification. Evol. Comput. 3(4): 417-452 (1995) - [c22]Hitoshi Iba, Taisuke Sato, Hugo de Garis:
Temporal Data Processing Using Genetic Programming. ICGA 1995: 279-286 - [c21]Taisuke Sato:
A Statistical Learning Method for Logic Programs with Distribution Semantics. ICLP 1995: 715-729 - 1994
- [c20]Hitoshi Iba, Taisuke Sato, Hugo de Garis:
System Identification Approach to Genetic Programming. International Conference on Evolutionary Computation 1994: 401-406 - [c19]Hitoshi Iba, Hugo de Garis, Taisuke Sato:
Genetic Programming with Local Hill-Climbing. PPSN 1994: 302-311 - 1993
- [c18]Taisuke Sato, Sumitaka Akiba:
Inductive Resolution. ALT 1993: 101-110 - [c17]Hitoshi Iba, Takio Kurita, Hugo de Garis, Taisuke Sato:
System Identification using Structured Genetic Algorithms. ICGA 1993: 279-286 - [c16]Hitoshi Iba, Tetsuya Higuchi, Hugo de Garis, Taisuke Sato:
Evolutionary Learning Strategy using Bug-Based Search. IJCAI 1993: 960-966 - [c15]Sumitaka Akiba, Taisuke Sato:
Learning Logic Programs and Regularities from Examples by Inductive Inference. Machine Intelligence 14 1993: 191-212 - 1992
- [j6]Taisuke Sato:
Equivalence-Preserving First-Order Unfold/Fold Transformation Systems. Theor. Comput. Sci. 105(1): 57-84 (1992) - [c14]Taisuke Sato:
Meta-Programming through a Truth Predicate. JICSLP 1992: 526-540 - [c13]Hitoshi Iba, Sumitaka Akiba, Tetsuya Higuchi, Taisuke Sato:
BUGS: A Bug-Based Search Strategy using Genetic Algorithms. PPSN 1992: 167- - 1991
- [c12]Taisuke Sato:
Full First Order Logic Programming and Truth Predicate. ICLP 1991: 948 - [c11]Taisuke Sato, Fumio Motoyoshi:
A Complete Top-Down Interpreter for First Order Programs. ISLP 1991: 35-53 - [e1]Setsuo Arikawa, Akira Maruoka, Taisuke Sato:
Algorithmic Learning Theory, 2nd International Workshop, ALT '91, Tokyo, Japan, October 23-25, 1991, Proceedings. Ohmsha 1991 [contents] - 1990
- [j5]Taisuke Sato:
Completed Logic Programs and their Consistency. J. Log. Program. 9(1): 33-44 (1990) - [c10]Taisuke Sato:
An Equivalence Preserving First Order Unfold/fold Transformation System. ALP 1990: 173-188
1980 – 1989
- 1989
- [j4]Taisuke Sato, Hisao Tamaki:
First Order Compiler: A Deterministic Logic Program Synthesis Algorithm. J. Symb. Comput. 8(6): 605-627 (1989) - [j3]Taisuke Sato, Hisao Tamaki:
Existential Continuation. New Gener. Comput. 6(4): 421-438 (1989) - 1986
- [c9]Hisao Tamaki, Taisuke Sato:
OLD Resolution with Tabulation. ICLP 1986: 84-98 - 1984
- [j2]Taisuke Sato, Hisao Tamaki:
Enumeration of Success Patterns in Logic Programs. Theor. Comput. Sci. 34: 227-240 (1984) - [c8]Taisuke Sato, Hisao Tamaki:
Transformational Logic Program Synthesis. FGCS 1984: 195-201 - [c7]Hisao Tamaki, Taisuke Sato:
Unfold/Fold Transformation of Logic Programs. ICLP 1984: 127-138 - 1983
- [j1]Hisao Tamaki, Taisuke Sato:
Program Transformation Through Meta-shifting. New Gener. Comput. 1(1): 93-98 (1983) - [c6]Taisuke Sato, Hisao Tamaki:
Enumeration of Success Patterns in Logic Programs. ICALP 1983: 640-652 - 1982
- [c5]Taisuke Sato:
Negation and Semantics of Prolog Programs. ICLP 1982: 169-174 - [c4]Taisuke Sato:
An Algorithm for Intelligent Backtracking. RIMS Symposium on Software Science and Engineering 1982: 88-98 - 1980
- [c3]Taisuke Sato:
SGS: A System For Mechanical Generation Of Japanese Sentences. COLING 1980: 21-28
1970 – 1979
- 1979
- [c2]Hozumi Tanaka, Taisuke Sato, Fumio Motoyoshi:
Predictive Control Parser: Extended LINGOL. IJCAI 1979: 868-870 - [c1]Toshio Yokoi, Shooichi Yokoyama, Taisuke Sato, Fumio Motoyoshi, Kazuhiro Fuchi:
SYSP: A New Programming Language for the Next Generation. IJCAI 1979: 998-1000
Coauthor Index
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