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ORCIDYoshitaka Kameya
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- affiliation: Meijo University, Japan
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2020 – today
- 2023
[c31]Tatsuya Nishizawa
, Shogo Hanabusa, Yoshitaka Kameya, Kazuo Takahashi, Naotake Tsuboi, Tomohiro Mizuno:
Ante- and Post-Hoc Explanations for Prediction Models of Cisplatin-Induced Acute Kidney Injury: A Comparative Study. ICMHI 2023: 66-71- [c30]Toru Tanaka, Takaki Fukazawa, Yoshitaka Kameya, Keiichi Yamada, Kazuhiro Hotta, Tomoichi Takahashi, Naoto Sassa, Yoshihisa Matsukawa, Shingo Iwano, Tokunori Yamamoto:
Kidney Cancer Detection from CT Images by Transformer-Based Classifiers. IIAI-AAI 2023: 456-461 - 2021
- [c29]Kentaro Sakurai, Yoshitaka Kameya:
Shared-Memory Parallelization of FP-growth with Dynamic Load Estimation and Balancing. IWCIA 2021: 1-6 - [c28]Muneaki Suzuki, Yoshitaka Kameya, Takuro Kutsuna, Naoki Mitsumoto:
Understanding the Reason for Misclassification by Generating Counterfactual Images. MVA 2021: 1-5
2010 – 2019
- 2019
- [c27]Hideomi Tsunakawa, Yoshitaka Kameya, Hanju Lee, Yosuke Shinya, Naoki Mitsumoto:
Contrastive Relevance Propagation for Interpreting Predictions by a Single-Shot Object Detector. IJCNN 2019: 1-9 - [c26]Kentaro Maeda, Yoshitaka Kameya:
Associative Classification using Common Instances among Conflicting Discriminative Patterns. TAAI 2019: 1-6 - [i7]Yoshitaka Kameya:
Towards Efficient Discriminative Pattern Mining in Hybrid Domains. CoRR abs/1908.06801 (2019) - 2017
- [c25]Yoshitaka Kameya, Ken'ya Ito:
Dynamic Re-ordering in Mining Top-k Productive Discriminative Patterns. TAAI 2017: 172-177 - 2016
- [c24]Yoshitaka Kameya:
An Exhaustive Covering Approach to Parameter-Free Mining of Non-redundant Discriminative Itemsets. DaWaK 2016: 143-159 - [c23]Yoshitaka Kameya, Kentaro Hayashi:
Bottom-Up Cell Suppression that Preserves the Missing-at-random Condition. TrustBus 2016: 65-78 - 2015
- [c22]Tomoichi Takahashi, Kensaku Asahi, Hidekazu Suzuki, Mikiko Kawasumi, Yoshitaka Kameya:
A Cloud Education Environment to Support Self-Learning at Home - Analysis of Self-Learning Styles from Log Data. IIAI-AAI 2015: 437-440 - 2014
- [j5]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) - [i6]Taisuke Sato, Keiichi Kubota, Yoshitaka Kameya:
A Logic-based Approach to Generatively Defined Discriminative Modeling. CoRR abs/1410.3935 (2014) - 2013
- [c21]Yoshitaka Kameya, Hiroki Asaoka:
Depth-First Traversal over a Mirrored Space for Non-redundant Discriminative Itemsets. DaWaK 2013: 196-208 - 2012
- [c20]Yoshitaka Kameya, Taisuke Sato:
RP-growth: Top-k Mining of Relevant Patterns with Minimum Support Raising. SDM 2012: 816-827 - 2011
- [c19]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 - [c18]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 - [c17]Yoshitaka Kameya, Chativit Prayoonsri:
Pattern-based preservation of building blocks in genetic algorithms. IEEE Congress on Evolutionary Computation 2011: 2578-2585 - [c16]Yoshitaka Kameya:
Time Series Discretization via MDL-Based Histogram Density Estimation. ICTAI 2011: 732-739 - [c15]Yoshitaka Kameya, Satoru Nakamura, Tatsuya Iwasaki, Taisuke Sato:
Verbal Characterization of Probabilistic Clusters Using Minimal Discriminative Propositions. ICTAI 2011: 873-875 - [c14]Masakazu Ishihata, Yoshitaka Kameya, Taisuke Sato:
Variational Bayes Inference for Logic-Based Probabilistic Models on BDDs. ILP 2011: 189-203 - [i5]Yoshitaka Kameya, Taisuke Sato:
Parameter Learning of Logic Programs for Symbolic-Statistical Modeling. CoRR abs/1106.1797 (2011) - [i4]Yoshitaka Kameya, Satoru Nakamura, Tatsuya Iwasaki, Taisuke Sato:
Verbal Characterization of Probabilistic Clusters using Minimal Discriminative Propositions. CoRR abs/1108.5002 (2011) - 2010
- [j4]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) - [c13]Neng-Fa Zhou, Yoshitaka Kameya, Taisuke Sato:
Mode-Directed Tabling for Dynamic Programming, Machine Learning, and Constraint Solving. ICTAI (2) 2010: 213-218 - [c12]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 - [i3]Jon Sneyers, Wannes Meert, Joost Vennekens, Yoshitaka Kameya, Taisuke Sato:
CHR(PRISM)-based Probabilistic Logic Learning. CoRR abs/1007.3858 (2010)
2000 – 2009
- 2009
- [c11]Katsumi Inoue, Taisuke Sato, Masakazu Ishihata, Yoshitaka Kameya, Hidetomo Nabeshima:
Evaluating Abductive Hypotheses using an EM Algorithm on BDDs. IJCAI 2009: 810-815 - 2008
- [j3]Taisuke Sato, Yoshitaka Kameya, Kenichi Kurihara:
Variational Bayes via propositionalized probability computation in PRISM. Ann. Math. Artif. Intell. 54(1-3): 135-158 (2008) - [c10]Yoshitaka Kameya, Junichi Kumagai, Yoshiaki Kurata:
Accelerating genetic programming by frequent subtree mining. GECCO 2008: 1203-1210 - [p1]Taisuke Sato, Yoshitaka Kameya:
New Advances in Logic-Based Probabilistic Modeling by PRISM. Probabilistic Inductive Logic Programming 2008: 118-155 - 2007
- [j2]Kenichi Kurihara, Yoshitaka Kameya, Taisuke Sato:
Discovering Concepts from Word Co-occurrences with a Relational Model. Inf. Media Technol. 2(1): 317-325 (2007) - [i2]Taisuke Sato, Yoshitaka Kameya, Kenichi Kurihara:
Variational Bayes via Propositionalization. Probabilistic, Logical and Relational Learning - A Further Synthesis 2007 - 2005
- [c9]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
- [c8]Yoshitaka Kameya, Taisuke Sato, Neng-Fa Zhou:
Yet More Efficient EM Learning for Parameterized Logic Programs by Inter-Goal Sharing. ECAI 2004: 490-494 - [c7]Taisuke Sato, Yoshitaka Kameya:
Negation Elimination for Finite PCFGs. LOPSTR 2004: 117-132 - 2002
- [c6]Taisuke Sato, Yoshitaka Kameya:
Statistical Abduction with Tabulation. Computational Logic: Logic Programming and Beyond 2002: 567-587 - 2001
- [j1]Taisuke Sato, Yoshitaka Kameya:
Parameter Learning of Logic Programs for Symbolic-Statistical Modeling. J. Artif. Intell. Res. 15: 391-454 (2001) - [c5]Taisuke Sato, Shigeru Abe, Yoshitaka Kameya, Kiyoaki Shirai:
A Separate-and-Learn Approach to EM Learning of PCFGs. NLPRS 2001: 255-262 - 2000
- [c4]Yoshitaka Kameya, Taisuke Sato:
Efficient EM Learning with Tabulation for Parameterized Logic Programs. Computational Logic 2000: 269-284
1990 – 1999
- 1999
- [c3]Yoshitaka Kameya, Nobuhisa Ueda, Taisuke Sato:
A Graphical Method for Parameter Learning of Symbolic-Statistical Models. Discovery Science 1999: 264-276 - 1998
- [c2]Yoshitaka Kameya, Taisuke Sato:
Abstracting a Human's Decision Process by PRISM. Discovery Science 1998: 389-390 - 1997
- [c1]Taisuke Sato, Yoshitaka Kameya:
PRISM: A Language for Symbolic-Statistical Modeling. IJCAI 1997: 1330-1339
Coauthor Index
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