Yoshitaka Kameya

44 papers A* 2A 3B 10C 3Misc 1Journal 10Unranked 14

Year	Rank	Type	Title / Venue / Authors
2023	—	`conf`	Ante- and Post-Hoc Explanations for Prediction Models of Cisplatin-Induced Acute Kidney Injury: A Comparative Study. ICMHI Tatsuya Nishizawa, Shogo Hanabusa, Yoshitaka Kameya, Kazuo Takahashi, Naotake Tsuboi, Tomohiro Mizuno
2023	—	`conf`	Kidney Cancer Detection from CT Images by Transformer-Based Classifiers. IIAI-AAI Toru Tanaka, Takaki Fukazawa, Yoshitaka Kameya, Keiichi Yamada, Kazuhiro Hotta, Tomoichi Takahashi, Naoto Sassa, Yoshihisa Matsukawa, Shingo Iwano, Tokunori Yamamoto
2021	C	`conf`	Shared-Memory Parallelization of FP-growth with Dynamic Load Estimation and Balancing. IWCIA Kentaro Sakurai, Yoshitaka Kameya
2021	Misc	`conf`	Understanding the Reason for Misclassification by Generating Counterfactual Images. MVA Muneaki Suzuki, Yoshitaka Kameya, Takuro Kutsuna, Naoki Mitsumoto
2019	—	`conf`	Associative Classification using Common Instances among Conflicting Discriminative Patterns. TAAI Kentaro Maeda, Yoshitaka Kameya
2019	B	`conf`	Contrastive Relevance Propagation for Interpreting Predictions by a Single-Shot Object Detector. IJCNN Hideomi Tsunakawa, Yoshitaka Kameya, Hanju Lee, Yosuke Shinya, Naoki Mitsumoto
2019	J	`jnl`	Towards Efficient Discriminative Pattern Mining in Hybrid Domains. CoRR Yoshitaka Kameya
2017	—	`conf`	Dynamic Re-ordering in Mining Top-k Productive Discriminative Patterns. TAAI Yoshitaka Kameya, Ken'ya Ito
2016	B	`conf`	An Exhaustive Covering Approach to Parameter-Free Mining of Non-redundant Discriminative Itemsets. DaWaK Yoshitaka Kameya
2016	B	`conf`	Bottom-Up Cell Suppression that Preserves the Missing-at-random Condition. TrustBus Yoshitaka Kameya, Kentaro Hayashi
2015	—	`conf`	A Cloud Education Environment to Support Self-Learning at Home - Analysis of Self-Learning Styles from Log Data. IIAI-AAI Tomoichi Takahashi, Kensaku Asahi, Hidekazu Suzuki, Mikiko Kawasumi, Yoshitaka Kameya
2014	J	`jnl`	A Logic-based Approach to Generatively Defined Discriminative Modeling. CoRR Taisuke Sato, Keiichi Kubota, Yoshitaka Kameya
2014	J	`jnl`	Using WFSTs for Efficient EM Learning of Probabilistic CFGs and Their Extensions. Inf. Media Technol. Yoshitaka Kameya, Takashi Mori, Taisuke Sato
2013	B	`conf`	Depth-First Traversal over a Mirrored Space for Non-redundant Discriminative Itemsets. DaWaK Yoshitaka Kameya, Hiroki Asaoka
2012	A	`conf`	RP-growth: Top-k Mining of Relevant Patterns with Minimum Support Raising. SDM Yoshitaka Kameya, Taisuke Sato
2011	—	`conf`	Discretized Kinetic Models for Abductive Reasoning in Systems Biology. BIOSTEC (Selected Papers) Gabriel Synnaeve, Katsumi Inoue, Andrei Doncescu, Hidetomo Nabeshima, Yoshitaka Kameya, Masakazu Ishihata, Taisuke Sato
2011	—	`conf`	Kinetic Models and Qualitative Abstraction for Relational Learning in Systems Biology. BIOINFORMATICS Gabriel Synnaeve, Katsumi Inoue, Andrei Doncescu, Hidetomo Nabeshima, Yoshitaka Kameya, Masakazu Ishihata, Taisuke Sato
2011	J	`jnl`	Parameter Learning of Logic Programs for Symbolic-Statistical Modeling CoRR Yoshitaka Kameya, Taisuke Sato
2011	B	`conf`	Pattern-based preservation of building blocks in genetic algorithms. IEEE Congress on Evolutionary Computation Yoshitaka Kameya, Chativit Prayoonsri
2011	B	`conf`	Time Series Discretization via MDL-Based Histogram Density Estimation. ICTAI Yoshitaka Kameya
2011	B	`conf`	Variational Bayes Inference for Logic-Based Probabilistic Models on BDDs. ILP Masakazu Ishihata, Yoshitaka Kameya, Taisuke Sato
2011	B	`conf`	Verbal Characterization of Probabilistic Clusters Using Minimal Discriminative Propositions. ICTAI Yoshitaka Kameya, Satoru Nakamura, Tatsuya Iwasaki, Taisuke Sato
2011	J	`jnl`	Verbal Characterization of Probabilistic Clusters using Minimal Discriminative Propositions CoRR Yoshitaka Kameya, Satoru Nakamura, Tatsuya Iwasaki, Taisuke Sato
2010	C	`conf`	An EM Algorithm on BDDs with Order Encoding for Logic-based Probabilistic Models. ACML Masakazu Ishihata, Yoshitaka Kameya, Taisuke Sato, Shin-ichi Minato
2010	J	`jnl`	CHR(PRISM)-based Probabilistic Logic Learning CoRR Jon Sneyers, Wannes Meert, Joost Vennekens, Yoshitaka Kameya, Taisuke Sato
2010	J	`jnl`	CHR(PRISM)-based probabilistic logic learning. Theory Pract. Log. Program. Jon Sneyers, Wannes Meert, Joost Vennekens, Yoshitaka Kameya, Taisuke Sato
2010	—	`conf`	Mode-Directed Tabling for Dynamic Programming, Machine Learning, and Constraint Solving. ICTAI (2) Neng-Fa Zhou, Yoshitaka Kameya, Taisuke Sato
2009	A*	`conf`	Evaluating Abductive Hypotheses using an EM Algorithm on BDDs. IJCAI Katsumi Inoue, Taisuke Sato, Masakazu Ishihata, Yoshitaka Kameya, Hidetomo Nabeshima
2008	A	`conf`	Accelerating genetic programming by frequent subtree mining. GECCO Yoshitaka Kameya, Junichi Kumagai, Yoshiaki Kurata
2008	—	`ch.`	New Advances in Logic-Based Probabilistic Modeling by PRISM. Probabilistic Inductive Logic Programming Taisuke Sato, Yoshitaka Kameya
2008	J	`jnl`	Variational Bayes via propositionalized probability computation in PRISM. Ann. Math. Artif. Intell. Taisuke Sato, Yoshitaka Kameya, Kenichi Kurihara
2007	J	`jnl`	Discovering Concepts from Word Co-occurrences with a Relational Model. Inf. Media Technol. Kenichi Kurihara, Yoshitaka Kameya, Taisuke Sato
2007	—	`conf`	Variational Bayes via Propositionalization. Probabilistic, Logical and Relational Learning - A Further Synthesis Taisuke Sato, Yoshitaka Kameya, Kenichi Kurihara
2005	A*	`conf`	Generative Modeling with Failure in PRISM. IJCAI Taisuke Sato, Yoshitaka Kameya, Neng-Fa Zhou
2005	—	`conf`	Learning through failure. Probabilistic, Logical and Relational Learning Taisuke Sato, Yoshitaka Kameya
2004	C	`conf`	Negation Elimination for Finite PCFGs. LOPSTR Taisuke Sato, Yoshitaka Kameya
2004	A	`conf`	Yet More Efficient EM Learning for Parameterized Logic Programs by Inter-Goal Sharing. ECAI Yoshitaka Kameya, Taisuke Sato, Neng-Fa Zhou
2002	—	`conf`	Statistical Abduction with Tabulation. Computational Logic: Logic Programming and Beyond Taisuke Sato, Yoshitaka Kameya
2001	—	`conf`	A Separate-and-Learn Approach to EM Learning of PCFGs. NLPRS Taisuke Sato, Shigeru Abe, Yoshitaka Kameya, Kiyoaki Shirai
2001	J	`jnl`	Parameter Learning of Logic Programs for Symbolic-Statistical Modeling. J. Artif. Intell. Res. Taisuke Sato, Yoshitaka Kameya
2000	—	`conf`	Efficient EM Learning with Tabulation for Parameterized Logic Programs. Computational Logic Yoshitaka Kameya, Taisuke Sato
1999	B	`conf`	A Graphical Method for Parameter Learning of Symbolic-Statistical Models. Discovery Science Yoshitaka Kameya, Nobuhisa Ueda, Taisuke Sato
1998	B	`conf`	Abstracting a Human's Decision Process by PRISM. Discovery Science Yoshitaka Kameya, Taisuke Sato
1997	—	`conf`	PRISM: A Language for Symbolic-Statistical Modeling. IJCAI Taisuke Sato, Yoshitaka Kameya