PRISM: A Language for Symbolic-Statistical Modeling. - Taisuke Sato; Yoshitaka Kameya (IJCAI, 1997)

Abstracting a Human's Decision Process by PRISM. - Yoshitaka Kameya; Taisuke Sato (Discovery Science, 1998)

A Graphical Method for Parameter Learning of Symbolic-Statistical Models. - Yoshitaka Kameya; Nobuhisa Ueda; Taisuke Sato (Discovery Science, 1999)

Efficient EM Learning with Tabulation for Parameterized Logic Programs. - Yoshitaka Kameya; Taisuke Sato (Computational Logic, 2000)

A Separate-and-Learn Approach to EM Learning of PCFGs. - Taisuke Sato; Shigeru Abe; Yoshitaka Kameya; Kiyoaki Shirai (NLPRS, 2001)

Parameter Learning of Logic Programs for Symbolic-Statistical Modeling. - Taisuke Sato; Yoshitaka Kameya (J. Artif. Intell. Res., 2001)

Statistical Abduction with Tabulation. - Taisuke Sato; Yoshitaka Kameya (Computational Logic: Logic Programming and Beyond, 2002)

Yet More Efficient EM Learning for Parameterized Logic Programs by Inter-Goal Sharing. - Yoshitaka Kameya; Taisuke Sato; Neng-Fa Zhou (ECAI, 2004)

Negation Elimination for Finite PCFGs. - Taisuke Sato; Yoshitaka Kameya (LOPSTR, 2004)

Learning through failure. - Taisuke Sato; Yoshitaka Kameya (Probabilistic, Logical and Relational Learning, 2005)

Generative Modeling with Failure in PRISM. - Taisuke Sato; Yoshitaka Kameya; Neng-Fa Zhou (IJCAI, 2005)

Variational Bayes via Propositionalization. - Taisuke Sato; Yoshitaka Kameya; Kenichi Kurihara (Probabilistic, Logical and Relational Learning - A Further Synthesis, 2007)

Discovering Concepts from Word Co-occurrences with a Relational Model. - Kenichi Kurihara; Yoshitaka Kameya; Taisuke Sato (Inf. Media Technol., 2007)

Accelerating genetic programming by frequent subtree mining. - Yoshitaka Kameya; Junichi Kumagai; Yoshiaki Kurata (GECCO, 2008)

New Advances in Logic-Based Probabilistic Modeling by PRISM. - Taisuke Sato; Yoshitaka Kameya (Probabilistic Inductive Logic Programming, 2008)

Variational Bayes via propositionalized probability computation in PRISM. - Taisuke Sato; Yoshitaka Kameya; Kenichi Kurihara (Ann. Math. Artif. Intell., 2008)

Evaluating Abductive Hypotheses using an EM Algorithm on BDDs. - Katsumi Inoue; Taisuke Sato; Masakazu Ishihata; Yoshitaka Kameya; Hidetomo Nabeshima (IJCAI, 2009)

Mode-Directed Tabling for Dynamic Programming, Machine Learning, and Constraint Solving. - Neng-Fa Zhou; Yoshitaka Kameya; Taisuke Sato (ICTAI (2), 2010)

An EM Algorithm on BDDs with Order Encoding for Logic-based Probabilistic Models. - Masakazu Ishihata; Yoshitaka Kameya; Taisuke Sato; Shin-ichi Minato (ACML, 2010)

CHR(PRISM)-based probabilistic logic learning. - Jon Sneyers; Wannes Meert; Joost Vennekens; Yoshitaka Kameya; Taisuke Sato (Theory Pract. Log. Program., 2010)

Kinetic Models and Qualitative Abstraction for Relational Learning in Systems Biology. - Gabriel Synnaeve; Katsumi Inoue; Andrei Doncescu; Hidetomo Nabeshima; Yoshitaka Kameya; Masakazu Ishihata; Taisuke Sato (BIOINFORMATICS, 2011)

Discretized Kinetic Models for Abductive Reasoning in Systems Biology. - Gabriel Synnaeve; Katsumi Inoue; Andrei Doncescu; Hidetomo Nabeshima; Yoshitaka Kameya; Masakazu Ishihata; Taisuke Sato (BIOSTEC (Selected Papers), 2011)

Pattern-based preservation of building blocks in genetic algorithms. - Yoshitaka Kameya; Chativit Prayoonsri (IEEE Congress on Evolutionary Computation, 2011)

Time Series Discretization via MDL-Based Histogram Density Estimation. - Yoshitaka Kameya (ICTAI, 2011)

Verbal Characterization of Probabilistic Clusters Using Minimal Discriminative Propositions. - Yoshitaka Kameya; Satoru Nakamura; Tatsuya Iwasaki; Taisuke Sato (ICTAI, 2011)

Variational Bayes Inference for Logic-Based Probabilistic Models on BDDs. - Masakazu Ishihata; Yoshitaka Kameya; Taisuke Sato (ILP, 2011)

RP-growth: Top-k Mining of Relevant Patterns with Minimum Support Raising. - Yoshitaka Kameya; Taisuke Sato (SDM, 2012)

Depth-First Traversal over a Mirrored Space for Non-redundant Discriminative Itemsets. - Yoshitaka Kameya; Hiroki Asaoka (DaWaK, 2013)

A Logic-based Approach to Generatively Defined Discriminative Modeling. - Taisuke Sato; Keiichi Kubota; Yoshitaka Kameya (CoRR, 2014)

Using WFSTs for Efficient EM Learning of Probabilistic CFGs and Their Extensions. - Yoshitaka Kameya; Takashi Mori; Taisuke Sato (Inf. Media Technol., 2014)

A Cloud Education Environment to Support Self-Learning at Home - Analysis of Self-Learning Styles from Log Data. - Tomoichi Takahashi; Kensaku Asahi; Hidekazu Suzuki; Mikiko Kawasumi; Yoshitaka Kameya (IIAI-AAI, 2015)

An Exhaustive Covering Approach to Parameter-Free Mining of Non-redundant Discriminative Itemsets. - Yoshitaka Kameya (DaWaK, 2016)

Bottom-Up Cell Suppression that Preserves the Missing-at-random Condition. - Yoshitaka Kameya; Kentaro Hayashi 003 (TrustBus, 2016)

Dynamic Re-ordering in Mining Top-k Productive Discriminative Patterns. - Yoshitaka Kameya; Ken'ya Ito (TAAI, 2017)

Contrastive Relevance Propagation for Interpreting Predictions by a Single-Shot Object Detector. - Hideomi Tsunakawa; Yoshitaka Kameya; Hanju Lee; Yosuke Shinya; Naoki Mitsumoto (IJCNN, 2019)

Associative Classification using Common Instances among Conflicting Discriminative Patterns. - Kentaro Maeda; Yoshitaka Kameya (TAAI, 2019)

Towards Efficient Discriminative Pattern Mining in Hybrid Domains. - Yoshitaka Kameya (CoRR, 2019)

Shared-Memory Parallelization of FP-growth with Dynamic Load Estimation and Balancing. - Kentaro Sakurai; Yoshitaka Kameya (IWCIA, 2021)

Understanding the Reason for Misclassification by Generating Counterfactual Images. - Muneaki Suzuki; Yoshitaka Kameya; Takuro Kutsuna; Naoki Mitsumoto (MVA, 2021)

Ante- and Post-Hoc Explanations for Prediction Models of Cisplatin-Induced Acute Kidney Injury: A Comparative Study. - Tatsuya Nishizawa; Shogo Hanabusa; Yoshitaka Kameya; Kazuo Takahashi; Naotake Tsuboi; Tomohiro Mizuno (ICMHI, 2023)

Kidney Cancer Detection from CT Images by Transformer-Based Classifiers. - Toru Tanaka; Takaki Fukazawa; Yoshitaka Kameya; Keiichi Yamada; Kazuhiro Hotta; Tomoichi Takahashi; Naoto Sassa; Yoshihisa Matsukawa; Shingo Iwano; Tokunori Yamamoto (IIAI-AAI, 2023)