Yoshitaka Kameya

Publication Activity (10 Years)

Years Active: 1997-2023
Publications (10 Years): 9

Top Topics

Top Venues

Publications

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)
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)
Muneaki Suzuki, Yoshitaka Kameya, Takuro Kutsuna, Naoki Mitsumoto
Understanding the Reason for Misclassification by Generating Counterfactual Images. MVA (2021)
Kentaro Maeda, Yoshitaka Kameya
Associative Classification using Common Instances among Conflicting Discriminative Patterns. TAAI (2019)
Hideomi Tsunakawa, Yoshitaka Kameya, Hanju Lee, Yosuke Shinya, Naoki Mitsumoto
Contrastive Relevance Propagation for Interpreting Predictions by a Single-Shot Object Detector. IJCNN (2019)
Yoshitaka Kameya
Towards Efficient Discriminative Pattern Mining in Hybrid Domains. CoRR (2019)
Yoshitaka Kameya, Ken'ya Ito
Dynamic Re-ordering in Mining Top-k Productive Discriminative Patterns. TAAI (2017)
Yoshitaka Kameya, Kentaro Hayashi
Bottom-Up Cell Suppression that Preserves the Missing-at-random Condition. TrustBus (2016)
Yoshitaka Kameya
An Exhaustive Covering Approach to Parameter-Free Mining of Non-redundant Discriminative Itemsets. DaWaK (2016)
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)
Taisuke Sato, Keiichi Kubota, Yoshitaka Kameya
A Logic-based Approach to Generatively Defined Discriminative Modeling. CoRR (2014)
Yoshitaka Kameya, Takashi Mori, Taisuke Sato
Using WFSTs for Efficient EM Learning of Probabilistic CFGs and Their Extensions. Inf. Media Technol. 9 (4) (2014)
Yoshitaka Kameya, Hiroki Asaoka
Depth-First Traversal over a Mirrored Space for Non-redundant Discriminative Itemsets. DaWaK (2013)
Yoshitaka Kameya, Taisuke Sato
RP-growth: Top-k Mining of Relevant Patterns with Minimum Support Raising. SDM (2012)
Kentaro Sakurai, Yoshitaka Kameya
Shared-Memory Parallelization of FP-growth with Dynamic Load Estimation and Balancing. IWCIA (2012)
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)
Yoshitaka Kameya, Chativit Prayoonsri
Pattern-based preservation of building blocks in genetic algorithms. IEEE Congress on Evolutionary Computation (2011)
Yoshitaka Kameya, Satoru Nakamura, Tatsuya Iwasaki, Taisuke Sato
Verbal Characterization of Probabilistic Clusters using Minimal Discriminative Propositions CoRR (2011)
Masakazu Ishihata, Yoshitaka Kameya, Taisuke Sato
Variational Bayes Inference for Logic-Based Probabilistic Models on BDDs. ILP (2011)
Yoshitaka Kameya, Taisuke Sato
Parameter Learning of Logic Programs for Symbolic-Statistical Modeling CoRR (2011)
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)
Yoshitaka Kameya
Time Series Discretization via MDL-Based Histogram Density Estimation. ICTAI (2011)
Yoshitaka Kameya, Satoru Nakamura, Tatsuya Iwasaki, Taisuke Sato
Verbal Characterization of Probabilistic Clusters Using Minimal Discriminative Propositions. ICTAI (2011)
Masakazu Ishihata, Yoshitaka Kameya, Taisuke Sato, Shin-ichi Minato
An EM Algorithm on BDDs with Order Encoding for Logic-based Probabilistic Models. ACML (2010)
Neng-Fa Zhou, Yoshitaka Kameya, Taisuke Sato
Mode-Directed Tabling for Dynamic Programming, Machine Learning, and Constraint Solving. ICTAI (2) (2010)
Jon Sneyers, Wannes Meert, Joost Vennekens, Yoshitaka Kameya, Taisuke Sato
CHR(PRISM)-based Probabilistic Logic Learning CoRR (2010)
Jon Sneyers, Wannes Meert, Joost Vennekens, Yoshitaka Kameya, Taisuke Sato
CHR(PRISM)-based probabilistic logic learning. Theory Pract. Log. Program. 10 (4-6) (2010)
Katsumi Inoue, Taisuke Sato, Masakazu Ishihata, Yoshitaka Kameya, Hidetomo Nabeshima
Evaluating Abductive Hypotheses using an EM Algorithm on BDDs. IJCAI (2009)
Yoshitaka Kameya, Junichi Kumagai, Yoshiaki Kurata
Accelerating genetic programming by frequent subtree mining. GECCO (2008)
Taisuke Sato, Yoshitaka Kameya, Kenichi Kurihara
Variational Bayes via propositionalized probability computation in PRISM. Ann. Math. Artif. Intell. 54 (1-3) (2008)
Taisuke Sato, Yoshitaka Kameya, Kenichi Kurihara
Variational Bayes via Propositionalization. Probabilistic, Logical and Relational Learning - A Further Synthesis (2007)
Kenichi Kurihara, Yoshitaka Kameya, Taisuke Sato
Discovering Concepts from Word Co-occurrences with a Relational Model. Inf. Media Technol. 2 (1) (2007)
Taisuke Sato, Yoshitaka Kameya
Learning through failure. Probabilistic, Logical and Relational Learning (2005)
Taisuke Sato, Yoshitaka Kameya, Neng-Fa Zhou
Generative Modeling with Failure in PRISM. IJCAI (2005)
Taisuke Sato, Yoshitaka Kameya
Negation Elimination for Finite PCFGs. LOPSTR (2004)
Yoshitaka Kameya, Taisuke Sato, Neng-Fa Zhou
Yet More Efficient EM Learning for Parameterized Logic Programs by Inter-Goal Sharing. ECAI (2004)
Taisuke Sato, Yoshitaka Kameya
Statistical Abduction with Tabulation. Computational Logic: Logic Programming and Beyond (2002)
Taisuke Sato, Shigeru Abe, Yoshitaka Kameya, Kiyoaki Shirai
A Separate-and-Learn Approach to EM Learning of PCFGs. NLPRS (2001)
Taisuke Sato, Yoshitaka Kameya
Parameter Learning of Logic Programs for Symbolic-Statistical Modeling. J. Artif. Intell. Res. 15 (2001)
Yoshitaka Kameya, Taisuke Sato
Efficient EM Learning with Tabulation for Parameterized Logic Programs. Computational Logic (2000)
Yoshitaka Kameya, Nobuhisa Ueda, Taisuke Sato
A Graphical Method for Parameter Learning of Symbolic-Statistical Models. Discovery Science (1999)
Yoshitaka Kameya, Taisuke Sato
Abstracting a Human's Decision Process by PRISM. Discovery Science (1998)
Taisuke Sato, Yoshitaka Kameya
PRISM: A Language for Symbolic-Statistical Modeling. IJCAI (1997)