亀谷由隆 (Kameya, Yoshitaka)

名城大学理工学部情報工学科 准教授

発表文献（査読付き）2015年以前

• Takahashi, T., Asahi, K., Suzuki, H., Kawasumi, M. and Kameya, Y.: A cloud education environment to support self-learning at home — Analysis of self-learning styles from log data. Proceedings of the 2015 IIAI 4th International Conference on Advanced Applied Informatics (IIAI-AAI-2015), pp. 437–440, 2015. [paper] (IEEE Xplore)
• Kameya, Y., Mori, T. and Sato, T.: Using WFSTs for efficient EM learning of probabilistic CFGs and their extensions. Journal of Natural Language Processing, Vol. 21, No. 4, pp. 619–658, 2014（言語処理学会20周年記念企画で行われた2001年論文の翻訳）. [paper] (J-STAGE)
• Kameya, Y. and Asaoka, H.: Depth-first traversal over a mirrored space for non-redundant discriminative itemsets. Proceedings of the 15th International Conference on Data Warehousing and Knowledge Discovery (DaWaK-2013), pp. 196–208, 2013. [paper] (Springer) [paper] (Self-archive) [slides]
• Kameya, Y. and Sato, T.: RP-growth: Top-k mining of relevant patterns with minimum support raising. Proceedings of the 2012 SIAM International Conference on Data Mining (SDM-2012), pp. 816–827, 2012. [paper] (SIAM) [poster]
• Ishihata, M., Kameya, Y. and Sato, T.: Variational Bayes inference for logic-based probabilistic models on BDDs. Proceedings of the 21st International Conference on Inductive Logic Programming (ILP-2011), pp. 189–203, 2011. [paper] (Springer)
• Kameya, Y.: Time series discretization via MDL-based histogram density estimation. Proceedings of the 23rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI-2011), pp. 732–739, 2011. [paper] (IEEE Xplore) [paper] (Self-archive) [slides]
• Kameya, Y., Nakamura, S., Iwasaki, T. and Sato, T.: Verbal characterization of probabilistic clusters using minimal discriminative propositions. Proceedings of the 23rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI-2011), pp. 873–875, 2011. [paper] (Short version, IEEE Xplore) [paper] (Short version, Self-archive) [paper] (Full version, ArXiv) [poster]
• Kameya, Y. and Prayoonsri, C.: Pattern-based preservation of building blocks in genetic algorithms. Proceedings of the 2011 IEEE Congress on Evolutionary Computation (CEC-2011), pp. 2578–2585, 2011. [paper] (IEEE Xplore) [paper] (Self-archive) [poster]
• Kameya, Y., Nakamura, S., Iwasaki, T. and Sato, T.: Characterizing probabilistic clusters by minimal discriminative propositions. Extended abstract at the 7th Workshop on Learning with Logics and Logics for Learning (LLLL-2011), 2011.
• Synnaeve, G., Inoue, K., Doncescu, A., Nabeshima, H., Kameya, Y., Ishihata, M. and Sato, T.: Kinetic models and qualitative abstraction for relational learning in systems biology. Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS-2011), 2011.
• Ishihata M., Kameya, Y., Sato, T. and Minato, S.: An EM algorithm on BDDs with order encoding for logic-based probabilistic models. Proceedings of the 2nd Asian Conference on Machine Learning (ACML-2010), pp. 161–176, 2010.
• Kameya, Y., Synnaeve, G., Doncescu, A., Inoue, K. and Sato, T.: A Bayesian hybrid approach to unsupervised time series discretization. Proceedings of the 2010 International Conference on Technologies and Applications of Artificial Intelligence (TAAI-2010), pp. 342–349, 2010.
• Zhou, N.-F., Kameya, Y. and Sato, T.: Mode-directed tabling for dynamic programming, machine learning, and constraint solving. Proceedings of the 22nd International Conference on Tools with Artificial Intelligence (ICTAI-2010), Vol. 2, pp. 213–218, 2010.
• 石畠正和, 亀谷由隆, 佐藤泰介, 湊真一: BDD上の命題化計算に基づくEMアルゴリズム. 人工知能学会論文誌, Vol. 25, No. 3, pp. 475–484, 2010.
• Sneyers, J., Meert, W., Vennekens, J., Kameya, Y. and Sato, T.: CHR(PRISM)-based probabilistic logic learning. Theory and Practice of Logic Programming, Vol. 10, No. 4–6, pp. 433–447, 2010.
• Inoue, K., Sato, T., Ishihata, M., Kameya, Y. and Nabeshima, H.: Evaluating abductive hypotheses using an EM algorithm on BDDs. Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI-2009), pp. 810–815, 2009.
• Sato, T., Kameya, Y., Kurihara, K.: Variational Bayes via propositionalized probability computation in PRISM. Annals of Mathematics and Artificial Intelligence, Vol. 54, No. 1–3, pp. 135–158, 2009.
• Kameya, Y., Kumagai, J. and Kurata, Y.: Accelerating genetic programming by frequent subtree mining. Proceedings of the 2008 Genetic and Evolutionary Computation Conference (GECCO-2008), pp. 1203–1210, 2008.
• Sato, T. and Kameya, Y.: New advances in logic-based probabilistic modeling by PRISM. In Probabilistic Inductive Logic Programming, LNCS 4911, Springer, pp. 118–155, 2008.
• 亀谷由隆, 佐藤泰介, 周能法, 泉祐介, 岩崎達也: PRISM: 確率モデリングのための論理プログラミング処理系, コンピュータソフトウェア, Vol. 24, No. 4, pp. 2-22, 2007.
• 熊谷潤一, 小島康夫, 高重聡一, 亀谷由隆, 佐藤泰介: 頻出部分木発見手法を用いた遺伝的プログラミングの交通信号制御問題への適用, 人工知能学会論文誌, Vol. 22, No. 2, pp. 127–139, 2007.
• Kurihara, K., Kameya, Y. and Sato, T.: Discovering concepts from word co-occurrences with a relational model. Transactions of the Japanese Society for Artificial Intelligence, Vol. 22, No. 2, pp. 218–226, 2007.
• Izumi, Y., Kameya, Y. and Sato, T.: Parallel EM learning for symbolic-statistical models. Proceedings of the International Workshop on Data-Mining and Statistical Science (DMSS-2006), pp. 133–140, 2006.
• Sato,T. and Kameya, Y.: Negation elimination for finite PCFGs. Proceedings of the International Symposium on Logic-based Program Synthesis and Transformation 2004 (LOPSTR-04), later selectively published as Logic-based Program Synthesis and Transformation, Springer LNCS 3573, S. Etalle (Ed.), pp. 117–132, 2005.
• Sato, T., Kameya, Y. and Zhou, N.-F.: Generative modeling with failure in PRISM. Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI-2005), pp. 847–852, 2005.
• Kameya, Y., Sato, T. and Zhou, N.-F.: Yet more efficient EM learning for parameterized logic programs by inter-goal sharing. Proceedings of the 16th European Conference on Artificial Intelligence (ECAI-2004), pp. 490-494, 2004.
• 栗原賢一，亀谷由隆，佐藤泰介， 構文森を用いた実コーパスからの大規模な確率自由文脈文法の高速学習法， 人工知能学会論文誌，Vol. 19，No. 5，pp. 360–367，2004．
• Sato, T. and Kameya, Y.: Statistical abduction with tabulation. Computational Logic: Logic Programming and Beyond, Kakas, A. and Sadri, F. (eds), pp. 567–587, LNAI Vol. 2408, Springer, 2002.
• Sato, T. and Kameya, Y.: Parameter learning of logic programs for symbolic-statistical modeling. Journal of Artificial Intelligence Research (JAIR), Vol. 15, pp. 391–454, 2001.
• Sato, T., Abe, S., Kameya, Y., and Shirai, K.: A separate-and-learn approach to EM learning of PCFGs. Proceedings of the 6th Natural Language Processing Pacific Rim Symposium (NLPRS-2001), pp. 255–262, 2001.
• 亀谷由隆, 森高志, 佐藤泰介: WFST に基づく確率文脈自由文法およびその拡張文法の高速 EM 学習, 自然言語処理 Vol. 8 No. 1, pp. 49-84, 2001.
• 上田展久，亀谷由隆，佐藤泰介， 括弧付けなしの文に対する確率文脈自由文法の効率的訓練法, 電子情報通信学会論文誌, Vol. J83-D-I, No. 11，pp. 1178–1186, November, 2000．
• Kameya, Y. and Sato, T.: Efficient EM learning with tabulation for parameterized logic programs. Proceedings of the 1st International Conference on Computational Logic (CL-2000), LNAI Vol. 1861, pp. 269-294, 2000.
• Kameya, Y., Ueda, N., and Sato, T.: A graphical method for parameter learning of symbolic-statistical models. Proceedings of the 2nd International Conference on Discovery Science (DS-99), LNAI Vol. 1721, pp. 264 - 276, 1999.
• Ueda, N., Kameya, Y., and Sato, T.: A parameter updating of stochastic context-free grammars in linear time on the number of productions. In Proceedings of the 1st IMC workshop, 1999.
• Kameya, Y. and Sato, T.: Abstracting human's decision process by PRISM. Proceedings of the 1st International Conference on Discovery Science (DS-98), pp. 389-390, 1998.
• Sato, T. and Kameya, Y.: PRISM: A symbolic-statistical modeling language. Proceedings of the 15th International Joint Conference on Artificial Intelligence (IJCAI-97), pp. 1330–1335, 1997.

発表文献（査読なし：解説記事，研究会発表，テクニカルレポート等）2015年以前

• 牧野剛, 渡邉悠太, 佐藤成利, 校條卓, 亀谷由隆: 楽曲コメント文を利用した視覚的な音楽推薦システム, 2015年電子情報通信学会総合大会予稿集, 2015.
• 高橋和志, 亀谷由隆: FP-Growth 法に基づく平均超過パターンの発見, 2015年電子情報通信学会総合大会予稿集, 2015.
• 森本拓也, 小酒井智貴, 亀谷由隆: 掲示板ログを利用した話題の連想を行う雑談プログラム, 2015年電子情報通信学会総合大会予稿集, 2015.
• 吉田章人, 亀谷由隆: 尤度フィルタリングによるBOAの収束速度の向上, 2015年電子情報通信学会総合大会予稿集, 2015.
• 小酒井翼, 菊池祐輔, 亀谷由隆: ナンバークロスワードパズルにおける難易度の定量化, 2015年電子情報通信学会総合大会予稿集, 2015.
• Sato, T., Kubota, K. and Kameya, Y.: Logic-based Approach to Generatively Defined Discriminative Modeling, arXiv:1410.3935, October, 2014 (Previously presented at ILP-2013).
• 佐藤靖浩, 亀谷由隆: 回帰手法に基づくレシピ文からの調理時間の推定, 2014年電子情報通信学会総合大会予稿集, 2014.
• 小島諒介，亀谷由隆，佐藤泰介: Naive Bayesモデルを用いた効率的なクラスタラベリング手法. 人工知能学会第83回人工知能基本問題研究会 (SIG-FPAI) 予稿集, SIG-FPAI-B203, pp. 19–24, 2013.
• 亀谷由隆, 佐藤泰介: 最小サポート上昇法に基づく上位k関連パターン発見, データ指向構成マイニングとシミュレーション研究会 （人工知能学会創立25周年記念合同研究会）予稿集, SIG-DOCMAS-B101-4, 2011．
• 亀谷由隆: 識別パターンを利用した遺伝的アルゴリズムの部分解保護に向けて, 第5回進化計算シンポジウム予稿集, 2011.
• Kameya, Y., Nakamura, S., Iwasaki, T. and Sato, T.: Verbal Characterization of Probabilistic Clusters using Minimal Discriminative Propositions, arXiv:1108.5002, August, 2011.
• 石畠正和, 亀谷由隆, 佐藤泰介: 命題論理に基づく確率モデルのためのベイズ推定, 第25回人工知能学会全国大会予稿集，2011．
• 亀谷由隆: 論理に基づく確率モデリングのこれまで，これから. 第4回情報論的学習理論と機械学習 (IBISML) 研究会, 招待講演, 2011.
• 亀谷由隆, Chativit Prayoonsri: パターンに基づく遺伝的アルゴリズムの部分解保護. 人工知能学会第6回進化計算フロンティア研究会 (SIG-ECF) 予稿集, 2011.
• 石畠正和, 亀谷由隆, 佐藤泰介, 湊真一: 否定枝を含む shared BDD 上で動作する EM アルゴリズム. 人工知能学会第9回データマイニングと統計数理研究会 (SIG-DMSM) 予稿集, SIG-DMSM-A803, pp. 11-19, 2009.
• Ishihata, M., Kameya, Y., Sato, T. and Minato, S.: Propositionalizing the EM algorithm by BDDs. Late breaking papers at the 18th International Conference on Inductive Logic Programming (ILP-2008), 2008.
• 石畠正和, 亀谷由隆, 佐藤泰介, 湊真一: BDD 上の命題化確率計算に基づくEMアルゴリズム, 人工知能学会第70回人工知能基本問題研究会(SIG-FPAI)予稿集, SIG-FPAI-A801, pp. 15–22, 2008.
• Ishihata, M., Kameya, Y., Sato, T. and Minato, S.: Propositionalizing the EM algorithm by BDDs, Technical Report TR08-0004, Dept. of Computer Science, Tokyo Institute of Technology, June, 2008.
• 倉田芳明, 亀谷由隆, 佐藤泰介: 頻出部分木発見に基づく遺伝的プログラミング手法のベンチマーク評価, 第21回人工知能学会全国大会予稿集，2007．
• 佐藤泰介, 亀谷由隆: グラフィカルモデルにおける論理的アプローチ, 人工知能学会誌, Vol. 22, No. 3, pp. 306–319, 2007.
• Kurihara, K., Kameya, Y. and Sato, T.: A frequency-based stochastic blockmodel. Proceedings of IBIS 2006.
• Sato, T. and Kameya, Y.: Learning through failure. Dagstuhl Seminar Proceedings on Probabilistic, Logical and Relational Learning - Towards a Synthesis, 2006.
• Kameya, Y. and Sato, T.: Computation of probabilistic relationship between concepts and their attributes using a statistical analysis of Japanese corpora. Proceedings of Symposium on Large-scale Knowledge Resources (LKR-2005), 2005.
• 大久保隆晴，亀谷由隆，佐藤泰介， 事例に基づく関係的な強化学習のエレベータ制御問題への適用， 第19回人工知能学会全国大会予稿集，2005．
  
• Sato, T. and Kameya, Y.: A dynamic programming approach to parameter learning of generative models with failure. Proceedings of ICML Workshop on Statistical Relational Learning and its Connection to the Other Fields (SRL-2004), 2004.
• 栗原賢一，亀谷由隆，佐藤泰介， 動的計画法に基づく確率文脈自由文法の変分ベイズ法， 情報処理学会 自然言語処理研究会 (NL) 159-29，pp. 209–214，2004．
• 森高志，亀谷由隆，佐藤泰介: 確率文脈自由文法およびその拡張モデルに対する EM アルゴリズムの評価実験. Technical Report TR01-0009, Dept. of Computer Science, Tokyo Institute of Technology, July, 2001.
• Sato, T., Kameya, Y., Abe, S., and Shirai, K.: Fast EM learning of a family of PCFGs, Technical Report TR01-0006, Dept. of Computer Science, Tokyo Institute of Technology, May, 2001.
• 森高志，亀谷由隆，佐藤泰介: 確率文脈自由文法およびその拡張文法の高速 EM 学習法， 情報処理学会 自然言語処理研究会 (NL) 139-12，pp. 85–92，2000．
• 亀谷由隆，佐藤泰介: 統計的記号処理言語PRISM， bit別冊「発見科学とデータマイニング」，第2章，2000．
• Sato, T. and Kameya, Y.: A Viterbi-like algorithm and EM learning for statistical abduction. Proceedings of UAI-2000 Workshop on Fusion of Domain Knowledge with Data for Decision Support, 2000.
• 亀谷由隆, 上田展久, 佐藤泰介: Tabling による記号的統計モデルの学習高速化に関する考察, 第37回人工知能基礎論研究会(SIG-FAI)予稿集, 1999.
• 亀谷由隆, 佐藤泰介: 記号的統計モデル言語PRISM, 電子情報通信学会技術研究報告 Vol. 97 No. 373, pp. 71-78, 1997．

多くの論文はこちらから電子版をダウンロードできます．

Last update: June 16, 2024