A picture of me

Takeshi Yamada

Senior Research Scientist, Supervisor
Executive Manager of
Innovative Communication Laboratory
NTT Communication Science Laboratories
2-4 Hikaridai Seika-cho Soraku-gun
Kyoto, 619-0237, JAPAN
PHONE +81(774)93-5100,
FAX +81(774)93-5105
yamada.tak 'at' lab.ntt.co.jp
[Japanese version]

B.S. Mathematics, University of Tokyo, Japan (1988).
Joined the Electrical Communication Laboratories, NTT (1988),
Visiting Researcher, School of Mathematical and Information Sciences, Coventry University, UK (1996-1997),
Doctor of Informatics from Kyoto University (2003).
Group Leader of Emergent Learning and Systems Research Group (2006-2009)
Currently, Executive Manager of Innovative Communication Laboratory at NTT Communication Science Laboratories
IEEE Senior Member
IEICE Senior Member
IPSJ Member, ACM Member

[ Areas of interest | Ph.D Thesis | Publications | Publications in Japanese | Useful links | My hobby ]

Areas of interest

My current research has focused on Statitstical Machine Learning, Data Mining, Network Analysis, Data Visualization, and Combinatorial Optimization, especially Scheduling.

Ph.D Thesis

My Ph.D Thesis titled "Studies on Metaheuristics for Jobshop and Flowshop Scheduling Problems" (2003) is available here in pdf (about 1M).

Academic Actitities

IEEE Kansai Section: Chair of Technical Program Committee (2009-2010) (Past Chair: 2011-)
Publications

  1. Tomoharu Iwata, Takeshi Yamada, Naonori Ueda, "Modeling Noisy Annotated Data with Application to Social Annotation," IEEE Transactions on Knowledge and Data Engineering, to appear
  2. Katsuhiko Ishiguro, Takeshi Yamada, Shoko Araki, Tomohiro Nakatani and Hiroshi Sawada, "Probabilistic Speaker Diarization with Bag-of-words Representations of Speaker Angle Information," IEEE Transactions on Audio, Speech and Language Processing, Vol. 20, No. 2, pp. 447-460, 2012.
  3. Tomoharu Iwata, Takeshi Yamada, Yasushi Sakurai, Naonori Ueda, "Sequential Modeling of Topic Dynamics with Multiple Timescales," ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 5 Issue 4, 19:1-19:27, 2012
  4. Tomoharu Iwata, Tomoko Kojiri, Takeshi Yamada, Toyohide Watanabe, "Recommendation for English Multiple-choice Cloze Questions Based on Expected Test Scores," International Journal of Knowledge-based and Intelligent Engineering Systems, Volume 15, Number 1, 2011
  5. Takuya Goto, Tomoko Kojiri, Toyohide Watanabe, Tomoharu Iwata, Takeshi Yamada, "Automatic Generation System of Multiple-choice Cloze Questions and its Evaluation," Knowledge Management & E-Learning: An International Journal (KM&EL), Vol 2, No 3, 2010
  6. Tomoharu Iwata, Toshiyuki Tanaka, Takeshi Yamada, Naonori Ueda, "Improving Classifier Performance using Data with Different Taxonomies," IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 23, No. 11, 1668-1677, 2011
  7. Daichi Mochihashi, Takeshi Yamada and Naonori Ueda, "Bayesian Unsupervised Word Segmentation with Nested Pitman-Yor Language Modeling", ACL-IJCNLP 2009, pp.100-108, 2009
  8. Tomoharu Iwata, Shinji Watanabe, Takeshi Yamada, Naonori Ueda, "Topic Tracking Model for Analyzing Consumer Purchase Behavior," IJCAI2009 (accepted), (2009)
  9. Kazuo Aoyama, Kazumi Saito, Takashi Yamada and Naonori Ueda, "Fast Similarity Search in Small-World Networks," CompleNet 2009, International Workshop on Complex Networks (accepted), 2009
  10. Takuya Goto, Tomoko Kojiri, Toyohide Watanabe, Takeshi Yamada, Tomoharu Iwata, "English Grammar Learning System Based on Knowledge Network of Fill-in-the-Blank Exercises," Proc. of 12th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES2008), Part III, LNAI 5179, 588--595, (2008)
  11. Tomoharu Iwata, Tomoko Kojiri, Takeshi Yamada, Toyohide Watanabe, "Recommendation Algorithm for Learning Materials that Maximizes Expected Test Scores," Proc. of 10th Pacific Rim International Conference on Artificial Intelligence (PRICAI2008), 2008
  12. Saito, K., Yamada, T., and Kazama, K., "Extracting Communities from Complex Networks by the k-dense Method," IEICE Transactions, Vol.E91-A,No.11,pp.-,Nov. 2008
  13. Tomoharu Iwata, Kazumi Saito, Takeshi Yamada, "Recommendation Method for Improving Customer Lifetime Value," IEEE Transactions on Knowledge and Data Engineering, Vol.20, No.9, 1254-1263, 2008
  14. Ishiguro, K., Yamada, T., & Ueda, N.: Simultaneous Clustering and Tracking Unknown Number of Objects, Proc. of the 19th IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR08) (in press).(2008)
  15. Tomoharu Iwata, Takeshi Yamada, Naonori Ueda, "Probabilistic Latent Semantic Visualization: Topic Model for Visualizing Documents," Proc. of 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2008), to appear, 2008
  16. Ko Fujimura, Shigeru Fujimura, Tatsushi Matsubayashi, Takeshi Yamada and Hidenori Okuda "Topigraphy: Visualization for Large-scale Tag Clouds", (WWW2008 poster), http://www2008.org/papers/pp104.html Best Poster Awards!
  17. Tatsushi Matsubayashi and Takeshi Yamada,
    A Force-directed Graph Drawing based on the Hierarchical Individual Timestep Method, International Journal of Electronics, Circuits and Systems, Vol.1, No.2, pp.116--121, (2007)
  18. Tomoharu Iwata, Kazumi Saito and Takeshi Yamada,
    Modeling User Behavior in Recommender Systems based on Maximum Entropy, Proc. of the 16th International World Wide Web conference (WWW2007 poster), pp.1281--1282, (2007)
  19. Yasuhiro Minami, Minako Sawaki, Kohji Dohsaka, Ryuichiro Higashinaka, Kentaro Ishizuka, Hideki Isozaki, Tatsushi Matsubayashi, Masato Miyoshi, Atsushi Nakamura, Takanobu Oba, Hiroshi Sawada, Takeshi Yamada, and Eisaku Maeda,
    "The World of Mushrooms: human-computer interaction prototype systems for ambient intelligence", The Ninth International Conference on Multimodal Interfaces (ICMI 2007)
  20. Kazumi Saito, Takeshi Yamada and Kazuhiro Kazama,
    Extracting Communities from Complex Networks by the k-dense method, Proc. of the ICDM2006 Workshop on Mining Complex Data (MCD2006), (2006).
  21. Tomoharu Iwata, Kazumi Saito and Takeshi Yamada,
    Recommendation Method for Extending Subscription Periods, Proc. of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2006), pp.574--579, (2006)
  22. Charles Kemp, Josh Tenenbaum, Tom Griffiths, Takeshi Yamada, and Naonori Ueda,
    Learning Systems of Concepts with an Infinite Relational Model, Proc. of the 21st National Conference on Artificial Intelligence, (AAAI-06), pp. 381-388 (2006)
  23. Takeshi Yamada, Yamada, Kazumi Saito, and Kazuhiro Kazama,
    Network Analyses to Understand the Structure of Wikipedia Proc. of Adaptation in Artificial and Biological Systems 2006 (AISB2006)
  24. Takeshi Yamada, Kazumi Saito and Naonori Ueda
    "Cross-entropy directed embedding of network data" in Proc. of ICML2003, pp. 832--839 (2003) (pdf).
  25. Takeshi Yamada
    A Pruning Pattern List Approach to the Permutation Flowshop Scheduling Problem, in Essays and Surveys in Metaheuristics, Kluwer academic publishers, pp. 641--651 (2002) (pdf).
  26. Takeshi Yamada, Kazuyuki Yoshimura, and Ryohei Nakano
    Information Operator Scheduling by Genetic Algorithms
    X. Yao et al. (Eds.): SEAL'98, LNCS 1585, pp. 50-57, 1999.
    (c) Springer-Verlag Berlin Heidelberg 1999. (gzip'ed ps)|(pdf)
  27. C.R.Reeves and T.Yamada
    Genetic Algorithms, Path Relinking and the Flowshop Sequencing Problem
    Evolutionary Computation journal (MIT press), Vol.6 No.1, pp. 230-234 Spring 1998. (gzip'ed ps)|(pdf)
  28. C.R.Reeves and T.Yamada
    Implicit tabu search methods for flowshop sequencing.
    Proc. IMACS International Conference on Computational Engineering in Systems Applications, pp.78-81, 1998.
  29. T.Yamada and C.R.Reeves
    Solving the Csum Permutation Flowshop Scheduling Problem by Genetic Local Search
    Proc. of 1998 IEEE International Conference on Evolutionary Computation, pp.230-234, 1998. (gzip'ed ps)|(pdf)
  30. T.Yamada and R.Nakano
    Chapter 7: Job Shop Scheduling,
    in Genetic algorithms in engineering systems,
    The Institution of Electrical Engineers, London, UK, 1997 (gzip'ed ps)|(pdf)
  31. T.Yamada and R.Nakano
    Genetic Algorithms for Job-Shop Scheduling Problems,
    Proc. of Modern Heuristic for Decision Support,
    pp.67-81, UNICOM seminar, 18-19 March 1997, London. (gzip'ed ps)|(pdf)
    The slides are also available. (gzip'ed ps)|(pdf)
  32. T.Yamada and C.R.Reeves
    Permutation flowshop scheduling by genetic local search,
    Proc. of the 2nd IEE/IEEE Int. Conf. on Genetic ALgorithms in Engineering Systems (GALESIA '97),
    pp. 232-238, 1997. (gzip'ed ps)|(pdf)
  33. T.Yamada and R.Nakano.
    A Fusion of Crossover and Local Search.
    Proc. of IEEE Int. Conf. on Industrial Technology 1996, pp.426-430 (gzip'ed ps)|(pdf)
  34. T.Yamada and R.Nakano.
    Scheduling by Genetic Local Search with Multi-Step Crossover.
    Proc. of The Fourth International Conference on Parallel Problem Solving from Nature (PPSN '96) , pp.960-969, 1996 (gzip'ed ps)|(pdf)
  35. T.Yamada and R.Nakano.
    Job-Shop Scheduling by Simulated Annealing Combined with Deterministic Local Search.
    in Meta-heuristics: theory & applications,
    Kluwer academic publishers MA, USA, pp. 237-248, 1996. (gzip'ed ps)|(pdf)
  36. T.Yamada and R.Nakano.
    A Genetic Algorithm with Multi-Step Crossover for Job-Shop Scheduling Problems.
    Proc. of the 1st IEE/IEEE Int. Conf. on Genetic ALgorithms in Engineering Systems (GALESIA '95),
    pp.146-151, 1995. (gzip'ed ps)|(pdf)
  37. T.Yamada, B.E.Rosen and R.Nakano.
    A Simulated Annealing Approach to Job Shop Scheduling using Critical Block Transition Operators.
    Proc. of IEEE International Conference on Neural Networks (ICNN '94), pp.4687-4692, 1994.
  38. Y.Davidor, T.Yamada and R.Nakano.
    The ECOlogical Framework II: Improving GA Performance At Virtually Zero Cost.
    Proc. of International Conference on Genetic Algorithms (ICGA '93), pp.171-176, 1993. (pdf)
  39. T.Yamada and R.Nakano.
    A Genetic Algorithm Applicable to Large-Scale Job-Shop Problems.
    Proc. of The Second International Conference on Parallel Problem Solving from Nature PPSN '92, pp.281-290, 1992. (pdf)
  40. R.Nakano, and T.Yamada.
    Conventional genetic algorithm for job shop problems.
    Proc. of International Conference on Genetic Algorithms (ICGA '91) , pp.474-479, 1991. (pdf)

JAPANESE

  1. T.Yamada and C.R.Reeves.
    Landscape Analysis of the Flowshop Scheduling Problem and Genetic Local Search.
    Transactions of Information Processing Society of Japan Vol.39 No.7, pp. 2112-2123, 1998. (In Japanese).
  2. T.Yamada and R.Nakano.
    Job-Shop Scheduling by Genetic Local Search.
    Transactions of Information Processing Society of Japan.
    Vol.38 No.6, pp. 1126-1138, 1997. (In Japanese).
  3. T.Yamada and R.Nakano.
    Job-Shop Scheduling by Simulated Annealing Combined with Deterministic Local Search.
    Transactions of Information Processing Society of Japan.
    Vol.37 No.4, 1996. (In Japanese).
  4. T.Yamada, B.E.Rosen, R.Nakano
    Critical Block Simulated Annealing for Job Shop Scheduling.
    The Transaction of The Institute of Electrical Engineers of Japan
    Vol.114-C, No.4, pp.476-482, 1994. (In Japanese).

Useful links

INFORMS OR/MS Resource Collection
Shop Scheduling page at Bauhaus-Universitaet Weimar
JOBSHOP, a set of C programs for the job-shop scheduling problems (by Applegate and Cook)
To solve a large-scale problem, you have to change the value of ONEMACH_BBNODES in bottle.h as well as MAXJOBS and MAXMACHS.
Journal of Scheduling (JOS)
Journal of Heuristics
Evolutionary Computation

My hobby