Achievement

Referred Publications (since 2007)

  1. New Nancy Mst Kanij Rabeya and Yoshitaka Yamamoto: A Feasibility Study of Federated Learning for Fish Order Classification with Habitat-Defined Clients, 20th IIAI International Congress on Advanced Applied Informatics, pp. 1-6, 2026.7
  2. New Shunya Kuwayama, Masanori Matsuda, Kei Asada, Masafumi Nishimura, and Yoshitaka Yamamoto: Towards Detection of Mild Intoxication Based on the Skeletal Dynamics of Seated Posture, 20th IIAI International Congress on Advanced Applied Informatics, pp. 1-6, 2026.7
  3. New Jun Kutsuzawa and Yoshitaka Yamamoto: Towards On-device Physiological Data Monitoring Using the Time-series Range-Counting Summary, Proc. of IEEE 8th International Conference on Activity and Behavior Computing (ABC'26), pp. 1-10, 2026.3
  4. New Toshihiro Tsukagoshi, Masanori Matsuda, Kei Asada, Yoshitaka Yamamoto, and Masafumi Nishimura: Estimating Intermediate Alcohol Intoxication States from Paired Facial Images, 2026 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing, pp. 1-5, 2026.2
  5. Thanapol Phungtua-eng and Yoshitaka Yamamoto: TriLinear: Time Series Anomaly Detection Using Tricube Smoothing Decomposition and a Linear Forecasting Model, Proc. of International Conference on Advanced Data Mining and Applications (ADMA'25) (Best Paper Runner-up Award), pp. 19-33, 2025.10
  6. Kosuke Nakamura, Taro Ueyama, Masafumi Nishimura, Takayuki Nakano, Takahiro Aoki, and Yoshitaka Yamamoto: Cross-silo human training in operational assembly: Integrating machine feedback for enhanced efficiency, Computers & Industrial Engineering, Vol. 213, pp. 1-14, 2025
  7. Jun Kutsuzawa, Kazuhide Suga, Masafumi Nishimura, Masanori Matsuda, Kei Asada, Nakano Ishinabe, Yoshinori Kajihara, and Yoshitaka Yamamoto: Feature Analysis of Drunk States Using Biometric Sensing Data, 2025 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing, pp. 1-5, 2025.3
  8. Shunsuke Kawano, Yoshitaka Yamamoto, and Daisuke Kaji: Personalized federated learning for assessing characteristic client data, IEEE i-COSTE workshop, pp. 1-6, 2024.11
  9. Thanapol Phungtua-eng and Yoshitaka Yamamoto: Adaptive seasonal-trend decomposition for streaming time series data with transitions and fluctuations in seasonality, ECML-PKDD, pp. 426-443, 2024.9
  10. Thanapol Phungtua-eng and Yoshitaka Yamamoto: A fast season length estimation using sliding discrete fourier transform for time series streaming data, 16th IIAI International Congress on Advanced Applied Informatics, pp. 1-6, 2024.7
  11. Tomoya Hirade, Reiki Shirasawa, Takayuki Nakano, Takahiro Aoki, Yoshitaka Yamamoto, and Masafumi Nishimura: Visualization of the Proficiency Level of Assembly Work Using Inertial and Sound Sensors, 2024 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP'24 Student Paper Award), 2024.3
  12. Hinano Sako and Yoshitaka Yamamoto: Online Closed Episode Mining with Root-Order Decomposition, IEEE BigData2023 Workshop on Real-time Stream Analytics, Stream Mining, CER/CEP & Stream Data Management, pp. 1-6, 2023.12
  13. Yuto Shimizu, Yoshitaka Yamamoto, Masafumi Nishimura, Yuki Shiono, Reiki Shirasawa, Takayuki Nakano, and Takahiro Aoki: Understanding Human Work Behavior by Action Segmentation Model with Feature Selection, IEEE CSDE2023, pp. 1-6, 2023.12
  14. Thanapol Phungtua-eng, Shigeyuki Sako, Yushi Nishikawa, and Yoshitaka Yamamoto: Elastic Data Binning: Time-Series Sketching for Time-Domain Astrophysics Analysis, ACM SIGAPP Applied Computing Review, Vol. 23, pp. 5-22, 2023.7
  15. Keisuke Nakamura, Yoshitaka Yamamoto, Masafumi Nishimura, Yuki Shiono, Reiki Shirasawa, Takayuki Nakano, and Takahiro Aoki: Regularizing Over-smoothing of Temporal Convolutional Networks for Action Segmentation on Human Assembly Operations, Journal of Signal Processing, Vol. 27, pp. 75-79, 2023.5
  16. Thanapol Phungtua-eng, Yoshitaka Yamamoto, and Shigeyuki Sako: Elastic Data Binning for Transient Pattern Analysis in Time-Domain Astrophysics, The 38th ACM/SIGAPP Symposium on Applied Computing, pp. 342-349, 2023.3
  17. Keisuke Nakamura, Yoshitaka Yamamoto, Masafumi Nishimura, Yuki Shiono, Reiki Shirasawa, Takayuki Nakano, and Takahiro Aoki: Tackling Over-smoothing on Temporal Convolutional Networks for Operating Work Segmentation, 2023 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP'23 Student Paper Award), 2023.3
  18. Yuto Shimizu, Yoshitaka Yamamoto, Masafumi Nishimura, Yuki Shiono, Reiki Shirasawa, Takayuki Nakano, and Takahiro Aoki: Temporal convolutional networks with feature selection for human manufacturing action analysis, 2023 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing, 2023.3
  19. Kento Yajima, Koji Iwanuma, and Yoshitaka Yamamoto: A bottom-up enumeration algorithm of minimal generators without support counting for compressing negative association rules, 12th International Congress on Advanced Applied Informatics (IIAI-AAI), pp. 665-668, 2022.7
  20. Thanapol Phungtua-eng, Yoshitaka Yamamoto, and Shigeyuki Sako: Dynamic binning for the unknown transient patterns analysis in astronomical time series, IEEE BigData2021 poster, 2021.12
  21. Koji Iwanuma, Kento Yajima, and Yoshitaka Yamamoto: Enumerating minimal generators from closed itemsets-toward effective compression of negative association rules, IEEE CSDE2021, 2021.11
  22. Thanapol Phungtua-eng, Yoshitaka Yamamoto, and Shigeyuki Sako: Detection for transient patterns with unpredictable duration using Chebyshev inequality and dynamic binning, CANDAR'21 WANC International Workshop, 2021.11
  23. Koji Iwanuma, Kento Yajima, and Yoshitaka Yamamoto: Mining Consistent, Non-Redundant and Minimal Negative Rules Based on Minimal Generators, Proceedings of IEEE BigData2019 in poster, 2020.12
  24. Thanapol Phungtua-eng, Yoshitaka Yamamoto, and Shigeyuki Sako: Transient pattern detection from streaming nature data, Proceedings of CANDAR'20 WANC workshop, 2020.11
  25. Yoshitaka Yamamoto, Yasuo Tabei, and Koji Iwanuma: PARASOL: a hybrid approximation approach for scalable frequent itemset mining in streaming data, Journal of Intelligent Information Systems, to appear, 2020
  26. Koji Iwanuma, Takumi Nishina, and Yoshitaka Yamamoto: Accelerating an On-Line Approximation Mining for Large Closed Itemsets, Proceedings of IEEE BigData2019, to appear, 2019
  27. Koji Iwanuma, Yoshitaka Yamamoto, and Shoshi Fukuda: An On-Line Approximation Algorithm for Mining Frequent Closed Itemsets Based on Incremental Intersection, Proceedings of 19th Extended Database Technology (EDBT2015), pp. 704-705, 2015
  28. Yoshitaka Yamamoto and Koji Iwanuma: Online Pattern Mining for High-Dimensional Data Streams, Proceedings of IEEE BigData2015, pp. 2615-2617, 2015
  29. Adrien Rougny, Yoshitaka Yamamoto, Hidetomo Nabeshima, Gauvain Bourgne, Anne Poupon, Katsumi Inoue, and Christine Froidevaux: Completing Signaling Networks by Abductive Reasoning with Perturbation Experiments, Proceedings of the 25th International Conference on Inductive Logic Programming (ILP2015), to appear, 2015
  30. Yoshitaka Yamamoto, Adrien Rougny, Hidetomo Nabeshima, Katsumi Inoue, Hisao Moriya, Christine Froidevaux, and Koji Iwanuma: Completing SBGN-AF Networks by Logic-Based Hypothesis Finding, Proceedings of the 1st International Conference on Formal Methods in Macro-Biology (FMMB2014), Lecture Notes in Bioinformatics, Vol. 8738, pp. 165-179, 2014
  31. Adrien Rougny, Christine Froidevaux, Yoshitaka Yamamoto, and Katsumi Inoue: Analyzing SBGN-AF Networks using Normal Logic Programs, in Logical Modeling of Biological Systems, Katsumi Inoue and Luis Farinas (eds.), ISTE-Ltd, ISBN: 978-1-84821-680-8, 2014
  32. Adrien Rougny, Christine Froidevaux, Yoshitaka Yamamoto, and Katsumi Inoue: Translating the SBGN-AF Language into Logics to Analyze Signalling Networks, Post-Proceedings of the 1st International Workshop on Learning and Nonmonotonic Reasoning (LNMR2013), CoRR, Vol. 975, pp. 43-54, 2013
  33. Yoshitaka Yamamoto, Koji Iwanuma, and Hidetomo Nabeshima: Practically Fast Non-monotone Dualization based on Monotone Dualization, Post-Proceedings of the 1st International Workshop on Learning and Nonmonotonic Reasoning (LNMR2013), CoRR, Vol. 975, pp. 55-66, 2013
  34. Yoshitaka Yamamoto, Koji Iwanuma, and Katsumi Inoue: Non-monotone dualization via Monotone Dualization, Proceedings of the 22nd International Conference on Inductive Logic Programming (ILP2012), CEUR, Vol. 975, pp. 74-79, 2012
  35. Yoshitaka Yamamoto, Katsumi Inoue, and Koji Iwanuma: Heuristic Inverse Subsumption in Full-clausal Theories, Proceedings of the 22nd International Conference on Inductive Logic Programming (ILP2012), 2012. An extended version is published in: Inductive Logic Programming: Revised Selected Papers from the 22nd International Conference (ILP '12), Lecture Notes in Artificial Intelligence, Vol. 7842, pp. 241-256, Springer, 2013
  36. Yoshitaka Yamamoto, Katsumi Inoue, and Koji Iwanuma: Comparison of Upward and Downward Generalizations in CF-induction, Proceedings of the 21st International Conference on Inductive Logic Programming (ILP 2011), 2011. An extended version is published in: Inductive Logic Programming: Revised Selected Papers from the 21st International Conference (ILP '11), Lecture Notes in Artificial Intelligence, Vol. 7207, pp. 373-388, Springer, 2012
  37. Yoshitaka Yamamoto, Katsumi Inoue, and Koji Iwanuma: Inverse Subsumption for Complete Explanatory Induction, Journal of Machine Learning, DOI: 10.1007/s10994-011-5250-y, 2011
  38. Yoshitaka Yamamoto, Katsumi Inoue, and Koji Iwanuma: From Inverse Entailment to Inverse Subsumption, Proceedings of the 20th International Conference on Inductive Logic Programming (ILP 2010), 2010
  39. Yoshitaka Yamamoto, Katsumi Inoue, and Andrei Doncescu: Integrating Abduction and Induction in Biological Inference using CF-Induction, in Huma Lodhi and Stephen Muggleton (eds.), Elements of Computational Systems Biology, Wiley Book Series on Bioinformatics, pp. 213-234, John Wiley and Sons, Inc., 2009
  40. Yoshitaka Yamamoto, Katsumi Inoue, and Koji Iwanuma: Hypothesis enumeration by CF-induction, Proceedings of the Sixth Workshop on Learning with Logics and Logics for Learning (LLLL2009), pp. 80-87, The Japanese Society for Artificial Intelligence, 2009
  41. Yoshitaka Yamamoto, Katsumi Inoue, and Andrei Doncescu: Abductive reasoning in cancer therapy, Proceedings of the 23rd International Conference on Advanced Information Networking and Applications (AINA 2009), pp. 948-953, IEEE Computer Society, 2009
  42. Yoshitaka Yamamoto, Oliver Ray, and Katsumi Inoue: Towards a logical reconstruction of CF-induction, in New Frontiers in Artificial Intelligence: JSAI 2007 Conference and Workshop Revised Selected Papers, Lecture Notes in Artificial Intelligence, Vol. 4914, pp. 330-343, Springer, 2008
  43. Yoshitaka Yamamoto and Katsumi Inoue: An efficient hypothesis-finding system implemented with deduction and dualization, Proceedings of the 22nd Workshop on Logic Programming (WLP 2008), pp. 92-103, University Halle–Wittenberg Institute of Computer Science Technical Report, 2008
  44. Yoshitaka Yamamoto, Katsumi Inoue, and Andrei Doncescu: Inferring inhibition and pathway rules using CF-induction, Poster presentation at the 6th Asia Pacific Bioinformatics Conference (APBC 2008), Japan, 2008
  45. Yoshitaka Yamamoto, Katsumi Inoue, and Andrei Doncescu: Estimation of possible reaction states in metabolic pathways using inductive logic programming, Proceedings of the 22nd International Conference on Advanced Information Networking and Applications (AINA 2008), pp. 808-813, IEEE Computer Society, 2008
  46. Andrei Doncescu, Katsumi Inoue, and Yoshitaka Yamamoto: Knowledge-based discovery in systems biology using CF-induction, in New Trends in Applied Artificial Intelligence: Proceedings of the 20th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE 2007), Lecture Notes in Artificial Intelligence, Vol. 4570, pp. 395-404, Springer, 2007
  47. Yoshitaka Yamamoto, Oliver Ray, and Katsumi Inoue: Towards a logical reconstruction of CF-Induction, Proceedings of the 5th International Workshop on Learning with Logics and Logics for Learning (LLLL 2007), pp. 18-24, The Japanese Society for Artificial Intelligence, 2007
  48. Andrei Doncescu, Yoshitaka Yamamoto, and Katsumi Inoue: Biological systems analysis using Inductive Logic Programming, Proceedings of the 21st International Conference on Advanced Information Networking and Applications (AINA 2007), pp. 690-695, IEEE Computer Society, 2007

Oral presentations (since 2007)

  1. New Yuya Kishikami and Yoshitaka Yamamoto: An Efficient Time-Series Summary for Range-counting Queries with Applications to Transient Detection in Time-domain Astronomy, 5th SU-CNU Joint Symposium (Poster presentation), 2026.9
  2. Yoshitaka Yamamoto: Application and Limitation of Itemset-Frequency Sketches, CompressedAI2025: Compressed Data Structures for Advanced Intelligent Data Analysis, 2025.7
  3. Thanapol Phungtua-eng, Yushi Nishikawa, and Yoshitaka Yamamoto: Exploring the utilization of elastic data binning for time-series representation for Tomo-e light curve data, Kiso Summit Symposium 2023, 2023.5
  4. Thanapol Phungtua-eng and Yoshitaka Yamamoto: Elastic data binning a novel sketching time-series data, The 9th International Symposium toward the Future of Advanced Researches in Shizuoka University (ISFAR-SU2023), 2023.3
  5. Thanapol Phungtua-eng and Yoshitaka Yamamoto: A novel framework of non-parametric for adjusting the window size, WSSIT2022, 2022.3
  6. Yoshitaka Yamamoto: Approximation and compression in streaming data mining, 23rd International Symposium on String Processing and Information Retrieval (SPIRE2016) [Invited talk], 2016.9
  7. Yoshitaka Yamamoto: Resource-oriented Online Approach for Itemset-Mining and Hypothesis-Finding, The ILP NII-Satellite Meeting, 2015
  8. Yoshitaka Yamamoto: A Case Study on Network Completion in Yeast Glucose Repression, The LRI-NII-Yamanshi Workshop on Analyzing GPCRs with Inference in Molecular Networks, 2014
  9. Yoshitaka Yamamoto: Completing SBGN based networks using meta-level abduction and SOLAR, The 5th JFLI-NII-LRI Workshop on Formal Approaches for Modeling and Analyzing Biological Networks, 2013
  10. Yoshitaka Yamamoto, Koji Iwanuma, and Katsumi Inoue: On Subclasses of Non-monotone Dualization Equivalent to Monotone Dualization, The CRIL-NII Collaborative Meeting on Reasoning about Dynamic Constraint Networks, 2012
  11. Yoshitaka Yamamoto, Haruka Sakamoto, and Koji Iwanuma: Logical Verification of Biological Networks with Gene Expression Data, The Fourth JFLI-LRI-NII Workshop on Consequence Finding and Satisfiability Testing in Distributed Environments and Systems Biology, 2012
  12. Yoshitaka Yamamoto, Katsumi Inoue, and Koji Iwanuma: An incremental way for finding characteristic hypotheses in CF-induction, The Third Franco-Japanese Symposium on Knowledge Discovery in Systems Biology (FJ'09), 2009
  13. Yoshitaka Yamamoto and Katsumi Inoue: CF-induction for hypothesis enumeration, The Second Franco-Japanese Symposium on Knowledge Discovery in Systems Biology (FJ'08), 2008
  14. Yoshitaka Yamamoto and Katsumi Inoue: An Efficient Hypothesis-finding System Implemented with Deduction and Dualization, One day Workshop for Answer Set Programming and Abduction, 2008
  15. Yoshitaka Yamamoto, Katsumi Inoue, and Andrei Doncescu: Integration of abduction and induction in biological networks using CF-induction, The First Franco-Japanese Symposium on Knowledge Discovery in Systems Biology (FJ'07), 2007