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ORCIDTsuyoshi Idé
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- affiliation: IBM Research
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2020 – today
- 2024
[c40]Dongxia Wu, Tsuyoshi Idé, Georgios Kollias, Jirí Navrátil, Aurélie C. Lozano, Naoki Abe, Yi-An Ma, Rose Yu:
Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes. AISTATS 2024: 415-423- [i12]Dongxia Wu, Tsuyoshi Idé, Aurélie C. Lozano, Georgios Kollias, Jirí Navrátil, Naoki Abe, Yi-An Ma, Rose Yu:
Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes. CoRR abs/2402.03726 (2024) - [i11]Conor M. Artman, Aditya Mate, Ezinne Nwankwo, Aliza Heching, Tsuyoshi Idé, Jirí Navrátil, Karthikeyan Shanmugam, Wei Sun, Kush R. Varshney, Lauri Goldkind, Gidi Kroch, Jaclyn Sawyer, Ian Watson:
A resource-constrained stochastic scheduling algorithm for homeless street outreach and gleaning edible food. CoRR abs/2403.10638 (2024) - [i10]Tsuyoshi Idé, Dzung T. Phan, Rudy Raymond:
Decentralized Collaborative Learning Framework with External Privacy Leakage Analysis. CoRR abs/2404.01270 (2024) - [i9]Tsuyoshi Idé, Jokin Labaien, Pin-Yu Chen:
Improving Transformers using Faithful Positional Encoding. CoRR abs/2405.09061 (2024) - 2023
- [j8]Jokin Labaien
, Tsuyoshi Idé, Pin-Yu Chen, Ekhi Zugasti, Xabier De Carlos:
Diagnostic spatio-temporal transformer with faithful encoding. Knowl. Based Syst. 274: 110639 (2023) - [c39]Yonas Sium, Georgios Kollias, Tsuyoshi Idé, Payel Das, Naoki Abe, Aurélie C. Lozano, Qi Li:
Direction Aware Positional and Structural Encoding for Directed Graph Neural Networks. ICASSP 2023: 1-5 - [c38]Tsuyoshi Idé, Naoki Abe:
Generative Perturbation Analysis for Probabilistic Black-Box Anomaly Attribution. KDD 2023: 845-856 - [e5]Hisashi Kashima, Tsuyoshi Idé, Wen-Chih Peng:
Advances in Knowledge Discovery and Data Mining - 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25-28, 2023, Proceedings, Part I. Lecture Notes in Computer Science 13935, Springer 2023, ISBN 978-3-031-33373-6 [contents] - [e4]Hisashi Kashima, Tsuyoshi Idé, Wen-Chih Peng:
Advances in Knowledge Discovery and Data Mining - 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25-28, 2023, Proceedings, Part II. Lecture Notes in Computer Science 13936, Springer 2023, ISBN 978-3-031-33376-7 [contents] - [e3]Hisashi Kashima, Tsuyoshi Idé, Wen-Chih Peng:
Advances in Knowledge Discovery and Data Mining - 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25-28, 2023, Proceedings, Part III. Lecture Notes in Computer Science 13937, Springer 2023, ISBN 978-3-031-33379-8 [contents] - [e2]Hisashi Kashima, Tsuyoshi Idé, Wen-Chih Peng:
Advances in Knowledge Discovery and Data Mining - 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25-28, 2023, Proceedings, Part IV. Lecture Notes in Computer Science 13938, Springer 2023, ISBN 978-3-031-33382-8 [contents] - [i8]Jokin Labaien, Tsuyoshi Idé, Pin-Yu Chen, Ekhi Zugasti, Xabier De Carlos:
Diagnostic Spatio-temporal Transformer with Faithful Encoding. CoRR abs/2305.17149 (2023) - [i7]Tsuyoshi Idé, Naoki Abe:
Black-Box Anomaly Attribution. CoRR abs/2305.18440 (2023) - [i6]Tsuyoshi Idé, Naoki Abe:
Generative Perturbation Analysis for Probabilistic Black-Box Anomaly Attribution. CoRR abs/2308.04708 (2023) - 2022
- [c37]Georgios Kollias, Vasileios Kalantzis, Tsuyoshi Idé, Aurélie C. Lozano, Naoki Abe:
Directed Graph Auto-Encoders. AAAI 2022: 7211-7219 - [i5]Georgios Kollias, Vasileios Kalantzis, Tsuyoshi Idé, Aurélie C. Lozano, Naoki Abe:
Directed Graph Auto-Encoders. CoRR abs/2202.12449 (2022) - [i4]Tsuyoshi Idé, Keerthiram Murugesan, Djallel Bouneffouf, Naoki Abe:
Targeted Advertising on Social Networks Using Online Variational Tensor Regression. CoRR abs/2208.10627 (2022) - [i3]Tsuyoshi Idé, Georgios Kollias, Dzung T. Phan, Naoki Abe:
Cardinality-Regularized Hawkes-Granger Model. CoRR abs/2208.10671 (2022) - [i2]Tsuyoshi Idé, Rudy Raymond:
Decentralized Collaborative Learning with Probabilistic Data Protection. CoRR abs/2208.10674 (2022) - [i1]Tsuyoshi Idé, Amit Dhurandhar, Jirí Navrátil, Moninder Singh, Naoki Abe:
Anomaly Attribution with Likelihood Compensation. CoRR abs/2208.10679 (2022) - 2021
- [c36]Tsuyoshi Idé, Amit Dhurandhar, Jirí Navrátil, Moninder Singh, Naoki Abe:
Anomaly Attribution with Likelihood Compensation. AAAI 2021: 4131-4138 - [c35]Tsuyoshi Idé, Georgios Kollias, Dzung T. Phan, Naoki Abe:
Cardinality-Regularized Hawkes-Granger Model. NeurIPS 2021: 2682-2694 - [c34]Tsuyoshi Idé, Rudy Raymond:
Decentralized Collaborative Learning with Probabilistic Data Protection. SMDS 2021: 234-243
2010 – 2019
- 2019
- [c33]Tsuyoshi Idé:
Tensorial Change Analysis Using Probabilistic Tensor Regression. AAAI 2019: 3902-3909 - [c32]Long H. Vu, Sarah Kefayati, Tsuyoshi Idé, Venkata N. Pavuluri, Gretchen P. Jackson, Lisa Latts, Yuxiang Zhong, Pratik Agrawal, Yuan-Chi Chang:
Predicting Nocturnal Hypoglycemia from Continuous Glucose Monitoring Data with Extended Prediction Horizon. AMIA 2019 - [c31]Tsuyoshi Idé, Rudy Raymond, Dzung T. Phan:
Efficient Protocol for Collaborative Dictionary Learning in Decentralized Networks. IJCAI 2019: 2585-2591 - [c30]Dzung T. Phan, Tsuyoshi Idé:
ℓ0-Regularized Sparsity for Probabilistic Mixture Models. SDM 2019: 172-180 - 2018
- [c29]Tsuyoshi Idé:
Collaborative Anomaly Detection on Blockchain from Noisy Sensor Data. ICDM Workshops 2018: 120-127 - 2017
- [j7]Tsuyoshi Idé, Amit Dhurandhar:
Supervised item response models for informative prediction. Knowl. Inf. Syst. 51(1): 235-257 (2017) - [j6]Tsuyoshi Idé, Takayuki Katsuki, Tetsuro Morimura, Robert J. T. Morris:
City-Wide Traffic Flow Estimation From a Limited Number of Low-Quality Cameras. IEEE Trans. Intell. Transp. Syst. 18(4): 950-959 (2017) - [c28]Tsuyoshi Idé, Dzung T. Phan, Jayant Kalagnanam:
Multi-task Multi-modal Models for Collective Anomaly Detection. ICDM 2017: 177-186 - [c27]Dzung T. Phan, Tsuyoshi Idé, Jayant Kalagnanam, Matt Menickelly, Katya Scheinberg:
A Novel l0-Constrained Gaussian Graphical Model for Anomaly Localization. ICDM Workshops 2017: 830-833 - 2016
- [c26]Tsuyoshi Idé, Ankush Khandelwal, Jayant Kalagnanam:
Sparse Gaussian Markov Random Field Mixtures for Anomaly Detection. ICDM 2016: 955-960 - [c25]Takayuki Katsuki, Tetsuro Morimura, Tsuyoshi Idé:
Unsupervised object counting without object recognition. ICPR 2016: 3627-3632 - [c24]Tsuyoshi Idé, Dzung T. Phan, Jayant Kalagnanam:
Change Detection Using Directional Statistics. IJCAI 2016: 1613-1619 - 2015
- [c23]Tsuyoshi Idé, Amit Dhurandhar:
Informative Prediction Based on Ordinal Questionnaire Data. ICDM 2015: 191-200 - [c22]Tsuyoshi Idé, Sinem Güven, Ee-Ea Jan, Sergey Makogon, Alejandro Venegas:
Latent trait analysis for risk management of complex information technology projects. IM 2015: 305-312 - [c21]Ea-Ee Jan, Kuan-Yu Chen, Tsuyoshi Idé:
Probabilistic text analytics framework for information technology service desk tickets. IM 2015: 870-873 - 2014
- [c20]Sinem Güven, Mathias Steiner, Tsuyoshi Idé, Amit M. Paradkar, Sergey Makogon, Alejandro Venegas:
Mining for Gold: How to Predict Service Contract Performance with Optimal Accuracy Based on Ordinal Risk Assessment Data. IEEE SCC 2014: 315-322 - [c19]Ea-Ee Jan, Kuan-Yu Chen, Tsuyoshi Idé:
A Probabilistic Concept Annotation for IT Service Desk Tickets. ESAIR 2014: 21-23 - [c18]Bin Tong, Tetsuro Morimura, Einoshin Suzuki, Tsuyoshi Idé:
Probabilistic Two-Level Anomaly Detection for Correlated Systems. ECAI 2014: 1109-1110 - 2013
- [j5]Takayuki Osogami, Takashi Imamichi, Hideyuki Mizuta, Toyotaro Suzumura, Tsuyoshi Idé:
Toward simulating entire cities with behavioral models of traffic. IBM J. Res. Dev. 57(5) (2013) - [c17]Tetsuro Morimura, Takayuki Osogami, Tsuyoshi Idé:
Solving inverse problem of Markov chain with partial observations. NIPS 2013: 1655-1663 - 2012
- [j4]Shohei Hido, Shoko Suzuki, Risa Nishiyama, Takashi Imamichi, Rikiya Takahashi, Tetsuya Nasukawa, Tsuyoshi Idé, Yusuke Kanehira, Rinju Yohda, Takeshi Ueno, Akira Tajima, Toshiya Watanabe:
Modeling Patent Quality: A System for Large-scale Patentability Analysis using Text Mining. Inf. Media Technol. 7(3): 1180-1191 (2012) - [j3]Shohei Hido, Shoko Suzuki, Risa Nishiyama, Takashi Imamichi, Rikiya Takahashi, Tetsuya Nasukawa, Tsuyoshi Idé, Yusuke Kanehira, Rinju Yohda, Takeshi Ueno, Akira Tajima, Toshiya Watanabe:
Modeling Patent Quality: A System for Large-scale Patentability Analysis using Text Mining. J. Inf. Process. 20(3): 655-666 (2012) - [c16]Toshihiro Takahashi, Tsuyoshi Idé:
Predicting battery life from usage trajectory patterns. ICPR 2012: 2946-2949 - 2011
- [c15]Tsuyoshi Idé, Masashi Sugiyama:
Trajectory Regression on Road Networks. AAAI 2011: 203-208 - [c14]Takashi Imamichi, Hidetoshi Numata, Hideyuki Mizuta, Tsuyoshi Idé:
Nonlinear optimization to generate non-overlapping random dot patterns. WSC 2011: 2419-2430 - 2010
- [j2]Masashi Sugiyama, Tsuyoshi Idé, Shinichi Nakajima, Jun Sese:
Semi-supervised local Fisher discriminant analysis for dimensionality reduction. Mach. Learn. 78(1-2): 35-61 (2010)
2000 – 2009
- 2009
- [j1]Hisashi Kashima, Tsuyoshi Idé, Tsuyoshi Kato, Masashi Sugiyama:
Recent Advances and Trends in Large-Scale Kernel Methods. IEICE Trans. Inf. Syst. 92-D(7): 1338-1353 (2009) - [c13]Tsuyoshi Idé, Aurélie C. Lozano, Naoki Abe, Yan Liu:
Proximity-Based Anomaly Detection Using Sparse Structure Learning. SDM 2009: 97-108 - [c12]Tsuyoshi Idé, Sei Kato:
Travel-Time Prediction Using Gaussian Process Regression: A Trajectory-Based Approach. SDM 2009: 1185-1196 - [e1]Hiromitsu Hattori, Takahiro Kawamura, Tsuyoshi Idé, Makoto Yokoo, Yohei Murakami:
New Frontiers in Artificial Intelligence, JSAI 2008 Conference and Workshops, Asahikawa, Japan, June 11-13, 2008, Revised Selected Papers. Lecture Notes in Computer Science 5447, Springer 2009, ISBN 978-3-642-00608-1 [contents] - 2008
- [c11]Shohei Hido, Tsuyoshi Idé, Hisashi Kashima, Harunobu Kubo, Hirofumi Matsuzawa:
Unsupervised Change Analysis Using Supervised Learning. PAKDD 2008: 148-159 - [c10]Masashi Sugiyama, Tsuyoshi Idé, Shinichi Nakajima, Jun Sese:
Semi-Supervised Local Fisher Discriminant Analysis for Dimensionality Reduction. PAKDD 2008: 333-344 - 2007
- [c9]Tsuyoshi Idé, Spiros Papadimitriou, Michail Vlachos:
Computing Correlation Anomaly Scores Using Stochastic Nearest Neighbors. ICDM 2007: 523-528 - [c8]Tsuyoshi Idé, Koji Tsuda:
Change-Point Detection using Krylov Subspace Learning. SDM 2007: 515-520 - 2006
- [c7]Tsuyoshi Idé:
Translational Symmetry in Subsequence Time-Series Clustering. JSAI 2006: 5-18 - [c6]Tsuyoshi Idé:
Why Does Subsequence Time-Series Clustering Produce Sine Waves? PKDD 2006: 211-222 - 2005
- [c5]Hisashi Kashima, Tadashi Tsumura, Tsuyoshi Idé, Takahide Nogayama, Ryo Hirade, Hiroaki Etoh, Takeshi Fukuda:
Network-Based Problem Detection for Distributed Systems. ICDE 2005: 978-989 - [c4]Tsuyoshi Idé:
Pairwise Symmetry Decomposition Method for Generalized Covariance Analysis. ICDM 2005: 657-660 - [c3]Tsuyoshi Idé, Keisuke Inoue:
Knowledge Discovery from Heterogeneous Dynamic Systems using Change-Point Correlations. SDM 2005: 571-575 - 2004
- [c2]Tsuyoshi Idé, Hisashi Kashima:
Effective Dimension in Anomaly Detection: Its Application to Computer Systems. JSAI Workshops 2004: 189-204 - [c1]Tsuyoshi Idé, Hisashi Kashima:
Eigenspace-based anomaly detection in computer systems. KDD 2004: 440-449
Coauthor Index
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last updated on 2024-09-02 00:11 CEST by the dblp team
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