Einoshin Suzuki

发表

Sample based crowding method for multimodal optimization in continuous domain

Shigenobu Kobayashi, Einoshin Suzuki, Shin Ando, 2005, 2005 IEEE Congress on Evolutionary Computation.

An information theoretic approach to detection of minority subsets

Shigenobu Kobayashi, Jun Sakuma, Einoshin Suzuki, 2007 .

Evaluation Scheme for Exception Rule/Group Discovery

Einoshin Suzuki, 2004 .

Detection of unique temporal segments by information theoretic meta-clustering

Einoshin Suzuki, Shin Ando, S. Ando, 2009, KDD.

A Symbolic Representation for Trajectory Data

Einoshin Suzuki, Einoshin Suzuki, Huy Nguyen, 2010 .

Toward a platform for collecting, mining, and utilizing behavior data for detecting students with depression risks

Masanori Sugimoto, Hiroaki Ogata, Tetsu Matsukawa, 2015, PETRA.

Toward knowledge-driven spiral discovery of exception rules

Einoshin Suzuki, Y. Yamada, Einoshin Suzuki, 2002, 2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291).

Foundations of Intelligent Systems

Shusaku Tsumoto, Ning Zhong, Einoshin Suzuki, 2003, Lecture Notes in Computer Science.

Human Detection by a Small Autonomous Mobile Robot

Einoshin Suzuki, Shigeru Takano, Kouhei Takemoto, 2012, European Grid Conference.

Construction of micro-expression benchmark data in conversation game

Einoshin Suzuki, Tetsu Matsukawa, Hirofumi Fujita, 2016 .

Categorizing Undirected Discovery of Exception Rules (小特集「発見科学」及び一般演題)

Jan M. Zytkow, Einoshin Suzuki, Einoshin Suzuki, 2000 .

Outlier Detection Based on Decision Tree and Boosting

Einoshin Suzuki, Takeshi Watanabe, Einoshin Suzuki, 2002 .

Statistical Implicative Analysis

Fabrice Guillet, Einoshin Suzuki, Einoshin Suzuki, 2008 .

GIAD-ST: Detecting anomalies in human monitoring based on generative inpainting via self-supervised multi-task learning

Einoshin Suzuki, Ning Dong, 2022, Journal of Intelligent Information Systems.

Sparse Nonnegative Interaction Models

Einoshin Suzuki, Hiroto Saigo, Y. Tabei, 2021, IEEE Access.

Iterative Data Squashing for Boosting Based on a Distribution-Sensitive Distance

Einoshin Suzuki, Yuta Choki, 2002, PKDD.

Detecting outliers with one-class selective transfer machine

Einoshin Suzuki, Tetsu Matsukawa, Hirofumi Fujita, 2019, Knowledge and Information Systems.

Transfer learning by centroid pivoted mapping in noisy environment

T. H. Nguyen, Einoshin Suzuki, Bin Tong, 2013, Journal of Intelligent Information Systems.

Classifying actions based on histogram of oriented velocity vectors

Einoshin Suzuki, Somar Boubou, 2015, Journal of Intelligent Information Systems.

Finding peculiar compositions of two frequent strings with background texts

Einoshin Suzuki, Daisuke Ikeda, 2014, Knowledge and Information Systems.

Experimental Evaluation of GAN-Based One-Class Anomaly Detection on Office Monitoring

Tetsu Matsukawa, Einoshin Suzuki, Yusuke Hatae, 2020, International Syposium on Methodologies for Intelligent Systems.

Web Intelligence and Intelligent Agent Technology

Jean-Marc Petit, Einoshin Suzuki, Jomi Fred Hübner, 2011 .

Detecting Anomalous Regions from an Image based on Deep Captioning

Tetsu Matsukawa, Einoshin Suzuki, Yusuke Hatae, 2020, VISIGRAPP.

Finding an Optimal Gain-Ratio Subset-Split Test for a Set-Valued Attribute in Decision Tree Induction

Einoshin Suzuki, Fumio Takechi, Einoshin Suzuki, 2002, ICML.

Adaptive and hybrid context-aware fine-grained word sense disambiguation in topic modeling based document representation

Einoshin Suzuki, Wenbo Li, Einoshin Suzuki, 2021, Inf. Process. Manag..

GIAD: Generative Inpainting-Based Anomaly Detection via Self-Supervised Learning for Human Monitoring

Einoshin Suzuki, Ning Dong, Einoshin Suzuki, 2021, PRICAI.

Disease Definition Based on Spiral Discovery of Exceptions (Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ and IEICE-SIGAI on Active Mining) -- (Session 2: Medical Active Mining)

Einoshin Suzuki, Masatoshi Jumi, Muneaki Ohshima, 2004 .

Une règle d'exception en Analyse Statistique Implicative

Régis Gras, Pascale Kuntz, Einoshin Suzuki, 2007, EGC.

Discovery of Exception Association Rules Based on Breadth-First Search

Einoshin Suzuki, Mitsutoshi Nagahama, Einoshin Suzuki, 2001 .

LF-007 Classifying Unique Web Pages Using a Search Engine

Einoshin Suzuki, Masayuki Hirose, Einoshin Suzuki, 2004 .

Decision-tree Induction from Time-series Data Based on Dynamic Time Warping

Einoshin Suzuki, Yuu Yamada, Hideto Yokoi, 2003 .

Discovery system for exception knowledge based on a stochastic confidence evaluation method

Einoshin Suzuki, Einoshin Suzuki, 1997 .

Pitfalls for Categorizations of Objective Interestingness Measures for Rule Discovery

Einoshin Suzuki, Einoshin Suzuki, 2008, Statistical Implicative Analysis.

Exploiting Micro-Clusters to Close The Loop in Data-Mining Robots for Human Monitoring

Einoshin Suzuki, Einoshin Suzuki, 2018, AAAI Spring Symposia.

Contrastive Goal Grouping for Policy Generalization in Goal-Conditioned Reinforcement Learning

Qiming Zou, Einoshin Suzuki, Einoshin Suzuki, 2021, ICONIP.

Context-Based Anomaly Detection via Spatial Attributed Graphs in Human Monitoring

Einoshin Suzuki, Muhammad Fikko Fadjrimiratno, Kang Zhang, 2021, International Conference on Neural Information Processing.

Minimizing response time in time series classification

S. Ando, Einoshin Suzuki, 2016, Knowledge and Information Systems.

ACE: Anomaly Clustering Ensemble for Multi-perspective Anomaly Detection in Robot Behaviors

Einoshin Suzuki, Yoichi Seki, Shin Ando, 2011, SDM.

Topology Preserving SOM with Transductive Confidence Machine

Zhiguang Qin, Einoshin Suzuki, Bin Tong, 2010, Discovery Science.

RoClust: Role discovery for graph clustering

Einoshin Suzuki, Bin-Hui Chou, Einoshin Suzuki, 2013, Web Intell. Agent Syst..

Role Discovery for Graph Clustering

Einoshin Suzuki, Bin-Hui Chou, Einoshin Suzuki, 2011, APWeb.

Discovering Community-Oriented Roles of Nodes in a Social Network

Einoshin Suzuki, Bin-Hui Chou, Einoshin Suzuki, 2010, DaWak.

Transfer dimensionality reduction by Gaussian process in parallel

Junbin Gao, Thach Huy Nguyen, Hao Shao, 2013, Knowledge and Information Systems.

Linear Semi-Supervised Dimensionality Reduction with Pairwise Constraint for Multiple Subclasses

Einoshin Suzuki, Bin Tong, Yanli Ji, 2012, IEICE Trans. Inf. Syst..

Gaussian Process for Dimensionality Reduction in Transfer Learning

Junbin Gao, Thach Huy Nguyen, Einoshin Suzuki, 2011, SDM.

Subclass-Oriented Dimension Reduction with Constraint Transformation and Manifold Regularization

Einoshin Suzuki, Bin Tong, Einoshin Suzuki, 2010, PAKDD.

An Efficient Algorithm for Reducing Clauses Based on Constraint Satisfaction Techniques

Einoshin Suzuki, Jérôme Maloberti, Einoshin Suzuki, 2004, ILP.

Linear semi-supervised projection clustering by transferred centroid regularization

Hao Shao, Einoshin Suzuki, Bin Tong, 2012, Journal of Intelligent Information Systems.

Unified algorithm for undirected discovery of exception rules

Jan M. Zytkow, Einoshin Suzuki, Einoshin Suzuki, 2005, Int. J. Intell. Syst..

Exception Rule Mining with a Relative Interestingness Measure

Hongjun Lu, Huan Liu, Einoshin Suzuki, 2000, PAKDD.

Improving Efficiency of Frequent Query Discovery by Eliminating Non-relevant Candidates

Einoshin Suzuki, Jérôme Maloberti, Einoshin Suzuki, 2003, Discovery Science.

Finding the k-Most Abnormal Subgraphs from a Single Graph

Einoshin Suzuki, Bin-Hui Chou, JianBin Wang, 2009, Discovery Science.

A Parameter-Free Method for Discovering Generalized Clusters in a Network

Einoshin Suzuki, Bin-Hui Chou, Hiroshi Hirai, 2011, Discovery Science.

Distributed Multi-objective GA for Generating Comprehensive Pareto Front in Deceptive Optimization Problems

Einoshin Suzuki, Shin Ando, S. Ando, 2006, 2006 IEEE International Conference on Evolutionary Computation.

Topic modeling for sequential documents based on hybrid inter-document topic dependency

Einoshin Suzuki, Bin Tong, Hiroto Saigo, 2021, Journal of Intelligent Information Systems.

Mining Financial Data with Scheduled Discovery of Exception Rules

Einoshin Suzuki, Einoshin Suzuki, 2000 .

Scheduled Discovery of Exception Rules

Einoshin Suzuki, Einoshin Suzuki, 1999, Discovery Science.

Mini-Car-Soccer as a testbed for granular computing

Einoshin Suzuki, Yukihiro Nakamura, Masanori Yoshinaga, 2005, 2005 IEEE International Conference on Granular Computing.

Exception Rule Mining with a RelativeInterestingness

Hongjun Lu, Huan Liu, Einoshin Suzuki, 2000 .

Exceptional Knowledge Discovery in Databases Based on Information Theory

Masamichi Shimura, Einoshin Suzuki, Einoshin Suzuki, 1996, KDD.

On the Feasibility of Discovering Meta-Patterns from a Data Ensemble

Einoshin Suzuki, Einoshin Suzuki, 2015, Discovery Science.

Intelligent Data Analysis by a Home-Use Human Monitoring Robot

Einoshin Suzuki, Asuki Kouno, Shinsuke Sugaya, 2012, IDA.

Mining Peculiar Compositions of Frequent Substrings from Sparse Text Data Using Background Texts

Daisuke Ikeda, Einoshin Suzuki, Einoshin Suzuki, 2009, ECML/PKDD.

Discovering Action Rules That Are Highly Achievable from Massive Data

Einoshin Suzuki, Einoshin Suzuki, 2009, PAKDD.

Data Mining Methods for Discovering Interesting Exceptions from an Unsupervised Table

Einoshin Suzuki, Einoshin Suzuki, 2006, J. Univers. Comput. Sci..

Discovering Interesting Exception Rules with Rule Pair

Einoshin Suzuki, Einoshin Suzuki, 2004 .

Fast Clustering for Time-series Data with Average-time-sequence-vector Generation Based on Dynamic Time Warping

Einoshin Suzuki, Yuu Yamada, Kazuki Nakamoto, 2003 .

Undirected Discovery of Interesting Exception Rules

Einoshin Suzuki, Einoshin Suzuki, 2002, Int. J. Pattern Recognit. Artif. Intell..

Data Squashing for Speeding Up Boosting-Based Outlier Detection

Einoshin Suzuki, Shutaro Inatani, Einoshin Suzuki, 2002, ISMIS.

In Pursuit of Interesting Patterns with Undirected Discovery of Exception Rules

Einoshin Suzuki, Einoshin Suzuki, 2002, Progress in Discovery Science.

Worst-Case Analysis of Rule Discovery

Einoshin Suzuki, Einoshin Suzuki, 2001, Discovery Science.

Issues in Organizing a Successful Knowledge Discovery Contest

Einoshin Suzuki, Einoshin Suzuki, 2000, Discovery Science.

Visualizing Discovered Rule Sets with Visual Graphs Based on Compressed Entropy Density

Einoshin Suzuki, Hiroki Ishihara, Einoshin Suzuki, 1999, RSFDGrC.

Logic-based approach to expert systems in chemistry

Tatsuya Akutsu, Setsuo Ohsuga, Einoshin Suzuki, 1991, Knowl. Based Syst..

Ensemble anomaly detection from multi-resolution trajectory features

S. Ando, Einoshin Suzuki, Y. Seki, 2013, Data Mining and Knowledge Discovery.

Person re-identification using CNN features learned from combination of attributes

Tetsu Matsukawa, Einoshin Suzuki, Einoshin Suzuki, 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).

Hierarchical Gaussian Descriptor for Person Re-identification

Takahiro Okabe, Yoichi Sato, Tetsu Matsukawa, 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

IAT'06 and WI'06 Conference Organization

Marcin S. Szczuka, E. Feigenbaum, Xiaowen Chu, 2006 .

Decision-tree Induction from Time-series Data Based on a Standard-example Split Test

Einoshin Suzuki, Katsuhiko Takabayashi, Yuu Yamada, 2003, ICML.

Autonomous Discovery of Reliable Exception Rules

Einoshin Suzuki, Einoshin Suzuki, 1997, KDD.

Compression-Based Measures for Mining Interesting Rules

Einoshin Suzuki, Einoshin Suzuki, 2009, IEA/AIE.

Unifying Framework for Rule Semantics: Application to Gene Expression Data

Jean-Marc Petit, Einoshin Suzuki, Marie Pailloux, 2007, Fundam. Informaticae.

Interestingness Measures - Limits, Desiderata, and Recent Results -

Einoshin Suzuki, Einoshin Suzuki, 2009 .

Compact Coding for Hyperplane Classifiers in Heterogeneous Environment

Hao Shao, Einoshin Suzuki, Bin Tong, 2011, ECML/PKDD.

Negative Encoding Length as a Subjective Interestingness Measure for Groups of Rules

Einoshin Suzuki, Einoshin Suzuki, 2009, PAKDD.

Semi-Supervised Few-Shot Classification with Deep Invertible Hybrid Models pdf

Tetsu Matsukawa, Einoshin Suzuki, Yusuke Ohtsubo, 2021, ArXiv.

Hierarchical Gaussian Descriptors with Application to Person Re-Identification

Takahiro Okabe, Yoichi Sato, Tetsu Matsukawa, 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Context-Aware Latent Dirichlet Allocation for Topic Segmentation

Tetsu Matsukawa, Einoshin Suzuki, Hiroto Saigo, 2020, PAKDD.

Extended MDL principle for feature-based inductive transfer learning

Einoshin Suzuki, Bin Tong, Hao Shao, 2012, Knowledge and Information Systems.

Convolutional Feature Transfer via Camera-Specific Discriminative Pooling for Person Re-Identification

Tetsu Matsukawa, Einoshin Suzuki, Einoshin Suzuki, 2021, 2020 25th International Conference on Pattern Recognition (ICPR).

Judging Instinct Exploitation in Statistical Data Explanations Based on Word Embedding

Einoshin Suzuki, Kang Zhang, Hiroaki Shinden, 2022, AIES.

Hybrid Context-Aware Word Sense Disambiguation in Topic Modeling based Document Representation

Einoshin Suzuki, Wenbo Li, 2020, 2020 IEEE International Conference on Data Mining (ICDM).

Detecting Anomalies from Human Activities by an Autonomous Mobile Robot based on "Fast and Slow" Thinking

Tetsu Matsukawa, Einoshin Suzuki, Yusuke Hatae, 2021, VISIGRAPP.

Strategy Diagram for Identifying Play Strategies in Multi-view Soccer Video Data

Einoshin Suzuki, Yukihiro Nakamura, Shin Ando, 2006, Discovery Science.

Region Anomaly Detection via Spatial and Semantic Attributed Graph in Human Monitoring

Muhammad Fikko Fadjrimiratno, Einoshin Suzuki, Kang Zhang, 2023, Sensors.

Query by Committee in a Heterogeneous Environment

Hao Shao, Einoshin Suzuki, Bin Tong, 2012, ADMA.

Feature-based Inductive Transfer Learning through Minimum Encoding

Hao Shao, Einoshin Suzuki, Einoshin Suzuki, 2011, SDM.

An Information Theoretic Approach to Detection of Minority Subsets in Database

Einoshin Suzuki, Shin Ando, S. Ando, 2006, Sixth International Conference on Data Mining (ICDM'06).

On-Board Evolutionary Algorithm and Off-Line Rule Discovery for Column Formation in Swarm Robotics

Michèle Sebag, Marc Schoenauer, Einoshin Suzuki, 2011, 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology.

Retraining: A Simple Way to Improve the Ensemble Accuracy of Deep Neural Networks for Image Classification

Tetsu Matsukawa, Einoshin Suzuki, Kaikai Zhao, 2018, 2018 24th International Conference on Pattern Recognition (ICPR).

Transfer dimensionality reduction by Gaussian process in parallel

T. H. Nguyen, Einoshin Suzuki, Junbin Gao, 2013, Knowledge and Information Systems.

Discovery of Surprising Exception Rules Based on Intensity of Implication

Einoshin Suzuki, Yves Kodratoff, Einoshin Suzuki, 1998, PKDD.

Facial Expression Data Constructed with Kinect and Their Clustering Stability

Wei Chen, Einoshin Suzuki, Kaikai Zhao, 2014, AMT.

Probabilistic Two-Level Anomaly Detection for Correlated Systems

Einoshin Suzuki, Tetsuro Morimura, Tsuyoshi Idé, 2014, ECAI.

Towards Facilitating the Development of Monitoring Systems with Low-Cost Autonomous Mobile Robots

Jean-Marc Petit, Einoshin Suzuki, Vasile-Marian Scuturici, 2013, ISIP.

Detecting interesting exceptions from medical test data with visual summarization

Einoshin Suzuki, Takeshi Watanabe, Katsuhiko Takabayashi, 2003, Third IEEE International Conference on Data Mining.

Simulating Swarm Robots for Collision Avoidance Problem Based on a Dynamic Bayesian Network

Einoshin Suzuki, Shigeru Takano, Hiroshi Hirai, 2009, ECAL.

Toward a novel design of swarm robots based on the dynamic Bayesian network

Hiroshi Hirai, Einoshin Suzuki, Shigeru Takano, 2009 .

Sample-Efficient Goal-Conditioned Reinforcement Learning via Predictive Information Bottleneck for Goal Representation Learning

Einoshin Suzuki, Qiming Zou, 2023, 2023 IEEE International Conference on Robotics and Automation (ICRA).

Hidden Fatigue Detection for a Desk Worker Using Clustering of Successive Tasks

Einoshin Suzuki, Yutaka Deguchi, Einoshin Suzuki, 2015, AmI.

Statistical Implicative Analysis, Theory and Applications

Fabrice Guillet, Einoshin Suzuki, Filippo Spagnolo, 2008, Statistical Implicative Analysis.

2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology: WI-IAT 2015: December 6-9, Singapore: Proceedings

Yuefeng Li, Ah-Hwee Tan, Ee-peng Lim, 2016 .

Hierarchical Gaussian Descriptors with Application to Person Re-Identification

Einoshin Suzuki, Yoichi Sato, Takahiro Okabe, 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Harnessing GAN with Metric Learning for One-Shot Generation on a Fine-Grained Category

Tetsu Matsukawa, Einoshin Suzuki, Yusuke Ohtsubo, 2019, 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI).

Web Intelligence and Intelligent Agent Technology

Einoshin Suzuki, Jean-Marc Petit, J. Hübner, 2011 .