Kenji Yamanishi

According to our database1, Kenji Yamanishi authored at least 121 papers between 1991 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Dimensionality selection for hyperbolic embeddings using decomposed normalized maximum likelihood code-length.
Knowl. Inf. Syst., December, 2023

Detecting signs of model change with continuous model selection based on descriptive dimensionality.
Appl. Intell., November, 2023

Network Change Detection Based on Random Walk in Latent Space.
IEEE Trans. Knowl. Data Eng., June, 2023

Adaptive Topological Feature via Persistent Homology: Filtration Learning for Point Clouds.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Tight and fast generalization error bound of graph embedding in metric space.
Proceedings of the International Conference on Machine Learning, 2023

Dimensionality and Curvature Selection of Graph Embedding using Decomposed Normalized Maximum Likelihood Code-Length.
Proceedings of the IEEE International Conference on Data Mining, 2023

GMMDA: Gaussian Mixture Modeling of Graph in Latent Space for Graph Data Augmentation.
Proceedings of the IEEE International Conference on Data Mining, 2023

Balancing Summarization and Change Detection in Graph Streams.
Proceedings of the IEEE International Conference on Data Mining, 2023

Learning with the Minimum Description Length Principle
Springer, ISBN: 978-981-99-1789-1, 2023

2022
Mixture Complexity and Its Application to Gradual Clustering Change Detection.
Entropy, 2022

Dimensionality Selection of Hyperbolic Graph Embeddings using Decomposed Normalized Maximum Likelihood Code-Length.
Proceedings of the IEEE International Conference on Data Mining, 2022

Change Detection with Probabilistic Models on Persistence Diagrams.
Proceedings of the IEEE International Conference on Data Mining, 2022

2021
MixSp: A Framework for Embedding Heterogeneous Information Networks With Arbitrary Number of Node and Edge Types.
IEEE Trans. Knowl. Data Eng., 2021

Fourier-Analysis-Based Form of Normalized Maximum Likelihood: Exact Formula and Relation to Complex Bayesian Prior.
IEEE Trans. Inf. Theory, 2021

Summarizing Finite Mixture Model with Overlapping Quantification.
Entropy, 2021

Word2vec Skip-Gram Dimensionality Selection via Sequential Normalized Maximum Likelihood.
Entropy, 2021

Multi-label learning with missing and completely unobserved labels.
Data Min. Knowl. Discov., 2021

Generalization Bounds for Graph Embedding Using Negative Sampling: Linear vs Hyperbolic.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

PAMI: A Computational Module for Joint Estimation and Progression Prediction of Glaucoma.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Generalization Error Bound for Hyperbolic Ordinal Embedding.
Proceedings of the 38th International Conference on Machine Learning, 2021

Graph Summarization with Latent Variable Probabilistic Models.
Proceedings of the Complex Networks & Their Applications X - Volume 2, Proceedings of the Tenth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2021, Madrid, Spain, November 30, 2021

Detecting Gradual Structure Changes of Non-parametric Distributions via Kernel Complexity.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020
Grafting for combinatorial binary model using frequent itemset mining.
Data Min. Knowl. Discov., 2020

A Novel Global Spatial Attention Mechanism in Convolutional Neural Network for Medical Image Classification.
CoRR, 2020

Change Sign Detection with Differential MDL Change Statistics and its Applications to COVID-19 Pandemic Analysis.
CoRR, 2020

Online Robust and Adaptive Learning from Data Streams.
CoRR, 2020

Discovering Latent Class Labels for Multi-Label Learning.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Detecting Hierarchical Changes in Latent Variable Models.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

2019
Correction to Efficient Computation of Normalized Maximum Likelihood Codes for Gaussian Mixture Models With Its Applications to Clustering.
IEEE Trans. Inf. Theory, 2019

Detecting Metachanges in Data Streams from the Viewpoint of the MDL Principle.
Entropy, 2019

Model Selection for Non-Negative Tensor Factorization with Minimum Description Length.
Entropy, 2019

The decomposed normalized maximum likelihood code-length criterion for selecting hierarchical latent variable models.
Data Min. Knowl. Discov., 2019

Descriptive Dimensionality and Its Characterization of MDL-based Learning and Change Detection.
CoRR, 2019

Glaucoma Progression Prediction Using Retinal Thickness via Latent Space Linear Regression.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Modern MDL meets Data Mining Insights, Theory, and Practice.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Attributed Subspace Clustering.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Detecting Model Changes and their Early Warning Signals Using MDL Change Statistics.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Adaptive Minimax Regret against Smooth Logarithmic Losses over High-Dimensional l1-Balls via Envelope Complexity.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Hyperbolic Ordinal Embedding.
Proceedings of The 11th Asian Conference on Machine Learning, 2019

Orderly Subspace Clustering.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Traffic Risk Mining From Heterogeneous Road Statistics.
IEEE Trans. Intell. Transp. Syst., 2018

Model Change Detection With the MDL Principle.
IEEE Trans. Inf. Theory, 2018

High-dimensional penalty selection via minimum description length principle.
Mach. Learn., 2018

Adaptive Minimax Regret against Smooth Logarithmic Losses over High-Dimensional ε<sub>1</sub>-Balls via Envelope Complexity.
CoRR, 2018

Stable Geodesic Update on Hyperbolic Space and its Application to Poincare Embeddings.
CoRR, 2018

Estimating Glaucomatous Visual Sensitivity from Retinal Thickness with Pattern-Based Regularization and Visualization.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Exact Calculation of Normalized Maximum Likelihood Code Length Using Fourier Analysis.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Ranking Preserving Nonnegative Matrix Factorization.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Detecting Latent Structure Uncertainty with Structural Entropy.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017
Online detection of continuous changes in stochastic processes.
Int. J. Data Sci. Anal., 2017

Grafting for Combinatorial Boolean Model using Frequent Itemset Mining.
CoRR, 2017

An Upper Bound on Normalized Maximum Likelihood Codes for Gaussian Mixture Models.
CoRR, 2017

Sparse Graphical Modeling via Stochastic Complexity.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Decomposed Normalized Maximum Likelihood Codelength Criterion for Selecting Hierarchical Latent Variable Models.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Multi-view Learning over Retinal Thickness and Visual Sensitivity on Glaucomatous Eyes.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Latent Dimensionality Estimation for Probabilistic Canonical Correlation Analysis Using Normalized Maximum Likelihood Code-Length.
Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017

Discovering potential traffic risks in Japan using a supervised learning approach.
Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

Detecting changes in streaming data with information-theoretic windowing.
Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016
Predicting Glaucoma Visual Field Loss by Hierarchically Aggregating Clustering-based Predictors.
CoRR, 2016

Rank Selection for Non-negative Matrix Factorization with Normalized Maximum Likelihood Coding.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Structure Selection for Convolutive Non-negative Matrix Factorization Using Normalized Maximum Likelihood Coding.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Temporal Network Change Detection Using Network Centralities.
Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics, 2016

Traffic Risk Mining Using Partially Ordered Non-Negative Matrix Factorization.
Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics, 2016

Web Behavior Analysis Using Sparse Non-Negative Matrix Factorization.
Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics, 2016

Predicting Glaucomatous Progression with Piecewise Regression Model from Heterogeneous Medical Data.
Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016), 2016

Detecting gradual changes from data stream using MDL-change statistics.
Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015
Early detection of persistent topics in social networks.
Soc. Netw. Anal. Min., 2015

Sequential network change detection with its applications to ad impact relation analysis.
Data Min. Knowl. Discov., 2015

Discovery of Glaucoma Progressive Patterns Using Hierarchical MDL-Based Clustering.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

On-line detection of continuous changes in stochastic processes.
Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015

2014
Discovering Emerging Topics in Social Streams via Link-Anomaly Detection.
IEEE Trans. Knowl. Data Eng., 2014

Data Fusion Using Restricted Boltzmann Machines.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

Extracting Latent Skills from Time Series of Asynchronous and Incomplete Examinations.
Proceedings of the 7th International Conference on Educational Data Mining, 2014

Predicting glaucoma progression using multi-task learning with heterogeneous features.
Proceedings of the 2014 IEEE International Conference on Big Data (IEEE BigData 2014), 2014

2013
Efficient Computation of Normalized Maximum Likelihood Codes for Gaussian Mixture Models With Its Applications to Clustering.
IEEE Trans. Inf. Theory, 2013

Graph Partitioning Change Detection Using Tree-Based Clustering.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

Quantitative Prediction of Glaucomatous Visual Field Loss from Few Measurements.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

Extracting Time-evolving Latent Skills from Examination Time Series.
Proceedings of the 6th International Conference on Educational Data Mining, 2013

An NML-based model selection criterion for general relational data modeling.
Proceedings of the 2013 IEEE International Conference on Big Data (IEEE BigData 2013), 2013

2012
Normalized Maximum Likelihood Coding for Exponential Family with Its Applications to Optimal Clustering
CoRR, 2012

Detecting changes of clustering structures using normalized maximum likelihood coding.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Comparison of dynamic model selection with infinite HMM for statistical model change detection.
Proceedings of the 2012 IEEE Information Theory Workshop, 2012

An MDL-based change-detection algorithm with its applications to learning piecewise stationary memoryless sources.
Proceedings of the 2012 IEEE Information Theory Workshop, 2012

2011
Real-Time Change-Point Detection Using Sequentially Discounting Normalized Maximum Likelihood Coding.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2011

Efficient computation of normalized maximum likelihood coding for Gaussian mixtures with its applications to optimal clustering.
Proceedings of the 2011 IEEE International Symposium on Information Theory Proceedings, 2011

2009
Latent variable mining with its applications to anomalous behavior detection.
Stat. Anal. Data Min., 2009

Mining abnormal patterns from heterogeneous time-series with irrelevant features for fault event detection.
Stat. Anal. Data Min., 2009

Network anomaly detection based on Eigen equation compression.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

2007
Dynamic Model Selection With its Applications to Novelty Detection.
IEEE Trans. Inf. Theory, 2007

2006
A Unifying Framework for Detecting Outliers and Change Points from Time Series.
IEEE Trans. Knowl. Data Eng., 2006

2005
Dynamic syslog mining for network failure monitoring.
Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2005

2004
On-Line Unsupervised Outlier Detection Using Finite Mixtures with Discounting Learning Algorithms.
Data Min. Knowl. Discov., 2004

Tracking dynamics of topic trends using a finite mixture model.
Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

Dynamic model selection with its applications to computer security.
Proceedings of the 2004 IEEE Information Theory Workshop, 2004

2003
Topic analysis using a finite mixture model.
Inf. Process. Manag., 2003

Distributed cooperative mining for information consortia.
Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 24, 2003

2002
Text classification using ESC-based stochastic decision lists.
Inf. Process. Manag., 2002

Mining Open Answers in Questionnaire Data.
IEEE Intell. Syst., 2002

A unifying framework for detecting outliers and change points from non-stationary time series data.
Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2002

Mining product reputations on the Web.
Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2002

2001
Discovering outlier filtering rules from unlabeled data: combining a supervised learner with an unsupervised learner.
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, 2001

Mining from open answers in questionnaire data.
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, 2001

1999
Distributed Cooperative Bayesian Learning Strategies.
Inf. Comput., 1999

Extended Stochastic Complexity and Minimax Relative Loss Analysis.
Proceedings of the Algorithmic Learning Theory, 10th International Conference, 1999

1998
A Decision-Theoretic Extension of Stochastic Complexity and Its Applications to Learning.
IEEE Trans. Inf. Theory, 1998

Minimax Relative Loss Analysis for Sequential Prediction Algorithms Using Parametric Hypotheses.
Proceedings of the Eleventh Annual Conference on Computational Learning Theory, 1998

1997
On-Line Maximum Likelihood Prediction with Respect to General Loss Functions.
J. Comput. Syst. Sci., 1997

Document Classification Using a Finite Mixture Model.
Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and 8th Conference of the European Chapter of the Association for Computational Linguistics, 1997

1996
A Randomized Approximation of the MDL for Stochastic Models with Hidden Variables.
Proceedings of the Ninth Annual Conference on Computational Learning Theory, 1996

1995
A Loss Bound Model for On-Line Stochastic Prediction Algorithms
Inf. Comput., May, 1995

Probably Almost Discriminative Learning.
Mach. Learn., 1995

alpha-Helix region prediction with stochastic rule learning.
Comput. Appl. Biosci., 1995

Randomized Approximate Aggregating Strategies and Their Applications to Prediction and Discrimination.
Proceedings of the Eigth Annual Conference on Computational Learning Theory, 1995

1994
The Minimum <i>L</i>-Complexity Algorithm and its Applications to Learning Non-Parametric Rules.
Proceedings of the Seventh Annual ACM Conference on Computational Learning Theory, 1994

1993
Learning non-parametric smooth rules by stochastic rules with finite partitioning.
Proceedings of the First European Conference on Computational Learning Theory, 1993

On Polynomial-Time Probably almost Discriminative Learnability.
Proceedings of the Sixth Annual ACM Conference on Computational Learning Theory, 1993

1992
A Learning Criterion for Stochastic Rules.
Mach. Learn., 1992

Protein Secondary Structure Prediction Based on Stochastic-Rule Learning.
Proceedings of the Algorithmic Learning Theory, Third Workshop, 1992

1991
Learning Stochastic Motifs from Genetic Sequences.
Proceedings of the Eighth International Workshop (ML91), 1991

A Loss Bound Model for On-Line Stochastic Prediction Strategies.
Proceedings of the Fourth Annual Workshop on Computational Learning Theory, 1991

Learning non-parametric densities by finite-dimensional parametric hypotheses.
Proceedings of the Algorithmic Learning Theory, 2nd International Workshop, 1991


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