Kazuho Watanabe

Orcid: 0000-0001-6357-5141

According to our database1, Kazuho Watanabe authored at least 58 papers between 2004 and 2024.

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

Timeline

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On csauthors.net:

Bibliography

2024
Unbiased Estimating Equation and Latent Bias Under f-Separable Bregman Distortion Measures.
IEEE Trans. Inf. Theory, August, 2024

Unbiased Estimating Equation on Inverse Divergence and its Conditions.
Proceedings of the IEEE International Symposium on Information Theory, 2024

2022
Gaze-driven placement of items for proactive visual exploration.
J. Vis., 2022

Approximate Empirical Bayes Estimation of the Regularization Parameter in ℓ1 Trend Filtering.
Proceedings of the IEEE International Symposium on Information Theory, 2022

2021
Generalized Dirichlet-process-means for <i>f</i>-separable distortion measures.
Neurocomputing, 2021

Unified Likelihood Ratio Estimation for High- to Zero-Frequency <i>N</i>-Grams.
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2021

Unified Likelihood Ratio Estimation for High- to Zero-frequency N-grams.
CoRR, 2021

Statistical Learning of the Insensitive Parameter in Support Vector Models.
Proceedings of the IEEE International Symposium on Information Theory, 2021

2020
Context-aware placement of items with gaze-based interaction.
Proceedings of the VINCI 2020: The 13th International Symposium on Visual Information Communication and Interaction, 2020

Unbiased Estimation Equation under f-Separable Bregman Distortion Measures.
Proceedings of the IEEE Information Theory Workshop, 2020

Discrete Optimal Reconstruction Distributions for Itakura-Saito Distortion Measure.
Proceedings of the IEEE International Symposium on Information Theory, 2020

Multi-Decoder RNN Autoencoder Based on Variational Bayes Method.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019
Generalized Dirichlet-process-means for f-separable distortion measures.
CoRR, 2019

Minimax Online Prediction of Varying Bernoulli Process under Variational Approximation.
Proceedings of The 11th Asian Conference on Machine Learning, 2019

2018
Empirical Bayes Estimation for <i>L</i><sub>1</sub> Regularization: A Detailed Analysis in the One-Parameter Lasso Model.
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2018

Generalized Dirichlet-Process-Means for Robust and Maximum Distortion Criteria.
Proceedings of the International Symposium on Information Theory and Its Applications, 2018

Sparse Regression Code with Sparse Dictionary for Absolute Error Criterion.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Automatic DNN Node Pruning Using Mixture Distribution-based Group Regularization.
Proceedings of the 19th Annual Conference of the International Speech Communication Association, 2018

2017
Rate-Distortion Bounds for Kernel-Based Distortion Measures.
Entropy, 2017

Projection to Mixture Families and Rate-Distortion Bounds with Power Distortion Measures.
Entropy, 2017

Rate-distortion tradeoffs under Kernel-based distortion measures.
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Making many-to-many parallel coordinate plots scalable by asymmetric biclustering.
Proceedings of the 2017 IEEE Pacific Visualization Symposium, 2017

2016
Rate-Distortion Functions for Gamma-Type Sources Under Absolute-Log Distortion Measure.
IEEE Trans. Inf. Theory, 2016

Rate-Distortion Bounds for <i>ε</i>-Insensitive Distortion Measures.
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2016

Constant-width rate-distortion bounds for power distortion measures.
Proceedings of the 2016 IEEE Information Theory Workshop, 2016

2015
Variational Inference With ARD Prior for NIRS Diffuse Optical Tomography.
IEEE Trans. Neural Networks Learn. Syst., 2015

Variational Bayesian Inference Algorithms for Infinite Relational Model of Network Data.
IEEE Trans. Neural Networks Learn. Syst., 2015

Entropic risk minimization for nonparametric estimation of mixing distributions.
Mach. Learn., 2015

Achievability of asymptotic minimax regret by horizon-dependent and horizon-independent strategies.
J. Mach. Learn. Res., 2015

Vector quantization based on ε-insensitive mixture models.
Neurocomputing, 2015

Biclustering multivariate data for correlated subspace mining.
Proceedings of the 2015 IEEE Pacific Visualization Symposium, 2015

2014
Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Spectral-Based Contractible Parallel Coordinates.
Proceedings of the 18th International Conference on Information Visualisation, 2014

Bayesian properties of normalized maximum likelihood and its fast computation.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

2013
Rate-Distortion Bounds for an Epsilon-Insensitive Distortion Measure
CoRR, 2013

Rate-distortion bounds for an ε-insensitive distortion measure.
Proceedings of the 2013 IEEE Information Theory Workshop, 2013

Rate-distortion function for gamma sources under absolute-log distortion measure.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

Vector Quantization Using Mixture of Epsilon-Insensitive Components.
Proceedings of the Neural Information Processing - 20th International Conference, 2013

Achievability of Asymptotic Minimax Regret in Online and Batch Prediction.
Proceedings of the Asian Conference on Machine Learning, 2013

2012
An alternative view of variational Bayes and asymptotic approximations of free energy.
Mach. Learn., 2012

Packet loss rate estimation with active and passive measurements.
Proceedings of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2012

2011
Divergence measures and a general framework for local variational approximation.
Neural Networks, 2011

Approximate Bayesian Estimation of Varying Binomial Process.
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2011

Phase diagrams of a variational Bayesian approach with ARD prior in NIRS-DOT.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

2010
Phase Transition of Variational Bayes Learning in Bernoulli Mixture.
Aust. J. Intell. Inf. Process. Syst., 2010

2009
Variational Bayesian Mixture Model on a Subspace of Exponential Family Distributions.
IEEE Trans. Neural Networks, 2009

Upper bound for variational free energy of Bayesian networks.
Mach. Learn., 2009

Transfer Matrix Method for Instantaneous Spike Rate Estimation.
IEICE Trans. Inf. Syst., 2009

2008
Clustering on a Subspace of Exponential Family Using Variational Bayes Method.
Proceedings of the 2008 International Conference on Information Theory and Statistical Learning, 2008

Firing Rate Estimation Using an Approximate Bayesian Method.
Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008

2007
Stochastic complexity for mixture of exponential families in generalized variational Bayes.
Theor. Comput. Sci., 2007

Stochastic complexities of general mixture models in variational Bayesian learning.
Neural Networks, 2007

2006
Stochastic Complexities of Gaussian Mixtures in Variational Bayesian Approximation.
J. Mach. Learn. Res., 2006

Upper Bounds for Variational Stochastic Complexities of Bayesian Networks.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2006

Free Energy of Stochastic Context Free Grammar on Variational Bayes.
Proceedings of the Neural Information Processing, 13th International Conference, 2006

2005
Variational Bayesian Stochastic Complexity of Mixture Models.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Stochastic Complexity for Mixture of Exponential Families in Variational Bayes.
Proceedings of the Algorithmic Learning Theory, 16th International Conference, 2005

2004
Estimation of the Data Region Using Extreme-Value Distributions.
Proceedings of the Algorithmic Learning Theory, 15th International Conference, 2004


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