Daniel Andrade

Last Updated :2024/06/04

Affiliations, Positions
Education and Research Center for Artificial Intelligence and Data Innovation, Associate Professor
E-mail
andradehiroshima-u.ac.jp
Self-introduction
My research covers a broad field in applied machine learning ranging from classification, natural language processing, clustering/outlier detection and uncertainty quantification in various domains (e.g. text, medical and security). My current research interests are especially in Text/Numerical Data Analysis, Model Selection, Bayesian Inference and Bayesian Statistics in general.

Basic Information

Major Professional Backgrounds

  • 2011/10/01, 2021/01/31, NEC, Central Research Laboratories, Researcher
  • 2020/04/01, Rikkyo University, Graduate School of Artificial Intelligence and Science, Visiting Associate Professor
  • 2021/02/01, Hiroshima University, Education and Research Center for Artificial Intelligence and Data Innovation, Associate Professor

Educational Backgrounds

  • University of Passau, Department of Informatics and Mathematics, Informatics, Germany, 2001/10, 2007/10
  • The University of Tokyo, Graduate School of Information Science and Technology, Computer Science, Japan, 2008/10, 2011/09
  • The Graduate University for Advanced Studies (SOKENDAI), School of Multidisciplinary Sciences, Department of Statistical Science, Statistics, 2016/04, 2019/09

Academic Degrees

  • PhD (Statistics), The Graduate University for Advanced Studies (SOKENDAI)
  • PhD (Computer Science), The University of Tokyo
  • Diploma (Informatics), University of Passau

Research Fields

  • Informatics;Principles of Informatics;Statistical science

Research Keywords

  • Machine Learning, Probabilistic Modeling, Natural Language Processing, Model Selection, Regression and Clustering Analysis, Bayesian Statistics

Affiliated Academic Societies

  • International Society for Bayesian Analysis

Educational Activity

Course in Charge

  1. 2024, Liberal Arts Education Program1, 2Term, Computer Programming
  2. 2024, Undergraduate Education, 2Term, Linear Regression Model
  3. 2024, Undergraduate Education, 4Term, Informatics and Data Science Exercise IV
  4. 2024, Undergraduate Education, 1Term, Data Science Seminar I
  5. 2024, Undergraduate Education, 2Term, Data Science Seminar II
  6. 2024, Undergraduate Education, Second Semester, Graduation Thesis
  7. 2024, Graduate Education (Master's Program) , 1Term, Special Exercises on Informatics and Data Science A
  8. 2024, Graduate Education (Master's Program) , 2Term, Special Exercises on Informatics and Data Science A
  9. 2024, Graduate Education (Master's Program) , 3Term, Special Exercises on Informatics and Data Science B
  10. 2024, Graduate Education (Master's Program) , 4Term, Special Exercises on Informatics and Data Science B
  11. 2024, Graduate Education (Master's Program) , Academic Year, Special Study on Informatics and Data Science
  12. 2024, Graduate Education (Master's Program) , 4Term, Practical Machine Learning

Research Activities

Academic Papers

  1. LOFT - Stable Training of Normalizing Flows for Variational Inference, Workshop on Tractable Probabilistic Modeling (TPM), 2023
  2. Robust Gaussian Process Regression with the Trimmed Marginal Likelihood, Proceedings of Conference on Uncertainty in Artificial Intelligence (UAI), 2023
  3. Knowledge Fusion Using Dempster-Shafer Theory and the Imprecise Dirichlet Model, Proceedings of IEEE Soft Computing in Industrial Applications (SMCia), 142-148, 2008
  4. Lower bound Bayesian networks: an efficient inference of lower bounds on probability distributions in Bayesian networks, Proceedings of Conference on Uncertainty in Artificial Intelligence (UAI), 10-18, 2009
  5. Robust Measurement and Comparison of Context Similarity for Finding Translation Pairs, Proceedings of International Conference on Computational Linguistics (COLING), 19-27, 2010
  6. Effective use of Dependency Structure for Bilingual Lexicon Creation, Proceedings of International Conference on Computational Linguistics and Intelligent Text Processing (CiCling), 80-92, 2011
  7. Learning the Optimal use of Dependency-parsing Information for Finding Translations with Comparable Corpora, Proceedings of ACL Workshop on Building and Using Comparable Corpora, 10-18, 2011
  8. Translation Acquisition Using Synonym Sets, Proceedings of Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (HLT-NAACL), 655-660, 2013
  9. Synonym Acquisition Using Bilingual Comparable Corpora, Proceedings of International Joint Conference on Natural Language Processing (IJCNLP), 1077-1081, 2013
  10. Chinese Informal Word Normalization: an Experimental Study, Proceedings of International Joint Conference on Natural Language Processing (IJCNLP), 127-135, 2013
  11. Cross-lingual Text Classification Using Topic-Dependent Word Probabilities, Proceedings of Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (HLT-NAACL), 1466-1471, 2015
  12. Analogy-based Reasoning with Memory Networks for Future Prediction, Workshop on Cognitive Computation: Integrating Neural and Symbolic Approaches (CoCo), CEUR Workshop Proceedings, 1-9, 2016
  13. Efficient Bayes Risk Estimation for Cost-Sensitive Classification, International Conference on Artificial Intelligence and Statistics (AISTATS), Proceedings of Machine Learning Research (PMLR), 3372-3381, 2019
  14. POSTER: Detecting Suspicious Processes from Log-Data via a Bayesian Block Model, Proceedings of the ACM Asia Conference on Computer and Communications Security, 922-924, 2020
  15. Statistical Extraction and Comparison of Pivot Words for Bilingual Lexicon Extension, ACM Transactions on Asian Language Information Processing (TALIP), 11(2), 1-31, 2012
  16. Analysis of the Use of Background Distribution for Naive Bayes Classifiers, Journal of Intelligent Systems, 28(2), 1-15, 2017
  17. Leveraging knowledge bases for future prediction with memory comparison networks, AI Communications, 31(6), 465-483, 2018
  18. ★, Exploiting Covariate Embeddings for Classification Using Gaussian Processes, Pattern Recognition Letters, 104(1), 8-14, 2018
  19. ★, Robust Bayesian model selection for variable clustering with the Gaussian graphical model, Statistics and Computing, 30(2), 351-376, 2020
  20. Disjunct Support Spike and Slab Priors for Variable Selection in Regression under Quasi- sparseness, Stat, 1-19, 2020
  21. Adaptive covariate acquisition for minimizing total cost of classification, MACHINE LEARNING, 110(5), 1067-1104, 202105
  22. Convex covariate clustering for classification, PATTERN RECOGNITION LETTERS, 151, 193-199, 202111

Invited Lecture, Oral Presentation, Poster Presentation

  1. Stable Training of Normalizing Flows for Variational Inference, 2023, With Invitation, English, Arizona State University
  2. Robust Methods for Gaussian Process Regression and the Trimmed Marginal Likelihood Approach, 2022, With Invitation, Japanese, Kanto Gakuin University
  3. Introduction to Statistics and Machine Learning for AI, 2017, Japanese, Public Lecture, Iida
  4. Special Seminar on Artificial Intelligence (Probabilistic Modeling), Visiting Associate Professor, 2020, Japanese, Rikkyo University
  5. Introduction to Informatics (AI Systems, ICT, Computational Theory), Visiting Associate Professor, 2020, Japanese, Rikkyo University
  6. The Basics of Feature selection in Regression Models, 2021, With Invitation, Japanese, Organization for AI Data Innovation Education and Research Initiatives, Hiroshima University
  7. Introduction to Informatics (AI Systems, ICT, Computational Theory), Visiting Associate Professor, 2021, Japanese, Rikkyo University
  8. Special Seminar on Artificial Intelligence (Probabilistic Modeling), Visiting Associate Professor, 2021, Japanese, Rikkyo University

Awards

  1. 2008/06, Best Paper Award, IEEE Soft Computing in Industrial Applications (SMCia)
  2. 2009/05, IBM Ph.D. Scholarship Award
  3. 2011/02, Best Paper Award (3rd Place), Conference on Computational Linguistics and Intelligent Text Processing (CiCling)
  4. 2016/06, IPSJ Kiyasu Special Industrial Achievement Award)
  5. 2016/06, Best Reviewer Award, Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT)
  6. 2019/09, Dean's Award, School of Multidisciplinary Sciences, SOKENDAI
  7. 2020/09, Best Reviewer Award (Top 33%), International Conference on Machine Learning (ICML)

Patented

  1. Patent, 11201404678R (SG), 2015/05, Term Synonym Acquisition Method and Term Synonym Acquisition Apparatus
  2. Patent, 11201404225W (SG), 2016/05, Term Translation Acquisition Method and Term Translation Acquisition Apparatus
  3. Patent, 11201604193Q (SG), 2016/09, Document Classification Method
  4. Patent, 09542386 (US), 2017/01, Entailment Evaluation Device, Entailment Evaluation Method and Recording Medium
  5. Patent, 06090531, 2017/02, Word Translation Acquisition Method
  6. Patent, 6281491, 2018/02, Text Mining System
  7. Patent, 10409848 (US), 2018/04, Text Mining System
  8. Patent, 6455068, 2018/12, Keyword Extraction System
  9. Patent, 6467893, 2019/01, Information Enrichment of Existing Word Embeddings
  10. Patent, 20190164072 (US), 2019/05, Inference System, Information Processing System, Inference Method, and Recording Medium
  11. Patent, 20190180192 (US), 2019/06, An Information Processing System, An Information Processing Method and a Computer Readable Storage Medium
  12. Patent, 10324971, 2019/06, Feature Weighting for Naïve Bayes Classifiers Using a Generative Model
  13. Patent, 10354010 (US), 2019/07, Incorporating Word Similarity in Bag-of-words Representations
  14. Patent, 6690713, 2020/05, Inference System

External Funds

Acceptance Results of Competitive Funds

  1. KAKENHI-C (Basic Research Funding), Computationally Feasible Confidence Regions for Bayes Factors with Iteratively Refined Normalizing Flows

Social Activities

History as Committee Members

  1. Annual Conference of the Japanese Society for Artificial Intelligence, 2021/01, 2021/06

History as Peer Reviews of Academic Papers

  1. 2024, ICML 2024 (International Conference on Machine Learning)
  2. 2023, Scientific Reports
  3. 2023, ICML 2023 (International Conference on Machine Learning)
  4. 2022, AISTATS 2022 (Artificial Intelligence and Statistics)
  5. 2022, BMC Medical Research Methodology
  6. 2021, NeurIPS 2021 (Conference on Neural Information Processing Systems)
  7. 2021, ICML 2021 (International Conference on Machine Learning)
  8. 2020, ICLR 2021 (International Conference on Learning Representations)
  9. 2020, Computational Statistics & Data Analysis
  10. 2020, ICML 2020 (International Conference on Machine Learning)
  11. 2020, IEEE Transactions on Neural Networks and Learning Systems
  12. 2018, Knowledge-Based Systems
  13. 2018, ACL 2018 (Annual Conference of the Association for Computational Linguistics) Program Committee Member
  14. 2016, NAACL HLT 2016 (Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies)
  15. 2014, IEICE Transactions on Information and Systems