Publications

Publications

• Selected Journals / Conference papers
  • Eugene Ndiaye, Tam Le, Olivier Fercoq, Joseph Salmon, Ichiro Takeuchi, Safe Grid Search with Optimal Complexity, to appear in International Conference on Machine Learning (ICML), US, 2019. [ArXiv/Code] (Acceptance rate: 773/3424=22.6%)
  • Tam Le, Makoto Yamada, Persistence Fisher Kernel: A Riemannian Manifold Kernel for Persistence Diagrams, The 32nd Conference on Neural Information Processing Systems (NeurIPS), Canada, 2018. [PDF/Supplemental/PROJECT/POSTER] (Acceptance rate: 1011/4856=20.8%)
  • Tam Le, Marco Cuturi, Unsupervised Riemannian Metric Learning for Histograms Using Aitchison Transformations, International Conference on Machine Learning (ICML), France, 2015. [VideoLecture/PDF/Supplemental/SLIDE/POSTER] (Acceptance rate: 270/1037 = 26.0%)
  • Tam Le, Marco Cuturi, Adaptive Euclidean Maps for Histograms: Generalized Aitchison Embeddings, Machine Learning Journal (MLJ), 2014. [PDF/PROJECT]
• Preprints / Technical reports
  • Tam Le, Makoto Yamada, Kenji Fukumizu, Marco Cuturi, Tree-Sliced Variants of Wasserstein Distances, ArXiv 1902.00342 [ArXiv]
  • Tatsuya Shiraishi, Tam Le, Hisashi Kashima, Makoto Yamada, Topological Bayesian Optimization with Persistence Diagrams, ArXiv 1902.09722 [ArXiv]
• Other journals / conference papers
  • Randy Jalem, Masanobu Nakayama, Yusuke Noda, Tam Le, Ichiro Takeuchi, Yoshitaka Tateyama, Hisatsugu Yamazaki, A General Representation Scheme for Crystalline Solids based on Voronoi-Tessellation Real Feature Values and Atomic Property Data, Science and Technology of Advance Materials Journal, 2018. [PDF]
  • Tam Le, Marco Cuturi, Generalized Aitchison Embeddings for Histograms, The 5th Asian Conference on Machine Learning (ACML), JMLR vol.29, Australia, 2013 (oral). [PDF/SLIDE/PROJECT] (Acceptance rate: 31%, oral paper rate: 9.7%)
  • Tam Le, Yousun Kang, Akihiro Sugimoto, Image Categorization Using Hierarchical Spatial Matching Kernel, Journal of the Institute of Image Electronics Engineers of Japan (IIEEJ), Vol. 42, No. 2, 2013. [PDF/PROJECT]
  • Tam Le, Yousun Kang, Akihiro Sugimoto, Son Tran, Thuc Nguyen, Hierarchical Spatial Matching Kernel for Image Categorization, International Conference on Image Processing and Recognition (ICIAR), LNCS 6753, Canada, 2011 (oral). [PDF/SLIDE/PROJECT] (Acceptance rate: 57%, oral paper rate: 25%)
  • Tam Le, Son Tran, Seichii Mita, Thuc Nguyen, Realtime Traffic Sign Detection Using Color and Shape-Based Features, The 2nd Asian Conference on Intelligent Information and Database Systems (ACIIDS), LNAI 5991, Vietnam, 2010 (oral). [PDF/PROJECT]
• Thesis
  • Tam Le, Geometry-Aware Learning Algorithms for Histogram Data Using Adaptive Metric Embeddings and Kernel Functions, PhD thesis, Kyoto University, Japan, 2015. [PDF]

Talks / Workshop Posters

• Workshop Posters
  • 2019, Tree-Sliced Approximation of Wasserstein Distances, Korea-Japan Machine Learning workshop, Korea. [Poster]
  • 2019, Persistence Fisher Kernel: A Riemannian Manifold Kernel for Persistence Diagrams, Korea-Japan Machine Learning workshop, Korea.
  • 2018, Persistence Fisher Kernel: A Riemannian Manifold Kernel for Persistence Diagrams, ICML workshops (Geometry in Machine Learning), Sweden. [PDF / a longer version at NIPS'18]
  • 2018, Riemannian Manifold Kernel for Persistence Diagrams, Transatlantic and Transpacific Workshop on Machine Learning and Discrete Optimization, USA.
  • Eugene Ndiaye, Tam Le, Olivier Fercoq, Joseph Salmon, Ichiro Takeuchi, Optimal Approximation for regularization and validation path. Journees SMAI MODE, France, 2018.
  • Eugene Ndiaye, Tam Le, Olivier Fercoq, Joseph Salmon, Ichiro Takeuchi, GridSearch: Complexite et Garantie pour la Validation (GridSearch: Complexity and Guarantee for Validation). Conference Sur L'Apprentissage Automatique (CAp), France, 2018.
• Talks
  • 2016, Geometry-Aware Metric Learning for Histograms, MI2I Open Seminar Series at National Institute for Materials Science (NIMS), Japan. [SLIDE]
  • 2015, Metric Learning for Histograms, Nagoya Institute of Technology, Japan.
  • 2015, Unsupervised Riemannian Metric Learning for Histograms, Bioinformatics Center, Institute for Chemical Research, Kyoto University, Japan.
  • 2015, Unsupervised Riemannian Metric Learning for Histograms Using Aitchison Transformations, IST Seminar, Graduate School of Informatics, Kyoto University, Japan. [SLIDE]
  • 2014, Adaptive Euclidean Maps for Histograms: Generalized Aitchison Embeddings, Lear, INRIA Rhone-Alpes, Grenoble, France. [SLIDE]