I am a research associate working with Arthur Gretton
at the Gatsby Unit.
My main research interests are information theory (ITE toolbox
), statistical machine learning, empirical processes, kernel methods.
I am also working on applications including remote sensing (sustainability), distribution regression, hypothesis testing, structured sparsity, independent
subspace analysis and its extensions, collaborative filtering.
- Paper (+):
- TR: Interpretable Distribution Features with Maximum Testing Power. [paper, code; May 24, 2016]
- Paper accepted at ICML-2016:Data-Efficient ML workshop [paper, spotlight, poster, code; May 6, 2016].
- Submission accepted at ISNPS 2016 [abstract, slides, code; Mar. 17, 2016].
TR: Learning Theory for Distribution Regression. [paper, code; Jan. 21, 2016]
- Paper@Theory of Big Data Workshop [abstract, poster, Dec. 4, 2015]
- 3 papers at NIPS-2015 [Sept. 4, 2015].
- Invited talk (+):
- PRNI-2016 [abstract, slides; Jun. 22-24, 2016]
- University of California, San Diego [slides, code; Apr. 25, 2016]
- MASCOT-NUM 2016@IMT, INSA Toulouse [abstract, slides, code; Mar. 23-25, 2016]
- MPI Tübingen: Special Symposium on Intelligent Systems. [abstract, slides, code; Mar. 15-16, 2016]
- Else (+):