Scholar
Alex Lambert
Google Scholar ID: iK4XH44AAAAJ
Postdoctoral fellow, KU Leuven
Citations & Impact
Citations
62
H-index
3
i10-index
3
Publications
11
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- Paper 'Accelerating Spectral Clustering under Fairness Constraints' accepted at ICML; paper 'Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method' accepted at ICML; part of the organizing team for the DEEPK workshop on deep learning and kernel methods at Leuven; gave a talk at the MIND/SODA team seminar on 'Robustness and sparsity through Moreau envelopes in kernel-based settings'; paper 'Extending Kernel PCA through Dualization: Sparsity, Robustness, and Fast Algorithms' accepted at ICML; paper on robust and sparse functional output regression accepted at ICML.
Research Experience
- Worked as a researcher at KU Leuven, collaborating with Johan Suykens on kernel methods and duality. Took a leave from research to work as a data engineer at Dataminded.
Education
- PhD in Machine Learning from Télécom Paris, supervised by Florence d'Alché-Buc and Zoltan Szabo. Graduated with a Master's in Data Science from Institut Polytechnique de Paris.
Background
- Research interests include: operator-valued kernels, integral operators, random features for large scale learning; convex optimization, shape constraints, differences of convex functions; multi-task learning, functional output regression, quantile regression; kernel PCA, kernel SVD.
Miscellany
- More information about his background can be found on his resume.
Co-authors