Andreas Argyriou

• Multi-task Learning and Learning the Kernel (NIPS workshop on learning the kernel 2008).

(longer version)

Publications

2009:

• On Spectral Learning (with C. A. Micchelli and M. Pontil). To appear in Journal of Machine Learning Research.

2008:

• When Is There a Representer Theorem? Vector versus Matrix Regularizers (with C. A. Micchelli and M. Pontil). To appear in Journal of Machine Learning Research.

• An Algorithm for Transfer Learning in a Heterogeneous Environment (with A. Maurer and M. Pontil). ECML 2008.

2007:

• A Spectral Regularization Framework for Multi-Task Structure Learning (with C. A. Micchelli, M. Pontil and Y. Ying). NIPS 2007.

• Convex Multi-Task Feature Learning (with T. Evgeniou and M. Pontil). Machine Learning, 73, 3, 243-272, Special Issue on Inductive Transfer Learning, 2008.

• Learning to Integrate Data from Different Sources and Tasks PhD Thesis.

2006:

• Multi-Task Feature Learning (with T. Evgeniou and M. Pontil). NIPS 2006.

• A DC-Programming Algorithm for Kernel Selection (with R. Hauser, C. A. Micchelli and M. Pontil). ICML 2006.

2005:

• Combining Graph Laplacians for Semi--Supervised Learning (with M. Herbster and M. Pontil). NIPS 2005.

• Learning Convex Combinations of Continuously Parameterized Basic Kernels (with C.A. Micchelli and M. Pontil). COLT 2005.

2004:

• Efficient Approximation Methods for Harmonic Semi-Supervised Learning Master's Thesis.

Software

Curriculum Vitae

Advanced Topics in Machine Learning course (UCL, spring 2009)