Andreas Argyriou

发表

A General Framework for Structured Sparsity via Proximal Optimization pdf

Luca Baldassarre, Massimiliano Pontil, Jean Morales, 2012, AISTATS.

A Spectral Regularization Framework for Multi-Task Structure Learning

Charles A. Micchelli, Massimiliano Pontil, Yiming Ying, 2007, NIPS.

Approximating Combined Discrete Total Variation and Correlated Sparsity With Convex Relaxations

Matthew B. Blaschko, Andreas Argyriou, Eugene Belilovsky, 2014, NIPS 2014.

Multi-Task Feature Learning

Massimiliano Pontil, Theodoros Evgeniou, Andreas Argyriou, 2006, NIPS.

On Sparsity Inducing Regularization Methods for Machine Learning

Charles A. Micchelli, Luca Baldassarre, Massimiliano Pontil, 2013, Empirical Inference.

In Search for a Cure: Recommendation With Knowledge Graph on CORD-19

Jianxun Lian, Andreas Argyriou, Tao Wu, 2020, KDD.

Convex multi-task feature learning

Massimiliano Pontil, Theodoros Evgeniou, Andreas Argyriou, 2008, Machine Learning.

Combining Graph Laplacians for Semi-Supervised Learning

Mark Herbster, Massimiliano Pontil, Andreas Argyriou, 2005, NIPS.

Sparse Prediction with the k-Overlap Norm pdf

Nathan Srebro, Rina Foygel, Andreas Argyriou, 2012, ArXiv.

Learning Convex Combinations of Continuously Parameterized Basic Kernels

Charles A. Micchelli, Massimiliano Pontil, Andreas Argyriou, 2005, COLT.

Nonconvex Proximal Splitting with Computational Errors Suvrit Sra

Johan A. K. Suykens, Marco Signoretto, Andreas Argyriou, 2014 .

Hybrid algorithms with applications to sparse and low rank regularization

Johan A. K. Suykens, Marco Signoretto, Andreas Argyriou, 2014 .

Hybrid Conditional Gradient - Smoothing Algorithms with Applications to Sparse and Low Rank Regularization pdf

Johan A. K. Suykens, Marco Signoretto, Andreas Argyriou, 2014, ArXiv.

Automatic Recognition of Facial Expressions

Massimiliano Pontil, Andreas Argyriou, Nadia Bianchi-Berthouze, 2012 .

A Regularization Approach for Prediction of Edges and Node Features in Dynamic Graphs pdf

Theodoros Evgeniou, Nicolas Vayatis, Andreas Argyriou, 2012, ArXiv.

PRISMA: PRoximal Iterative SMoothing Algorithm pdf

Francesco Orabona, Nathan Srebro, Andreas Argyriou, 2012, ArXiv.

An Algorithm for Transfer Learning in a Heterogeneous Environment

Massimiliano Pontil, Andreas Maurer, Andreas Argyriou, 2008, ECML/PKDD.

A Unifying View of Representer Theorems

Andreas Argyriou, Francesco Dinuzzo, Andreas Argyriou, 2014, ICML.

Efficient First Order Methods for Linear Composite Regularizers pdf

Lixin Shen, Yuesheng Xu, Charles A. Micchelli, 2011, ArXiv.

Massimiliano Pontil, Andreas Argyriou, Nadia Bianchi-Berthouze, 2012, AISTATS.

When is there a representer theorem? Vector versus matrix regularizers

Charles A. Micchelli, Massimiliano Pontil, Andreas Argyriou, 2008, J. Mach. Learn. Res..

Convex relaxations of penalties for sparse correlated variables with bounded total variation

Matthew B. Blaschko, Gaël Varoquaux, Andreas Argyriou, 2015, Machine Learning.

Microsoft Recommenders: Best Practices for Production-Ready Recommendation Systems

Andreas Argyriou, Le Zhang, Miguel González-Fierro, 2020, WWW.

On Spectral Learning

Charles A. Micchelli, Massimiliano Pontil, Andreas Argyriou, 2010, J. Mach. Learn. Res..

Learning to integrate data from different sources and tasks

Andreas Argyriou, Andreas Argyriou, 2008 .

A DC-programming algorithm for kernel selection

Charles A. Micchelli, Massimiliano Pontil, Andreas Argyriou, 2006, ICML.

Sparse Prediction with the $k$-Support Norm

Nathan Srebro, Rina Foygel, Andreas Argyriou, 2012, NIPS.

Probability of symbol error for coherent and non-coherent detection of M-ary frequency-shift keyed (MFSK) signals affected by co-channel interference and additive white Gaussian noise (AWGN) in a fading channel

Andreas Argyriou, 2000 .

Regularization, Optimization, Kernels, and Support Vector Machines

Johan A. K. Suykens, Marco Signoretto, Andreas Argyriou, 2014 .

Learning the Graph of Relations Among Multiple Tasks

Stéphan Clémençon, Andreas Argyriou, Ruocong Zhang, 2013 .

International workshop on advances in regularization, optimization, kernel methods and support vector machines : theory and applications (ROKS 2013)

Vanya Van Belle, Johan A. K. Suykens, Joos Vandewalle, 2013 .