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2020 – today
- 2020
[c13]Iris Shen, Le Zhang, Jianxun Lian, Chieh-Han Wu, Miguel González-Fierro, Andreas Argyriou, Tao Wu:
In Search for a Cure: Recommendation With Knowledge Graph on CORD-19. KDD 2020: 3519-3520- [c12]Andreas Argyriou, Miguel González-Fierro, Le Zhang:
Microsoft Recommenders: Best Practices for Production-Ready Recommendation Systems. WWW (Companion Volume) 2020: 50-51
2010 – 2019
- 2015
- [j4]Eugene Belilovsky, Andreas Argyriou, Gaël Varoquaux
, Matthew B. Blaschko:
Convex relaxations of penalties for sparse correlated variables with bounded total variation. Mach. Learn. 100(2-3): 533-553 (2015) - 2014
- [c11]Andreas Argyriou, Francesco Dinuzzo:
A Unifying View of Representer Theorems. ICML 2014: 748-756 - [i8]Andreas Argyriou, Marco Signoretto, Johan A. K. Suykens:
Hybrid Conditional Gradient - Smoothing Algorithms with Applications to Sparse and Low Rank Regularization. CoRR abs/1404.3591 (2014) - 2013
- [c10]Andreas Argyriou, Luca Baldassarre, Charles A. Micchelli, Massimiliano Pontil:
On Sparsity Inducing Regularization Methods for Machine Learning. Empirical Inference 2013: 205-216 - [i7]Andreas Argyriou, Luca Baldassarre, Charles A. Micchelli, Massimiliano Pontil:
On Sparsity Inducing Regularization Methods for Machine Learning. CoRR abs/1303.6086 (2013) - 2012
- [c9]Andreas Argyriou, Rina Foygel, Nathan Srebro:
Sparse Prediction with the $k$-Support Norm. NIPS 2012: 1466-1474 - [c8]Luca Baldassarre, Jean Morales, Andreas Argyriou, Massimiliano Pontil:
A General Framework for Structured Sparsity via Proximal Optimization. AISTATS 2012: 82-90 - [c7]Bernardino Romera-Paredes, Andreas Argyriou, Nadia Berthouze, Massimiliano Pontil:
Exploiting Unrelated Tasks in Multi-Task Learning. AISTATS 2012: 951-959 - [i6]Emile Richard, Andreas Argyriou, Theodoros Evgeniou, Nicolas Vayatis:
A Regularization Approach for Prediction of Edges and Node Features in Dynamic Graphs. CoRR abs/1203.5438 (2012) - [i5]Andreas Argyriou, Rina Foygel, Nathan Srebro:
Sparse Prediction with the k-Overlap Norm. CoRR abs/1204.5043 (2012) - [i4]Francesco Orabona, Andreas Argyriou, Nathan Srebro:
PRISMA: PRoximal Iterative SMoothing Algorithm. CoRR abs/1206.2372 (2012) - 2011
- [i3]Andreas Argyriou, Charles A. Micchelli, Massimiliano Pontil, Lixin Shen, Yuesheng Xu:
Efficient First Order Methods for Linear Composite Regularizers. CoRR abs/1104.1436 (2011) - [i2]Andreas Argyriou, Luca Baldassarre, Jean Morales, Massimiliano Pontil:
A General Framework for Structured Sparsity via Proximal Optimization. CoRR abs/1106.5236 (2011) - 2010
- [j3]Andreas Argyriou, Charles A. Micchelli, Massimiliano Pontil:
On Spectral Learning. J. Mach. Learn. Res. 11: 935-953 (2010)
2000 – 2009
- 2009
- [j2]Andreas Argyriou, Charles A. Micchelli, Massimiliano Pontil:
When Is There a Representer Theorem? Vector Versus Matrix Regularizers. J. Mach. Learn. Res. 10: 2507-2529 (2009) - 2008
- [b1]Andreas Argyriou:
Learning to integrate data from different sources and tasks. University College London, UK, 2008 - [j1]Andreas Argyriou, Theodoros Evgeniou, Massimiliano Pontil:
Convex multi-task feature learning. Mach. Learn. 73(3): 243-272 (2008) - [c6]Andreas Argyriou, Andreas Maurer, Massimiliano Pontil:
An Algorithm for Transfer Learning in a Heterogeneous Environment. ECML/PKDD (1) 2008: 71-85 - [i1]Andreas Argyriou, Charles A. Micchelli, Massimiliano Pontil:
When is there a representer theorem? Vector versus matrix regularizers. CoRR abs/0809.1590 (2008) - 2007
- [c5]Andreas Argyriou, Charles A. Micchelli, Massimiliano Pontil, Yiming Ying:
A Spectral Regularization Framework for Multi-Task Structure Learning. NIPS 2007: 25-32 - 2006
- [c4]Andreas Argyriou, Raphael Hauser, Charles A. Micchelli, Massimiliano Pontil:
A DC-programming algorithm for kernel selection. ICML 2006: 41-48 - [c3]Andreas Argyriou, Theodoros Evgeniou, Massimiliano Pontil:
Multi-Task Feature Learning. NIPS 2006: 41-48 - 2005
- [c2]Andreas Argyriou, Charles A. Micchelli, Massimiliano Pontil:
Learning Convex Combinations of Continuously Parameterized Basic Kernels. COLT 2005: 338-352 - [c1]Andreas Argyriou, Mark Herbster, Massimiliano Pontil:
Combining Graph Laplacians for Semi-Supervised Learning. NIPS 2005: 67-74
Coauthor Index
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