| Year |
Citation |
Score |
| 2024 |
Rando M, James M, Verri A, Rosasco L, Seminara A. Q-Learning to navigate turbulence without a map. Arxiv. PMID 38711433 |
0.587 |
|
| 2017 |
Rudi A, De Vito E, Verri A, Odone F. Regularized Kernel Algorithms for Support Estimation Frontiers in Applied Mathematics and Statistics. 3. DOI: 10.3389/fams.2017.00023 |
0.308 |
|
| 2015 |
Stagliano A, Noceti N, Verri A, Odone F. Online space-variant background modeling with sparse coding. Ieee Transactions On Image Processing : a Publication of the Ieee Signal Processing Society. 24: 2415-28. PMID 25872209 DOI: 10.1109/TIP.2015.2421435 |
0.321 |
|
| 2014 |
Salzo S, Masecchia S, Verri A, Barla A. Alternating proximal regularized dictionary learning. Neural Computation. 26: 2855-95. PMID 25248086 DOI: 10.1162/NECO_a_00672 |
0.368 |
|
| 2014 |
Villa S, Rosasco L, Mosci S, Verri A. Proximal methods for the latent group lasso penalty Computational Optimization and Applications. 58: 381-407. DOI: 10.1007/s10589-013-9628-6 |
0.653 |
|
| 2013 |
Zycinski G, Barla A, Squillario M, Sanavia T, Camillo BD, Verri A. Knowledge Driven Variable Selection (KDVS) - a new approach to enrichment analysis of gene signatures obtained from high-throughput data. Source Code For Biology and Medicine. 8: 2. PMID 23302187 DOI: 10.1186/1751-0473-8-2 |
0.309 |
|
| 2013 |
Villa S, Salzo S, Baldassarre L, Verri A. Accelerated and inexact forward-backward algorithms Siam Journal On Optimization. 23: 1607-1633. DOI: 10.1137/110844805 |
0.32 |
|
| 2013 |
Rosasco L, Villa S, Mosci S, Santoro M, Verri A. Nonparametric sparsity and regularization Journal of Machine Learning Research. 14: 1665-1714. |
0.579 |
|
| 2012 |
Mosci S, Rosasco L, Santoro M, Verri A, Villa S. Is there sparsity beyond additive models? Ifac Proceedings Volumes (Ifac-Papersonline). 16: 971-976. DOI: 10.3182/20120711-3-BE-2027.00364 |
0.66 |
|
| 2012 |
Villa S, Rosasco L, Mosci S, Verri A. Consistency of learning algorithms using Attouch-Wets convergence Optimization. 61: 287-305. DOI: 10.1080/02331934.2010.511671 |
0.651 |
|
| 2012 |
Baldassarre L, Rosasco L, Barla A, Verri A. Multi-output learning via spectral filtering Machine Learning. 87: 259-301. DOI: 10.1007/s10994-012-5282-y |
0.667 |
|
| 2010 |
Fardin P, Cornero A, Barla A, Mosci S, Acquaviva M, Rosasco L, Gambini C, Verri A, Varesio L. Identification of multiple hypoxia signatures in neuroblastoma cell lines by l1-l2 regularization and data reduction. Journal of Biomedicine & Biotechnology. 2010: 878709. PMID 20652058 DOI: 10.1155/2010/878709 |
0.613 |
|
| 2010 |
Fardin P, Barla A, Mosci S, Rosasco L, Verri A, Versteeg R, Caron HN, Molenaar JJ, Ora I, Eva A, Puppo M, Varesio L. A biology-driven approach identifies the hypoxia gene signature as a predictor of the outcome of neuroblastoma patients. Molecular Cancer. 9: 185. PMID 20624283 DOI: 10.1186/1476-4598-9-185 |
0.601 |
|
| 2010 |
Mosci S, Rosasco L, Santoro M, Verri A, Villa S. Solving structured sparsity regularization with proximal methods Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6322: 418-433. DOI: 10.1007/978-3-642-15883-4_27 |
0.575 |
|
| 2010 |
Baldassarre L, Rosasco L, Barla A, Verri A. Vector field learning via spectral filtering Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6321: 56-71. DOI: 10.1007/978-3-642-15880-3_10 |
0.59 |
|
| 2010 |
Rosasco L, Santoro M, Mosci S, Verri A, Villa S. A regularization approach to nonlinear variable selection Journal of Machine Learning Research. 9: 653-660. |
0.554 |
|
| 2010 |
Mosci S, Villa S, Verri A, Rosasco L. A primal-dual algorithm for group sparse regularization with overlapping groups Advances in Neural Information Processing Systems 23: 24th Annual Conference On Neural Information Processing Systems 2010, Nips 2010. |
0.562 |
|
| 2009 |
Fardin P, Barla A, Mosci S, Rosasco L, Verri A, Varesio L. The l1-l2 regularization framework unmasks the hypoxia signature hidden in the transcriptome of a set of heterogeneous neuroblastoma cell lines. Bmc Genomics. 10: 474. PMID 19832978 DOI: 10.1186/1471-2164-10-474 |
0.627 |
|
| 2009 |
De Mol C, Mosci S, Traskine M, Verri A. A regularized method for selecting nested groups of relevant genes from microarray data. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology. 16: 677-90. PMID 19432538 DOI: 10.1089/cmb.2008.0171 |
0.321 |
|
| 2009 |
Destrero A, De Mol C, Odone F, Verri A. A sparsity-enforcing method for learning face features. Ieee Transactions On Image Processing : a Publication of the Ieee Signal Processing Society. 18: 188-201. PMID 19095529 DOI: 10.1109/TIP.2008.2007610 |
0.351 |
|
| 2009 |
Destrero A, De Mol C, Odone F, Verri A. A regularized framework for feature selection in face detection and authentication International Journal of Computer Vision. 83: 164-177. DOI: 10.1007/s11263-008-0180-2 |
0.357 |
|
| 2009 |
Destrero A, Mosci S, De Mol C, Verri A, Odone F. Feature selection for high-dimensional data Computational Management Science. 6: 25-40. DOI: 10.1007/s10287-008-0070-7 |
0.352 |
|
| 2008 |
Lo Gerfo L, Rosasco L, Odone F, De Vito E, Verri A. Spectral algorithms for supervised learning. Neural Computation. 20: 1873-97. PMID 18254698 DOI: 10.1162/neco.2008.05-07-517 |
0.662 |
|
| 2008 |
Mosci S, Verri A, Barla A, Rosasco L. Finding structured gene signatures Proceedings - 2008 Ieee International Conference On Bioinformatics and Biomedicine Workshops, Bibmw. 158-165. DOI: 10.1109/BIBMW.2008.4686230 |
0.548 |
|
| 2008 |
Barla A, Mosci S, Rosasco L, Verri A. A method for robust variable selection with significance assessment Esann 2008 Proceedings, 16th European Symposium On Artificial Neural Networks - Advances in Computational Intelligence and Learning. 83-88. |
0.565 |
|
| 2007 |
Mosci S, Rosasco L, Verri A. Dimensionality reduction and generalization Acm International Conference Proceeding Series. 227: 657-664. DOI: 10.1145/1273496.1273579 |
0.551 |
|
| 2007 |
Caponnetto A, Rosasco L, Odone F, Verri A. Support vectors algorithms as regularization networks Esann 2005 Proceedings - 13th European Symposium On Artificial Neural Networks. 595-600. |
0.576 |
|
| 2006 |
Delponte E, Isgrò F, Odone F, Verri A. SVD-matching using SIFT features Graphical Models. 68: 415-431. DOI: 10.1016/j.gmod.2006.07.002 |
0.334 |
|
| 2006 |
Daliri MR, Delponte E, Verri A, Torre V. Shape categorization using string kernels Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4109: 297-305. DOI: 10.1007/11815921_32 |
0.736 |
|
| 2005 |
Camastra F, Verri A. A novel kernel method for clustering. Ieee Transactions On Pattern Analysis and Machine Intelligence. 27: 801-5. PMID 15875800 DOI: 10.1109/TPAMI.2005.88 |
0.317 |
|
| 2005 |
Odone F, Barla A, Verri A. Building kernels from binary strings for image matching. Ieee Transactions On Image Processing : a Publication of the Ieee Signal Processing Society. 14: 169-80. PMID 15700522 DOI: 10.1109/TIP.2004.840701 |
0.344 |
|
| 2005 |
Odone F, Barla A, Franceschi E, Verri A. Web tools to support image classification Proceedings of Spie - the International Society For Optical Engineering. 5670: 197-206. DOI: 10.1117/12.586685 |
0.308 |
|
| 2004 |
Rosasco L, De Vito E, Caponnetto A, Piana M, Verri A. Are loss functions all the same? Neural Computation. 16: 1063-76. PMID 15070510 DOI: 10.1162/089976604773135104 |
0.597 |
|
| 2004 |
De Vito E, Rosasco L, Caponnetto A, Piana M, Verri A. Some properties of regularized kernel methods Journal of Machine Learning Research. 5: 1363-1390. |
0.579 |
|
| 2002 |
Heisele B, Verri A, Poggio T. Learning and vision machines Proceedings of the Ieee. 90: 1164-1176. DOI: 10.1109/JPROC.2002.801450 |
0.609 |
|
| 2002 |
Evgeniou T, Poggio T, Pontil M, Verri A. Regularization and statistical learning theory for data analysis Computational Statistics and Data Analysis. 38: 421-432. DOI: 10.1016/S0167-9473(01)00069-X |
0.747 |
|
| 2001 |
Odone F, Trucco E, Verri A. General Purpose Matching of Grey Level Arbitrary Images Lecture Notes in Computer Science. 573-582. DOI: 10.1007/3-540-45129-3_53 |
0.306 |
|
| 2000 |
Poggio T, Verri A. Introduction: Learning and vision at CBCL International Journal of Computer Vision. 38: 5-7. DOI: 10.1023/A:1008127215780 |
0.644 |
|
| 2000 |
Pittore M, Campani M, Verri A. Learning to recognize visual dynamic events from examples International Journal of Computer Vision. 38: 35-44. DOI: 10.1023/A:1008114700759 |
0.302 |
|
| 1998 |
Pontil M, Verri A. Support vector machines for 3D object recognition Ieee Transactions On Pattern Analysis and Machine Intelligence. 20: 637-646. DOI: 10.1109/34.683777 |
0.33 |
|
| 1992 |
Orban GA, Lagae L, Verri A, Raiguel S, Xiao D, Maes H, Torre V. First-order analysis of optical flow in monkey brain. Proceedings of the National Academy of Sciences of the United States of America. 89: 2595-9. PMID 1557363 DOI: 10.1073/Pnas.89.7.2595 |
0.617 |
|
| 1992 |
Verri A, Straforini M, Torre V. Computational aspects of motion perception in natural and artificial vision systems. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences. 337: 429-43. PMID 1359590 DOI: 10.1098/rstb.1992.0119 |
0.602 |
|
| 1992 |
Campani M, Verri A. Motion analysis from first-order properties of optical flow Cvgip: Image Understanding. 56: 90-107. DOI: 10.1016/1049-9660(92)90088-K |
0.317 |
|
| 1989 |
Verri A, Poggio T. Motion field and optical flow: qualitative properties Ieee Transactions On Pattern Analysis and Machine Intelligence. 11: 490-498. DOI: 10.1109/34.24781 |
0.619 |
|
| 1988 |
Uras S, Girosi F, Verri A, Torre V. A computational approach to motion perception Biological Cybernetics. 60: 79-87. DOI: 10.1007/Bf00202895 |
0.331 |
|
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