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2015
Anselmi, F., Rosasco, L., Tan, C. & Poggio, T. Deep Convolutional Networks are Hierarchical Kernel Machines. (2015).PDF icon CBMM Memo 035_rev5.pdf (975.65 KB)
Zhang, C., Voinea, S., Evangelopoulos, G., Rosasco, L. & Poggio, T. Discriminative Template Learning in Group-Convolutional Networks for Invariant Speech Representations. INTERSPEECH-2015 (International Speech Communication Association (ISCA), 2015). at <http://www.isca-speech.org/archive/interspeech_2015/i15_3229.html>
Nickel, M., Rosasco, L. & Poggio, T. Holographic Embeddings of Knowledge Graphs. (2015).PDF icon holographic-embeddings.pdf (677.87 KB)
Anselmi, F., Rosasco, L. & Poggio, T. On Invariance and Selectivity in Representation Learning. (2015).PDF icon CBMM Memo No. 029 (812.07 KB)
Poggio, T., Anselmi, F. & Rosasco, L. I-theory on depth vs width: hierarchical function composition. (2015).PDF icon cbmm_memo_041.pdf (1.18 MB)
Rosasco, L. & Villa, S. Learning with incremental iterative regularization. NIPS 2015 (2015). at <https://papers.nips.cc/paper/6015-learning-with-incremental-iterative-regularization>PDF icon Learning with Incremental Iterative Regularization_1405.0042v2.pdf (504.66 KB)
Rudi, A., Camoriano, R. & Rosasco, L. Less is More: Nyström Computational Regularization. NIPS 2015 (2015). at <https://papers.nips.cc/paper/5936-less-is-more-nystrom-computational-regularization>PDF icon Less is More- Nystr ̈om Computational Regularization_1507.04717v4.pdf (287.14 KB)
Poggio, T., Rosasco, L., Shashua, A., Cohen, N. & Anselmi, F. Notes on Hierarchical Splines, DCLNs and i-theory. (2015).PDF icon CBMM Memo 037 (1.83 MB)
Anselmi, F. et al. Unsupervised learning of invariant representations. Theoretical Computer Science (2015). doi:10.1016/j.tcs.2015.06.048

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