1. F. Anselmi, L. Rosasco, C. Tan, T. Poggio. Deep Convolutional Networks are Hierarchical Kernel Machines, Center for Brains, Minds and Machines (CBMM) Memo No. 035, The Center for Brains, Minds and Machines, USA, 2015.
2. T. Poggio, L. Rosasco, A. Shashua, N. Cohen, F. Anselmi. Notes on Hierarchical Splines, DCLNs and i-theory, Center for Brains, Minds and Machines (CBMM) Memo No. 037, The Center for Brains, Minds and Machines, USA, 2015.
3. T. Poggio, F. Anselmi, L. Rosasco. I-theory on Depth vs Width: Hierarchical Function Composition, Center for Brains, Minds and Machines (CBMM) Memo No. 041, The Center for Brains, Minds and Machines, USA, 2015.
4. H. Mhaskar, Q. L. Liao, T. Poggio. Learning Real and Boolean Functions: When is Deep Better than Shallow, Center for Brains, Minds and Machines (CBMM) Memo No. 045, The Center for Brains, Minds and Machines, USA, 2016.
5. H. N. Mhaskar, T. Poggio. Deep Vs. Shallow Networks: An Approximation Theory Perspective, Center for Brains, Minds and Machines (CBMM) Memo No. 054, The Center for Brains, Minds and Machines, USA, 2016.