Publication

Found 161 results
Author Title Type [ Year(Desc)]
Filters: Author is Tomaso A. Poggio  [Clear All Filters]
2024
Gan, Y. & Poggio, T. For HyperBFs AGOP is a greedy approximation to gradient descent. (2024).PDF icon CBMM-Memo-148.pdf (1.06 MB)
Ziyin, L., Chuang, I., Galanti, T. & Poggio, T. Formation of Representations in Neural Networks. (2024).PDF icon CBMM-Memo-150.pdf (4.03 MB)
Pinto, A., Rangamani, A. & Poggio, T. On Generalization Bounds for Neural Networks with Low Rank Layers. (2024).PDF icon CBMM-Memo-151.pdf (697.31 KB)
Gan, Y., Galanti, T., Poggio, T. & Malach, E. On the Power of Decision Trees in Auto-Regressive Language Modeling. (2024).PDF icon CBMM-Memo-149.pdf (2.11 MB)
Liao, Q. et al. Self-Assembly of a Biologically Plausible Learning Circuit. (2024).PDF icon CBMM-Memo-152.pdf (1.84 MB)
2025
Poggio, T. A. & Xu, M. On efficiently computable functions, deep networks and sparse compositionality. (2025).PDF icon Deep_sparse_networks_approximate_efficiently_computable_functions.pdf (223.15 KB)
Dubach, R., Abdallah, M. S. & Poggio, T. Multiplicative Regularization Generalizes Better Than Additive Regularization. (2025).PDF icon CBMM Memo 158.pdf (4.8 MB)
Danhofer, D. A., D’Ascenzo, D., Dubach, R. & Poggio, T. Position: A Theory of Deep Learning Must Include Compositional Sparsity. (2025).PDF icon CBMM Memo 159.pdf (676.35 KB)
Tiwary, K. et al. What if Eye..? Computationally Recreating Vision Evolution. arXiv (2025). at <https://arxiv.org/abs/2501.15001>PDF icon 2501.15001v1.pdf (5.2 MB)
2026
Poggio, T. Associative Memory as the Core of Intelligence in Technology and Evolution. (2026).PDF icon Review_On_Associative_Memories-14.pdf (245.78 KB)
Poggio, T. A Perspective: Sparse Compositionality and Efficiently Computable Intelligence. (2026).PDF icon Perspective_SPCOMP-9.pdf (170.23 KB)

Pages