Brando Miranda
Brando Miranda
Verified email at mit.edu - Homepage
Title
Cited by
Cited by
Year
Why and when can deep-but not shallow-networks avoid the curse of dimensionality: a review
T Poggio, H Mhaskar, L Rosasco, B Miranda, Q Liao
International Journal of Automation and Computing 14 (5), 503-519, 2017
2772017
High-performance and scalable on-chip digital Fourier transform spectroscopy
DM Kita, B Miranda, D Favela, D Bono, J Michon, H Lin, T Gu, J Hu
Nature communications 9 (1), 1-7, 2018
702018
Theory of deep learning III: explaining the non-overfitting puzzle
T Poggio, K Kawaguchi, Q Liao, B Miranda, L Rosasco, X Boix, J Hidary, ...
arXiv preprint arXiv:1801.00173, 2017
692017
Theory of deep learning IIb: Optimization properties of SGD
C Zhang, Q Liao, A Rakhlin, B Miranda, N Golowich, T Poggio
arXiv preprint arXiv:1801.02254, 2018
40*2018
Theory of deep learning iii: Generalization properties of sgd
C Zhang, Q Liao, A Rakhlin, K Sridharan, B Miranda, N Golowich, ...
arXiv preprint arXiv:1801.00173, 2017
292017
A surprising linear relationship predicts test performance in deep networks
Q Liao, B Miranda, A Banburski, J Hidary, T Poggio
arXiv preprint arXiv:1807.09659, 2018
252018
Theory IIIb: Generalization in deep networks
T Poggio, Q Liao, B Miranda, A Banburski, X Boix, J Hidary
arXiv preprint arXiv:1806.11379, 2018
182018
Theory of deep learning iii: the non-overfitting puzzle
T Poggio, K Kawaguchi, Q Liao, B Miranda, L Rosasco, X Boix, J Hidary, ...
CBMM Memo. 073, 2018
152018
Theory of deep learning III: Dynamics and generalization in deep networks
A Banburski, Q Liao, B Miranda, T Poggio, L Rosasco, B Liang, J Hidary
Center for Brains, Minds and Machines [CBMM], Cambridge, MA, 2019
102019
Theory I: Why and when can deep-but not shallow-networks avoid the curse of dimensionality
T Poggio, H Mhaskar, L Rosasco, B Miranda, Q Liao
Center for Brains, Minds and Machines [CBMM], Cambridge, MA, 2016
92016
Digital Fourier transform spectroscopy: a high-performance, scalable technology for on-chip spectrum analysis
DM Kita, B Miranda, D Favela, D Bono, J Michon, H Lin, T Gu, J Hu
arXiv preprint arXiv:1802.05270, 2018
82018
Theory III: Dynamics and Generalization in Deep Networks1
A Banburski, Q Liao, B Miranda, T Poggio, L Rosasco, F De La Torre, ...
arXiv preprint arXiv:1903.04991, 2019
52019
Theory III: Dynamics and Generalization in Deep Networks--a simple solution
A Banburski, Q Liao, B Miranda, L Rosasco, J Hidary, T Poggio
arXiv preprint arXiv:1903.04991, 2019
42019
High-resolution on-chip digital Fourier transform spectroscopy
DM Kita, B Miranda, D Favela, D Bono, J Michon, H Lin, T Gu, J Hu
CLEO: Science and Innovations, SF1A. 1, 2018
42018
Classical generalization bounds are surprisingly tight for deep networks
Q Liao, B Miranda, J Hidary, T Poggio
Center for Brains, Minds and Machines (CBMM), 2018
22018
Why and when can deep–but not shallow–networks avoid the curse of dimensionality
T Poggio, H Mhaskar, L Rosasco, B Miranda, Q Liao
Center for Brains, Minds and Machines (CBMM) Memo No. 58, arXiv preprintá…, 2016
22016
Sketching: a Cognitively inspired Compositional Theorem Prover that Learns to Prove-a Proposal
B Miranda
12020
Establishing the foundations of Meta-learning-a Proposal
B Miranda
12020
An empirical study of the properties of meta-learning-presentation
B Miranda
12020
DiMO: Differentiable Model Optimization and metaDiMO
B Miranda
12019
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Articles 1–20