Brando Miranda
Brando Miranda
Verified email at mit.edu
TitleCited byYear
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
1562017
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
362017
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), 4405, 2018
332018
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
31*2017
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
222018
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
152018
Theory IIIb: Generalization in deep networks
T Poggio, Q Liao, B Miranda, A Banburski, X Boix, J Hidary
arXiv preprint arXiv:1806.11379, 2018
132018
Theory of deep learning iii: the non-overfitting puzzle
T Poggio, K Kawaguchi, Q Liao, B Miranda, L Rosasco, X Boix, J Hidary, ...
Technical report, Technical report, CBMM memo 073, 2018
132018
On the use of Singular Spectrum Analysis
AM Tomé, D Malafaia, AR Teixeira, EW Lang
arXiv preprint arXiv:1807.10679, 2018
62018
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
tech. rep., CBMM Memo, 0
6
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
Theory III: Dynamics and Generalization in Deep Networks
A Banburski, Q Liao, B Miranda, L Rosasco, B Liang, J Hidary, T Poggio
arXiv preprint arXiv:1903.04991, 2019
22019
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 preprint …, 2016
22016
Theory i: Why and when can deep networks avoid the curse of dimensionality?
T Poggio, H Mhaskar, L Rosasco, B Miranda, Q Liao
Center for Brains, Minds and Machines (CBMM), arXiv, 2016
12016
Chip-scale Digital Fourier Transform Spectroscopy
DM Kita, B Miranda, D Favela, D Bono, J Michon, H Lin, T Gu, J Hu
Applied Industrial Optics: Spectroscopy, Imaging and Metrology, W3A. 1, 2019
2019
Chip-scale high-performance digital Fourier Transform (dFT) spectrometers
DM Kita, B Miranda, C Ríos, D Favela, D Bono, J Michon, H Lin, T Gu, ...
Next-Generation Spectroscopic Technologies XII 10983, 1098306, 2019
2019
Training hierarchical networks for function approximation
B Miranda
Massachusetts Institute of Technology, 2016
2016
Dark Cloud: A Secure File System
B Miranda, M Polanco, P Cattori
2013
Theory III: Dynamics and Generalization in Deep Networks1
T Poggio, Q Liao, B Miranda, S Rakhlin, A Banburski, L Rosasco, ...
The system can't perform the operation now. Try again later.
Articles 1–20