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Akshay Rangamani
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Automated software vulnerability detection with machine learning
JA Harer, LY Kim, RL Russell, O Ozdemir, LR Kosta, A Rangamani, ...
arXiv preprint arXiv:1803.04497, 2018
2302018
Dynamics in Deep Classifiers trained with the Square Loss: normalization, low rank, neural collapse and generalization bounds
M Xu, A Rangamani, Q Liao, T Galanti, T Poggio
Research, 2023
44*2023
Feature learning in deep classifiers through intermediate neural collapse
A Rangamani, M Lindegaard, T Galanti, TA Poggio
International Conference on Machine Learning, 28729-28745, 2023
392023
Deep learning-based target tracking and classification for low quality videos using coded aperture cameras
C Kwan, B Chou, J Yang, A Rangamani, T Tran, J Zhang, ...
Sensors 19 (17), 3702, 2019
382019
A scale invariant flatness measure for deep network minima
A Rangamani, NH Nguyen, A Kumar, D Phan, SH Chin, TD Tran
arXiv preprint arXiv:1902.02434, 2019
36*2019
Real-time and deep learning based vehicle detection and classification using pixel-wise code exposure measurements
C Kwan, D Gribben, B Chou, B Budavari, J Larkin, A Rangamani, T Tran, ...
Electronics 9 (6), 1014, 2020
312020
Sparse coding and autoencoders
A Rangamani, A Mukherjee, A Basu, A Arora, T Ganapathi, S Chin, ...
2018 IEEE International Symposium on Information Theory (ISIT), 36-40, 2018
29*2018
Target tracking and classification using compressive sensing camera for SWIR videos
C Kwan, B Chou, J Yang, A Rangamani, T Tran, J Zhang, ...
Signal, Image and Video Processing 13 (8), 1629-1637, 2019
252019
Target tracking and classification using compressive measurements of MWIR and LWIR coded aperture cameras
C Kwan, B Chou, J Yang, A Rangamani, T Tran, J Zhang, ...
Journal of Signal and Information Processing 10 (3), 73-95, 2019
252019
Neural collapse in deep homogeneous classifiers and the role of weight decay
A Rangamani, A Banburski-Fahey
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022
242022
Neural-guided, bidirectional program search for abstraction and reasoning
S Alford, A Gandhi, A Rangamani, A Banburski, T Wang, S Dandekar, ...
Complex Networks & Their Applications X: Volume 1, Proceedings of the Tenth …, 2022
222022
Detection and confirmation of multiple human targets using pixel-wise code aperture measurements
C Kwan, D Gribben, A Rangamani, T Tran, J Zhang, R Etienne-Cummings
Journal of Imaging 6 (6), 40, 2020
192020
Spectral gap extrapolation and radio frequency interference suppression using 1D UNets
AA Nair, A Rangamani, LH Nguyen, MAL Bell, TD Tran
2021 IEEE Radar Conference (RadarConf21), 1-6, 2021
92021
Predicting local field potentials with recurrent neural networks
L Kim, J Harer, A Rangamani, J Moran, PD Parks, A Widge, E Eskandar, ...
2016 38th Annual International Conference of the IEEE Engineering in …, 2016
92016
Chief: A change pattern based interpretable failure analyzer
D Patel, LM Nguyen, A Rangamani, S Shrivastava, J Kalagnanam
2018 IEEE International Conference on Big Data (Big Data), 1978-1985, 2018
72018
Automated software vulnerability detection with machine learning. CoRR abs/1803.04497 (2018)
JA Harer, LY Kim, RL Russell, O Ozdemir, LR Kosta, A Rangamani, ...
71803
Automated software vulnerability detection with machine learning. arXiv 2018
JA Harer, LY Kim, RL Russell, O Ozdemir, LR Kosta, A Rangamani, ...
arXiv preprint arXiv:1803.04497, 0
7
For interpolating kernel machines, minimizing the norm of the erm solution minimizes stability
A Rangamani, L Rosasco, T Poggio
arXiv preprint arXiv:2006.15522, 2020
62020
Automated software vulnerability detection with machine learning.(2018)
JA Harer, LY Kim, RL Russell, O Ozdemir, LR Kosta, A Rangamani, ...
arXiv preprint cs.SE/1803.04497, 2018
62018
Skip Connections Increase the Capacity of Associative Memories in Variable Binding Mechanisms
Y Xie, Y Li, A Rangamani
Center for Brains, Minds and Machines (CBMM), 2023
52023
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