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Igor Fedorov
Igor Fedorov
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Micronets: Neural network architectures for deploying tinyml applications on commodity microcontrollers
C Banbury, C Zhou, I Fedorov, R Matas, U Thakker, D Gope, ...
Proceedings of machine learning and systems 3, 517-532, 2021
2122021
Sparse: Sparse architecture search for cnns on resource-constrained microcontrollers
I Fedorov, RP Adams, M Mattina, P Whatmough
Advances in Neural Information Processing Systems 32, 2019
1612019
TinyLSTMs: Efficient neural speech enhancement for hearing aids
I Fedorov, M Stamenovic, C Jensen, LC Yang, A Mandell, Y Gan, ...
arXiv preprint arXiv:2005.11138, 2020
862020
Compressing rnns for iot devices by 15-38x using kronecker products
U Thakker, J Beu, D Gope, C Zhou, I Fedorov, G Dasika, M Mattina
arXiv preprint arXiv:1906.02876, 2019
402019
Mango: A python library for parallel hyperparameter tuning
SS Sandha, M Aggarwal, I Fedorov, M Srivastava
Icassp 2020-2020 ieee international conference on acoustics, speech and …, 2020
332020
Automated Worker Activity Analysis in Indoor Environments for Direct-Work Rate Improvement from Long Sequences of RGB-D Images
A Khosrowpour, I Fedorov, A Holynski, JC Niebles, M Golparvar-Fard
Journal of Construction Engineering and Management, 2015
302015
Automated Worker Activity Analysis in Indoor Environments for Direct-Work Rate Improvement from Long Sequences of RGB-D Images
A Khosrowpour, I Fedorov, A Holynski, JC Niebles, M Golparvar-Fard
Construction Research Congress 2014@ sConstruction in a Global Network, 729-738, 2014
302014
Rectified Gaussian scale mixtures and the sparse non-negative least squares problem
A Nalci, I Fedorov, M Al-Shoukairi, TT Liu, BD Rao
IEEE Transactions on Signal Processing 66 (12), 3124-3139, 2018
232018
Power delivery for series connected voltage domains in digital circuits
PS Shenoy, I Fedorov, T Neyens, PT Krein
2011 International Conference on Energy Aware Computing, 1-6, 2011
192011
UDC: Unified DNAS for Compressible TinyML Models for Neural Processing Units
I Fedorov, R Matas, H Tann, C Zhou, M Mattina, P Whatmough
Advances in Neural Information Processing Systems, 2022
18*2022
Pushing the limits of rnn compression
U Thakker, I Fedorov, J Beu, D Gope, C Zhou, G Dasika, M Mattina
2019 Fifth Workshop on Energy Efficient Machine Learning and Cognitive …, 2019
162019
Robust Bayesian method for simultaneous block sparse signal recovery with applications to face recognition
I Fedorov, R Giri, BD Rao, TQ Nguyen
2016 IEEE International Conference on Image Processing (ICIP), 3872-3876, 2016
152016
A Unified Framework for Sparse Non-Negative Least Squares using Multiplicative Updates and the Non-Negative Matrix Factorization Problem
I Fedorov, A Nalci, R Giri, BD Rao, TQ Nguyen, H Garudadri
Signal Processing, 2018
122018
Multimodal sparse Bayesian dictionary learning applied to multimodal data classification
I Fedorov, BD Rao, TQ Nguyen
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
122017
Image denoising neural network architecture and method of training the same
M El-Khamy, I Fedorov, J Lee
US Patent 10,726,525, 2020
102020
Multimodal sparse bayesian dictionary learning
I Fedorov, BD Rao
arXiv preprint arXiv:1804.03740, 2018
82018
Compressing RNNs to kilobyte budget for IoT devices using Kronecker products
U Thakker, I Fedorov, C Zhou, D Gope, M Mattina, G Dasika, J Beu
ACM Journal on Emerging Technologies in Computing Systems (JETC) 17 (4), 1-18, 2021
62021
Restructurable activation networks
K Bhardwaj, J Ward, C Tung, D Gope, L Meng, I Fedorov, A Chalfin, ...
arXiv preprint arXiv:2208.08562, 2022
52022
SSGD: Sparsity-promoting stochastic gradient descent algorithm for unbiased DNN pruning
CH Lee, I Fedorov, BD Rao, H Garudadri
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
42020
Relevance subject machine: a novel person re-identification framework
I Fedorov, R Giri, BD Rao, TQ Nguyen
arXiv preprint arXiv:1703.10645, 2017
42017
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