Marcel Nassar
Marcel Nassar
Intel AI Lab
Verified email at - Homepage
Cited by
Cited by
Flexpoint: An adaptive numerical format for efficient training of deep neural networks
U Köster, T Webb, X Wang, M Nassar, AK Bansal, W Constable, O Elibol, ...
Advances in neural information processing systems 30, 2017
Impulsive noise mitigation in powerline communications using sparse Bayesian learning
J Lin, M Nassar, BL Evans
IEEE Journal on Selected Areas in Communications 31 (7), 1172-1183, 2013
Local utility power line communications in the 3–500 kHz band: Channel impairments, noise, and standards
M Nassar, J Lin, Y Mortazavi, A Dabak, IH Kim, BL Evans
IEEE signal processing magazine 29 (5), 116-127, 2012
Cyclostationary Noise Modeling in Narrowband Powerline Communication for Smart Grid Applications
M Nassar, A Dabak, IH Kim, T Pande, BL Evans
Mitigating near-field interference in laptop embedded wireless transceivers
M Nassar, K Gulati, MR DeYoung, BL Evans, KR Tinsley
Journal of Signal Processing Systems 63, 1-12, 2011
Statistical modeling of asynchronous impulsive noise in powerline communication networks
M Nassar, K Gulati, Y Mortazavi, BL Evans
2011 IEEE Global Telecommunications Conference-GLOBECOM 2011, 1-6, 2011
A factor graph approach to joint OFDM channel estimation and decoding in impulsive noise environments
M Nassar, P Schniter, BL Evans
IEEE Transactions on Signal Processing 62 (6), 1576-1589, 2013
Cyclic spectral analysis of power line noise in the 3–200 kHz band
KF Nieman, J Lin, M Nassar, K Waheed, BL Evans
2013 IEEE 17th International Symposium on Power Line Communications and Its …, 2013
System and method for a unified architecture multi-task deep learning machine for object recognition
M El-Khamy, A Yedla, M Nassar, J Lee
US Patent 10,032,067, 2018
Non-parametric impulsive noise mitigation in OFDM systems using sparse Bayesian learning
J Lin, M Nassar, BL Evans
2011 IEEE Global Telecommunications Conference-GLOBECOM 2011, 1-5, 2011
System and method for a deep learning machine for object detection
A Yedla, M Nassar, M El-Khamy, J Lee
US Patent 10,380,741, 2019
Low complexity EM-based decoding for OFDM systems with impulsive noise
M Nassar, BL Evans
2011 Conference Record of the Forty Fifth Asilomar Conference on Signals …, 2011
Bayesian active learning for drug combinations
M Park, M Nassar, H Vikalo
IEEE transactions on biomedical engineering 60 (11), 3248-3255, 2013
Variational Bayesian inference for forecasting hierarchical time series
M Park, M Nassar
International conference on machine learning (ICML), workshop on divergence …, 2014
Adaptive modulation and coding with frame size adjustment for power line communications (PLC)
M Nassar, IH Kim, T Pande, AG Dabak
US Patent 8,743,974, 2014
IAB topology design: A graph embedding and deep reinforcement learning approach
M Simsek, O Orhan, M Nassar, O Elibol, H Nikopour
IEEE Communications Letters 25 (2), 489-493, 2020
Stochastic modeling of microwave oven interference in WLANs
M Nassar, XE Lin, BL Evans
2011 IEEE International Conference on Communications (ICC), 1-6, 2011
Flexpoint: Predictive numerics for deep learning
V Popescu, M Nassar, X Wang, E Tumer, T Webb
2018 IEEE 25th Symposium on Computer Arithmetic (ARITH), 1-4, 2018
Connection management xAPP for O-RAN RIC: A graph neural network and reinforcement learning approach
O Orhan, VN Swamy, T Tetzlaff, M Nassar, H Nikopour, S Talwar
2021 20th IEEE International Conference on Machine Learning and Applications …, 2021
Hierarchical bipartite graph convolution networks
M Nassar
arXiv preprint arXiv:1812.03813, 2018
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