navid ghadermarzy
navid ghadermarzy
Unknown affiliation
Verified email at math.ubc.ca - Homepage
Title
Cited by
Cited by
Year
Reinforcement learning using quantum Boltzmann machines
D Crawford, A Levit, N Ghadermarzy, JS Oberoi, P Ronagh
arXiv preprint arXiv:1612.05695, 2016
502016
Near-optimal sample complexity for convex tensor completion
N Ghadermarzy, Y Plan, O Yilmaz
arXiv preprint arXiv:1711.04965, 2017
112017
Free energy-based reinforcement learning using a quantum processor
A Levit, D Crawford, N Ghadermarzy, JS Oberoi, E Zahedinejad, ...
arXiv preprint arXiv:1706.00074, 2017
112017
Learning tensors from partial binary measurements
N Ghadermarzy, Y Plan, O Yilmaz
IEEE Transactions on Signal Processing 67 (1), 29-40, 2018
102018
Non-convex compressed sensing using partial support information
N Ghadermarzy, H Mansour, O Yilmaz
arXiv preprint arXiv:1311.3773, 2013
52013
Free Energy-Based Reinforcement Learning Using Quantum Monte Carlo and Quantum Annealing
P Ronagh, A Levit, D Crawford, N Ghadermarzy, J Oberoi, E Zahedinejad
APS 2018, P34. 010, 2018
22018
Weighted and reweighted approximate message passing
N Ghadermarzy, O Yilmaz
Wavelets and Sparsity XV 8858, 88580C, 2013
22013
Seismic trace interpolation with approximate message passing
N Ghadermarzy, F Herrmann, Yilmaz
SEG Technical Program Expanded Abstracts 2014, 3621-3626, 2014
12014
Using prior support information in compressed sensing
N Ghadermarzy
University of British Columbia, 2013
12013
Reinforcement Learning via Replica Stacking of Quantum Measurements for the Training of Quantum Boltzmann Machines
A Levit, D Crawford, N Ghadermarzy, JS Oberoi, E Zahedinejad, ...
2018
Sparse inversion simplified
N Tu, N Ghadermarzy, R Kumar
2018
Near-optimal sample complexity for noisy or 1-bit tensor completion
N Ghadermarzy
University of British Columbia, 2018
2018
Reinforcement Learning via Boltzmann Machines Implemented on Quantum Annealers
A Levit, D Crawford, P Ronagh, J Oberoi, N Ghadermarzy
AGUFM 2016, IN11D-1644, 2016
2016
Quantum Reinforcement Learning
D Crawford, A Levit, N Ghadermarzy, JS Oberoi, P Ronagh
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Articles 1–14