Gábor Hannák
Gábor Hannák
Nokia Bell Labs
Verified email at nokia-bell-labs.com
Title
Cited by
Cited by
Year
Joint channel estimation and activity detection for multiuser communication systems
G Hannak, M Mayer, A Jung, G Matz, N Goertz
2015 IEEE International Conference on Communication Workshop (ICCW), 2086-2091, 2015
372015
Graphical lasso based model selection for time series
A Jung, G Hannak, N Goertz
IEEE Signal Processing Letters 22 (10), 1781-1785, 2015
352015
Graph signal recovery via primal-dual algorithms for total variation minimization
P Berger, G Hannak, G Matz
IEEE Journal of Selected Topics in Signal Processing 11 (6), 842-855, 2017
312017
On the convergence of average consensus with generalized Metropolis-Hasting weights
V Schwarz, G Hannak, G Matz
2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014
202014
Scalable graph signal recovery for big data over networks
A Jung, P Berger, G Hannak, G Matz
2016 IEEE 17th International Workshop on Signal Processing Advances in …, 2016
162016
Measurement based evaluation of interference alignment on the vienna MIMO testbed
M Mayer, G Artner, G Hannak, M Lerch, M Guillaud
ISWCS 2013; The Tenth International Symposium on Wireless Communication …, 2013
142013
Performance Analysis of Approximate Message Passing for Distributed Compressed Sensing
G Hannak, A Perelli, N Goertz, G Matz, ME Davies
IEEE Journal of Selected Topics in Signal Processing 12 (5), 857-870, 2018
112018
Efficient graph signal recovery over big networks
G Hannak, P Berger, G Matz, A Jung
2016 50th Asilomar Conference on Signals, Systems and Computers, 1839-1843, 2016
112016
Graph learning based on total variation minimization
P Berger, M Buchacher, G Hannak, G Matz
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
72018
Generalized approximate message passing for one-bit compressed sensing with AWGN
O Musa, G Hannak, N Goertz
2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2016
72016
Efficient graph learning from noisy and incomplete data
P Berger, G Hannak, G Matz
IEEE Transactions on Signal and Information Processing over Networks 6, 105-119, 2020
62020
On the information-theoretic limits of graphical model selection for Gaussian time series
G Hannak, A Jung, N Goertz
2014 22nd European Signal Processing Conference (EUSIPCO), 516-520, 2014
62014
Semi-supervised multiclass clustering based on signed total variation
P Berger, T Dittrich, G Hannak, G Matz
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
42019
Bayesian QAM demodulation and activity detection for multiuser communication systems
G Hannak, M Mayer, G Matz, N Goertz
2016 IEEE International Conference on Communications Workshops (ICC), 596-601, 2016
42016
Efficient recovery from noisy quantized compressed sensing using generalized approximate message passing
O Musa, G Hannak, N Goertz
2017 IEEE 7th International Workshop on Computational Advances in Multi …, 2017
32017
Fast Bayesian signal recovery in compressed sensing with partially unknown discrete prior
N Goertz, G Hannak
WSA 2017; 21th International ITG Workshop on Smart Antennas, 1-8, 2017
32017
An approach to complex Bayesian-optimal approximate message passing
G Hannak, M Mayer, G Matz, N Goertz
arXiv preprint arXiv:1511.08238, 2015
32015
Graphical LASSO based model selection for time series
A Jung, G Hannak, N Görtz
arXiv preprint arXiv:1410.1184, 2014
32014
Coordinate descent accelerations for signal recovery on scale-free graphs based on total variation minimization
P Berger, G Hannak, G Matz
2017 25th European Signal Processing Conference (EUSIPCO), 1689-1693, 2017
22017
Exploiting joint sparsity in compressed sensing-based RFID
M Mayer, G Hannak, N Goertz
EURASIP Journal on Embedded Systems 2016 (1), 1-15, 2016
12016
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