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Fast Hybrid Algorithm for Big Matrix Recovery

Tengfei Zhou, Hui Qian, Zebang Shen, Congfu Xu
2016 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
The experiments on large-scale collaborative filtering datasets demonstrate very competitive performance of these fast hybrid methods compared to the state-of-the-arts.  ...  We prove that our Hybrid method of ADMM and NT (HADMNT) converges to an optimum of NNLS at least quadratically.  ...  Algorithms We provide two hybrid methods: the Hybrid of ADMM and NT (HADMNT), and the Hybrid of ADMM and CG (HADMCG) in Algorithm 3.  ... 
doi:10.1609/aaai.v30i1.10161 fatcat:g6rzzemefjdgdfu5ziff4yaoqi

Optimizing the error recovery capabilities of LDPC-staircase codes featuring a Gaussian elimination decoding scheme

Mathieu Cunche, Vincent Roca
2008 2008 10th International Workshop on Signal Processing for Space Communications  
We show that a simple modification of the parity check matrix can significantly improve their recovery capabilities when using a GE decoding.  ...  This work focuses on the LDPC codes for the packet erasure channel, also called AL-FEC (Application-Level Forward Error Correction codes).  ...  Even if using a GE scheme has an impact on the decoding complexity, the hybrid decoder remains relatively fast.  ... 
doi:10.1109/spsc.2008.4686723 fatcat:r42v55luabfdtdjboxomrfrx4m

Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization

Fanhua Shang, Yuanyuan Liu, James Cheng
2016 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
We also design two efficient proximal alternating linearzied minimization algorithms for solving representative matrix completion problems.  ...  Finally, we provide the global convergence and performance guarantees for our algorithms, which have better convergence properties than existing algorithms.  ...  Acknowledgements We thank the reviewers for their constructive comments. The authors are partially supported by the SHIAE fund 8115048 and the Hong Kong GRF 2150851.  ... 
doi:10.1609/aaai.v30i1.10266 fatcat:3xl7yxje25gp7blsptwynpb6ve

Efficient Tensor Robust PCA under Hybrid Model of Tucker and Tensor Train [article]

Yuning Qiu, Guoxu Zhou, Zhenhao Huang, Qibin Zhao, Shengli Xie
2021 arXiv   pre-print
Recently, tensor train (TT) decomposition has been verified effective to capture the global low-rank correlation for tensor recovery tasks.  ...  In this letter, we propose an efficient TRPCA under hybrid model of Tucker and TT.  ...  [18] presented the exact recovery guarantee for SNN-based TRPCA.  ... 
arXiv:2112.10771v1 fatcat:iigwyhyz3vdx7b2jntqzrr2ysy

2020 Index IEEE Transactions on Knowledge and Data Engineering Vol. 32

2021 IEEE Transactions on Knowledge and Data Engineering  
Approximation Approach for Fast Error Recovery in Big Sensing Data on Cloud.  ...  ., +, TKDE Nov. 2020 2060-2074 A Scalable Multi-Data Sources Based Recursive Approximation Approach for Fast Error Recovery in Big Sensing Data on Cloud.  ... 
doi:10.1109/tkde.2020.3038549 fatcat:75f5fmdrpjcwrasjylewyivtmu

A Compressed Sensing Improvement Algorithm Based on Power Quality Transient Disturbance Signal

Yi Zhong, Kai Zhang, Xin Juan Zheng
2014 Applied Mechanics and Materials  
Because of the existence of disturbance signal for the presence of power, it requires two times higher than the sampling frequency of the original signal, resulting in many problems, such as a high cost  ...  Therefore, this paper presents a modified algorithm based on Nesta algorithm to reduce the amount of data sampled of power quality signal, the complexity of the algorithm to improve the algorithm's speed  ...  For active power signal, CS recovery data causes individual big errors randomly due to some sample data are irregular and aperiodic, CS algorithm would work well at those moments.  ... 
doi:10.4028/www.scientific.net/amm.610.407 fatcat:ljff7q4lsfgahf7sxvohekr7be

2021 Index IEEE Transactions on Knowledge and Data Engineering Vol. 33

2022 IEEE Transactions on Knowledge and Data Engineering  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  ., +, TKDE May 2021 1906-1918 Discrete Matrix Factorization and Extension for Fast Item Recommendation.  ...  Wang, Y., +, TKDE Nov. 2021 3507-3519 Discrete Matrix Factorization and Extension for Fast Item Recommendation.  ... 
doi:10.1109/tkde.2021.3128365 fatcat:4m5kefreyrbhpb3lhzvgqzm3qu

Backup rules in Software-Defined Networks

Niels L. M. van Adrichem, Farabi Iqbal, Fernando A. Kuipers
2016 2016 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN)  
In this work, we propose algorithms for computing an all-to-all primary and backup network forwarding configuration that is capable of circumventing link and node failures.  ...  Failure recovery processes are therefore needed. Failure recovery is mainly influenced by (1) detection of the failure, and (2) circumvention of the detected failure.  ...  [19] derive and compute an MILP formulation for preplanning recovery paths including QoS metrics.  ... 
doi:10.1109/nfv-sdn.2016.7919495 dblp:conf/nfvsdn/AdrichemIK16 fatcat:lborhpztdzad5d3gfwkicuh43u

Adaptive Recovery of Distorted Data Based on Credibilistic Fuzzy Clustering Approach

Yevgeniy V. Bodyanskiy, Alina Shafronenko, Iryna Klymova
2021 International Conference on Computational Linguistics and Intelligent Systems  
Therefore as alternative, to known clustering algorithms we propose adaptive recovery of distorted data algorithm based on credibilistic fuzzy clustering approach.  ...  The problems of big data clustering is very interesting area of artificial intelligence nowadays.  ...  Acknowledgement The work is supported by the state budget scientific research project of Kharkiv National University of Radio Electronics "Deep hybrid systems of computational intelligence for data stream  ... 
dblp:conf/colins/BodyanskiySK21 fatcat:tco2w3i5j5eahhv4lewkjmseza

Hybrid Approach to an Automated Chain Graph Construction

Taghi Aliyev
2016 Zenodo  
The shortage of the literature and available software for learning and integrating multi -omics data into a single chain graph, makes them a rather unpopular approach.  ...  For Skeleton Recovery stage of the hybrid approach, algorithm proposed in [39] is used.  ...  Proposed algorithm is made of several algorithms, all known to work well with big data sets.  ... 
doi:10.5281/zenodo.3533552 fatcat:tzyxwd6xgbgrvceaiy7nhfptue

GAMP-SBL-based channel estimation for millimeter-wave MIMO systems

Jianfeng Shao, Xianpeng Wang, Xiang Lan, Zhiguang Han, Ting Su
2021 EURASIP Journal on Advances in Signal Processing  
We then improve a refined algorithm to handle the dictionary matrix mismatching problem in sparse representation.  ...  inversion of a high-dimensional matrix.  ...  • We formulate a sparse recovery problem and develop a DGAMP-SBL algorithm for the coarse estimation channel of the hybrid MIMO system.  ... 
doi:10.1186/s13634-021-00792-w fatcat:lrwq2rhcrbbgxek26rdlxeo3iu

Computing backup forwarding rules in Software-Defined Networks [article]

Niels L. M. van Adrichem, Farabi Iqbal, Fernando A. Kuipers
2016 arXiv   pre-print
In this work, we propose algorithms for computing an all-to-all primary and backup network forwarding configuration that is capable of circumventing link and node failures.  ...  After initial recovery, we recompute network configuration to guarantee protection from future failures. Our algorithms use packet-labeling to guarantee correct and shortest detour forwarding.  ...  Input: Adjacency matrix adj = G(N, L) Output: Forwarding matrix f w containing primary and backup rules 1: set f w to all-to-all shortest paths matrix 2: for each node n ∈ N 3: for each outgoing link  ... 
arXiv:1605.09350v1 fatcat:5dvxvb4ihzhghntsmvtc3doux4

Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization [article]

Fanhua Shang and Yuanyuan Liu and James Cheng
2016 arXiv   pre-print
We also design two efficient proximal alternating linearized minimization algorithms for solving representative matrix completion problems.  ...  Finally, we provide the global convergence and performance guarantees for our algorithms, which have better convergence properties than existing algorithms.  ...  Acknowledgements We thank the reviewers for their constructive comments. The authors are partially supported by the SHIAE fund 8115048 and the Hong Kong GRF 2150851.  ... 
arXiv:1606.01245v1 fatcat:rhxt4gftlbd27lneh5sg7guhiy

Data-Assisted Low Complexity Compressive Spectrum Sensing on Real-Time Signals Under Sub-Nyquist Rate

Zhijin Qin, Yue Gao, Clive G. Parini
2016 IEEE Transactions on Wireless Communications  
detection performance under sub-Nyquist sampling rates for wideband spectrum sensing, and to reduce the computational complexity during signal recovery.  ...  In the hybrid framework, a geo-location database algorithm is proposed to be stored locally at secondary users (SUs) to remove the extra transmission link to a centralized remote geo-location database.  ...  The authors would also like to thank Nominet and Ofcom for providing access to the geo-location database, and CRFS Ltd for providing the RFeye node.  ... 
doi:10.1109/twc.2015.2485992 fatcat:oeqxeydgs5avrai2jk6qa5vleq

Bayesian Matching Pursuit Based Channel Estimation for Millimeter Wave Communication

You You, Li Zhang
2019 IEEE Communications Letters  
For hybrid precoding, the channel state information (CSI) is critical but hard to obtain because of the analog precoding at RF and the large number of antennas. mmWave channel has been proved to be sparse  ...  Hybrid precoding is considered as a solution to reduce the high power consumption caused by devices operating at radio frequency (RF) in millimeter wave (mmWave) communication.  ...  Q = √ P (F T ⊗ W H )A D ∈ C M ×N is the sensing matrix. (6) is a sparse signal recovery problem as h has only L nonzero elements and L ≪ N .  ... 
doi:10.1109/lcomm.2019.2953706 fatcat:chbkve7rdrhxhodabta7dp66ey
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