Concurrent checkpoint initiation and recovery algorithms on asynchronous ring networks

2004 ◽  
Vol 64 (5) ◽  
pp. 649-661 ◽  
Author(s):  
Partha Sarathi Mandal ◽  
Krishnendu Mukhopadhyaya
Keyword(s):  
Ring Networks ◽  
Recovery Algorithms

Symmetric degree-four chordal ring networks

1990 ◽  
Vol 137 (4) ◽  
pp. 310 ◽  
Author(s):  
R.F. Browne ◽  
R.M. Hodgson
Keyword(s):  
Ring Networks ◽  
Chordal Ring

scholarly journals Heuristic rank selection with progressively searching tensor ring network

2021 ◽  
Author(s):  
Nannan Li ◽  
Yu Pan ◽  
Yaran Chen ◽  
Zixiang Ding ◽  
Dongbin Zhao ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Compression Ratio ◽  
State Of The Art ◽  
Heuristic Method ◽  
Ring Networks ◽  
Ring Network ◽  
Narrow Region ◽  
Network Search ◽  
Deep Networks ◽  
Evolutionary Phase

AbstractRecently, tensor ring networks (TRNs) have been applied in deep networks, achieving remarkable successes in compression ratio and accuracy. Although highly related to the performance of TRNs, rank selection is seldom studied in previous works and usually set to equal in experiments. Meanwhile, there is not any heuristic method to choose the rank, and an enumerating way to find appropriate rank is extremely time-consuming. Interestingly, we discover that part of the rank elements is sensitive and usually aggregate in a narrow region, namely an interest region. Therefore, based on the above phenomenon, we propose a novel progressive genetic algorithm named progressively searching tensor ring network search (PSTRN), which has the ability to find optimal rank precisely and efficiently. Through the evolutionary phase and progressive phase, PSTRN can converge to the interest region quickly and harvest good performance. Experimental results show that PSTRN can significantly reduce the complexity of seeking rank, compared with the enumerating method. Furthermore, our method is validated on public benchmarks like MNIST, CIFAR10/100, UCF11 and HMDB51, achieving the state-of-the-art performance.

A reality check for radiometric camera response recovery algorithms

2013 ◽  
Vol 37 (7) ◽  
pp. 935-943 ◽  
Author(s):  
Ahmet Oğuz Akyüz ◽  
Aslı Gençtav
Keyword(s):  
Reality Check ◽  
Response Recovery ◽  
Recovery Algorithms

Classification of ISAR images using sparse recovery algorithms

2014 ◽  
Author(s):  
Seung-Jae Lee ◽  
Ji-Hoon Bae ◽  
Byung-Soo Kang ◽  
Kyung-Tae Kim ◽  
Eun-Jung Yang
Keyword(s):  
Sparse Recovery ◽  
Recovery Algorithms

Microstructure reconstructions from 2-point statistics using phase-recovery algorithms

2008 ◽  
Vol 56 (5) ◽  
pp. 942-948 ◽  
Author(s):  
David T. Fullwood ◽  
Stephen R. Niezgoda ◽  
Surya R. Kalidindi
Keyword(s):  
Phase Recovery ◽  
Recovery Algorithms
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