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CVPR20(11263-11272)
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Computer architecture, Search problems, DNA, Linear programming,
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Dictionaries, Sparse representation, Robustness, Coherence,
Neural networks, Computer architecture, Machine learning
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CVPR20(11214-11223)
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2008
Training, Computational modeling, Computer architecture,
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CVPR20(10425-10433)
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Computational modeling, Manuals, Tools, Sociology, Statistics,
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CVPR20(9480-9489)
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Augment NN with attention model.
Robustness, Computational modeling,
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CVPR20(6438-6447)
IEEE DOI
2008
Training, Principal component analysis, Covariance matrices,
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Can Weight Sharing Outperform Random Architecture Search? An
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CVPR20(14311-14320)
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Computer architecture, Search problems, Google,
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CVPR20(14569-14578)
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2008
Semantics, Visualization, Task analysis, Knowledge discovery,
Message passing, Computational modeling, Biological neural networks
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Regularizing Neural Networks via Minimizing Hyperspherical Energy,
CVPR20(6916-6925)
IEEE DOI
2008
Neurons, Biological neural networks, Training, Optimization,
Task analysis, Testing, Linear programming
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He, Z.,
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Chen, K.,
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Gonzalez, J.E.,
FBNetV2: Differentiable Neural Architecture Search for Spatial and
Channel Dimensions,
CVPR20(12962-12971)
IEEE DOI
2008
DNA, Computer architecture, Convolution, Neural networks, Training,
Computational efficiency, Space exploration
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Mozejko, M.,
Latkowski, T.,
Treszczotko, L.,
Szafraniuk, M.,
Trojanowski, K.,
Superkernel Neural Architecture Search for Image Denoising,
NTIRE20(2002-2011)
IEEE DOI
2008
Training, Task analysis, Image denoising, Kernel, Memory management, Graphics processing units
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Yang, Y.,
Jiang, Y.,
Zhu, W.,
Liu, Y.,
Fast Hardware-Aware Neural Architecture Search,
EDLCV20(2959-2967)
IEEE DOI
2008
Hardware, Computer architecture, Graphics processing units,
Hurricanes, Training, Measurement
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Gao, Y.,
Bai, H.,
Jie, Z.,
Ma, J.,
Jia, K.,
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MTL-NAS: Task-Agnostic Neural Architecture Search Towards
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CVPR20(11540-11549)
IEEE DOI
2008
Task analysis, Computer architecture, Entropy, Neural networks,
Feature extraction, Semantics, Convolution
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Zhou, D.,
Zhou, X.,
Zhang, W.,
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Yi, S.,
Zhang, X.,
Ouyang, W.,
EcoNAS: Finding Proxies for Economical Neural Architecture Search,
CVPR20(11393-11401)
IEEE DOI
2008
Training, Computer architecture, Reliability,
Graphics processing units, Acceleration, Computer vision, Measurement
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Zheng, X.,
Ji, R.,
Wang, Q.,
Ye, Q.,
Li, Z.,
Tian, Y.,
Tian, Q.,
Rethinking Performance Estimation in Neural Architecture Search,
CVPR20(11353-11362)
IEEE DOI
2008
Computer architecture, Estimation, Microprocessors, Training,
Optimization, Search problems, Learning (artificial intelligence)
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Fang, J.,
Sun, Y.,
Zhang, Q.,
Li, Y.,
Liu, W.,
Wang, X.,
Densely Connected Search Space for More Flexible Neural Architecture
Search,
CVPR20(10625-10634)
IEEE DOI
2008
Routing, Computer architecture, Tensile stress, Estimation,
Approximation algorithms, Spatial resolution, Microprocessors
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Li, Y.,
Jin, X.,
Mei, J.,
Lian, X.,
Yang, L.,
Xie, C.,
Yu, Q.,
Zhou, Y.,
Bai, S.,
Yuille, A.L.,
Neural Architecture Search for Lightweight Non-Local Networks,
CVPR20(10294-10303)
IEEE DOI
2008
Computer architecture, Neural networks, Computational modeling,
Task analysis, Graphics processing units, Mobile handsets,
Computational complexity
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Hu, S.K.[Shou-Kang],
Xie, S.R.[Si-Rui],
Zheng, H.H.[He-Hui],
Liu, C.X.[Chun-Xiao],
Shi, J.P.[Jian-Ping],
Liu, X.Y.[Xun-Ying],
Lin, D.H.[Da-Hua],
DSNAS: Direct Neural Architecture Search Without Parameter Retraining,
CVPR20(12081-12089)
IEEE DOI
2008
Task analysis, Computer architecture, Optimization, Training,
Search problems, Measurement, Machine learning
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Atzmon, M.[Matan],
Lipman, Y.[Yaron],
SAL: Sign Agnostic Learning of Shapes From Raw Data,
CVPR20(2562-2571)
IEEE DOI
2008
Surface reconstruction, Shape,
Neural networks, Interpolation, Mathematical model, Training
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Li, C.,
Peng, J.,
Yuan, L.,
Wang, G.,
Liang, X.,
Lin, L.,
Chang, X.,
Block-Wisely Supervised Neural Architecture Search With Knowledge
Distillation,
CVPR20(1986-1995)
IEEE DOI
2008
Computer architecture, Network architecture,
Knowledge engineering, Training, DNA, Convergence, Feature extraction
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Tang, Y.H.[Ye-Hui],
Wang, Y.H.[Yun-He],
Xu, Y.X.[Yi-Xing],
Chen, H.T.[Han-Ting],
Shi, B.X.[Bo-Xin],
Xu, C.[Chao],
Xu, C.J.[Chun-Jing],
Tian, Q.[Qi],
Xu, C.[Chang],
A Semi-Supervised Assessor of Neural Architectures,
CVPR20(1807-1816)
IEEE DOI
2008
Computer architecture, Training, Task analysis, Microprocessors,
Optimization, Neural networks, Feature extraction
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Li, Z.,
Xi, T.,
Deng, J.,
Zhang, G.,
Wen, S.,
He, R.,
GP-NAS: Gaussian Process Based Neural Architecture Search,
CVPR20(11930-11939)
IEEE DOI
2008
Computer architecture, Correlation, Kernel, Training, Task analysis,
Network architecture, Mutual information
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Wang, N.,
Gao, Y.,
Chen, H.,
Wang, P.,
Tian, Z.,
Shen, C.,
Zhang, Y.,
NAS-FCOS: Fast Neural Architecture Search for Object Detection,
CVPR20(11940-11948)
IEEE DOI
2008
Object detection, Computer architecture, Search problems,
Task analysis, Decoding, Feature extraction, Detectors
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He, C.,
Ye, H.,
Shen, L.,
Zhang, T.,
MiLeNAS: Efficient Neural Architecture Search via Mixed-Level
Reformulation,
CVPR20(11990-11999)
IEEE DOI
2008
Mathematical model, Training, Computer architecture,
Optimization methods, Training data, Neural networks
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Tao, Y.,
Ma, R.,
Shyu, M.,
Chen, S.,
Challenges in Energy-Efficient Deep Neural Network Training with FPGA,
LPCV20(1602-1611)
IEEE DOI
2008
Field programmable gate arrays, Computational modeling, Training,
Hardware, Neural networks, Machine learning, Graphics processing units
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Liu, P.,
Wu, B.,
Ma, H.,
Seok, M.,
MemNAS: Memory-Efficient Neural Architecture Search With Grow-Trim
Learning,
CVPR20(2105-2113)
IEEE DOI
2008
Memory management, Neural networks, Correlation,
Performance evaluation, Computational modeling
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Gao, C.,
Chen, Y.,
Liu, S.,
Tan, Z.,
Yan, S.,
AdversarialNAS: Adversarial Neural Architecture Search for GANs,
CVPR20(5679-5688)
IEEE DOI
2008
Computer architecture, Generators, Task analysis,
Convolution, Generative adversarial networks, Computer vision
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Li, G.H.[Guo-Hao],
Qian, G.C.[Guo-Cheng],
Delgadillo, I.C.[Itzel C.],
Müller, M.[Matthias],
Thabet, A.[Ali],
Ghanem, B.[Bernard],
SGAS: Sequential Greedy Architecture Search,
CVPR20(1617-1627)
IEEE DOI
2008
Neural Architecture Search.
Computer architecture, Correlation, Search problems, Task analysis,
Optimization, Computational efficiency, Microprocessors
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Chen, X.[Xin],
Xie, L.X.[Ling-Xi],
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Progressive Differentiable Architecture Search:
Bridging the Depth Gap Between Search and Evaluation,
ICCV19(1294-1303)
IEEE DOI
2004
Code, Search.
WWW Link. approximation theory, image recognition,
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Computational modeling
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Banerjee, S.,
Chakraborty, S.,
Deepsub: A Novel Subset Selection Framework for Training Deep
Learning Architectures,
ICIP19(1615-1619)
IEEE DOI
1910
Submodular optimization, Deep learning
BibRef
Xiong, Y.,
Mehta, R.,
Singh, V.,
Resource Constrained Neural Network Architecture Search:
Will a Submodularity Assumption Help?,
ICCV19(1901-1910)
IEEE DOI
2004
learning (artificial intelligence), neural nets, optimisation,
neural network architecture search, empirical feedback,
Heuristic algorithms
BibRef
Zhao, R.,
Luk, W.,
Efficient Structured Pruning and Architecture Searching for Group
Convolution,
NeruArch19(1961-1970)
IEEE DOI
2004
convolutional neural nets, group theory, network theory (graphs),
neural net architecture, search problems, network pruning,
efficient inference
BibRef
Li, X.[Xin],
Zhou, Y.M.[Yi-Ming],
Pan, Z.[Zheng],
Feng, J.[Jiashi],
Partial Order Pruning: For Best Speed/Accuracy Trade-Off in Neural
Architecture Search,
CVPR19(9137-9145).
IEEE DOI
2002
BibRef
Guo, M.H.[Ming-Hao],
Zhong, Z.[Zhao],
Wu, W.[Wei],
Lin, D.[Dahua],
Yan, J.J.[Jun-Jie],
IRLAS: Inverse Reinforcement Learning for Architecture Search,
CVPR19(9013-9021).
IEEE DOI
2002
search network structures that are topologically inspired by
human-designed network
BibRef
Gong, X.,
Chang, S.,
Jiang, Y.,
Wang, Z.,
AutoGAN: Neural Architecture Search for Generative Adversarial
Networks,
ICCV19(3223-3233)
IEEE DOI
2004
Code, Generative Adversarial Network.
WWW Link. image classification, image segmentation, neural nets,
neural architecture search, generative adversarial networks,
Prediction algorithms
BibRef
Yan, S.,
Fang, B.,
Zhang, F.,
Zheng, Y.,
Zeng, X.,
Zhang, M.,
Xu, H.,
HM-NAS: Efficient Neural Architecture Search via Hierarchical Masking,
NeruArch19(1942-1950)
IEEE DOI
2004
Code, Neural Netowrks.
WWW Link. learning (artificial intelligence), neural net architecture,
multilevel architecture, flexible network architectures,
Hierarchical Masking
BibRef
Wu, B.C.[Bi-Chen],
Dai, X.L.[Xiao-Liang],
Zhang, P.Z.[Pei-Zhao],
Wang, Y.H.[Yang-Han],
Sun, F.[Fei],
Wu, Y.M.[Yi-Ming],
Tian, Y.D.[Yuan-Dong],
Vajda, P.[Peter],
Jia, Y.Q.[Yang-Qing],
Keutzer, K.[Kurt],
FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable
Neural Architecture Search,
CVPR19(10726-10734).
IEEE DOI
2002
BibRef
Cui, J.,
Chen, P.,
Li, R.,
Liu, S.,
Shen, X.,
Jia, J.,
Fast and Practical Neural Architecture Search,
ICCV19(6508-6517)
IEEE DOI
2004
learning (artificial intelligence), neural nets, FPNAS,
search process, bi-level optimization problem, design networks,
Network architecture
BibRef
Bashivan, P.[Pouya],
Tensen, M.[Mark],
Dicarlo, J.[James],
Teacher Guided Architecture Search,
ICCV19(5319-5328)
IEEE DOI
2004
convolutional neural nets,
learning (artificial intelligence), neural net architecture,
Network architecture
BibRef
Zheng, X.,
Ji, R.,
Tang, L.,
Zhang, B.,
Liu, J.,
Tian, Q.,
Multinomial Distribution Learning for Effective Neural Architecture
Search,
ICCV19(1304-1313)
IEEE DOI
2004
Code, Neural Networks.
WWW Link. graphics processing units,
learning (artificial intelligence), neural nets,
Search problems
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Zhu, H.,
An, Z.,
Yang, C.,
Xu, K.,
Zhao, E.,
Xu, Y.,
EENA: Efficient Evolution of Neural Architecture,
NeruArch19(1891-1899)
IEEE DOI
2004
learning (artificial intelligence), neural net architecture,
search problems, crossover operations, evolution process,
guidance of experience gained
BibRef
Tan, M.X.[Ming-Xing],
Chen, B.[Bo],
Pang, R.[Ruoming],
Vasudevan, V.[Vijay],
Sandler, M.[Mark],
Howard, A.[Andrew],
Le, Q.V.[Quoc V.],
MnasNet: Platform-Aware Neural Architecture Search for Mobile,
CVPR19(2815-2823).
IEEE DOI
2002
BibRef
Dong, X.Y.[Xuan-Yi],
Yang, Y.[Yi],
Searching for a Robust Neural Architecture in Four GPU Hours,
CVPR19(1761-1770).
IEEE DOI
2002
BibRef
Dong, X.Y.[Xuan-Yi],
Yang, Y.[Yi],
One-Shot Neural Architecture Search via Self-Evaluated Template
Network,
ICCV19(3680-3689)
IEEE DOI
2004
image sampling, knowledge based systems,
learning (artificial intelligence), neural net architecture,
BibRef
Rashwan, A.,
Kalra, A.,
Poupart, P.,
Matrix Nets: A New Deep Architecture for Object Detection,
NeruArch19(2025-2028)
IEEE DOI
2004
learning (artificial intelligence), neural net architecture,
object detection, Matrix Nets, deep architecture, object detection,
neural architecture
BibRef
Cheng, H.,
Zhang, T.,
Yang, Y.,
Yan, F.,
Teague, H.,
Chen, Y.,
Li, H.,
MSNet: Structural Wired Neural Architecture Search for Internet of
Things,
NeruArch19(2033-2036)
IEEE DOI
2004
convolutional neural nets, Internet of Things,
learning (artificial intelligence), mobile computing,
neural architecture search
BibRef
Chen, H.T.[Han-Ting],
Wang, Y.H.[Yun-He],
Xu, C.[Chang],
Yang, Z.H.[Zhao-Hui],
Liu, C.J.[Chuan-Jian],
Shi, B.X.[Bo-Xin],
Xu, C.J.[Chun-Jing],
Xu, C.[Chao],
Tian, Q.[Qi],
Data-Free Learning of Student Networks,
ICCV19(3513-3521)
IEEE DOI
2004
computer vision, convolutional neural nets,
learning (artificial intelligence), neural net architecture,
Knowledge engineering
BibRef
Liu, C.X.[Chen-Xi],
Zoph, B.[Barret],
Neumann, M.[Maxim],
Shlens, J.[Jonathon],
Hua, W.[Wei],
Li, L.J.[Li-Jia],
Fei-Fei, L.[Li],
Yuille, A.L.[Alan L.],
Huang, J.[Jonathan],
Murphy, K.[Kevin],
Progressive Neural Architecture Search,
ECCV18(I: 19-35).
Springer DOI
1810
New method for learning CNN
BibRef
Srinivas, S.[Suraj],
Babu, V.[Venkatesh],
Learning Neural Network Architectures using Backpropagation,
BMVC16(xx-yy).
HTML Version.
1805
BibRef
Hasegawa, R.[Ryoma],
Hotta, K.[Kazuhiro],
PLSNet: A simple network using Partial Least Squares regression for
image classification,
ICPR16(1601-1606)
IEEE DOI
1705
Convolution, Databases, Feature extraction, Image classification,
Network architecture, Principal component analysis, Training,
Convolutional Neural Network, Deep Learning, PCANet, PLSNet,
Partial Least Squares Regression, Stacked, PLS
BibRef
Espinal, A.[Andrés],
Carpio, M.[Martín],
Ornelas, M.[Manuel],
Puga, H.[Héctor],
Melín, P.[Patricia],
Sotelo-Figueroa, M.[Marco],
Developing Architectures of Spiking Neural Networks by Using
Grammatical Evolution Based on Evolutionary Strategy,
MCPR14(71-80).
Springer DOI
1407
BibRef
Elliman, D.G.[David G.],
Youssef, S.M.[Sherin M.],
Contextual Swarm-Based Multi-layered Lattices:
A New Architecture for Contextual Pattern Recognition,
DAS04(496-507).
Springer DOI
0505
BibRef
Yang, Z.,
Wang, Y.,
Chen, X.,
Shi, B.,
Xu, C.,
Xu, C.,
Tian, Q.,
Xu, C.,
CARS: Continuous Evolution for Efficient Neural Architecture Search,
CVPR20(1826-1835)
IEEE DOI
2008
Optimization, Nickel, Computer architecture, Network architecture,
Sorting, Training, Automobiles
BibRef
Chen, Y.K.[Yu-Kang],
Meng, G.F.[Gao-Feng],
Zhang, Q.[Qian],
Xiang, S.M.[Shi-Ming],
Huang, C.[Chang],
Mu, L.[Lisen],
Wang, X.G.[Xing-Gang],
RENAS: Reinforced Evolutionary Neural Architecture Search,
CVPR19(4782-4791).
IEEE DOI
2002
BibRef
Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Neural Networks for Classification and Pattern Recognition .