• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 153 matches

• 2021
• 
  Abdelraouf Ishtaiwi, Feda Alshahwan, Naser Jamal, Wael Hadi, Muhammad AbuArqoub:
  A Dynamic Clause Specific Initial Weight Assignment for Solving Satisfiability Problems Using Local Search. Algorithms 14(1): 12 (2021)
• 
  Wadii Boulila, Maha Driss, Mohammed Al-Sarem, Faisal Saeed, Moez Krichen:
  Weight Initialization Techniques for Deep Learning Algorithms in Remote Sensing: Recent Trends and Future Perspectives. CoRR abs/2102.07004 (2021)
• 2020
• 
  Richard N. M. Rudd-Orthner, Lyudmila Mihaylova:
  Repeatable determinism using non-random weight initialisations in smart city applications of deep learning. J. Reliab. Intell. Environ. 6(1): 31-49 (2020)
• 
  Mafalda Falcão Ferreira, Rui Camacho, Luís Filipe Teixeira:
  Using autoencoders as a weight initialization method on deep neural networks for disease detection. BMC Medical Informatics Decis. Mak. 20-S(5): 141 (2020)
• 
  Zile Deng, Yuanlong Cao, Xinyu Zhou, Yugen Yi, Yirui Jiang, Ilsun You:
  Toward Efficient Image Recognition in Sensor-Based IoT: A Weight Initialization Optimizing Method for CNN Based on RGB Influence Proportion. Sensors 20(10): 2866 (2020)
• 
  Seongchul Park, Sanghyun Seo, Changhoon Jeong, Juntae Kim:
  The weights initialization methodology of unsupervised neural networks to improve clustering stability. J. Supercomput. 76(8): 6421-6437 (2020)
• 
  Huimin Li, Marina Krcek, Guilherme Perin:
  A Comparison of Weight Initializers in Deep Learning-Based Side-Channel Analysis. ACNS Workshops 2020: 126-143
• 
  Eden Belouadah, Adrian Popescu, Ioannis Kanellos:
  Initial Classifier Weights Replay for Memoryless Class Incremental Learning. BMVC 2020
• 
  Kathrin Grosse, Thomas Alexander Trost, Marius Mosbach, Michael Backes, Dietrich Klakow:
  On the Security Relevance of Initial Weights in Deep Neural Networks. ICANN (1) 2020: 3-14
• 
  Kaihui Liu, Lingling Li, Liangtian Wan:
  Weighted Null Vector Initialization and its Application to Phase Retrieval. ICASSP 2020: 4861-4865
• 
  Yanli Yang, Yichuan He:
  A Weight Initialization Method Associated with Samples for Deep Feedforward Neural Network. ICCDE 2020: 54-59
• 
  Oscar Chang, Lampros Flokas, Hod Lipson:
  Principled Weight Initialization for Hypernetworks. ICLR 2020
• 
  Paolo Gabriel Cachi, Sebastián Ventura, Krzysztof Jozef Cios:
  Fast Convergence of Competitive Spiking Neural Networks with Sample-Based Weight Initialization. IPMU (3) 2020: 773-786
• 
  Zehan Chao, Longxiu Huang, Deanna Needell:
  Tensor Completion through Total Variation with Initialization from Weighted HOSVD. ITA 2020: 1-8
• 
  Mafalda Falcao Ferreira, Rui Camacho, Luís Filipe Teixeira:
  Autoencoders as Weight Initialization of Deep Classification Networks for Cancer versus Cancer Studies. CoRR abs/2001.05253 (2020)
• 
  Jesse Dodge, Gabriel Ilharco, Roy Schwartz, Ali Farhadi, Hannaneh Hajishirzi, Noah A. Smith:
  Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping. CoRR abs/2002.06305 (2020)
• 
  Zehan Chao, Longxiu Huang, Deanna Needell:
  Tensor Completion through Total Variationwith Initialization from Weighted HOSVD. CoRR abs/2003.09062 (2020)
• 
  Nadir Murru, Rosaria Rossini:
  A Bayesian approach for initialization of weights in backpropagation neural net with application to character recognition. CoRR abs/2004.01875 (2020)
• 
  Cristian Ivan, Razvan Florian:
  Training highly effective connectivities within neural networks with randomly initialized, fixed weights. CoRR abs/2006.16627 (2020)
• 
  Eden Belouadah, Adrian Popescu, Ioannis Kanellos:
  Initial Classifier Weights Replay for Memoryless Class Incremental Learning. CoRR abs/2008.13710 (2020)
• 
  Zimeng Lyu, AbdElRahman A. ElSaid, Joshua Karns, Mohamed Wiem Mkaouer, Travis Desell:
  An Experimental Study of Weight Initialization and Weight Inheritance Effects on Neuroevolution. CoRR abs/2009.09644 (2020)
• 
  Stone Yun, Alexander Wong:
  Where Should We Begin? A Low-Level Exploration of Weight Initialization Impact on Quantized Behaviour of Deep Neural Networks. CoRR abs/2011.14578 (2020)
• 
  R. J. Jesus, Mário Luis Pinto Antunes, R. A. da Costa, Sergey N. Dorogovtsev, J. F. F. Mendes, Rui L. Aguiar:
  Effect of the initial configuration of weights on the training and function of artificial neural networks. CoRR abs/2012.02550 (2020)
• 
  Huimin Li, Marina Krcek, Guilherme Perin:
  A Comparison of Weight Initializers in Deep Learning-based Side-channel Analysis. IACR Cryptol. ePrint Arch. 2020: 904 (2020)
• 2019
• 
  Maysa Ibrahem Almulla Khalaf, John Q. Gan:
  A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder. Artif. Intell. Res. 8(1): 41-50 (2019)
• 
  Simon D. Watt, Harvinder S. Sidhu, Zlatko Jovanoski, Isaac N. Towers, Z. Huang:
  Watershed initial conditions for propagating waves in a system with bistability: A weight-function approach. Appl. Math. Lett. 91: 106-112 (2019)
• 
  Liwen Peng, Yongguo Liu:
  Attribute weights-based clustering centres algorithm for initialising K-modes clustering. Clust. Comput. 22(Supplement): 6171-6179 (2019)
• 
  Feng-Ping An:
  Medical Image Classification Algorithm Based on Weight Initialization-Sliding Window Fusion Convolutional Neural Network. Complex. 2019: 9151670:1-9151670:15 (2019)
• 
  Yun Yang, Jianmin Jiang:
  Adaptive Bi-Weighting Toward Automatic Initialization and Model Selection for HMM-Based Hybrid Meta-Clustering Ensembles. IEEE Trans. Cybern. 49(5): 1657-1668 (2019)
• 
  Richard N. M. Rudd-Orthner, Lyudmila Mihaylova:
  Non-Random Weight Initialisation in Deep Learning Networks for Repeatable Determinism. DESSERT 2019: 223-230

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