• 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 271 matches

• 2021
• 
  Nakamasa Inoue, Eisuke Yamagata, Hirokatsu Kataoka:
  Initialization Using Perlin Noise for Training Networks with a Limited Amount of Data. CoRR abs/2101.07406 (2021)
• 2020
• 
  Mohammad Al Samman, Hazlie Mokhlis, Nurulafiqah Nadzirah Mansor, Hasmaini Mohamad, Hadi Suyono, Norazliani Md. Sapari:
  Fast Optimal Network Reconfiguration With Guided Initialization Based on a Simplified Network Approach. IEEE Access 8: 11948-11963 (2020)
• 
  Zixia Sang, Jiaqi Huang, Dongjun Yang, Jiong Yan, Zhi Du, Rengcun Fang:
  An Initialization-free Distributed Algorithm for Power Dispatch Problem with Multiple Resources of Future Distribution Network. Int. J. Artif. Intell. Tools 29(7-8): 2040006:1-2040006:11 (2020)
• 
  Seongbo Jang, Ye-Eun Jang, Young-Jin Kim, Hwanjo Yu:
  Input initialization for inversion of neural networks using k-nearest neighbor approach. Inf. Sci. 519: 229-242 (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)
• 
  Cheng Lian, Zhigang Zeng, Xiaoping Wang, Wei Yao, Yixin Su, Huiming Tang:
  Landslide displacement interval prediction using lower upper bound estimation method with pre-trained random vector functional link network initialization. Neural Networks 130: 286-296 (2020)
• 
  Mieczyslaw Bakula, Marcin Uradzinski, Kamil Krasuski:
  Network Code DGNSS Positioning for Faster L1-L5 GPS Ambiguity Initialization. Sensors 20(19): 5671 (2020)
• 
  Changho Yun, Suhan Choi:
  A Feasibility Analysis of an Application-Based Partial Initialization (API) Protocol for Underwater Wireless Acoustic Sensor Networks. Sensors 20(19): 5635 (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)
• 
  Ramina Ghods, Andrew S. Lan, Tom Goldstein, Christoph Studer:
  MSE-Optimal Neural Network Initialization via Layer Fusion. CISS 2020: 1-6
• 
  Patryk Pazura, Kamil Bortko, Jaroslaw Jankowski, Radoslaw Michalski:
  A Dynamic Vote-Rank Based Approach for Effective Sequential Initialization of Information Spreading Processes Within Complex Networks. ICCS (1) 2020: 638-651
• 
  Yanli Yang, Yichuan He:
  A Weight Initialization Method Associated with Samples for Deep Feedforward Neural Network. ICCDE 2020: 54-59
• 
  Wei Hu, Lechao Xiao, Jeffrey Pennington:
  Provable Benefit of Orthogonal Initialization in Optimizing Deep Linear Networks. ICLR 2020
• 
  Namhoon Lee, Thalaiyasingam Ajanthan, Stephen Gould, Philip H. S. Torr:
  A Signal Propagation Perspective for Pruning Neural Networks at Initialization. ICLR 2020
• 
  Yaniv Blumenfeld, Dar Gilboa, Daniel Soudry:
  Beyond Signal Propagation: Is Feature Diversity Necessary in Deep Neural Network Initialization? ICML 2020: 960-969
• 
  Yanxu Hou, Jun Li, Zihan Fang, Xuechao Zhang:
  An Initialization Method of Deep Q-network for Learning Acceleration of Robotic Grasp. ICNSC 2020: 1-6
• 
  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
• 
  Nikolaos Passalis, George Mourgias-Alexandris, Nikos Pleros, Anastasios Tefas:
  Adaptive Initialization for Recurrent Photonic Networks using Sigmoidal Activations. ISCAS 2020: 1-5
• 
  Ido Nachum, Amir Yehudayoff:
  On Symmetry and Initialization for Neural Networks. LATIN 2020: 401-412
• 
  Eric C. Cyr, Mamikon A. Gulian, Ravi G. Patel, Mauro Perego, Nathaniel A. Trask:
  Robust Training and Initialization of Deep Neural Networks: An Adaptive Basis Viewpoint. MSML 2020: 512-536
• 
  Yaoyu Zhang, Zhi-Qin John Xu, Tao Luo, Zheng Ma:
  A type of generalization error induced by initialization in deep neural networks. MSML 2020: 144-164
• 
  Pravendra Singh, Munender Varshney, Vinay P. Namboodiri:
  Cooperative Initialization based Deep Neural Network Training. WACV 2020: 1130-1139
• 
  Wenqing Lin, Feng He, Faqiang Zhang, Xu Cheng, Hongyun Cai:
  Initialization for Network Embedding: A Graph Partition Approach. WSDM 2020: 367-374
• 
  Pravendra Singh, Munender Varshney, Vinay P. Namboodiri:
  Cooperative Initialization based Deep Neural Network Training. CoRR abs/2001.01240 (2020)
• 
  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)
• 
  Wei Hu, Lechao Xiao, Jeffrey Pennington:
  Provable Benefit of Orthogonal Initialization in Optimizing Deep Linear Networks. CoRR abs/2001.05992 (2020)
• 
  Ramina Ghods, Andrew S. Lan, Tom Goldstein, Christoph Studer:
  MSE-Optimal Neural Network Initialization via Layer Fusion. CoRR abs/2001.10509 (2020)
• 
  Wei Huang, Weitao Du, Richard Yi Da Xu:
  On the Neural Tangent Kernel of Deep Networks with Orthogonal Initialization. CoRR abs/2004.05867 (2020)
• 
  Stratis Limnios, George Dasoulas, Dimitrios M. Thilikos, Michalis Vazirgiannis:
  Hcore-Init: Neural Network Initialization based on Graph Degeneracy. CoRR abs/2004.07636 (2020)
• 
  Maciej Skorski:
  Revisiting Initialization of Neural Networks. CoRR abs/2004.09506 (2020)

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