Learning modular neural network policies for multi-task and multi-robot transfer. In Robotics and Automation (ICRA), 2017 IEEE International Conference on, pages 2169-2176. IEEE, 2017.C. Devin, A. Gupta, T. Darrell, P. Abbeel, S. Levine. Learning modular neural network policies for multi-...
[2] J. Andreas, M. Rohrbach, T. Darrell, and D. Klein, “Learning to Compose Neural Networks for Question Answering,” inProceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, San Diego, California, Jun. 20...
Chandra R, Gupta A, Ong Y S, et al. Evolutionary multi-task learning for modular knowledge representation in neural networks[J]. Neural Processing Letters, 2018, 47: 993-1009. 本文提出了一种通过模块化网络拓扑进行神经网络(非传统的前馈神经网络,类似于储层网络)中模块化知识表示的多任务学习方法。...
更多例句筛选 1. Handwritten Digit Recognition Using Wavelet Neural Networks and Modular Neural Networks 基于小波网络和多模块网络的数字识别 ilib.cn 2. The Learning Algorithms of Optimum Modular Neural Networks in Multiclass Classification 多类分类优化模块神经网络学习算法 www.ilib.cn©...
Tingwu Wang, Renjie Liao, Jimmy Ba, and Sanja Fidler. Nervenet: Learning structured policy with graph neural networks. In International conference on learning representations, 2018. Wenlong Huang, Igor Mordatch, and Deepak Pathak. One policy to control them all: Shared modular policies for agent-...
In this chapter, we focus on two important areas in neural computation, i.e., deep and modular neural networks, given the fact that both deep and modular neural networks are among the most powerful machine learning and pattern recognition techniques for complex AI problem solving. We begin by...
,butmoreimportantlyoursystemusestechniquesfromreinforcementlearningtointernallycreateitsownexamples.Userscanalsoprovideadditionalinstructionthroughoutthelifeofanagent.Empiricalresultsonseveraldomainsshowtheadvantagesofourapproach.Keywords.Instructableandadaptivesoftwareagents,Webmining,machinelearning,neuralnetworks,information...
Modula is a deep learning framework designed for graceful scaling. Neural networks written in Modula automatically transfer learning rate across scale. We are slowly writingthe Modula docs. Check them out for an accessible introduction to scaling theory and the Modula API. Also, here are someslides...
To mitigate theses drawbacks in SDC, we therefore, propose a hierarchical dense dilated deep pyramid feature extraction through convolution neural network (CNN) for single image crowd counting (HDPF). It comprises of three modules: general feature extraction module (GFEM), deep pyramid feature ...
imtf-grn: integrative matrix tri-factorization for inference of gene regulatory networks. IEEE Access 2019;7:126154–63. https://doi.org/10.1109/access.2019.2936794.Search in Google Scholar 3. Wani, N, Raza, K. Mkl-grni: a parallel multiple kernel learning approach for supervised inference of...