<--- Back to Details
First PageDocument Content
Computational statistics / Machine learning / Computational biology / Sepp Hochreiter / Artificial neural networks / Computational neuroscience / Deep learning / Autoencoder / Principal component analysis / Normal distribution / Stochastic gradient descent / Support vector machine
Date: 2015-12-03 06:11:45
Computational statistics
Machine learning
Computational biology
Sepp Hochreiter
Artificial neural networks
Computational neuroscience
Deep learning
Autoencoder
Principal component analysis
Normal distribution
Stochastic gradient descent
Support vector machine

Rectified Factor Networks

Add to Reading List

Source URL: www.bioinf.jku.at

Download Document from Source Website

File Size: 3,70 MB

Share Document on Facebook

Similar Documents

Artificial intelligence / Applied mathematics / Learning / Machine learning / Computational neuroscience / Artificial neural networks / Computational statistics / Monte Carlo tree search / Convolutional neural network / Reinforcement learning / Q-learning / Structured prediction

Thinking Fast and Slow with Deep Learning and Tree Search Thomas Anthony1, , Zheng Tian1 , and David Barber1,2 arXiv:1705.08439v4 [cs.AI] 3 Dec 2017

DocID: 1xVZc - View Document

Computational neuroscience / Artificial intelligence / Machine learning algorithms / Neuroscience / Applied mathematics / Artificial neural networks / Reinforcement learning / Q-learning / Convolutional neural network / Distributed artificial intelligence / Deep learning / Intelligent agent

Cooperative Multi-Agent Control Using Deep Reinforcement Learning Jayesh K. Gupta Maxim Egorov

DocID: 1xVVh - View Document

Artificial neural networks / Computational neuroscience / Applied mathematics / Artificial intelligence / Long short-term memory / Cybernetics / Frequency modulation / Deep learning / Convolutional neural network / Speech recognition / OFF

1 Distributed Deep Learning Models for Wireless Signal Classification with Low-Cost Spectrum Sensors

DocID: 1xVRV - View Document

Proceedings of Machine Learning Research, 4th International Conference on Predictive Applications and APIs Flexible and Scalable Deep Learning with MMLSpark Mark Hamilton Sudarshan

DocID: 1xVPK - View Document

Robotics / Emerging technologies / Technology / Applied mathematics / Computational neuroscience / Artificial intelligence / Cybernetics / Trajectory optimization / Unmanned aerial vehicle / Quadcopter / Artificial neural network / Self-driving car

Deep Drone Racing: Learning Agile Flight in Dynamic Environments Elia Kaufmann1∗, Antonio Loquercio1∗, Ren´e Ranftl2 , Alexey Dosovitskiy2 , Vladlen Koltun2 , Davide Scaramuzza1 1 Robotics and Perception Group Depts

DocID: 1xVCK - View Document