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I think what differs deep learning from other machine learning techniques is the ability to form a hierarchy of features by itself. I think most of today's succ
by yzh 12y ago
I think what differs deep learning from other machine learning techniques is the ability to form a hierarchy of features by itself. I think most of today's successful deep learning systems focus on supervised learning. For me I certainly want to know more about CNN and Caffe, but I also want to learn more about how to apply deep learning to unsupervised learning and reinforcement learning. Any paper/course suggestion?
- NhanH 12y agoYou can look up the related papers about playing Atari with deep learning just released recently, that one is a reinforcement learning one. When deep learning first started, it was actually very unsupervised focused with stacked autoencoders and DBMs, the most well known paper around that time would probably be the youtube cat recognizing paper from Google/ Stanford [0]. A lot of the "early" works (from around 2006-2010) is unsupervised learning as well, just look up Geoff Hinton paper around that time. [0]:http://static.googleusercontent.com/external_content/untrusted_dlcp/research.google.com/en/us/pubs/archive/38115.pdf http://static.googleusercontent.com/external_content/untrust... .
- dustintran 12y agoThis is not completely accurate. Deep learning at the moment simply means the use of "deep" architectures in neural networks. Graphical models, standard Bayesian hierarchical models, and the likes all form hierarchies of features as well and are commonly practiced.
- wodenokoto 12y agoYou want to look for something called self-organizing-maps or SOM