benanne

10 ms·

61.
by benanne 12y ago
Yep, it's linear. This is essentially a regression task and the distribution of the factors across the dataset is pretty close to Gaussian in most cases, so it made sense not to have any nonlinearities there. As a sidenote, if it weren
62.
by benanne 12y ago
I haven't really optimized that part of the pipeline, for now I'm just using what I always use because getting the data and massaging it into the right format is quite time consuming. There is a lot of knowledge about good time-fr
63.
by benanne 12y ago
I haven't tried it, so I can't say for sure, but my intuition is that learning to predict the latent factors is a much less 'complex' task than learning good features to reconstruct the input (i.e. the spectrograms), in
64.
by benanne 12y ago
I can't really answer this question in general, but I can speak for myself: while it's not something a lot of PhD students do in Belgium (it seems to be more common in the US actually), I felt like it would be a great opportunity
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Recommending music on Spotify with deep learning(benanne.github.io)
140 points by benanne 12y ago|23 comments
66.
by benanne 12y ago
Afaik what you're talking about is more commonly referred to as "semi-supervised learning". Transduction is a more specific case of semi-supervised learning where you know the test set, i.e. you know which data points the mod
67.
by benanne 12y ago
I'd love to try out Torch7, but I've grown accustomed to Theano's automatic differentation, which is the killer feature for me. That's the one thing keeping me from exploring the alternatives. Not having to calculate any
68.
NASA’s Latest Robot: A Rolling Tangle of Rods That Can Take a Beating(wired.com)
1 points by benanne 13y ago|0 comments