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Results tagged with deep-learning
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user 18375
a new area of Machine Learning research concerned with the technologies used for learning hierarchical representations of data, mainly done with deep neural networks (i.e. networks with two or more hidden layers), but also with some sort of Probabilistic Graphical Models.
2
votes
How do neural networks account for outliers?
Here's a math answer for you.
Neural network is an approximation function $f(\theta)$ of the joint distribution $p(X, Y)$ of input data $X$ and labels $Y$. The learning process is the process of twea …
- 910
4
votes
What is the point of tensors in CNNs? Why not simply reshape the data into matrices?
Tensors come pretty natural in convolutionals networks.
Local pixel information matters: if $e$ is a pixel in your example above, it's important to know that $a$ through $i$ are its neighbors. This …
- 910
32
votes
Accepted
Why ReLU is better than the other activation functions
The biggest advantage of ReLu is indeed non-saturation of its gradient, which greatly accelerates the convergence of stochastic gradient descent compared to the sigmoid / tanh functions (paper by Kriz …
- 910