Explore >> Select a destination
|
You are here 
|
francisbach.com | ||
| | | | |
blog.ml.cmu.edu
|
|
| | | | | The latest news and publications regarding machine learning, artificial intelligence or related, brought to you by the Machine Learning Blog, a spinoff of the Machine Learning Department at Carnegie Mellon University. | |
| | | | |
fa.bianp.net
|
|
| | | | | Backtracking step-size strategies (also known as adaptive step-size or approximate line-search) that set the step-size based on a sufficient decrease condition are the standard way to set the step-size on gradient descent and quasi-Newton methods. However, these techniques are typically not used for Frank-Wolfe-like algorithms. In this blog post I discuss a backtracking line-search for the Frank-Wolfe algorithm. | |
| | | | |
windowsontheory.org
|
|
| | | | | Previous post: ML theory with bad drawings Next post: What do neural networks learn and when do they learn it, see also all seminar posts and course webpage. Lecture video (starts in slide 2 since I hit record button 30 seconds too late - sorry!) - slides (pdf) - slides (Powerpoint with ink and animation)... | |
| | | | |
algobeans.com
|
|
| | | While an artificial neural network could learn to recognize a cat on the left, it would not recognize the same cat if it appeared on the right. To solve this problem, we introduce convolutional neural networks. | ||
