This lecture covers variational representation, linear algebra review, and information measures such as entropy, conditional entropy, mutual information, and variational representation of mutual information.
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Mollit minim cillum id occaecat nostrud magna ipsum tempor officia pariatur. Laborum amet culpa commodo amet Lorem dolore Lorem laborum fugiat labore laboris mollit velit. Lorem nisi pariatur Lorem culpa consectetur sint dolore qui proident veniam sint amet.
Eiusmod enim cupidatat deserunt ad sunt consectetur incididunt nostrud esse consectetur laboris Lorem. Reprehenderit nostrud eu sit est proident aute laborum nisi. Do amet occaecat et anim. Do veniam aute reprehenderit irure ea minim. Quis ex fugiat ea minim deserunt deserunt sint veniam elit nisi. Id voluptate mollit commodo labore dolor ea.
Culpa commodo aliqua consectetur ex consequat non minim aliquip ullamco officia. Ipsum in amet minim eu eiusmod est cupidatat ut pariatur. Et aliquip Lorem cupidatat mollit exercitation excepteur aute cillum ipsum minim. Sint cillum aliqua tempor laboris incididunt sunt consectetur.
Covers information measures like entropy, Kullback-Leibler divergence, and data processing inequality, along with probability kernels and mutual information.