Your teaching skills are truly impressive! Thank you for sharing those insightful tips that make these approximations more understandable at their core, especially the link to the factor graphs. Very useful for someone who wishes to connect the dots and gain a comprehensive understanding of why and how these approaches work, rather than just applying their results.
Unfortunately for GPs, it seems for nearly every machine learning-like process the sparse Bernoulli model has been proven as superior, along with the rTop-k algorithm as of late 2020. From my understanding of course.
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Your teaching skills are truly impressive! Thank you for sharing those insightful tips that make these approximations more understandable at their core, especially the link to the factor graphs. Very useful for someone who wishes to connect the dots and gain a comprehensive understanding of why and how these approaches work, rather than just applying their results.
Thanks for sharing, very nice explanation!
Brilliant! It's a very niche topic and this lecture explains the currently available literature in a very intuitive manner.
Turner is so great at teaching, too!
Amazing explanation. Thanks a lot for uploading. Although I am out of the field, I could grasp it.
Great explanation, I'm sure it'll get more views as GPs become more mainstream
Unfortunately for GPs, it seems for nearly every machine learning-like process the sparse Bernoulli model has been proven as superior, along with the rTop-k algorithm as of late 2020. From my understanding of course.
Thanks a lot!