Summary of the Paper named Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models.
While proceeding to discuss batch renormalization, I assumed that you are quite familiar with Batch Normalization (BN). How does it help to converge faster to the optimal solution of the problem at hand? If not, please read batch normalization- a technique that enhances training.
Let’s briefly summarize BN:
Why is this most often used normalization technique in neural architectures?
While reading the BatchNormalization (BN) paper written by Sergey Ioffe and Christian Szegedy. I came across the fact that it is cited by around 29.5k till now. Also, noticed and I think we as ML practitioners are using batch normalization techniques very often.
In the paper, the authors themselves describe why are they using the batch normalization technique is that to accelerate…
Cells are considered a basic unit of life. Inside every cell in a body, billions of tiny molecular machines are hard at work. They are Proteins. Proteins are made up of a sequence of amino acids. An average protein has about 300 amino acid residues. Proteins compose structural and motor elements in the cell. Proteins underlie every biochemical reaction that occurs in living things.
If we consider that there are twenty different amino acids, the combinatorial number of protein sequences that can be made is astronomically high; by the most conservative calculation, the human body synthesizes at least 30,000…
“Abundant data generally belittles the importance of algorithm”. But we are not always blessed with the abundance. So, we need to have a good knowledge of all the tools and an intuitive sense for their applicability. This post aims at explaining one such tool, Support Vector Machine.
Support vector machines (SVM) are a set of supervised learning methods; used for regression, classification. Unlike other learning methods; SVM tries to fit the best decision boundary or hyperplane using some data samples from given training data which are called support vectors. …