Vanishing And Exploding Gradient Problems

21 May 2018 A look at the problem of vanishing or exploding gradients. Two of the common problems associated with training of deep neural networks using gradient-based learning methods and backpropagation" Read More...

Factorization Machines

27 Mar 2017 Factorization Machines (FM) the model and applications to the problem of sparse data for prediction in recommender systems. Read More...

Backpropagation In Convolutional Neural Networks

05 Sep 2016 A closer look at the concept of weights sharing in convolutional neural networks (CNNs) and an insight on how this affects the forward and backward propagation while computing the gradients during training Read More...

Formulating The ReLu

24 Aug 2016 A critical review of the rectified linear activation function (ReL) as an elementary unit of the modern deep neural network architecture Read More...