Assessing Reliability: A Review of Failure Rates in Large-Scale IT System
1. Introduction As the complexity of large-scale IT infrastructures increases, with clusters encompassing millions of components, the challenge of managing
Deep Learning Training Algorithm III: Second-Order Optimization Algorithms
In the previous blog post, we have introduced the Gradient-Based Optimization Algorithms, which use the first-order derivatives of the objective
Deep Learning Training Algorithms II: Gradient-Based Optimization Algorithms
Introduction Deep learning models are powerful tools for solving complex problems in a variety of domains, from image and speech
Deep Learning Training Algorithms I: Introduction
1. Introduction Deep learning has revolutionized the field of artificial intelligence, enabling machines to perform tasks that were previously thought
Review of Deep Learning Algorithms and Architectures V: RNN and LSTM
1. Brief Introduction to Recurrent Neural Networks Recurrent neural networks or RNNs (Rumelhart et al., 1986) are a family of
Review of Deep Learning Algorithms and Architectures IV: Boltzmann Machine
Boltzmann machines were originally introduced as a general "connectionist" approach to learning arbitrary probability distributions over binary vectors.
Review of Deep Learning Algorithms and Architectures III: Autoencoder
Autoencoders are generalizations of PCA. A PCA transforms multi-dimensional data into a linear representation, whereas, autoencoders go further and produce
Review of Deep Learning Algorithms and Architectures II: CNN Architectures
A Deep neural network consists of several layers of nodes. Different architectures have been developed to solve problems in different
Review of Deep Learning Algorithms and Architectures I: A Brief Introduction
Introduction Neural Network is a machine learning technique that is inspired by and resembles the human nervous system and the
Activation Functions III: Trainable Activation Functions
Introduction The idea of traninable activation functions is not new in the neural networks research field. In recent years, as
