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
Activation Functions II: Rectified-based Activation Functions
Introduction We have given a brief introduction to the basic activation functions in the previous blog. In this post, we
Activation Functions I: Basic AF
Deep learning is actually not a difficult or complicated algorithm. In the whole process of deep learning framework design, the
DAD Notes IV: Deep Anomaly Detection Models
In this post, we discuss various Deep Anomaly Detection Models (DAD) classified based on the availability of labels and training
DAD Notes III: Applications of Deep Anomaly Detection
Anomaly detection is applicable in a very large number and variety of domains, such as fraud detection, fault detection, system
DAD Notes II: Different Aspects of Deep Learning-based Anomaly Detection
Varous deep learning mothods are used to detect anomaly. When we encounter the difficulty to choose an apropriate one, we
DAD Notes I: Introduction to Deep Learning for Anomaly Detection
In data analysis, anomaly detection (also referred to as outlier detection) is generally understood to be the identification of rare
Portfolio Construction Based on Robust Covariance Matrix Estimation
According to the CAPM model, the relationship between premium return of individual share and that of S&P 500
High Dimensional Covariance Matrix Estimation
Covariance matrix estimation is fundamental for almost all areas of multivariate analysis and many other applied problems. For instance, according
What is DTW?
Short Answer In time series analysis, dynamic time warping (DTW) is one of the algorithms for measuring similarity between two
