Weekly Machine Learning Research Paper Reading List # 1
As a researcher, it is essential to keep up-to-date with literature. Staying up to date with literature is necessary for PhD Student.
Recently I started keeping track of papers that I have read, or I will read in a week. I come across with this post by Connor Shorten. As far as I know, he just posted once. Motivated from this, I thought of making a post on it every week to share with the research community.
From today, I am starting this new series of weekly reading lists where I will be sharing a list of machine learning papers that I will read in a week. This week starting from Aug 3, 2020, I will read five articles on outlier detection.
Isolation Forest
Authors: Fei Tony Liu, Kai Ming Ting, Zhi-Hua Zhou
Venue : 2008 Eighth IEEE International Conference on Data Mining, 413–422, 2008
Paper : PDF
Abstract:
Most existing model-based approaches to anomaly detection construct a profile of normal instances, then identify instances that do not conform to the normal profile as anomalies. This paper proposes a fundamentally different model-based method that explicitly isolates anomalies instead of profiles normal points. To our best knowledge, the concept of isolation…
