A Novel Vectors Surgeon Machine Based on Statistical Learning Theory

Intrusion Detection based on a Novel Hybrid Learning Approach

Information security and Intrusion Detection System (IDS) plays a critical role in the Internet. IDS is an essential tool for detecting different kinds of attacks in a network and maintaining data integrity, confidentiality and system availability against possible threats. In this paper, a hybrid approach towards achieving high performance is proposed. In fact, the important goal of this paper ...

Machine Learning on Statistical Manifold

This senior thesis project explores and generalizes some fundamental machine learning algorithms from the Euclidean space to the statisticalmanifold, an abstract space in which each point is a probability distribution. In this thesis, we adapt the optimal separating hyperplane, the k-means clusteringmethod, and the hierarchical clustering method for classifying and clustering probability distri...

Graph-based Learning for Statistical Machine Translation

Current phrase-based statistical machine translation systems process each test sentence in isolation and do not enforce global consistency constraints, even though the test data is often internally consistent with respect to topic or style. We propose a new consistency model for machine translation in the form of a graph-based semi-supervised learning algorithm that exploits similarities betwee...

Statistical Aspects of Logic-Based Machine Learning

A Novel Extreme Learning Machine Based on Hybrid Kernel Function

Extreme learning machine is a new learning algorithm for the single hidden layer feedforward neural networks (SLFNs). ELM has been widely used in various fields and applications to overcome the slow training speed and over-fitting problems of the conventional neural network learning algorithms. ELM algorithm is based on the empirical risk minimization, without considering the structural risk an...