- Paper EUSIPCO2020 "Consistency- and inconsistency-aware graph-based multi-view clustering"
Machine learning, optimization, and signal processing
We are dedicated to machine learning, optimization, and signal processing, and their theories, algorithms, and applications for small- and large-scale data. Specifically, we address learning algorithms and models, optimization algorithms, linear & non-linear optimization problems, convex & non-convex optimization problems, classification and clustering problems, distance and space learning problems, structure learning, and optimal transport problems. Our focus includes the development and validation of learning algorithms and optimization, the establishment of new machine learning models, and practical applications. For those items, we tackle with respect to theoretic approaches and numerical evaluations. Its applications include data analysis, computer vision, video surveillance, network traffic analysis, distributed sensing, graph analysis, etc.