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Full-Text Articles in Social and Behavioral Sciences
Psdboost: Matrix-Generation Linear Programming For Positive Semidefinite Matrices Learning, Chunhua Shen, Alan Welsh, Lei Wang
Psdboost: Matrix-Generation Linear Programming For Positive Semidefinite Matrices Learning, Chunhua Shen, Alan Welsh, Lei Wang
Faculty of Engineering and Information Sciences - Papers: Part A
In this work, we consider the problem of learning a positive semidefinite matrix. The critical issue is how to preserve positive semidefiniteness during the course of learning. Our algorithm is mainly inspired by LPBoost [1] and the general greedy convex optimization framework of Zhang [2]. We demonstrate the essence of the algorithm, termed PSDBoost (positive semidefinite Boosting), by focusing on a few different applications in machine learning. The proposed PSDBoost algorithm extends traditional Boosting algorithms in that its parameter is a positive semidefinite matrix with trace being one instead of a classifier. PSDBoost is based on the observation that any …
Distributed Generation Diversity Level For Optimal Investment Planning, An D. T Le, M A. Kashem, Michael Negnevitsky, G Ledwich
Distributed Generation Diversity Level For Optimal Investment Planning, An D. T Le, M A. Kashem, Michael Negnevitsky, G Ledwich
Faculty of Engineering and Information Sciences - Papers: Part A
The task of improving the supply quality and maintaining supply continuity during emergencies has become more feasible for a distribution company (DISCO), owing to new developments in Distributed Generation (DG) technologies. Even though the technical issues regarding DG interconnection to the main grid are of great importance and are being addressed by on-going research, it must be clearly placed in the context of on the financial performance of the utility. In this paper, a general approach to quantify the technical benefits of DG employment is proposed. The power system economic impact is assessed by evaluating supply quality, supply reliability, system …