楊海欽博士是本系金國慶教授和呂榮聰教授的前博士生。他憑論文“Online Learning for Multi-Task Feature Selection”，於2011年5月28日獲電氣電子工程學會頒發的香港區研究生論文比賽一等獎。其餘兩名得獎者分別獲得研究生論文比賽二等獎及三等獎及三位本科生論文比賽得獎者。電氣電子工程師學會舉辦本科生及研究生論文比賽，旨在鼓勵其香港學生成員將工程學知識應用於電氣及電子工程之研究項目中，並能將獲得的結果清楚準確地撰寫成優秀論文。
"Learning explanatory features across multiple related tasks, or multi-task feature selection (MTFS), is an important problem in the applications of data mining, machine learning, and bioinformatics. Previous MTFS methods fulfill this task by the batch-mode training. This makes them inefficient when data come in sequence or when the number of training data is so large that they cannot be loaded into the memory simultaneously. In order to tackle these problems, we propose a novel online learning framework to solve the MTFS problem. A main advantage of the online algorithm is its efficiency in both time complexity and memory cost. The weights of the MTFS models at each iteration can be updated by closed-form solutions based on the average of previous subgradients. This yields the worst-case bounds of the time complexity and memory cost both in the order of O(d*Q), where d is the number of feature dimensions and Q is the number of tasks. Moreover, we provide theoretical analysis for the average regret of the online learning algorithms, which also guarantees the convergence rate of the algorithms. Finally, we conduct detailed experiments to show the characteristics and merits of the online learning algorithms in solving the MTFS problem."