講題： Privacy-Preserving Data Classification with Support Vector Machines
主講人：林耕霈 博士(國立臺灣大學電機工程研究所博士)
時間：101年2月29日 (星期三13:30)
地點：三峽校區社科大樓社1F06教室
Abstract
The support vector machine (SVM) shows the state-of-the-art performance in data classification. Data privacy is a critical concern in applying the data mining techniques. Outsourcing has become popular in current cloud computing trends. Since the training algorithm of the SVM involves intensive computations, outsourcing to external service providers can benefit the data owner who possesses only limited computing resources. We study how to achieve privacy-preservation in outsourcing the SVM. The service provider generates the SVM classifier from the perturbed data where the classifier is also in perturbed form and cannot be accessed by the service provider. We also study the inherent privacy violation problem in the SVM classifier. Since support vectors in the SVM classifier are intact tuples taken from the training dataset, releasing the SVM classifier for public use or other parties will disclose the private content of support vectors. We propose an approach to post-process the SVM classifier to transform it to a privacy-preserving SVM classifier which does not disclose the private content of support vectors.
講題：當研究遇上產品 --雲端運算與軟體工程之實例分享
When research meets products
-- Real cases of cloud computing & software engineer
主講人：何承遠 博士
(國立交通大學資訊工程研究所博士)
時間：101年2月29日 (星期三14:10)
地點：三峽校區社科大樓社1F06教室
Abstract
研究人員除了探討未知領域與解決問題外，也希望其研究成果能被廣泛應用和回饋社會，然而有些學生們卻可能只關心“為何我要修這門課”，以後用得上嗎？在這場演講中，何博士將藉由分享其親身經驗來回答這個問題：
從客戶不清不楚的需求到一個實際產品上線，所包含的系統設計、開發、測試與產品化之完整過程中，雲端運算和軟體工程等知識要如何運用？有哪些地方是可以把理論實際化，又有哪些則是能將經驗數據化？
透過此次分享，何博士希望大家能夠稍微了解“系上為何開設這些課程”跟“學術與產業其實是可以相輔相成”；同時，他也期望學生們未來可以發揮所長、學以致用。
