报告题目：Enlightening the I/O Path: A Holistic Approach for Application Performance

报 告 人：吴小全

报告时间：2017年5月10日（周三） 下午 2:30

报告地点：贵州大学北校区博学楼603室

报告内容摘要：

In this paper, we propose a requestcentric I/O prioritization that dynamically detects and prioritizes I/Os delaying request handling at all layers in the I/O path. The proposed scheme is implemented on Linux and is evaluated with three applications, PostgreSQL, MongoDB,and Redis.

报告题目：Deep Canonical Correlation Analysis

报 告 人：王汝平

报告时间：2017年5月10日（周三） 下午 2:30

报告地点：贵州大学北校区博学楼603室

报告内容摘要：

In this paper, We introduce Deep Canonical Correlation Analysis (DCCA), a method to learn complex nonlinear transformations of two views of data such that the resulting representations are highly linearly correlated. Parameters of both transformations are jointly learned to maximize the (regularized) total correlation. It can be viewed as a nonlinear extension of the linear method canonical correlation analysis (CCA). It is an alternative to the nonparametric method kernel canonical correlation analysis (KCCA) for learning correlated nonlinear transformations.

报告题目：Computer-aided diagnosis of human brain tumor through MRI: A survey and a new algorithm

报 告 人：蒋欢

报告时间：2017年5月10日（周三） 下午 2:30

报告地点：贵州大学北校区博学楼603室

报告内容摘要：

In this paper, this paper is to review the recent published segmentation and classification techniques and their state-of-the-art for the human brain MRI,And we proposed a hybrid intelligent machine learning technique for computer-aided detection system for automatic detection of brain tumor through magnetic resonance images.