CAREER: An Ensemble of Classifiers Based Approach for Incremental Learning

这份提案概述了一系列研究和教育努力，作为PI职业发展计划的一部分，目的是在罗文大学建立模式识别和机器学习实验室。这项研究将使用分类器集成方法来解决在不丢失先前获得的知识的情况下增量学习新信息的问题。它还将解决可从集合方法中受益的相关问题，如估计分类置信度和在非静态环境中的学习。该研究将紧密结合到各种传统和非传统教育活动中。传统活动包括开发本科生和研究生课程、实验室练习和研讨会，而非传统活动包括成立综合研究和学习社区(IRLC)，将研究型教育引入本科课程。这些社区将由所有类别的学生组成，从一年级到研究生(纵向融合)，有意识地努力整合不同的性别、种族和种族背景(横向融合)。社区将致力于该项目的不同方面，由个人成员负责与其智力和学术技能相称的任务。这些活动将培养社区成员的研究、分析思维、解决问题、团队建设和沟通技能，同时为本科生和研究生提供最大限度的多学科研究机会。

This proposal outlines a set of research and educational endeavors as part of the PI's career development plan to establish a Pattern Recognition and Machine Learning Laboratory at Rowan University. The research will address the problem of incremental learning of new in-formation without losing previously acquired knowledge, using an ensemble of classifiers approach. It will also addresses related issues that can benefit from an ensemble approach, such as estimating classification confidence and learning in non-stationary environments.The research will be tightly integrated into a variety of traditional and nontraditional educational activities. Traditional activities include developing undergraduate and graduate courses, laboratory exercises and seminars, while nontraditional activities include forming integrated research and learning communities (IRLCs) to introduce research based education to undergraduate curriculum. These communities will consist of students of all classifications, freshman through graduate (vertical integration) with a conscious effort of integrating diverse gender, ethnic, and racial backgrounds (horizontal integration). Communities will be working on different aspects of the project, with individual members responsible of tasks that are commensurate with their intellectual and academic skills. These activities will develop research, analytical thinking, problem solving, team building and communication skills of the community members, while providing maximum multidisciplinary research exposure to both undergraduate and graduate students.