CAREER: An Information-Theoretic Approach to Computational Learning with Applications

信息论是研究信息的量化、编码和提取的科学。 本职业发展计划中提出的研究包括旨在通过开发一个严格的信息理论框架来加强计算学习的理论基础和经验适用性的工作，以调查这一学科。 具体而言，信息理论的框架，基于通信理论，提出了调查的可能近似正确（PAC）模型的机器学习。 这个框架被证明是强大的和可扩展的，新的学习算法，性能的一般措施，和分析技术都提出和证明。除了提供一种手段，加强计算学习的理论基础，这个框架还提供了一种机制，开发和严格分析新的学习算法。 新算法的假设提升，文档分类，文档过滤，和元搜索都提出了建议。建议的应用工作有理论和实验的组成部分：所有新的算法进行分析，实施和测试使用基准数据。教学和教育是这个职业发展计划的一个组成部分。 研究生和本科生都介绍了专题研究，理论和应用，通过projectsproposed。研究生和本科生都可以参加的新的学习和信息检索课程也被提出。

Information theory is the science of quantifying, encoding, andextracting information. The research proposed in this careerdevelopment plan consists of work designed to strengthen thetheoretical foundations and empirical applicability of computationallearning through the development of a rigorous, information-theoreticframework for investigating this discipline. Specifically, aninformation-theoretic framework, based on communication theory, isproposed for investigating the probably approximately correct (PAC)model of machine learning. This framework is shown to be robust andextensible; new learning algorithms, general measures of performance,and analysis techniques are all proposed and demonstrated.In addition to providing a means for strengthening the theoreticalfoundations of computational learning, this framework also provides amechanism for developing and rigorously analyzing new learningalgorithms. New algorithms for hypothesis boosting, documentclassification, document filtering, and meta-search are all proposed.The proposed applications work has both theoretical and experimentalcomponents: all new algorithms are to be analyzed, implemented andtested using benchmark data.Teaching and education are an integral part of this career developmentplan. Both graduate and undergraduate students are introduced totopical research, both theoretical and applied, through the projectsproposed. New courses on learning and information retrieval,accessible to both graduate and undergraduate students, are alsoproposed.