31st Annual Conference on Machine Learning (ICML 2014)

该补助金使学生能够参加国际机器学习会议（ICML）。 ICML是机器学习领域最重要的会议之一。 除了经过严格评审的会议论文外，它还设有海报会议，教程，研讨会和特邀演讲。该奖项为美国机构的学生提供旅行奖学金资金，以帮助支付他们参加会议的旅费和费用。资助学生的选择是基于遴选委员会对他们的作者和财务需求的审查。学生奖学金对于鼓励学生参与这次重要会议以及塑造整个领域的未来非常重要。将特别注意扩大传统上在计算机科学和机器学习研究中代表性不足的群体的学生的参与，以及来自机器学习专业知识有限的机构的学生，他们将受益于与来自世界各地的研究人员互动的机会。出席ICML为对机器学习研究感兴趣的学生提供了一个独特的机会。会议上的海报会议旨在使学生能够收到来自世界各地领先的机器学习研究人员的反馈，并帮助他们成为更大的机器学习研究社区的一部分。该奖项有助于在一个日益重要的领域教育和培训下一代研究人员和教育工作者。它还有助于扩大代表性不足的群体和妇女在机器学习研究中的参与。

This grant enables student participation at the International Conference on Machine Learning (ICML). ICML is one of the premier conferences in Machine Learning. In addition to rigorously refereed conference papers, it features poster sessions, tutorials, workshops and invited talks. This award provides funds for travel scholarships for students from US institutions to help cover their travel and costs of attending the conference. The selection of students to be funded is based on a review by the selection committee of their authorship and financial needs. The student scholarships are very important for encouraging student participation in this premier conference and for shaping the future of the field as a whole. Special attention will be paid to broadening the participation of students from groups that are traditionally underrepresented in Computer Science in general and Machine Learning research in particular, and students from institutions with limited Machine Learning expertise who would benefit from the opportunity to interact with researchers from around the world. Attendance at the ICML represents a unique opportunity for students interested in Machine Learning research. The poster sessions at the conference are designed enable students to recieve feedback from leading Machine Learning researchers from around the world and to help them become part of the larger Machine Learning research community. The award contributes to the education and training of the next generation of researchers and educators in an increasingly important area. It also helps broaden the participation of underrepresented groups and women in Machine Learning research.