31st Annual Conference on Machine Learning (ICML 2014)

这项资助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。除了严格审核的会议论文，它还包括海报会议、教程、研讨会和邀请演讲。该奖项为来自美国院校的学生提供旅行奖学金，以帮助他们支付旅行和参加会议的费用。获得资助的学生的选择是基于评选委员会对其作者身份和经济需求的审查。学生奖学金对于鼓励学生参与这个重要的会议和塑造整个领域的未来非常重要。将特别关注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，他们将从与来自世界各地的研究人员互动的机会中受益。参加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。该奖项有助于下一代研究人员和教育工作者在一个日益重要的领域的教育和培训。它还有助于扩大未被充分代表的群体和女性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.