Computational Challenges in Machine Learning

本次研讨会的目标是推进机器学习的算法前沿。目标领域包括贝叶斯统计，其中许多核心算法问题与理论计算机科学界已经深入研究的问题相似；大规模优化，在理论和实际部署的界面上出现了许多有趣的挑战。该研讨会将汇集算法、统计学、数学和人工智能领域的研究人员。它将向所有潜在的参与者开放，研讨会的结果（包括演示录像带）将分发给公众，以征求意见和参与。组织者将鼓励学生参加研讨会，并将积极招募来自不同背景的科学家，为广泛的算法主题做出贡献。

The goal of this workshop is to advance the algorithmic frontier of machine learning. Target areas include Bayesian statistics, in which many of the core algorithmic problems bear similarity to problems that have been studied intensively in the theoretical computer science community; and large-scale optimization, in which a host of interesting challenges arise at the interface of theory and practical deployment.The workshop will bring together researchers in algorithms, statistics, mathematics and artificial intelligence. It will be open to all potential participants, and the workshop findings (including videotapes of presentations) will be distributed to the public for comments and engagement. The organizers will encourage students to attend the workshop, and will actively recruit scientists from a diversity of backgrounds to contribute to a wide range of algorithmic topics.