We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
Abstract. In this paper we initiate an exploration of relationships between “preference elicitation”, a learning-style problem that arises in combinatorial auctions, and the pr...
Avrim Blum, Jeffrey C. Jackson, Tuomas Sandholm, M...
As a part of many e-learning initiatives, a set of learning units must be arranged in a particular order to meet the learners’ requirements. This process is known as sequencing ...
We present multi-task structure learning for Gaussian graphical models. We discuss uniqueness and boundedness of the optimal solution of the maximization problem. A block coordina...
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...