This paper analyzes the potential advantages and theoretical challenges of “active learning” algorithms. Active learning involves sequential sampling procedures that use infor...
In this paper, we present a general machine learning approach to the problem of deciding when to share probabilistic beliefs between agents for distributed monitoring. Our approac...
In this paper we present lessons learned in the Evaluating Predictive Uncertainty Challenge. We describe the methods we used in regression challenges, including our winning method ...
This paper presents a decoupled two stage solution to the multiple-instance learning (MIL) problem. With a constructed affinity matrix to reflect the instance relations, a modified...
This paper describes a new approach to automatically learning linguistic knowledge for spelling correction. A major feature of this approach is the fact that the acquired knowledg...