In this paper, we model multi-agent events in terms of a temporally varying sequence of sub-events, and propose a novel approach for learning, detecting and representing events in...
This paper considers the Valiant framework as it is applied to the task of learning logical concepts from random examples. It is argued that the current interpretation of this Val...
Complex questions that require inferencing and synthesizing information from multiple documents can be seen as a kind of topicoriented, informative multi-document summarization. I...
Temporal causal modeling has been a highly active research area in the last few decades. Temporal or time series data arises in a wide array of application domains ranging from med...
In this paper, we introduce a new, formal model of learning object metadata. The model enables more formal, rigorous reasoning over metadata. An important feature of the model is t...