The task of causal structure discovery from empirical data is a fundamental problem in many areas. Experimental data is crucial for accomplishing this task. However, experiments a...
Methods that learn from prior information about input features such as generalized expectation (GE) have been used to train accurate models with very little effort. In this paper,...
Access to historically significant email archives poses challenges that arise less often in personal collections. Most notably, searchers may need help making sense of the identit...
Abstract. An abstract recurrent neural network trained by an unsupervised method is applied to the kinematic control of a robot arm. The network is a novel extension of the Neural ...
In distance learning for computer literacy, a student's skill is dependent on personal experience. In such cases, it is important to determine the student's understandin...