For many machine learning solutions to complex applications, there are significant performance advantages to decomposing the overall task into several simpler sequential stages, c...
We present an interactive learning method that enables a user to iteratively refine a regression model. The user examines the output of the model, visualized as the vertical axis ...
This paper steps back from the standard infinite horizon formulation of reinforcement learning problems to consider the simpler case of finite horizon problems. Although finite ho...
This article advocates a new model for inductive learning. Called sequential induction, it helps bridge classical fixed-sample learning techniques (which are efficient but difficu...
A new inductive learning system, Lab Learning for ABduction, is presented which acquires abductive rules from a set of training examples. The goal is to nd a small knowledge base ...