In this paper we develop a novel generalization bound for learning the kernel problem. First, we show that the generalization analysis of the kernel learning problem reduces to in...
The sequential structure of complex actions is apparently at an abstract “cognitive” level in several regions of the frontal cortex, independent of the control of the immediate...
Kiran V. Byadarhaly, Mithun Perdoor, Suresh Vasa, ...
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...
In transfer learning we aim to solve new problems using fewer examples using information gained from solving related problems. Transfer learning has been successful in practice, a...
Our research addresses the issue of developing knowledge-based agents that capture and use the problem solving knowledge of subject matter experts from diverse application domains...