There exist a number of reinforcement learning algorithms which learn by climbing the gradient of expected reward. Their long-run convergence has been proved, even in partially ob...
Automatically building maps from sensor data is a necessary and fundamental skill for mobile robots; as a result, considerable research attention has focused on the technical chall...
: We present a distributed learning algorithm for optimizing transit prices in the inter-domain routing framework. We present a combined game theoretical and distributed algorithmi...
We describe a new boosting algorithm that is the first such algorithm to be both smooth and adaptive. These two features make possible performance improvements for many learning ...
In this paper, we propose and develop a novel approach to the problem of optimally managing the tax, and more generally debt, collections processes at financial institutions. Our...
Naoki Abe, Prem Melville, Cezar Pendus, Chandan K....