We present a simple and scalable algorithm for maximum-margin estimation of structured output models, including an important class of Markov networks and combinatorial models. We ...
Benjamin Taskar, Simon Lacoste-Julien, Michael I. ...
Abstract-- We consider reinforcement learning, and in particular, the Q-learning algorithm in large state and action spaces. In order to cope with the size of the spaces, a functio...
— In [17] we proposed an RL framework for control of flapping-wing MAVs. The algorithm has been discussed and simulation results using a quasi-steady model showed initial promis...
—Network management applications require large numbers of counters in order to collect traffic characteristics for each network flow. However, these counters often barely fit ...
We demonstrate how to use placement to ameliorate the predicted repeater explosion problem caused by poor interconnect scaling. We achieve repeater count reduction by dynamically ...
Brent Goplen, Prashant Saxena, Sachin S. Sapatneka...