We present a new method for nonlinear prediction of discrete random sequences under minimal structural assumptions. We give a mathematical construction for optimal predictors of s...
Abstract--In the Relational Reinforcement learning framework, we propose an algorithm that learns an action model allowing to predict the resulting state of each action in any give...
A new modeling framework is introduced for the analytical study of medium access control (MAC) protocols operating in multihop ad hoc networks. The model takes into account the eï...
Marcelo M. Carvalho, Jose Joaquin Garcia-Luna-Acev...
This paper develops a plug-and-play reusable LogGP model that can be used to predict the runtime and scaling behavior of different MPI-based pipelined wavefront applications runni...
Gihan R. Mudalige, Mary K. Vernon, Stephen A. Jarv...
Modeling TCP is fundamental for understanding Internet behavior. The reason is that TCP is responsible for carrying a huge quota of the Internet traffic. During last decade many a...
Gennaro Boggia, Pietro Camarda, Alessandro D'Alcon...