Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
Pascal Poupart, Nikos A. Vlassis, Jesse Hoey, Kevi...
We propose a novel method for reconstructing a complete 3D model of a given anatomy from minimal information. This reconstruction provides an appropriate intra-operative 3D visual...
We consider and analyze a new algorithm for balancing indivisible loads on a distributed network with n processors. The aim is minimizing the discrepancy between the maximum and m...
In most computer systems, page fault rate is currently minimized by generic page replacement algorithms which try to model the temporal locality inherent in programs. In this pape...
Karlton Sequeira, Mohammed Javeed Zaki, Boleslaw K...
Two central criteria for data quality are consistency and accuracy. Inconsistencies and errors in a database often emerge as violations of integrity constraints. Given a dirty dat...