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IEEEPACT
2008
IEEE
15 years 8 months ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...
NECO
2010
103views more  NECO 2010»
15 years 10 days ago
Posterior Weighted Reinforcement Learning with State Uncertainty
Reinforcement learning models generally assume that a stimulus is presented that allows a learner to unambiguously identify the state of nature, and the reward received is drawn f...
Tobias Larsen, David S. Leslie, Edmund J. Collins,...
IJCNN
2007
IEEE
15 years 8 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
VEE
2012
ACM
322views Virtualization» more  VEE 2012»
13 years 9 months ago
Modeling virtualized applications using machine learning techniques
With the growing adoption of virtualized datacenters and cloud hosting services, the allocation and sizing of resources such as CPU, memory, and I/O bandwidth for virtual machines...
Sajib Kundu, Raju Rangaswami, Ajay Gulati, Ming Zh...
WWW
2004
ACM
16 years 2 months ago
Learning block importance models for web pages
Some previous works show that a web page can be partitioned to multiple segments or blocks, and usually the importance of those blocks in a page is not equivalent. Also, it is pro...
Ruihua Song, Haifeng Liu, Ji-Rong Wen, Wei-Ying Ma