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ICML
2002
IEEE
16 years 5 months ago
Hierarchically Optimal Average Reward Reinforcement Learning
Two notions of optimality have been explored in previous work on hierarchical reinforcement learning (HRL): hierarchical optimality, or the optimal policy in the space defined by ...
Mohammad Ghavamzadeh, Sridhar Mahadevan
126
Voted
BMCBI
2010
98views more  BMCBI 2010»
15 years 5 months ago
A semi-nonparametric mixture model for selecting functionally consistent proteins
Background: High-throughput technologies have led to a new era of proteomics. Although protein microarray experiments are becoming more common place there are a variety of experim...
Lianbo Yu, R. W. Doerge
BMVC
2010
15 years 2 months ago
Background Modelling on Tensor Field for Foreground Segmentation
The paper proposes a new method to perform foreground detection by means of background modeling using the tensor concept. Sometimes, statistical modelling directly on image values...
Rui Caseiro, Jorge Batista, Pedro Martins
IMC
2007
ACM
15 years 6 months ago
On optimal probing for delay and loss measurement
Packet delay and loss are two fundamental measures of performance. Using active probing to measure delay and loss typically involves sending Poisson probes, on the basis of the PA...
François Baccelli, Sridhar Machiraju, Darry...
SIGMETRICS
2002
ACM
128views Hardware» more  SIGMETRICS 2002»
15 years 4 months ago
High-density model for server allocation and placement
It is well known that optimal server placement is NP-hard. We present an approximate model for the case when both clients and servers are dense, and propose a simple server alloca...
Craig W. Cameron, Steven H. Low, David X. Wei