Sciweavers

236 search results - page 7 / 48
» Bias and Variance Approximation in Value Function Estimates
Sort
View
CORR
2011
Springer
161views Education» more  CORR 2011»
13 years 10 days ago
Doubly Robust Policy Evaluation and Learning
We study decision making in environments where the reward is only partially observed, but can be modeled as a function of an action and an observed context. This setting, known as...
Miroslav Dudík, John Langford, Lihong Li
NIPS
2004
13 years 10 months ago
Maximum Likelihood Estimation of Intrinsic Dimension
We propose a new method for estimating intrinsic dimension of a dataset derived by applying the principle of maximum likelihood to the distances between close neighbors. We derive...
Elizaveta Levina, Peter J. Bickel
ICCBR
2005
Springer
14 years 2 months ago
CBR for State Value Function Approximation in Reinforcement Learning
CBR is one of the techniques that can be applied to the task of approximating a function over high-dimensional, continuous spaces. In Reinforcement Learning systems a learning agen...
Thomas Gabel, Martin A. Riedmiller
ICCD
2001
IEEE
119views Hardware» more  ICCD 2001»
14 years 5 months ago
A Functional Validation Technique: Biased-Random Simulation Guided by Observability-Based Coverage
We present a simulation-based semi-formal verification method for sequential circuits described at the registertransfer level. The method consists of an iterative loop where cove...
Serdar Tasiran, Farzan Fallah, David G. Chinnery, ...
PODS
2003
ACM
143views Database» more  PODS 2003»
14 years 8 months ago
Maintaining variance and k-medians over data stream windows
The sliding window model is useful for discounting stale data in data stream applications. In this model, data elements arrive continually and only the most recent N elements are ...
Brian Babcock, Mayur Datar, Rajeev Motwani, Liadan...