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» Using Learning for Approximation in Stochastic Processes
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ICML
2007
IEEE
16 years 3 months ago
Trust region Newton methods for large-scale logistic regression
Large-scale logistic regression arises in many applications such as document classification and natural language processing. In this paper, we apply a trust region Newton method t...
Chih-Jen Lin, Ruby C. Weng, S. Sathiya Keerthi
DIS
2008
Springer
15 years 4 months ago
Active Learning for High Throughput Screening
Abstract. An important task in many scientific and engineering disciplines is to set up experiments with the goal of finding the best instances (substances, compositions, designs) ...
Kurt De Grave, Jan Ramon, Luc De Raedt
ICML
1995
IEEE
16 years 3 months ago
Learning by Observation and Practice: An Incremental Approach for Planning Operator Acquisition
This paper describes an approach to automatically learn planning operators by observing expert solution traces and to further refine the operators through practice in a learning-b...
Xuemei Wang
JSAC
2006
128views more  JSAC 2006»
15 years 2 months ago
A framework for misuse detection in ad hoc networks- part II
We focus on detecting intrusions in ad hoc networks using the misuse detection technique. We allow for detection modules that periodically stop functioning due to operational failu...
D. Subhadrabandhu, S. Sarkar, F. Anjum
97
Voted
CVPR
2003
IEEE
16 years 4 months ago
An Efficient Approach to Learning Inhomogeneous Gibbs Model
Inhomogeneous Gibbs model (IGM) [4] is an effective maximum entropy model in characterizing complex highdimensional distributions. However, its training process is so slow that th...
Ziqiang Liu, Hong Chen, Heung-Yeung Shum