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» Generalization Improvement in Multi-Objective Learning
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IJSI
2008
156views more  IJSI 2008»
14 years 11 months ago
Co-Training by Committee: A Generalized Framework for Semi-Supervised Learning with Committees
Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
Mohamed Farouk Abdel Hady, Friedhelm Schwenker
STACS
1999
Springer
15 years 3 months ago
Costs of General Purpose Learning
Leo Harrington surprisingly constructed a machine which can learn any computable function f according to the following criterion (called Bc∗ -identification). His machine, on t...
John Case, Keh-Jiann Chen, Sanjay Jain
JCDL
2005
ACM
100views Education» more  JCDL 2005»
15 years 5 months ago
Automatic extraction of titles from general documents using machine learning
In this paper, we propose a machine learning approach to title extraction from general documents. By general documents, we mean documents that can belong to any one of a number of...
Yunhua Hu, Hang Li, Yunbo Cao, Dmitriy Meyerzon, Q...
116
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DAC
2010
ACM
14 years 11 months ago
A correlation-based design space exploration methodology for multi-processor systems-on-chip
Given the increasing complexity of multi-processor systems-onchip, a wide range of parameters must be tuned to find the best trade-offs in terms of the selected system figures of ...
Giovanni Mariani, Aleksandar Brankovic, Gianluca P...
SODA
2000
ACM
85views Algorithms» more  SODA 2000»
15 years 29 days ago
Improved bounds on the sample complexity of learning
We present a new general upper bound on the number of examples required to estimate all of the expectations of a set of random variables uniformly well. The quality of the estimat...
Yi Li, Philip M. Long, Aravind Srinivasan