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» On the Generalization Ability of On-Line Learning Algorithms
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NIPS
2001
11 years 2 months ago
On the Generalization Ability of On-Line Learning Algorithms
In this paper, it is shown how to extract a hypothesis with small risk from the ensemble of hypotheses generated by an arbitrary on-line learning algorithm run on an independent an...
Nicolò Cesa-Bianchi, Alex Conconi, Claudio ...
NIPS
2001
11 years 2 months ago
Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms
The paper studies machine learning problems where each example is described using a set of Boolean features and where hypotheses are represented by linear threshold elements. One ...
Roni Khardon, Dan Roth, Rocco A. Servedio
AROBOTS
2002
91views more  AROBOTS 2002»
11 years 1 months ago
Fast, On-Line Learning of Globally Consistent Maps
To navigate in unknown environments, mobile robots require the ability to build their own maps. A major problem for robot map building is that odometry-based dead reckoning cannot ...
Tom Duckett, Stephen Marsland, Jonathan Shapiro
COLT
2003
Springer
11 years 6 months ago
On-Line Learning with Imperfect Monitoring
We study on-line play of repeated matrix games in which the observations of past actions of the other player and the obtained reward are partial and stochastic. We define the Part...
Shie Mannor, Nahum Shimkin
ICML
2008
IEEE
12 years 2 months ago
Query-level stability and generalization in learning to rank
This paper is concerned with the generalization ability of learning to rank algorithms for information retrieval (IR). We point out that the key for addressing the learning proble...
Yanyan Lan, Tie-Yan Liu, Tao Qin, Zhiming Ma, Hang...
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