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CORR
2010
Springer
124views Education» more  CORR 2010»
13 years 8 months ago
Online Learning of Noisy Data with Kernels
We study online learning when individual instances are corrupted by adversarially chosen random noise. We assume the noise distribution is unknown, and may change over time with n...
Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, O...
AIMSA
2008
Springer
14 years 2 months ago
Prototypes Based Relational Learning
Relational instance-based learning (RIBL) algorithms offer high prediction capabilities. However, they do not scale up well, specially in domains where there is a time bound for c...
Rocío García-Durán, Fernando ...
IJCAI
1993
13 years 9 months ago
Learning Decision Lists over Tree Patterns and Its Application
This paper introduces a new concept, a decision tree (or list) over tree patterns, which is a natural extension of a decision tree (or decision list), for dealing with tree struct...
Satoshi Kobayashi, Koichi Hori, Setsuo Ohsuga
FLAIRS
2003
13 years 9 months ago
Learning from Reinforcement and Advice Using Composite Reward Functions
1 Reinforcement learning has become a widely used methodology for creating intelligent agents in a wide range of applications. However, its performance deteriorates in tasks with s...
Vinay N. Papudesi, Manfred Huber
ALT
1995
Springer
14 years 16 hour ago
Learning Unions of Tree Patterns Using Queries
This paper characterizes the polynomial time learnability of TPk, the class of collections of at most k rst-order terms. A collection in TPk de nes the union of the languages de n...
Hiroki Arimura, Hiroki Ishizaka, Takeshi Shinohara