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194
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CRV
2009
IEEE
115views Robotics» more  CRV 2009»
16 years 1 months ago
Learning Model Complexity in an Online Environment
In this paper we introduce the concept and method for adaptively tuning the model complexity in an online manner as more examples become available. Challenging classification pro...
Dan Levi, Shimon Ullman
SIGECOM
2010
ACM
149views ECommerce» more  SIGECOM 2010»
15 years 11 months ago
A new understanding of prediction markets via no-regret learning
We explore the striking mathematical connections that exist between market scoring rules, cost function based prediction markets, and no-regret learning. We first show that any c...
Yiling Chen, Jennifer Wortman Vaughan
LLL
1999
Springer
15 years 11 months ago
Learning to Lemmatise Slovene Words
Abstract. Automatic lemmatisation is a core application for many language processing tasks. In inflectionally rich languages, such as Slovene, assigning the correct lemma to each ...
Saso Dzeroski, Tomaz Erjavec
AAMAS
2006
Springer
15 years 7 months ago
An Evolutionary Dynamical Analysis of Multi-Agent Learning in Iterated Games
In this paper, we investigate Reinforcement learning (RL) in multi-agent systems (MAS) from an evolutionary dynamical perspective. Typical for a MAS is that the environment is not ...
Karl Tuyls, Pieter Jan't Hoen, Bram Vanschoenwinke...
ML
1998
ACM
131views Machine Learning» more  ML 1998»
15 years 6 months ago
Learning from Examples and Membership Queries with Structured Determinations
It is well known that prior knowledge or bias can speed up learning, at least in theory. It has proved di cult to make constructive use of prior knowledge, so that approximately c...
Prasad Tadepalli, Stuart J. Russell