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LREC
2008
110views Education» more  LREC 2008»
15 years 4 months ago
Cost-Sensitive Learning in Answer Extraction
One problem of data-driven answer extraction in open-domain factoid question answering is that the class distribution of labeled training data is fairly imbalanced. This imbalance...
Michael Wiegand, Jochen L. Leidner, Dietrich Klako...
KAIS
2010
144views more  KAIS 2010»
15 years 1 months ago
Boosting support vector machines for imbalanced data sets
Real world data mining applications must address the issue of learning from imbalanced data sets. The problem occurs when the number of instances in one class greatly outnumbers t...
Benjamin X. Wang, Nathalie Japkowicz
ICML
2006
IEEE
16 years 4 months ago
Learning algorithms for online principal-agent problems (and selling goods online)
In a principal-agent problem, a principal seeks to motivate an agent to take a certain action beneficial to the principal, while spending as little as possible on the reward. This...
Vincent Conitzer, Nikesh Garera
ECML
2007
Springer
15 years 9 months ago
Policy Gradient Critics
We present Policy Gradient Actor-Critic (PGAC), a new model-free Reinforcement Learning (RL) method for creating limited-memory stochastic policies for Partially Observable Markov ...
Daan Wierstra, Jürgen Schmidhuber
SSPR
2004
Springer
15 years 8 months ago
Finding Clusters and Components by Unsupervised Learning
We present a tutorial survey on some recent approaches to unsupervised machine learning in the context of statistical pattern recognition. In statistical PR, there are two classica...
Erkki Oja