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EMNLP
2010
15 years 5 months ago
A Semi-Supervised Method to Learn and Construct Taxonomies Using the Web
Although many algorithms have been developed to harvest lexical resources, few organize the mined terms into taxonomies. We propose (1) a semi-supervised algorithm that uses a roo...
Zornitsa Kozareva, Eduard H. Hovy
JMLR
2012
13 years 10 months ago
Contextual Bandit Learning with Predictable Rewards
Contextual bandit learning is a reinforcement learning problem where the learner repeatedly receives a set of features (context), takes an action and receives a reward based on th...
Alekh Agarwal, Miroslav Dudík, Satyen Kale,...
208
Voted
JMLR
2012
13 years 10 months ago
On Nonparametric Guidance for Learning Autoencoder Representations
Unsupervised discovery of latent representations, in addition to being useful for density modeling, visualisation and exploratory data analysis, is also increasingly important for...
Jasper Snoek, Ryan Prescott Adams, Hugo Larochelle
189
Voted
GECCO
2009
Springer
200views Optimization» more  GECCO 2009»
16 years 2 months ago
Optimization of the trading rule in foreign exchange using genetic algorithm
The generation of profitable trading rules for Foreign Exchange (FX) investments is a difficult but popular problem. The use of Machine Learning in this problem allows us to obtai...
Akinori Hirabayashi, Claus de Castro Aranha, Hitos...
180
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ICDM
2008
IEEE
110views Data Mining» more  ICDM 2008»
16 years 1 months ago
Start Globally, Optimize Locally, Predict Globally: Improving Performance on Imbalanced Data
Class imbalance is a ubiquitous problem in supervised learning and has gained wide-scale attention in the literature. Perhaps the most prevalent solution is to apply sampling to t...
David A. Cieslak, Nitesh V. Chawla