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JMLR
2010
82views more  JMLR 2010»
14 years 10 months ago
Negative Results for Active Learning with Convex Losses
We study the problem of active learning with convex loss functions. We prove that even under bounded noise constraints, the minimax rates for proper active learning are often no b...
Steve Hanneke, Liu Yang
IJCAI
2003
15 years 5 months ago
AUC: a Statistically Consistent and more Discriminating Measure than Accuracy
Predictive accuracy has been used as the main and often only evaluation criterion for the predictive performance of classification learning algorithms. In recent years, the area ...
Charles X. Ling, Jin Huang, Harry Zhang
139
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ICMLA
2008
15 years 5 months ago
Basis Function Construction in Reinforcement Learning Using Cascade-Correlation Learning Architecture
In reinforcement learning, it is a common practice to map the state(-action) space to a different one using basis functions. This transformation aims to represent the input data i...
Sertan Girgin, Philippe Preux
JMLR
2012
13 years 6 months ago
Learning Low-order Models for Enforcing High-order Statistics
Models such as pairwise conditional random fields (CRFs) are extremely popular in computer vision and various other machine learning disciplines. However, they have limited expre...
Patrick Pletscher, Pushmeet Kohli
JMLR
2012
13 years 6 months ago
Deep Learning Made Easier by Linear Transformations in Perceptrons
We transform the outputs of each hidden neuron in a multi-layer perceptron network to have zero output and zero slope on average, and use separate shortcut connections to model th...
Tapani Raiko, Harri Valpola, Yann LeCun