Sciweavers

ICML
2003
IEEE
15 years 15 days ago
Exploration and Exploitation in Adaptive Filtering Based on Bayesian Active Learning
In the task of adaptive information filtering, a system receives a stream of documents but delivers only those that match a person's information need. As the system filters i...
Yi Zhang, Wei Xu, James P. Callan
ICML
2003
IEEE
15 years 15 days ago
Modified Logistic Regression: An Approximation to SVM and Its Applications in Large-Scale Text Categorization
Logistic Regression (LR) has been widely used in statistics for many years, and has received extensive study in machine learning community recently due to its close relations to S...
Jian Zhang, Rong Jin, Yiming Yang, Alexander G. Ha...
ICML
2003
IEEE
15 years 15 days ago
Learning Metrics via Discriminant Kernels and Multidimensional Scaling: Toward Expected Euclidean Representation
Distance-based methods in machine learning and pattern recognition have to rely on a metric distance between points in the input space. Instead of specifying a metric a priori, we...
Zhihua Zhang
ICML
2003
IEEE
15 years 15 days ago
Isometric Embedding and Continuum ISOMAP
Hongyuan Zha, Zhenyue Zhang
ICML
2003
IEEE
15 years 15 days ago
Optimizing Classifier Performance via an Approximation to the Wilcoxon-Mann-Whitney Statistic
When the goal is to achieve the best correct classification rate, cross entropy and mean squared error are typical cost functions used to optimize classifier performance. However,...
Lian Yan, Robert H. Dodier, Michael Mozer, Richard...
ICML
2003
IEEE
15 years 15 days ago
Decision-tree Induction from Time-series Data Based on a Standard-example Split Test
This paper proposes a novel decision tree for a data set with time-series attributes. Our time-series tree has a value (i.e. a time sequence) of a time-series attribute in its int...
Yuu Yamada, Einoshin Suzuki, Hideto Yokoi, Katsuhi...
ICML
2003
IEEE
15 years 15 days ago
Cross-Entropy Directed Embedding of Network Data
We present a novel approach to embedding data represented by a network into a lowdimensional Euclidean space. Unlike existing methods, the proposed method attempts to minimize an ...
Takeshi Yamada, Kazumi Saito, Naonori Ueda
ICML
2003
IEEE
15 years 15 days ago
Bayesian Network Anomaly Pattern Detection for Disease Outbreaks
Weng-Keen Wong, Andrew W. Moore, Gregory F. Cooper...
ICML
2003
IEEE
15 years 15 days ago
Principled Methods for Advising Reinforcement Learning Agents
An important issue in reinforcement learning is how to incorporate expert knowledge in a principled manner, especially as we scale up to real-world tasks. In this paper, we presen...
Eric Wiewiora, Garrison W. Cottrell, Charles Elkan