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ECML
2007
Springer
16 years 1 months ago
Avoiding Boosting Overfitting by Removing Confusing Samples
Boosting methods are known to exhibit noticeable overfitting on some datasets, while being immune to overfitting on other ones. In this paper we show that standard boosting algorit...
Alexander Vezhnevets, Olga Barinova
ECML
2007
Springer
16 years 1 months ago
Clustering Trees with Instance Level Constraints
Abstract. Constrained clustering investigates how to incorporate domain knowledge in the clustering process. The domain knowledge takes the form of constraints that must hold on th...
Jan Struyf, Saso Dzeroski
ECML
2007
Springer
16 years 1 months ago
Stability Based Sparse LSI/PCA: Incorporating Feature Selection in LSI and PCA
The stability of sample based algorithms is a concept commonly used for parameter tuning and validity assessment. In this paper we focus on two well studied algorithms, LSI and PCA...
Dimitrios Mavroeidis, Michalis Vazirgiannis
ECML
2007
Springer
16 years 1 months ago
Separating Precision and Mean in Dirichlet-Enhanced High-Order Markov Models
Abstract. Robustly estimating the state-transition probabilities of highorder Markov processes is an essential task in many applications such as natural language modeling or protei...
Rikiya Takahashi
ECML
2007
Springer
16 years 1 months ago
Spectral Clustering and Embedding with Hidden Markov Models
Abstract. Clustering has recently enjoyed progress via spectral methods which group data using only pairwise affinities and avoid parametric assumptions. While spectral clustering ...
Tony Jebara, Yingbo Song, Kapil Thadani
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