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KDD
2008
ACM
120views Data Mining» more  KDD 2008»
16 years 7 months ago
Multi-class cost-sensitive boosting with p-norm loss functions
We propose a family of novel cost-sensitive boosting methods for multi-class classification by applying the theory of gradient boosting to p-norm based cost functionals. We establ...
Aurelie C. Lozano, Naoki Abe
KDD
2008
ACM
142views Data Mining» more  KDD 2008»
16 years 7 months ago
Weighted graphs and disconnected components: patterns and a generator
The vast majority of earlier work has focused on graphs which are both connected (typically by ignoring all but the giant connected component), and unweighted. Here we study numer...
Mary McGlohon, Leman Akoglu, Christos Faloutsos
KDD
2008
ACM
166views Data Mining» more  KDD 2008»
16 years 7 months ago
Generating succinct titles for web URLs
How can a search engine automatically provide the best and most appropriate title for a result URL (link-title) so that users will be persuaded to click on the URL? We consider th...
Deepayan Chakrabarti, Ravi Kumar, Kunal Punera
KDD
2008
ACM
140views Data Mining» more  KDD 2008»
16 years 7 months ago
On updates that constrain the features' connections during learning
In many multiclass learning scenarios, the number of classes is relatively large (thousands,...), or the space and time efficiency of the learning system can be crucial. We invest...
Omid Madani, Jian Huang 0002
KDD
2007
ACM
132views Data Mining» more  KDD 2007»
16 years 7 months ago
A scalable modular convex solver for regularized risk minimization
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and different r...
Choon Hui Teo, Alex J. Smola, S. V. N. Vishwanatha...
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