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FLAIRS
2008
15 years 7 months ago
Building Useful Models from Imbalanced Data with Sampling and Boosting
Building useful classification models can be a challenging endeavor, especially when training data is imbalanced. Class imbalance presents a problem when traditional classificatio...
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van H...
ASPDAC
2008
ACM
104views Hardware» more  ASPDAC 2008»
15 years 6 months ago
Variability-driven module selection with joint design time optimization and post-silicon tuning
Abstract-- Increasing delay and power variation are significant challenges to the designers as technology scales to the deep sub-micron (DSM) regime. Traditional module selection t...
Feng Wang 0004, Xiaoxia Wu, Yuan Xie
141
Voted
RECOMB
2010
Springer
15 years 6 months ago
Leveraging Sequence Classification by Taxonomy-Based Multitask Learning
In this work we consider an inference task that biologists are very good at: deciphering biological processes by bringing together knowledge that has been obtained by experiments u...
Christian Widmer, Jose Leiva, Yasemin Altun, Gunna...
AIPS
2004
15 years 6 months ago
A Lookahead Strategy for Heuristic Search Planning
The planning as heuristic search framework, initiated by the planners ASP from Bonet, Loerincs and Geffner, and HSP from Bonet and Geffner, lead to some of the most performant pla...
Vincent Vidal
139
Voted
NIPS
2003
15 years 6 months ago
Boosting versus Covering
We investigate improvements of AdaBoost that can exploit the fact that the weak hypotheses are one-sided, i.e. either all its positive (or negative) predictions are correct. In pa...
Kohei Hatano, Manfred K. Warmuth
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