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RECOMB
2008
Springer
16 years 6 months ago
Automatic Parameter Learning for Multiple Network Alignment
We developed Gr?mlin 2.0, a new multiple network aligner with (1) a novel scoring function that can use arbitrary features of a multiple network alignment, such as protein deletion...
Jason Flannick, Antal F. Novak, Chuong B. Do, Bala...
IJKESDP
2010
94views more  IJKESDP 2010»
15 years 1 months ago
Neuro-fuzzy-combiner: an effective multiple classifier system
: A neuro-fuzzy-combiner (NFC) is proposed to design an efficient multiple classifier system (MCS) with an aim to have an effective solution scheme for difficult classification pro...
Ashish Ghosh, B. Uma Shankar, Lorenzo Bruzzone, Sa...
TNN
2010
159views Management» more  TNN 2010»
15 years 1 months ago
Multiple incremental decremental learning of support vector machines
We propose a multiple incremental decremental algorithm of Support Vector Machine (SVM). Conventional single incremental decremental SVM can update the trained model efficiently w...
Masayuki Karasuyama, Ichiro Takeuchi
ECML
2004
Springer
15 years 12 months ago
A Boosting Approach to Multiple Instance Learning
In this paper we present a boosting approach to multiple instance learning. As weak hypotheses we use balls (with respect to various metrics) centered at instances of positive bags...
Peter Auer, Ronald Ortner
ICML
2009
IEEE
16 years 7 months ago
A convex formulation for learning shared structures from multiple tasks
Multi-task learning (MTL) aims to improve generalization performance by learning multiple related tasks simultaneously. In this paper, we consider the problem of learning shared s...
Jianhui Chen, Lei Tang, Jun Liu, Jieping Ye