Localized multiple kernel learning

By Mehmet Gönen, Ethem Alpaydin. International Conference on Machine Learning, 2008

313 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/ceb2ca8ac91a49c9326684f0c787c5b623805650

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Dacheng Tao
2. Chao Xu
3. Chang Xu
4. Marius Kloft
5. Jiebo Luo
6. Ulf Brefeld
7. Liangliang Cao
8. Sören Sonnenburg

In Computer Vision and Pattern Recognition

1. Dacheng Tao
2. Luc Van Gool
3. Ming-Hsuan Yang
4. Yi Yang
5. Trevor Darrell
6. Chang Xu
7. Cordelia Schmid
8. Xiaogang Wang

Citations in the corpus

• l p -Norm Multiple Kernel Learning (2011, background): “Although finding non-linear kernel mixtures (Gönen and Alpaydin, 2008; Varma and Babu, 2009) generally results in non-convex optimization problems, Cortes et al.”
• A Survey on Multi-view Learning (2013, background): “Gönen and Alpaydin (2008); Varma and Babu (2009); Rakotomamonjy et al. (2008) and Xu et al. (2010) used the benchmark datasets from the UCI machine learning repository.”
• Group-sensitive multiple kernel learning for object categorization (2009, methodology): “Inspired by [23], instead of solving directly, we use a normalized exponential weighting function to approximate the nonnegative .”
• Prediction of the Leadership Style of an Emergent Leader Using Audio and Visual Nonverbal Features (2017, unknown): “As mentioned in [15], the gradient calculation step”
• A multiple-kernel support vector regression approach for stock market price forecasting (2011, unknown): “…multiple-kernels to deal with these problems (Bach, Lanckriet, & Jordan, 2004; Bennett, Momma, & Embrechts, 2002; Crammer, Keshet, & Singer, 2003; Gönen et al., 2008; Lanckriet, Cristianini, Bartlett, Ghaoui, & Jordan, 2004; Ong, Smola, & Williamson, 2005; Rakotomamonjy, Bach, Canu, &…”
• Heterogeneous feature machines for visual recognition (2009, methodology): “6 Localized MKL [13] 61.”
• Multiple Kernel Fuzzy Clustering (2012, background): “Varma and Babu studied superlinear combinations of kernels [32], and Gonen et al. studied local combinations of kernels [33].”
• Multiple Kernel Learning Algorithms (2011, unknown): “Gönen and Alpaydın (2008) combine kernels using weights calculated from a gating model.”