Proceedings of the fifth annual workshop on Computational learning theory

By David Haussler. 1992

How researchers see this paper

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

1. Qiang Yang
2. Yoshua Bengio
3. Mingsheng Long
4. Dacheng Tao
5. Xiaojun Wan
6. Trevor Darrell
7. Sergey Levine
8. Charu C. Aggarwal

Citations in the corpus

• Statistical mechanics of learning from examples. (1992, background): “Indeed, even the realization of random dichotomies in a perceptron with binary weights is a hard problem both theoretically and computationally (see, e.g. , Krauth and Mezard [33] and also [34]).”
• Boosting for transfer learning (2007, methodology): “Comparison Methods In the experiments, we use Support Vector Machines (Boser et al., 1992; Joachims, 1999) as the basic learn­ers in TrAdaBoost.”
• Gene Selection for Cancer Classification using Support Vector Machines (2002, methodology): “In the discussion section (Section 6), we review computational complexity issues, contrast qualitatively our feature selection method with others, and propose possible extensions of the algorithm.”