We compute a common feature selection or kernel selection configuration for multiple support vector machines (SVMs) trained on different yet inter-related datasets. The method is ...
Standard Machine Learning approaches to text classification use the bag-of-words representation of documents to deceive the classification target function. Typical linguistic stru...
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
An intuitive approach to utilizing unlabeled data in kernel-based classification algorithms is to simply treat unknown labels as additional optimization variables. For marginbased...
Vikas Sindhwani, S. Sathiya Keerthi, Olivier Chape...
Kernel methods yield state-of-the-art performance in certain applications such as image classification and object detection. However, large scale problems require machine learning...
Sreekanth Vempati, Andrea Vedaldi, Andrew Zisserma...