… 5] and nonlinear [6] kernel machines in the form of additional linear … a classifier founded on
the kernel-matching pursuits (KMP) … putational efficiency and the unrestricted form of its kernel …

… new notions of efficient enumeration kernels by replacing the … kernels and polynomial-delay
enumeration kernels. Our paper … spot between the notion of full kernels, which is too strict for …

… Sminchisescu, “Efficient match kernel between sets of features for visual recognition,” in
Advances in Neural Information Processing Systems 22, NIPS 2009. Proceedings of a meeting …

… be efficiently computed with match kernels just by embedding the features in a suitable feature
space in advance. Match kernels … Here, we define kernel descriptors over sets of pixels be…

In this work we introduce a new dissimilarity measure for shape registration using the notion
of normal cycles, a concept from geometric measure theory which allows us to generalize …

… graph kernels can not be efficient. In Section 4 we discuss a general framework for graph
kernels … graph kernels. In Section 5 we propose a new instantiation of this framework, a graph …

… tracking algorithm that can also handle kernel hyperparameter paths. The algorithm has …
approximate kernel hyperparamter solution paths for support vector machines and robust kernel …

… high accurate binary classifiers and computational efficiency. … could create the unbalanced
trees and decreasing efficiency. … sum match kernel [14] that sums the local kernels between …

… kernel learning. Firstly, we introduce a probabilistic framework that allows joint learning of
model and kernel … Thirdly, we introduce a learnable Fourier based kernel embeddings that …

… Our features are based on a multi-level version of the HOG descriptor [7] and use histogram
intersection kernel SVM based on spatial pyramid match kernel introduced in [15]. Our …