We consider the problem of classification when multiple observations of a pattern are available, possibly under different transformations. We view this problem as a special case o...
Point processes are difficult to analyze because they provide only a sparse and noisy observation of the intensity function driving the process. Gaussian Processes offer an attrac...
John P. Cunningham, Krishna V. Shenoy, Maneesh Sah...
We present a data structure enabling efficient nearest neighbor (NN) retrieval for bregman divergences. The family of bregman divergences includes many popular dissimilarity measu...
We present a discriminative online algorithm with a bounded memory growth, which is based on the kernel-based Perceptron. Generally, the required memory of the kernelbased Percept...
We present an efficient method for maximizing energy functions with first and second order potentials, suitable for MAP labeling estimation problems that arise in undirected graph...