This paper is concerned with developing an information-theoretic framework to aggregate the state space of a Hidden Markov Model (HMM) on discrete state and observation spaces. The...
Approximating non-linear kernels using feature maps has gained a lot of interest in recent years due to applications in reducing training and testing times of SVM classifiers and...
Abstract. We study the space complexity of randomized streaming algorithms that provide one-sided approximation guarantees; e.g., the algorithm always returns an overestimate of th...
A directional spatial relationship to a reference object (e.g., "east of the post office") can be represented by a spatial template. The template partitions the space in...
We propose a view-dependent adaptive subdivision algorithm for rendering parametric surfaces on parallel hardware. Our framework allows us to bound the screen space error of a pie...
Christian Eisenacher, Quirin Meyer, Charles T. Loo...