Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Achieving interactive performance in cloth animation has significant implications in computer games and other interactive graphics applications. Although much progress has been m...
Recent research has studied the role of sparsity in high dimensional regression and signal reconstruction, establishing theoretical limits for recovering sparse models from sparse...
Shuheng Zhou, John D. Lafferty, Larry A. Wasserman
This paper proposes a novel representation of the free space of mobile robot by distinct, non-overlapping regions called Edge Visibility Regions (EVRs). An algorithm to partition ...
Abstract. We present new performance models and a new, more compact data structure for cache blocking when applied to the sparse matrixvector multiply (SpM×V) operation, y ← y +...
Rajesh Nishtala, Richard W. Vuduc, James Demmel, K...