Abstract. This paper proposes an algorithm for combinatorial optimizations that uses reinforcement learning and estimation of joint probability distribution of promising solutions ...
Existing estimation approaches for multi-dimensional databases often rely on the assumption that data distribution in a small region is uniform, which seldom holds in practice. Mo...
In this paper, we present a new method for texture classification which we call the regularized simultaneous autoregressive method (RSAR). The regularization technique is introduc...
Rapid evaluation and design space exploration at the algorithmic level are important issues in the design cycle. In this paper we propose an original area vs delay estimation meth...
Sebastien Bilavarn, Guy Gogniat, Jean Luc Philippe...
Cost-based XML query optimization calls for accurate estimation of the selectivity of path expressions. Some other interactive and internet applications can also benefit from suc...
Wei Wang 0011, Haifeng Jiang, Hongjun Lu, Jeffrey ...
Estimation of optical flow and physically motivated brightness changes can be formulated as parameter estimation in linear models. Accuracy of this estimation heavily depends on t...
Abstract. Motion estimation is essential in a variety of image processing and computer vision tasks, like video coding, tracking, directional filtering and denoising, scene analys...
Wireless sensor networks are capable of collecting an enormous amount of data over space and time. Often, the ultimate objective is to derive an estimate of a parameter or functio...
Modeling and estimation of switching activities remain to be important problems in low-power design and fault analysis. A probabilistic Bayesian Network based switching model can ...
We present a computationally efficient segmentationrestoration method, based on a probabilistic formulation, for the joint estimation of the label map (segmentation) and the para...