Richard M. Van Slyke

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This paper uses probability models on expansive wavelet transform coefficients with interpolation constraints to estimate missing blocks in images. We use simple probability models on wavelet coefficients to formulate the estimation process as a linear programming problem and solve it to recover the missing pixels. Our formulation is general and can be(More)
We present a simple, scaleable, distributed simplex implementation for large linear programs. It is designed for coarse grained computation, particularly, readily available networks of workstations. Scalability is achieved by using the standard form of the simplex rather than the revised method. Virtually all serious implementations are based on the revised(More)
We study two adaptive, distributed optimal flow control algorithms for a virtual circuit flow control in a decentralized network. These algorithms are based on greedy heuristics. Each virtual circuit (or user) attempts to adjusts its message rate to achieve an ideal tradeoff point between high throughput and low delay. The first algorithm is the bottleneck(More)
This paper presents a heuristic sytem for a special problem in communication network design with bulk facilities, called the TI problem. We apply AI to this problem. The knowledge acquired from an expert team is represented procedurally. Our work shows the promise of applying AI methodologies in solving network optimization problems.
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