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MP
2002
165views more  MP 2002»
15 years 4 months ago
A feasible semismooth asymptotically Newton method for mixed complementarity problems
Semismooth Newton methods constitute a major research area for solving mixed complementarity problems (MCPs). Early research on semismooth Newton methods is mainly on infeasible me...
Defeng Sun, Robert S. Womersley, Houduo Qi
ML
1998
ACM
101views Machine Learning» more  ML 1998»
15 years 4 months ago
Elevator Group Control Using Multiple Reinforcement Learning Agents
Recent algorithmic and theoretical advances in reinforcement learning (RL) have attracted widespread interest. RL algorithmshave appeared that approximatedynamic programming on an ...
Robert H. Crites, Andrew G. Barto
ML
1998
ACM
131views Machine Learning» more  ML 1998»
15 years 4 months ago
Learning from Examples and Membership Queries with Structured Determinations
It is well known that prior knowledge or bias can speed up learning, at least in theory. It has proved di cult to make constructive use of prior knowledge, so that approximately c...
Prasad Tadepalli, Stuart J. Russell
MOC
1998
175views more  MOC 1998»
15 years 4 months ago
Convergence of a non-stiff boundary integral method for interfacial flows with surface tension
Boundary integral methods to simulate interfacial flows are very sensitive to numerical instabilities. In addition, surface tension introduces nonlinear terms with high order spat...
Héctor D. Ceniceros, Thomas Y. Hou
MST
1998
91views more  MST 1998»
15 years 4 months ago
An Experimental Analysis of Parallel
We have developed a methodology for predicting the performance of parallel algorithms on real parallel machines. The methodology consists of two steps. First, we characterize a mac...
Guy E. Blelloch, Charles E. Leiserson
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