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Developing a MetaLevel Problem Solver for Integrated Learners
 IN PROCEEDINGS OF THE AAAI WORKSHOP ON METAREASONING: THINKING ABOUT THINKING
, 2008
"... A learning system may need several methods that follow different learning strategies in order to learn how to perform complex tasks. For example, a learning method may be used to generalize from user demonstrations, another to learn by practice and exploration, and another to test hypotheses with ex ..."
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Cited by 1 (0 self)
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with experiments. In such an integrated learning system, there is a need for systematically coordinating the activities of the participating learning agents especially to ensure that the system creates appropriate procedural knowledge. In this paper, we describe an approach for developing a metalevel problem
Chaff: Engineering an Efficient SAT Solver
, 2001
"... Boolean Satisfiability is probably the most studied of combinatorial optimization/search problems. Significant effort has been devoted to trying to provide practical solutions to this problem for problem instances encountered in a range of applications in Electronic Design Automation (EDA), as well ..."
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Cited by 1350 (18 self)
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Boolean Satisfiability is probably the most studied of combinatorial optimization/search problems. Significant effort has been devoted to trying to provide practical solutions to this problem for problem instances encountered in a range of applications in Electronic Design Automation (EDA), as well
Pegasos: Primal Estimated subgradient solver for SVM
"... We describe and analyze a simple and effective stochastic subgradient descent algorithm for solving the optimization problem cast by Support Vector Machines (SVM). We prove that the number of iterations required to obtain a solution of accuracy ɛ is Õ(1/ɛ), where each iteration operates on a singl ..."
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Cited by 542 (20 self)
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We describe and analyze a simple and effective stochastic subgradient descent algorithm for solving the optimization problem cast by Support Vector Machines (SVM). We prove that the number of iterations required to obtain a solution of accuracy ɛ is Õ(1/ɛ), where each iteration operates on a
Approximate Riemann Solvers, Parameter Vectors, and Difference Schemes
 J. COMP. PHYS
, 1981
"... Several numerical schemes for the solution of hyperbolic conservation laws are based on exploiting the information obtained by considering a sequence of Riemann problems. It is argued that in existing schemes much of this information is degraded, and that only certain features of the exact solution ..."
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Cited by 1010 (2 self)
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Several numerical schemes for the solution of hyperbolic conservation laws are based on exploiting the information obtained by considering a sequence of Riemann problems. It is argued that in existing schemes much of this information is degraded, and that only certain features of the exact solution
ATOMIC DECOMPOSITION BY BASIS PURSUIT
, 1995
"... The TimeFrequency and TimeScale communities have recently developed a large number of overcomplete waveform dictionaries  stationary wavelets, wavelet packets, cosine packets, chirplets, and warplets, to name a few. Decomposition into overcomplete systems is not unique, and several methods for d ..."
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Cited by 2728 (61 self)
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the smallest l 1 norm of coefficients among all such decompositions. We give examples exhibiting several advantages over MOF, MP and BOB, including better sparsity, and superresolution. BP has interesting relations to ideas in areas as diverse as illposed problems, in abstract harmonic analysis, total
CUTE: A Concolic Unit Testing Engine for C
 IN ESEC/FSE13: PROCEEDINGS OF THE 10TH EUROPEAN
, 2005
"... In unit testing, a program is decomposed into units which are collections of functions. A part of unit can be tested by generating inputs for a single entry function. The entry function may contain pointer arguments, in which case the inputs to the unit are memory graphs. The paper addresses the pro ..."
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Cited by 480 (22 self)
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the problem of automating unit testing with memory graphs as inputs. The approach used builds on previous work combining symbolic and concrete execution, and more specifically, using such a combination to generate test inputs to explore all feasible execution paths. The current work develops a method
Planning as heuristic search,
 5 – 33, ISSN
, 2001
"... Abstract In the AIPS98 Planning Contest, the HSP planner showed that heuristic search planners can be competitive with stateoftheart Graphplan and SAT planners. Heuristic search planners like HSP transform planning problems into problems of heuristic search by automatically extracting heuristics ..."
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Cited by 421 (33 self)
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heuristics from Strips encodings. They differ from specialized problem solvers such as those developed for the 24Puzzle and Rubik's Cube in that they use a general declarative language for stating problems and a general mechanism for extracting heuristics from these representations. In this paper, we
Benchmarking Optimization Software with Performance Profiles
, 2001
"... We propose performance profiles  distribution functions for a performance metric  as a tool for benchmarking and comparing optimization software. We show that performance profiles combine the best features of other tools for performance evaluation. 1 Introduction The benchmarking of optimi ..."
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Cited by 386 (8 self)
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involve tables displaying the performance of each solver on each problem for a set of metrics such...
The Test Incorporation Theory of Problem Solving (Preliminary Report)
 Oregon State Univ
, 1986
"... : Test incorporation is a program transformation in which a generateandtest problem solver is improved by moving information out of the test and into the generator. This paper sketches a theory of problem solving based on test incorporation. Two views of test incorporation are presented: (a) as a ..."
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Cited by 1 (0 self)
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need to generate and test possible answers. The theory introduces an infinite tower of metalevel problem solvers, each of which has the task of improving the performance (via test incorporation) of all of the problem solvers "below" it. This infinite tower can neither be constructed
A Fast LinearArithmetic Solver for DPLL(T)
, 2006
"... We present a new Simplexbased linear arithmetic solver that can be integrated efficiently in the DPLL(T) framework. The new solver improves over existing approaches by enabling fast backtracking, supporting a priori simplification to reduce the problem size, and providing an efficient form of the ..."
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Cited by 289 (13 self)
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We present a new Simplexbased linear arithmetic solver that can be integrated efficiently in the DPLL(T) framework. The new solver improves over existing approaches by enabling fast backtracking, supporting a priori simplification to reduce the problem size, and providing an efficient form
Results 1  10
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