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Optimal Capital Structure, Endogenous Bankruptcy, and the Term Structure of Credit Spreads
 THE JOURNAL OF FINANCE, VOL. 51, NO. 3, PAPERS AND PROCEEDINGS OF THE FIFTYSIXTH
, 1996
"... ..."
Learnability in Optimality Theory
, 1995
"... In this article we show how Optimality Theory yields a highly general Constraint Demotion principle for grammar learning. The resulting learning procedure specifically exploits the grammatical structure of Optimality Theory, independent of the content of substantive constraints defining any given gr ..."
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Cited by 528 (34 self)
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In this article we show how Optimality Theory yields a highly general Constraint Demotion principle for grammar learning. The resulting learning procedure specifically exploits the grammatical structure of Optimality Theory, independent of the content of substantive constraints defining any given
Optimal Structure Identification with Greedy Search
, 2002
"... In this paper we prove the socalled "Meek Conjecture". In particular, we show that if a is an independence map of another DAG then there exists a finite sequence of edge additions and covered edge reversals in such that (1) after each edge modification and (2) after all mod ..."
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Cited by 249 (1 self)
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In this paper we prove the socalled "Meek Conjecture". In particular, we show that if a is an independence map of another DAG then there exists a finite sequence of edge additions and covered edge reversals in such that (1) after each edge modification and (2) after all modifications H.
Dictionary of protein secondary structure: pattern recognition of hydrogenbonded and geometrical features
 Biopolymers
, 1983
"... structure ..."
A Limited Memory Algorithm for Bound Constrained Optimization
 SIAM Journal on Scientific Computing
, 1994
"... An algorithm for solving large nonlinear optimization problems with simple bounds is described. ..."
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Cited by 557 (9 self)
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An algorithm for solving large nonlinear optimization problems with simple bounds is described.
DataGuides: Enabling Query Formulation and Optimization in Semistructured Databases
, 1997
"... In semistructured databases there is no schema fixed in advance. To provide the benefits of a schema in such environments, we introduce DataGuides: concise and accurate structural summaries of semistructured databases. DataGuides serve as dynamic schemas, generated from the database; they are ..."
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Cited by 576 (14 self)
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; they are useful for browsing database structure, formulating queries, storing information such as statistics and sample values, and enabling query optimization. This paper presents the theoretical foundations of DataGuides along with an algorithm for their creation and an overview of incremental maintenance
The program dependence graph and its use in optimization
 ACM Transactions on Programming Languages and Systems
, 1987
"... In this paper we present an intermediate program representation, called the program dependence graph (PDG), that makes explicit both the data and control dependence5 for each operation in a program. Data dependences have been used to represent only the relevant data flow relationships of a program. ..."
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Cited by 989 (3 self)
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. Control dependence5 are introduced to analogously represent only the essential control flow relationships of a program. Control dependences are derived from the usual control flow graph. Many traditional optimizations operate more efficiently on the PDG. Since dependences in the PDG connect
Constrained model predictive control: Stability and optimality
 AUTOMATICA
, 2000
"... Model predictive control is a form of control in which the current control action is obtained by solving, at each sampling instant, a finite horizon openloop optimal control problem, using the current state of the plant as the initial state; the optimization yields an optimal control sequence and t ..."
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Cited by 696 (15 self)
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Model predictive control is a form of control in which the current control action is obtained by solving, at each sampling instant, a finite horizon openloop optimal control problem, using the current state of the plant as the initial state; the optimization yields an optimal control sequence
SNOPT: An SQP Algorithm For LargeScale Constrained Optimization
, 2002
"... Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective and constraints. Here we consider problems with general inequality constraints (linear and nonlinear). We assume that first deriv ..."
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Cited by 582 (23 self)
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Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective and constraints. Here we consider problems with general inequality constraints (linear and nonlinear). We assume that first
Improved algorithms for optimal winner determination in combinatorial auctions and generalizations
, 2000
"... Combinatorial auctions can be used to reach efficient resource and task allocations in multiagent systems where the items are complementary. Determining the winners is NPcomplete and inapproximable, but it was recently shown that optimal search algorithms do very well on average. This paper present ..."
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Cited by 598 (55 self)
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presents a more sophisticated search algorithm for optimal (and anytime) winner determination, including structural improvements that reduce search tree size, faster data structures, and optimizations at search nodes based on driving toward, identifying and solving tractable special cases. We also uncover
Results 1  10
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1,788,607