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An abstract machine for CLP(R)

Joxan Jaffar, Peter J. Stuckey, Spiro Michaylov, Roland H. C. Yap
1992 Proceedings of the ACM SIGPLAN 1992 conference on Programming language design and implementation - PLDI '92  
The core Constraint Logic Arithmetic Machine (CLAM) extends the Warren Abstract Machine (WAM) for compiling Prolog with facilities for handling rea 1 arithmetic constraints.  ...  Abstract machines have been used for implementing programming languages for many reasons.  ...  Linear form accumulator A linear constraint is built up using one instruction for the constant term, and one for each linear component.  ... 
doi:10.1145/143095.143127 dblp:conf/pldi/JaffarMSY92 fatcat:4adjnxq6dfhbbl3laf25vgy2ye

Decision Procedures in Soft, Hard and Bio-ware - Follow Up (Dagstuhl Seminar 11272)

Nikolaj Bjorner, Robert Nieuwenhuis, Helmut Veith, Andrei Voronkov, Marc Herbstritt
2011 Dagstuhl Reports  
The follow-on seminar focused on the remaining objectives, in particular to bio-ware and constraint solving methods.  ...  The Z3 SMT solver is used internally in a number of ways: to discharge queries that fall into the first-order fragment of separation logic; to reason about equality between pointer expressions, using unSat  ...  SLAyer uses separation logic to reason about memory safety properties of low-level heap-manipulating code.  ... 
doi:10.4230/dagrep.1.7.23 dblp:journals/dagstuhl-reports/BjornerNVV11 fatcat:wfkdnqhh6nbdbf5jgtirejs44u

Using Markov Chain and Nearest Neighbor Criteria in an Experience Based Study Planning System with Linear Time Search and Scalability

Juan Segura-ramirez, Willie Chang
2006 2006 IEEE International Conference on Information Reuse & Integration  
Since each query input is a set of constraints in a pre-determined order, the parametric combinations has an associated sorted list to look up in a one-pass linear process.  ...  Hence, we identify the similarity in the historic records to the set of constraints queried with a desired probability.  ...  Case-Base Reasoning System Case-Base Reasoning System (CBRS) can be used when little concrete knowledge is available about a domain but experts exist [1, 4, 5, 12, 13] .  ... 
doi:10.1109/iri.2006.252447 dblp:conf/iri/Segura-RamirezC06 fatcat:mtpfyhp7xbdopmaza3kslnfmg4

A Tutorial Introduction to the Logic of Parametric Probability [article]

Joseph W. Norman
2012 arXiv   pre-print
It is demonstrated how to embed logical formulas from the propositional calculus into parametric probability networks, thereby enabling sound reasoning about the probabilities of logical propositions.  ...  The computational method of parametric probability analysis is introduced.  ...  How can logic be used to reason about an implication that is true sometimes but not always?  ... 
arXiv:1201.3142v4 fatcat:scaoec5vcjbd3ocqnmhayf5id4

Solving parametric linear systems

Clemens Ballarin, Manuel Kauers
2004 ACM SIGSAM Bulletin  
We propose to use a technique from model theory known as constraint programming to gain more flexibility, and we show how it can be applied to the Gaussian algorithm to be used for parametric systems.  ...  Our experiments suggest that in practice this leads to results comparable to the algorithm for parametric linear systems by Sit [9] -at least if the parameters are sparse.  ...  Conclusions Constraint algebraic programming can be applied to parametric linear equation systems successfully.  ... 
doi:10.1145/1041791.1041793 fatcat:fjvw6jm245df7agbhf23dfcijm

Semi-parametric and Non-parametric Term Weighting for Information Retrieval [chapter]

Donald Metzler, Hugo Zaragoza
2009 Lecture Notes in Computer Science  
Such constraints may possibly degrade retrieval effectiveness. In this paper we propose two new classes of term weighting schemes that we call semi-parametric and nonparametric weighting.  ...  These weighting schemes make fewer assumptions about the underlying term weights and allow the data to speak for itself.  ...  For example, a linear or non-linear regression model may be used as the parametric form, with the model parameters depending on bin(t, Q) and bin(t, D).  ... 
doi:10.1007/978-3-642-04417-5_5 fatcat:dlu2vcxthfem3j5paf25ypng4a

Querying constraints

Jean-Louis Lassez
1990 Proceedings of the ninth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems - PODS '90  
We show how one can design a querying system for sets of linear constraints by using basic concepts from logic programming and symbolic computation, as well as algorithms from linear programming and computational  ...  We conclude by reporting briefly on how notions of negation and canonical representation used in linear constraints can be generalized to account for cases in term algebras, symbolic computation, affine  ...  The subsumption cone is therefore a new tool to reason about sets of constraints.  ... 
doi:10.1145/298514.298581 dblp:conf/pods/Lassez90 fatcat:2t3mosyfffdoffimr3co552og4

Symbolic Polytopes for Quantitative Interpolation and Verification [chapter]

Klaus von Gleissenthall, Boris Köpf, Andrey Rybalchenko
2015 Lecture Notes in Computer Science  
However, they cannot synthesize formulas that satisfy given cardinality constraints, which limits their applicability for inferring cardinality-based inductive arguments.  ...  In this paper we present an algorithm for synthesizing formulas for given cardinality constraints, which relies on the theory of counting integral points in symbolic polytopes.  ...  Thus, by reasoning about the cardinality of the set of values (c 1 , c 2 ) we track the memory consumption of the program.  ... 
doi:10.1007/978-3-319-21690-4_11 fatcat:rxmyywpcqjgh7liwjih424onwa

Case-based reasoning vs parametric models for software quality optimization

Adam Brady, Tim Menzies
2010 Proceedings of the 6th International Conference on Predictive Models in Software Engineering - PROMISE '10  
Aim: To assess case-based reasoning vs parametric modeling for quality optimization. Method: We compared the W case-based reasoner against the SEEWAW parametric modeling tool.  ...  In the first way, we construct a parametric model to represent prior software projects. In the second way, we just apply case-based reasoning to reason directly from historical cases.  ...  INTRODUCTION How should we reason about software projects? Should we extrapolate from old data to build a parametric model; e.g. using a Bayes net [9] , or the linear equations of COCOMO [5, 7] ?  ... 
doi:10.1145/1868328.1868333 dblp:conf/promise/BradyM10 fatcat:zfegzbfmi5gjdof5xq75gtsyqe

Model Reduction Framework with a New Take on Active Subspaces for Optimization Problems with Linearized Fluid-Structure Interaction Constraints [article]

Gabriele Boncoraglio, Charbel Farhat, Charbel Bou-Mosleh
2020 arXiv   pre-print
The framework is fully developed for MDAO problems with linearized fluid-structure interaction constraints.  ...  It is applied to the aeroelastic tailoring, under flutter constraints, of two different flight systems: a flexible configuration of NASA's Common Research Model; and NASA's Aeroelastic Research Wing #2  ...  Here, the computational expense associated with the enforcement of the parametric, linearized, FSI constraint̃ (q( ), ) = (8) is reduced by substituting this constraint with a linear, -parametric, FSI  ... 
arXiv:2002.07602v1 fatcat:r4eozdjihzfmlix3yi7fkgbz4u

A glimpse on constant delay enumeration (Invited Talk)

Luc Segoufin, Marc Herbstritt
2014 Symposium on Theoretical Aspects of Computer Science  
We survey some of the recent results about enumerating the answers to queries over a database.  ...  We focus on the case where the enumeration is performed with a constant delay between any two consecutive solutions, after a linear time preprocessing. This cannot be always achieved.  ...  It will use only a small fragment of this memory, as it runs in pseudo-linear time, but for reasons detailed in [19] , it requires initially more. ◮ Theorem 8.  ... 
doi:10.4230/lipics.stacs.2014.13 dblp:conf/stacs/Segoufin14 fatcat:yi6xqnceejdzxaof667rw6q2r4

Aristotle's Logic Computed by Parametric Probability and Linear Optimization [article]

Joseph W. Norman
2014 arXiv   pre-print
Using linear optimization methods, the minimum and maximum feasible values of certain queried probabilities are computed, subject to the constraints given as premises.  ...  Each Aristotelian problem is interpreted as a parametric probability network in which the premises give constraints on probabilities relating the problem's categorical terms (major, minor, and middle).  ...  Parametric probability networks such as this basic model are used like databases to answer queries. Each query requests an unconditioned probability or a conditional probability.  ... 
arXiv:1306.6406v6 fatcat:l5wrbbw56jhjrccsnxvzwkpx3a

Collaborative Filtering via Rating Concentration

Bert Huang, Tony Jebara
2010 Journal of machine learning research  
A joint probability distribution over queries of interest is estimated using maximum entropy regularization.  ...  The method accurately estimates rating distributions on synthetic and real data and is competitive with low rank and parametric methods which make more aggressive assumptions about the problem.  ...  Due to the linearity of the expectation operator, each bound above produces a linear inequality or half-space constraint on p(x ij |u i , v j ).  ... 
dblp:journals/jmlr/HuangJ10 fatcat:dydsn2fogvhzdko5cbwpenehfy

Optimal Web-Scale Tiering as a Flow Problem

Gilbert Leung, Novi Quadrianto, Alexander J. Smola, Kostas Tsioutsiouliklis
2010 Neural Information Processing Systems  
Our algorithm solves an integer linear program in an online fashion. It exploits total unimodularity of the constraint matrix and a Lagrangian relaxation to solve the problem as a convex online game.  ...  We apply the algorithm to optimize tier arrangement of over 84 million web pages on a layered set of caches to serve an incoming query stream optimally.  ...  Moreover, for reasons of practicality we need to design an algorithm which is linear in the amount of data presented (i.e. the number of queries) and whose storage requirements are only linear in the number  ... 
dblp:conf/nips/LeungQST10 fatcat:ofuxmh2p5nf43o3pik2erlkaoq

Variable ranges in linear constraints

Salvatore Ruggieri, Fred Mesnard
2010 Proceedings of the 2010 ACM Symposium on Applied Computing - SAC '10  
We introduce an extension of linear constraints, called linearrange constraints, which allows for (meta-)reasoning about the approximation width of variables.  ...  An extension of the constraint logic programming language CLP(R) is proposed by admitting linear-range constraints.  ...  Also, we extended CLP(R) with linear-range constraints, hence providing a form of meta-level reasoning about the range of variables.  ... 
doi:10.1145/1774088.1774521 dblp:conf/sac/RuggieriM10 fatcat:7uv6fg2vpjdz3d6bgbatjoznfq
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