نتایج جستجو برای: probabilistic constraints

تعداد نتایج: 249942  

2008
Ming-Wei Chang Lev-Arie Ratinov Nicholas Rizzolo Dan Roth

Probabilistic modeling has been a dominant approach in Machine Learning research. As the field evolves, the problems of interest become increasingly challenging and complex. Making complex decisions in real world problems often involves assigning values to sets of interdependent variables where the expressive dependency structure can influence, or even dictate, what assignments are possible. Ho...

El merouani, Mohamed, Lajjam, Azza, Medouri, Abdellatif, Tabaa, Yassine,

Due to the considerable growth in the worldwide container transportation, optimization of container terminal operations is becoming highly needed to rationalize the use of logistics resources. For this reason, we focus our study on the Quay Crane Scheduling Problem (QCSP), which is a core task of managing maritime container terminals. From this planning problem arise two decisions to be made: T...

1998
Thomas Lukasiewicz

We study the problem of probabilistic deduction with conditional constraints over basic events. We show that globally complete probabilistic deduction with conditional constraints over basic events is NP-hard. We then concentrate on the special case of probabilistic deduction in conditional constraint trees. We elaborate very eecient techniques for globally complete probabilistic deduction. In ...

2006
Nick Chater Christopher D. Manning

Probabilistic methods are providing new explanatory approaches to fundamental cognitive science questions of howhumans structure, process and acquire language. This review examines probabilistic models defined over traditional symbolic structures. Language comprehension and production involve probabilistic inference in such models; and acquisition involves choosing the best model, given innate ...

Journal: :Trends in cognitive sciences 2006
Nick Chater Christopher D Manning

Probabilistic methods are providing new explanatory approaches to fundamental cognitive science questions of how humans structure, process and acquire language. This review examines probabilistic models defined over traditional symbolic structures. Language comprehension and production involve probabilistic inference in such models; and acquisition involves choosing the best model, given innate...

2003
Qiang Liu Edmond C. Prakash

Unit quaternion is an ideal parameterization for joint rotations. However, due to the complexity of the geometry of S group, it’s hard to specify meaningful joint constraints with unit quaternion. In this paper, we have proposed an effective and accurate method to specify the rotation limits for joints parameterized with the unit quaternion. Joint constrains constructed with our method are adeq...

2001
Léa Meyer

We are concerned with probabilistic identification of indexed families of uniformly recursive languages from positive data under monotonicity constraints. Thereby, we consider conservative, strong-monotonic and monotonic probabilistic learning of indexed families with respect to class comprising, class preserving and proper hypothesis spaces, and investigate the probabilistic hierarchies in the...

2014
Ruiming Tang Dongxu Shao Mouhamadou Lamine Ba Huayu Wu

A probabilistic relational database is a compact form of a set of deterministic relational databases (namely, possible worlds), each of which has a probability. In our framework, the existence of tuples is determined by associated Boolean formulae based on elementary events. An estimation, within such a setting, of the probabilities of possible worlds uses a prior probability distribution speci...

1993
Marco Ramoni Alberto Riva

Belief maintenance systems are natural extensions of truth maintenance systems that use probabilities rather than boolean truth-values. This paper introduces a general method for belief maintenance, based on (the propositional fragment of) probabilistic logic, that extends the Boolean Constraint Propagation method used by the logic-based truth maintenance systems. From the concept of probabilis...

2001
Thomas Lukasiewicz

We present probabilistic logic programming un­ der inheritance with overriding. This approach is based on new notions of entailment for reasoning with conditional constraints, which are obtained from the classical notion of logical entailment by adding inheritance with overriding. This is done by using recent approaches to probabilistic de­ fault reasoning with conditional constraints. We analy...

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