Constraint-based recommendation systems are used in many different domains like notebooks, cars, and mobile phones. Such systems describe product domains in sets of product and customer variables, their domains, and constraints which define the relationship between the variables. Maintenance is a crucial task in constraint-based recommendation systems, because it is timeconsuming and error-pron...

Modeling overlapping phrases in an alignment model can improve alignment quality but comes with a high inference cost. For example, the model of DeNero and Klein (2010) uses an ITG constraint and beam-based Viterbi decoding for tractability, but is still slow. We first show that their model can be approximated using structured belief propagation, with a gain in alignment quality stemming from t...

We present a partitional cluster algorithm that minimizes the sum-of-squared-error criterion while imposing a hard constraint on the cluster variance. Conceptually, hypothesized clusters act in parallel and cooperate with their neighboring clusters in order to minimize the criterion and to satisfy the variance constraint. In order to enable the demarcation of the cluster neighborhood without cr...

Compressive sensing (CS) is a technique for estimating a sparse signal from the random measurements and the measurement matrix. Traditional sparse signal recovery methods have seriously degeneration with the measurement matrix uncertainty (MMU). Here the MMU is modeled as a bounded additive error. An anti-uncertainty constraint in the form of a mixed 2  and 1  norm is deduced from the sparse ...

Automatically extracted data is rarely “clean” with respect to pragmatic (real-world) constraints—which thus hinders applications that depend on quality data. We proffer a solution to detecting pragmatic constraint violations that works via a declarative and semantically enabled constraint-violation checker. In conjunction with an ensemble of automated information extractors, the implemented pr...

The paper proposes a theoretical approach of the debugging of constraint programs based on a notion of explanation tree. The proposed approach is an attempt to adapt algorithmic debugging to constraint programming. In this theoretical framework for domain reduction, explanations are proof trees explaining value removals. These proof trees are defined by inductive definitions which express the r...

This paper addresses a number of issues concerning the integration of visual and physical constraints f o r the synthesis and execution of error-tolerant mot ion strategies. Object features and their projections onto the image plane of a supervisory camera are used t o define visual constraint surfaces. These visual constraint surfaces can be directly used t o enforce the following types of con...

This paper is motivated by the declarative insuuciency diagnosis of constraint logic programs, but focuses only on theoretical viewpoints. Many techniques have been developed for logic programming but cannot be merely adapted to constraint logic programming. Constraint logic program semantics is redeened in terms of proof trees using a cover relation. Proof trees give an intrinsic deenition to ...

Although constraint programming offers a wealth of strong, general-purpose methods, in practice a complex, real application demands a person who selects, combines, and refines various available techniques for constraint satisfaction and optimization. Although such tuning produces efficient code, the scarcity of human experts slows commercialization. The necessary expertise is of two forms: cons...

In this paper we study necessary optimality conditions for nonsmooth mathematical programs with equilibrium constraints (MPECs). We first show that MPEC-LICQ is not a constraint qualification for the strong (S-) stationary condition when the objective function is nonsmooth. Enhanced Fritz John conditions provide stronger necessary optimality conditions under weaker constraint qualifications. In...