The application of machine learning methods in the engineering of intelligent technical systems often requires the integration of continuous constraints like positivity, monotonicity, or bounded curvature in the learned function to guarantee a reliable performance. We show that the extreme learning machine is particularly well suited for this task. Constraints involving arbitrary derivatives of...

This paper describes an improved speciication method of scheduling constraints for high-level synthesis. Communication with external devices imposes many scheduling constraints and added functionality on a design. Traditional methods require the designer to manually embed the external constraints from all outside devices into the description of the system being designed; this approach is both t...

We propose a novel probabilistic synchoronous context-free grammar formalism for statistical machine translation, in which syntactic nonterminal labels are represented as “soft” preferences rather than as “hard” matching constraints. This formalism allows us to efficiently score unlabeled synchronous derivations without forgoing traditional syntactic constraints. Using this score as a feature i...

Typically in a scheduling problem we are given jobs of different processing times pj and different priority weights wj , and need to schedule them on a single machine in order to minimize a specific cost function. In this paper we consider the non-linear objective function ∑ wjC β j , where Cj is the completion time of job j and β > 0 is some arbitrary real constant. Except for β = 1 the comple...

Recent progress in Biology and data-production technologies push research toward a new interdisciplinary field, named Systems Biology, where the challenge is to break the complexity walls for reasoning about large biomolecular interaction systems. Pioneered by Regev, Silverman and Shapiro, the application of process calculi to the description of biological processes has been a source of inspira...

Languages with rich inflectional morphology pose a difficult challenge for statistical machine translation. To address the problem of morphologically inconsistent output, we add unification-based constraints to the target-side of a string-to-tree model. By integrating constraint evaluation into the decoding process, implausible hypotheses can be penalised or filtered out during search. We use a...

The problem of finding a next best viewpoint for 3D modeling or scene mapping has been explored in computer vision over the last decade. This paper tackles a similar problem, but with different characteristics, and proposes a method for dynamic best viewpoint recovery of a target point while avoiding possible occlusions. Since the environment can change, the method has to iteratively find the n...

For a long time, the bilevel programming problem has essentially been considered as a special case of mathematical programs with equilibrium constraints (MPECs), in particular when the so-called KKT reformulation is in question. Recently though, this widespread believe was shown to be false in general. In this paper, other aspects of the difference between both problems are revealed as we consi...

This paper addresses two second-best toll pricing problems, one with fixed and the other with elastic travel demands, as mathematical programs with equilibrium constraints. Several equivalent nonlinear programming formulations for the two problems are discussed. One formulation leads to properties that are of interest to transportation economists. Another produces an algorithm that is capable o...