We present a simple spectral approach to the well-studied constrained clustering problem. It captures constrained clustering as a generalized eigenvalue problem with graph Laplacians. The algorithm works in nearly-linear time and provides concrete guarantees for the quality of the clusters, at least for the case of 2-way partitioning. In practice this translates to a very fast implementation th...

In this paper, we present a novel technique for signal synthesis in the presence of an inconsistent set of constraints. This technique represents a general, minimum norm, solution to the class of synthesis problems in which: the desired signal may be characterized as being an element of some Hilbert Space; each of the N design constraints generates a closed convex set in that space; and those N...

This paper proposes a closed form solution to L2-sensitivity minimization of 2nd-order statespace digital filters subject to L2-scaling constraints. The proposed solution reduces a constrained optimization problem to an unconstrained optimization problem by appropriate variable transformation. Furthermore, by restricting ourselves to the case of 2nd-order statespace digital filters, we can form...

Abstract. When a randomly perturbed dynamical system is subject to some constraints, the trajectories of the system and the noise-induced most probable transition pathways are restricted on the manifold associated with the given constraints. We present a constrained minimum action method to compute the optimal transition pathways on manifolds. By formulating the constrained stochastic dynamics ...

Random sampling strategies play critical roles in ran-domized motion planners, which are promising and practical for motion planning problems with many degrees of freedom (dofs). In this paper, we explore random sampling in a constrained connguration space { the contact connguration space between two polyhedra, motivated by the need for generating contact motion plans. Given a contact formation...

In this paper, we propose an application of confusion network for Mandarin mispronunciation detection. Compared to former published works, which are proven to work effectively and robustly in detecting mispronunciation in word level and only successfully detect mispronunciation in sentence level in strictly small constrained search space, our modified confusion network based Computer-aided Pron...

In this paper we continue our earlier studies 13, 14] on boundary operators for constrained parameter optimization problems. The signiicance of this line of research is based on the observation that usually the global solution for many optimization problems lies on the boundary of the feasible region. Thus, for many constrained numerical optimization problems it might be beneecial to search jus...

The Constrained Multiple Sequence Alignment problem is to align a set of sequences subject to a given constrained sequence, which arises from some knowledge of the structure of the sequences. This paper presents new algorithms for this problem, which are more efficient in terms of time and space (memory) than the previous algorithms [14], and with a worst-case guarantee on the quality of the al...