The ability of the servers to deliver services to the clients according to pre-defined agreements is becoming an important requirement. These pre-defined agreements are sometimes referred to as service level agreements (SLA). In most practical cases, these agreements are based on the response times observed by the customer. This service level ‘agreeability’ is not captured in the definitions of...

In this paper, we present a new framework for object matching between two images. This method could handle multiple pairs of overlapping and non-overlapping shapes, open curves, and landmarks. When implemented in 3-D, the same framework could be used to warp 3-D objects with minimal modification. Our approach is to use the level set formulation to represent the objects to be matched. Using this...

Semi-supervised clustering models, that incorporate user provided constraints to yield meaningful clusters, have recently become a popular area of research. In this paper, we propose a cluster-level semi-supervision model for inter-active clustering. Prototype based clustering algorithms typically alternate between updating cluster descriptions and assignment of data items to clusters. In our m...

Over the recent years, data-driven approaches that take advantage of the availability of large manually-annotated datasets have proven effective at visual perception tasks. We witnessed particularly rapid improvements in the image classification task, where machines now surpass human-level performance. However, the progress in certain instancelevel recognition tasks, such as object segmentation...

We extend the definition of level-crossing ordering of stochastic processes, proposed by Irle andGani (2001), to the case in which the times to exceed levels are compared using an arbitrary stochastic order, and work, in particular, with integral stochastic orders closed for convolution. Using a sample-path approach, we establish level-crossing ordering results for the case in which the slower ...

Recently, affinity propagation (AP) was introduced as an unsupervised learning algorithm for exemplar based clustering. Here we extend the AP model to account for semisupervised clustering. AP, which is formulated as inference in a factor-graph, can be naturally extended to account for ‘instancelevel’ constraints: pairs of data points that cannot belong to the same cluster (cannotlink), or must...

A key issue of semi-supervised clustering is how to utilize the limited but informative pairwise constraints. In this paper, we propose a new graph-based constrained clustering algorithm, named SCRAWL. It is composed of two random walks with different granularities. In the lower-level random walk, SCRAWL partitions the vertices (i.e., data points) into constrained and unconstrained ones, accord...

This paper proposes and implements a novel hybrid level set method which combines the numerical efficiency of the local level set approach with the temporal stability afforded by a semi-implicit technique. By introducing an extraction/insertion algorithm into the local level set approach, we can accurately capture complicated behaviors such as interface separation and coalescence. This techniqu...

Here a semi-implicit formulation of the gradient augmented level set method is presented. The method is a hybrid Lagrangian–Eulerian method that may be easily applied in two or three dimensions. By tracking both the level set function and the gradient of the level set function, highly accurate descriptions of a moving interface can be formed. Stability is enhanced by the addition of a smoothing...