A set label disagreement function is defined over the number of variables that deviates from the dominant label. The dominant label is the value assumed by the largest number of variables within a set of binary variables. The submodularity of a certain family of set label disagreement function is discussed in this manuscript. Such disagreement function could be utilized as a cost function in co...

A graph G is said to have a totally magic cordial labeling with constant C if there exists a mapping f : V (G) ∪ E(G) → {0, 1} such that f(a) + f(b) + f(ab) ≡ C (mod 2) for all ab ∈ E(G) and |nf (0) − nf (1)| ≤ 1, where nf (i) (i = 0, 1) is the sum of the number of vertices and edges with label i. In this paper, we give a necessary condition for an odd graph to be not totally magic cordial and ...

Multiprotocol label switching (MPLS) has several advantages over destination-based IP routing protocols: it allows to setup end to end paths explicitly (also called label switched paths, LSP), to better monitor the traffic on these LSPs, to perform admission control, etc. While routing along a LSP is considered faster than IP routing, the operation of changing a LSP pipe requires processing and...

Multi-label classification with many classes has recently drawn a lot of attention. Existing methods address this problem by performing linear label space transformation to reduce the dimension of label space, and then conducting independent regression for each reduced label dimension. These methods however do not capture nonlinear correlations of the multiple labels and may lead to significant...

Person re-identification methods have recently made tremendous progress on maximizing re-identification accuracy between camera pairs. However, this line of work mostly shares an critical limitation it assumes re-identification in a ‘closed world’. That is, between a known set of people who all appear in both views of a single pair of cameras. This is clearly far from a realistic application sc...

As a generalized form of multi-class classification, multilabel classification allows each sample to be associated with multiple labels. This task becomes challenging when the number of labels bulks up, which demands a high efficiency. Many approaches have been proposed to address this problem, among which one of the main ideas is to select a subset of labels which can approximately span the or...

Fast header processing in Optical Transport Networks (OTN) has been foreseen as one of the main challenges in All-Optical Packet Switched (AOPS) networks. The LASAGNE project aims at supporting All-Optical Label Swapping (AOLS), easing most of the header processing drawbacks in AOPS. However, AOLS is expensive mainly because each supported label requires the deployment of an All-Optical Logic X...

Abstract: Multi-label feature selection is designed to select a subset of features according to their importance to multiple labels. This task can be achieved by ranking the dependencies of features and selecting the features with the highest rankings. In a multi-label feature selection problem, the algorithm may be faced with a dataset containing a large number of labels. Because the computati...

Let G be a (p, q) graph. Let f : V (G) → {1, 2, . . . , k} be a map. For each edge uv, assign the label gcd (f(u), f(v)). f is called k-prime cordial labeling of G if |vf (i) − vf (j)| ≤ 1, i, j ∈ {1, 2, . . . , k} and |ef (0) − ef (1)| ≤ 1 where vf (x) denotes the number of vertices labeled with x, ef (1) and ef (0) respectively denote the number of edges labeled with 1 and not labeled with 1....