On the number of unlabeled vertices in edge-friendly labelings of graphs

Let $G$ be a graph with vertex set $V(G)$ and edge set $E(G)$, and $f$ be a 0-1 labeling of $E(G)$ so that the absolute difference in the number of edges labeled 1 and 0 is no more than one. Call such a labeling $f$ \emph{edge-friendly}. We say an edge-friendly labeling induces a \emph{partial vertex labeling} if vertices which are incident to more edges labeled 1 than 0, are labeled 1, and vertices which are incident to more edges labeled 0 than 1, are labeled 0. Vertices that are incident to an equal number of edges of both labels we call \emph{unlabeled}. Call a procedure on a labeled graph a \emph{label switching algorithm} if it consists of pairwise switches of labels. Given an edge-friendly labeling of $K_n$, we show a label switching algorithm producing an edge-friendly relabeling of $K_n$ such that all the vertices are labeled. We call such a labeling \textit{opinionated}.Comment: 7 pages, accepted to Discrete Mathematics, special issue dedicated to Combinatorics 201

Unifying and Merging Well-trained Deep Neural Networks for Inference Stage

We propose a novel method to merge convolutional neural-nets for the inference stage. Given two well-trained networks that may have different architectures that handle different tasks, our method aligns the layers of the original networks and merges them into a unified model by sharing the representative codes of weights. The shared weights are further re-trained to fine-tune the performance of the merged model. The proposed method effectively produces a compact model that may run original tasks simultaneously on resource-limited devices. As it preserves the general architectures and leverages the co-used weights of well-trained networks, a substantial training overhead can be reduced to shorten the system development time. Experimental results demonstrate a satisfactory performance and validate the effectiveness of the method.Comment: To appear in the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence, 2018. (IJCAI-ECAI 2018

Analysis and comparison of location strategies for reducing registration cost

Abstract. In mobile environments, a personal communication service (PCS) network must keep track of the location of each mobile user in order to correctly deliver calls. A basic scheme used in the standard IS-41 and GSM protocols is to always update the location of a mobile user whenever the mobile user moves to a new location. The problem with this approach is that the cost of location update operations is very high especially when the mobile user moves frequently. In recent years, various location management strategies for reducing the location update cost have been proposed. However, the performance issue of these proposed algorithms remains to be investigated. In this paper, we develop two Markov chains to analyze and compare the performance of two promising location update strategies, i.e., the two location algorithm (TLA) and the forwarding and resetting algorithm (FRA). By utilizing the Markov chain, we are able to quickly answer what-if questions regarding the performance of PCS networks under various workload conditions and also identify conditions under which one strategy can perform better than the others. Using the cost due to location update and search operations between two successive calls to a mobile user as a performance measure, we show that when the mobile user exhibits a high degree of locality and the mobile user’s call-to-mobility ratio (CMR) is low, TLA can significantly outperform both FRA and IS-41. On the other hand, when CMR is high, FRA is the winner. Furthermore, unlike TLA which may perform worse than IS-41 at hig

novoBreak: local assembly for breakpoint detection in cancer genomes.

We present novoBreak, a genome-wide local assembly algorithm that discovers somatic and germline structural variation breakpoints in whole-genome sequencing data. novoBreak consistently outperformed existing algorithms on real cancer genome data and on synthetic tumors in the ICGC-TCGA DREAM 8.5 Somatic Mutation Calling Challenge primarily because it more effectively utilized reads spanning breakpoints. novoBreak also demonstrated great sensitivity in identifying short insertions and deletions

Predicting Antigenic Variants of Influenza A/H3N2 Viruses

Models based on amino acid changes in influenza hemagglutinin protein were compared to predict antigenic variants of influenza A/H3N2 viruses

A non-reflecting metamaterial slab under the finite-embedded coordinate transformation

From the explicit solutions of Maxwell's equations under the coordinate transformation, the conditions for non-reflecting boundaries for the two-dimensionally propagating light waves, in a finite-embedded coordinate transformation metamaterial slab are derived in cases of extended two-dimensional. By exploring several examples, including some reported in the literatures and some novel developed in this study, we show that our approach can be used to efficiently determine the condition in which a finite-embedded coordinate transformed metamaterial slab is non-reflecting.Comment: 13 page