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In this paper we explore the connection between clustering categorical data and entropy: clusters of similar poi lower entropy than those of dissimilar ones. We use this connection to design an incremental heuristic algorithm, COOLCAT, which is capable of efficiently clustering large data sets of records with categorical attributes, and data streams. In(More)
We present region-based, fully convolutional networks for accurate and efficient object detection. In contrast to previous region-based detectors such as Fast/Faster R-CNN [7, 19] that apply a costly per-region subnetwork hundreds of times, our region-based detector is fully convolutional with almost all computation shared on the entire image. To achieve(More)
Ontology alignment identifies semantically matching entities in different ontologies. Various ontology alignment strategies have been proposed; however, few systems have explored how to automatically combine multiple strategies to improve the matching effectiveness. This paper presents a dynamic multistrategy ontology alignment framework, named RiMOM. The(More)
We performed a genome-wide association study (GWAS) of systemic lupus erythematosus (SLE) in a Chinese Han population by genotyping 1,047 cases and 1,205 controls using Illumina Human610-Quad BeadChips and replicating 78 SNPs in two additional cohorts (3,152 cases and 7,050 controls). We identified nine new susceptibility loci (ETS1, IKZF1, RASGRP3,(More)
PURPOSE The Head and Neck Intergroup conducted a phase III randomized trial to test the benefit of adding chemotherapy to radiation in patients with unresectable squamous cell head and neck cancer. PATIENTS AND METHODS Eligible patients were randomly assigned between arm A (the control), single daily fractionated radiation (70 Gy at 2 Gy/d); arm B,(More)
Spoofing with photograph or video is one of the most commonmanner to circumvent a face recognition system. In this paper, we present a real-time and non-intrusive method to address this based on individual images from a generic webcamera. The task is formulated as a binary classification problem, in which, however, the distribution of positive and negative(More)
In this work we describe a Convolutional Neural Network (CNN) to accurately predict image quality without a reference image. Taking image patches as input, the CNN works in the spatial domain without using hand-crafted features that are employed by most previous methods. The network consists of one convolutional layer with max and min pooling, two fully(More)
Text line segmentation in freestyle handwritten documents remains an open document analysis problem. Curvilinear text lines and small gaps between neighboring text lines present a challenge to algorithms developed for machine printed or hand-printed documents. In this paper, we propose a novel approach based on density estimation and a state-of-the-art(More)
We present a new general upper bound on the number of examples required to estimate all of the expectations of a set of random variables uniformly well. The quality of the estimates is measured using a variant of the relative error proposed by Haussler and Pollard. We also show that our bound is within a constant factor of the best possible. Our upper bound(More)
BACKGROUND The narrow host range of Mycobacterium leprae and the fact that it is refractory to growth in culture has limited research on and the biologic understanding of leprosy. Host genetic factors are thought to influence susceptibility to infection as well as disease progression. METHODS We performed a two-stage genomewide association study by(More)