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Belief function-based semi-supervised learning for brain tumor segmentation
Precise segmentation of a lesion area is important for optimizing its tr...
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Covid-19 classification with deep neural network and belief functions
Computed tomography (CT) image provides useful information for radiologi...
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Modeling Heterogeneous Statistical Patterns in High-dimensional Data by Adversarial Distributions: An Unsupervised Generative Framework
Since the label collecting is prohibitive and time-consuming, unsupervis...
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DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System
In general, recommendation can be viewed as a matching problem, i.e., ma...
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DIAG-NRE: A Deep Pattern Diagnosis Framework for Distant Supervision Neural Relation Extraction
Modern neural network models have achieved the state-of-the-art performa...
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On Finding Dense Subgraphs in Bipartite Graphs: Linear Algorithms with Applications to Fraud Detection
Detecting dense subgraphs from large graphs is a core component in many ...
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Bounding Entities within Dense Subtensors
Group-based fraud detection is a promising methodology to catch frauds o...
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BadLink: Combining Graph and Information-Theoretical Features for Online Fraud Group Detection
Frauds severely hurt many kinds of Internet businesses. Group-based frau...
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Online Semi-Supervised Learning on Quantized Graphs
In this paper, we tackle the problem of online semi-supervised learning ...
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An Analysis of the Convergence of Graph Laplacians
Existing approaches to analyzing the asymptotics of graph Laplacians typ...
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Mantis: Predicting System Performance through Program Analysis and Modeling
We present Mantis, a new framework that automatically predicts program p...
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