Application of information retrieval techniques to single writer documents

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How researchers see this paper

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One-Class Support Measure Machines for Group Anomaly Detection (2013, methodology): “Given the equivalence between OCSMM and MES, it is natural to ask if the spherical normalization (8) preserves the injectivity of the Hilbert space embedding.”
Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity (2019, methodology): “UGRAPHEMB is a general framework that should be able to preserve the graph-graph proximity under any graph proximity metric, such as GED and MCS.”
FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare (2019, background): “To this end, there are mainly two kinds of approaches: 1) instance reweighting [Huang et al., 2012; Huang et al., 2007], which reuses samples from the source domain according to some weighting technique; and 2) feature matching, which either performs subspace learning by exploiting the subspace geom”
Learning the Kernel Function via Regularization (2005, background): “We also wish to emphasize that although we focus on learning methods based on the minimization of the functional (1), the ideas whiche present here may prove useful for learning kernels or feature representations using different forms of regularization such as entropy regularization (Jaakkola, Meila”