1.2k citations
5 papers
Deep Learning for Anomaly Detection: A Survey
Raghavendra Chalapathy, Sanjay Chawla
Anomaly detection is an important problem that has been well-studied within diverse research areas and application domains. The aim of this survey is two-fold, firstly we present a…
Group Anomaly Detection using Deep Generative Models
Raghavendra Chalapathy, Edward Toth, Sanjay Chawla
Unlike conventional anomaly detection research that focuses on point anomalies, our goal is to detect anomalous collections of individual data points. In particular, we perform gro…
Anomaly Detection using One-Class Neural Networks
Raghavendra Chalapathy, Aditya Krishna Menon, Sanjay Chawla
We propose a one-class neural network (OC-NN) model to detect anomalies in complex data sets. OC-NN combines the ability of deep networks to extract a progressively rich representa…
Recurrent neural networks with specialized word embeddings for health-domain named-entity recognition
Inigo Jauregi Unanue, Ehsan Zare Borzeshi, Massimo Piccardi
Background. Previous state-of-the-art systems on Drug Name Recognition (DNR) and Clinical Concept Extraction (CCE) have focused on a combination of text "feature engineering" and c…
A Dual Method For Backward Stochastic Differential Equations with Application to Risk Valuation
Andrzej Ruszczynski, Jianing Yao
We propose a numerical recipe for risk evaluation defined by a backward stochastic differential equation. Using dual representation of the risk measure, we convert the risk valuati…