19 citations · 36 across the 26 of their papers we have counts for
10 papers · 1 filter
Fusing Dictionary Learning and Support Vector Machines for Unsupervised Anomaly Detection
Paul Irofti, Iulian-Andrei Hîji, Andrei Pătraşcu +1
We study in this paper the improvement of one-class support vector machines (OC-SVM) through sparse representation techniques for unsupervised anomaly detection. As Dictionary Lear…
Unsupervised Abnormal Traffic Detection through Topological Flow Analysis
Paul Irofti, Andrei Pătraşcu, Andrei Iulian Hîji
Cyberthreats are a permanent concern in our modern technological world. In the recent years, sophisticated traffic analysis techniques and anomaly detection (AD) algorithms have be…
Dictionary Learning with Uniform Sparse Representations for Anomaly Detection
Paul Irofti, Cristian Rusu, Andrei Pătraşcu
Many applications like audio and image processing show that sparse representations are a powerful and efficient signal modeling technique. Finding an optimal dictionary that genera…
Data-driven Leak Localization in Water Distribution Networks via Dictionary Learning and Graph-based Interpolation
Paul Irofti, Luis Romero-Ben, Florin Stoican +1
In this paper, we propose a data-driven leak localization method for water distribution networks (WDNs) which combines two complementary approaches: graph-based interpolation and d…
Complexity of Inexact Proximal Point Algorithm for minimizing convex functions with Holderian Growth
Andrei Pătraşcu, Paul Irofti
Several decades ago the Proximal Point Algorithm (PPA) started to gain a long-lasting attraction for both abstract operator theory and numerical optimization communities. Even in m…
Efficient and Parallel Separable Dictionary Learning
Cristian Rusu, Paul Irofti
Separable, or Kronecker product, dictionaries provide natural decompositions for 2D signals, such as images. In this paper, we describe a highly parallelizable algorithm that learn…
Stochastic Proximal Gradient Algorithm with Minibatches. Application to Large Scale Learning Models
Andrei Patrascu, Ciprian Paduraru, Paul Irofti
Stochastic optimization lies at the core of most statistical learning models. The recent great development of stochastic algorithmic tools focused significantly onto proximal gradi…
Unsupervised Dictionary Learning for Anomaly Detection
Paul Irofti, Andra Băltoiu
We investigate the possibilities of employing dictionary learning to address the requirements of most anomaly detection applications, such as absence of supervision, online formula…
Community-Level Anomaly Detection for Anti-Money Laundering
Andra Baltoiu, Andrei Patrascu, Paul Irofti
Anomaly detection in networks often boils down to identifying an underlying graph structure on which the abnormal occurrence rests on. Financial fraud schemes are one such example,…
Quick survey of graph-based fraud detection methods
Paul Irofti, Andrei Patrascu, Andra Baltoiu
In general, anomaly detection is the problem of distinguishing between normal data samples with well defined patterns or signatures and those that do not conform to the expected pr…