19 citations · 36 across the 26 of their papers we have counts for
31 papers
Multilingual Coreference Resolution via Cycle-Consistent Machine Translation
Adriana-Valentina Costache, Eduard Poesina, Silviu-Florin Gheorghe +2
Coreference resolution is a core NLP task, having a broad range of downstream applications, e.g.~machine translation, question answering, document summarization, etc. While the tas…
Real-time tightly coupled GNSS and IMU integration via Factor Graph Optimization
Radu-Andrei Cioaca, Paul Irofti, Cristian Rusu +3
Reliable positioning in dense urban environments remains challenging due to frequent GNSS signal blockage, multipath, and rapidly varying satellite geometry. While factor graph opt…
Real-time loosely coupled GNSS and IMU integration via Factor Graph Optimization
Radu-Andrei Cioaca, Cristian Rusu, Paul Irofti +3
Accurate positioning, navigation, and timing (PNT) is fundamental to the operation of modern technologies and a key enabler of autonomous systems. A very important component of PNT…
MOSLD-Bench: Multilingual Open-Set Learning and Discovery Benchmark for Text Categorization
Adriana-Valentina Costache, Daria-Nicoleta Dragomir, Silviu-Florin Gheorghe +3
Open-set learning and discovery (OSLD) is a challenging machine learning task in which samples from new (unknown) classes can appear at test time. It can be seen as a generalizatio…
A comparison between joint and dual UKF implementations for state estimation and leak localization in water distribution networks
Luis Romero-Ben, Paul Irofti, Florin Stoican +1
The sustainability of modern cities highly depends on efficient water distribution management, including effective pressure control and leak detection and localization. Accurate in…
Factor Graph Optimization for Leak Localization in Water Distribution Networks
Paul Irofti, Luis Romero-Ben, Florin Stoican +1
Detecting and localizing leaks in water distribution network systems is an important topic with direct environmental, economic, and social impact. Our paper is the first to explore…
XMAD-Bench: Cross-Domain Multilingual Audio Deepfake Benchmark
Ioan-Paul Ciobanu, Andrei-Iulian Hiji, Nicolae-Catalin Ristea +3
Recent advances in audio generation led to an increasing number of deepfakes, making the general public more vulnerable to financial scams, identity theft, and misinformation. Audi…
Detecting and Mitigating DDoS Attacks with AI: A Survey
Alexandru Apostu, Silviu Gheorghe, Andrei Hîji +5
Distributed Denial of Service attacks represent an active cybersecurity research problem. Recent research shifted from static rule-based defenses towards AI-based detection and mit…
Text Classification Under Class Distribution Shift: A Survey
Adriana Valentina Costache, Silviu Florin Gheorghe, Eduard Gabriel Poesina +2
The basic underlying assumption of machine learning (ML) models is that the training and test data are sampled from the same distribution. However, in daily practice, this assumpti…
Dual Unscented Kalman Filter Architecture for Sensor Fusion in Water Networks Leak Localization
Luis Romero-Ben, Paul Irofti, Florin Stoican +1
Leakage in water systems results in significant daily water losses, degrading service quality, increasing costs, and aggravating environmental problems. Most leak localization meth…
Deepfake Media Generation and Detection in the Generative AI Era: A Survey and Outlook
Florinel-Alin Croitoru, Andrei-Iulian Hiji, Vlad Hondru +7
We survey deepfake generation and detection techniques, covering all deepfake media types: image, video, audio and multimodal content. We identify various kinds of deepfakes and co…
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…
Learning Explicitly Conditioned Sparsifying Transforms
Andrei Pătraşcu, Cristian Rusu, Paul Irofti
Sparsifying transforms became in the last decades widely known tools for finding structured sparse representations of signals in certain transform domains. Despite the popularity o…
Nodal Hydraulic Head Estimation through Unscented Kalman Filter for Data-driven Leak Localization in Water Networks
Luis Romero-Ben, Paul Irofti, Florin Stoican +1
In this paper, we present a nodal hydraulic head estimation methodology for water distribution networks (WDN) based on an Unscented Kalman Filter (UKF) scheme with application to l…
Pinky: A Modern Malware-oriented Dynamic Information Retrieval Tool
Paul Irofti
We present here a reverse engineering tool that can be used for information retrieval and anti-malware techniques. Our main contribution is the design and implementation of an inst…
OpenBSD formal driver verification with SeL4
Adriana Nicolae, Paul Irofti, Ioana Leustean
The seL4 microkernel is currently the only kernel that has been fully formally verified. In general, the increased interest in ensuring the security of a kernel's code results from…
Learning Dictionaries from Physical-Based Interpolation for Water Network Leak Localization
Paul Irofti, Luis Romero-Ben, Florin Stoican +1
This article presents a leak localization methodology based on state estimation and learning. The first is handled by an interpolation scheme, whereas dictionary learning is consid…
Software Mitigation of RISC-V Spectre Attacks
Ruxandra Bălucea, Paul Irofti
Speculative attacks are still an active threat today that, even if initially focused on the x86 platform, reach across all modern hardware architectures. RISC-V is a newly proposed…
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…