Steven Latré

Steven Latré
University of Antwerp | UA · Department of Mathematics and Computer Science

PhD

About

236
Publications
68,468
Reads
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3,107
Citations
Introduction
Steven Latré is an assistant professor at the University of Antwerp, Belgium and the Future Internet Department at iMinds. He received a MSc degree in computer science from Ghent University, Belgium and a Ph.D. in Computer Science Engineering from the same university. His research activity focuses on autonomous management and control of both networking and computing applications. His recent work has focused on QoE optimization and management, distributed control and network virtualization.
Additional affiliations
October 2013 - present
University of Antwerp
Position
  • Professor (Assistant)
October 2013 - present
iMinds
Position
  • Professor (Assistant)
June 2011 - September 2013
Ghent University
Position
  • PostDoc Position
Education
October 2002 - July 2006
Ghent University
Field of study
  • Computer Science

Publications

Publications (236)
Article
Full-text available
The proliferation of multimedia services over access networks (e.g., IPTV or network-based Personal Video Recording) has introduced important new revenue potential for network and service providers but has also complicated the management burden. As a result, today's management of multimedia networks is often too static to cope with the increasing q...
Article
The recent emergence of multimedia services, such as Broadcast TV and Video on Demand over traditional twisted pair access networks, has complicated the network management in order to guarantee a decent Quality of Experience (QoE) for each user. The huge amount of services and the wide variety of service specifics require a QoE management on a per-...
Article
Full-text available
The important new revenue opportunities that multimedia services offer to network and service providers come with important management challenges. For providers, it is important to control the video quality that is offered and perceived by the user, typically known as the Quality of Experience (QoE). Both admission control and scalable video coding...
Preprint
Communication is crucial in multi-agent reinforcement learning when agents are not able to observe the full state of the environment. The most common approach to allow learned communication between agents is the use of a differentiable communication channel that allows gradients to flow between agents as a form of feedback. However, this is challen...
Article
Full-text available
Road weather conditions such as ice, snow, or heavy rain can have a significant impact on driver safety. In this paper, we present an approach to continuously monitor the road conditions in real time by equipping a fleet of vehicles with sensors. Based on the observed conditions, a physical road weather model is used to forecast the conditions for...
Article
Full-text available
The growth of mobile data traffic has led to the use of dense and heterogeneous networks with small cells in 4G and 5G. To manage such networks, dynamic and automated solutions for operation and maintenance tasks are needed to reduce human errors, save on Operating expense (OPEX) and optimize network resources. Self Organizing Networks (SON) are a...
Chapter
Full-text available
In the paper, we describe the technical details of a multi-player tracker system using tracking data obtained from a single low-cost stationary camera on field hockey games. Analyzing the tracking data of the players only from the transmitted video opens a multitude of applications that allows the cost of technology to be reduced. This method does...
Article
Full-text available
Reinforcement learning (RL) allows an agent to solve sequential decision-making problems by interacting with an environment in a trial-and-error fashion. When these environments are very complex, pure random exploration of possible solutions often fails, or is very sample inefficient, requiring an unreasonable amount of interaction with the environ...
Conference Paper
The plethora of heterogeneous and diversified services in 5G and beyond requires from networks to be flexible, adaptable, and programmable, i.e., to be able to correspondingly adapt to changes. As human intervention might significantly increase delays in MANagement and Orchestration (MANO) operations, automation and intelligence become imperative f...
Conference Paper
As manual Management and Orchestration (MANO) of services and resources might delay the execution of MANO operations and negatively impact the performance of 5G and beyond Vehicle-to-Everything (V2X) services, applying AI in MANO to enable automation and intelligence is an imperative. The Network Function Virtualization (NFV), Software Defined Netw...
Chapter
Recent work in multi-agent reinforcement learning has investigated inter agent communication which is learned simultaneously with the action policy in order to improve the team reward. In this paper, we investigate independent Q-learning (IQL) without communication and differentiable inter-agent learning (DIAL) with learned communication on an adap...
Chapter
The Sim2Real gap is a topic that has been receiving a great deal of attention lately. Many Artificial Intelligence techniques, for example Reinforcement Learning, require millions of iterations to achieve satisfactory performance. This requirement often forces these techniques to solely train in simulation. If the gap between the simulated environm...
Chapter
Situational awareness is getting traction in the field of autonomous inland vessels. Large amounts of data needs to be shared in order to set up this awareness. This ranges from relatively small positional updates, to consistent streams of sensory data. Point clouds, captured by LiDAR sensors, are heavily used by inland vessels as they give a detai...
Chapter
Object detection on real-time edge devices for new applications with no or a limited amount of annotated labels is difficult. Where traditional data-hungry methods fail, transfer learning can provide a solution by transferring knowledge from a source domain to the target application domain. We explore domain adaptation techniques on a one-stage det...
Chapter
In recent years, Capsule Networks (CapsNets) have achieved promising results in tasks such as object recognition thanks to their invariance characteristics towards pose and lighting. They have been proposed as an alternative to relational insensitive and translation invariant Convolutional Neural Networks (CNN). It has been empirically proven that...
Conference Paper
Full-text available
In recent years multi-label, multi-class video action recognition has gained significant popularity. While reasoning over temporally connected atomic actions is mundane for intelligent species, standard artificial neural networks (ANN) still struggle to classify them. In the real world, atomic actions often temporally connect to form more complex c...
Conference Paper
Next-generation mobile networks are expected to flaunt highly (if not fully) automated management. To achieve such a vision, Artificial Intelligence (AI) and Machine Learning (ML) techniques will be key enablers to craft the required intelligence for networking, i.e., Network Intelligence (NI), empowering myriad of orchestrators and controllers acr...
Preprint
Recent work in multi-agent reinforcement learning has investigated inter agent communication which is learned simultaneously with the action policy in order to improve the team reward. In this paper, we investigate independent Q-learning (IQL) without communication and differentiable inter-agent learning (DIAL) with learned communication on an adap...
Preprint
By using communication between multiple agents in multi-agent environments, one can reduce the effects of partial observability by combining one agent's observation with that of others in the same dynamic environment. While a lot of successful research has been done towards communication learning in cooperative settings, communication learning in m...
Preprint
In this paper, the authors investigate the Deep Sea Treasure (DST) problem as proposed by Vamplew et al. Through a number of proofs, the authors show the original DST problem to be quite basic, and not always representative of practical Multi-Objective Optimization problems. In an attempt to bring theory closer to practice, the authors propose an a...
Article
Full-text available
Professional road cycling is a very competitive sport, and many factors influence the outcome of the race. These factors can be internal (e.g., psychological preparedness, physiological profile of the rider, and the preparedness or fitness of the rider) or external (e.g., the weather or strategy of the team) to the rider, or even completely unpredi...
Chapter
Causal structure discovery in complex dynamical systems is an important challenge for many scientific domains. Although data from (interventional) experiments is usually limited, large amounts of observational time series data sets are usually available. Current methods that learn causal structure from time series often assume linear relationships....
Chapter
Full-text available
In this paper we address challenges facing lane marking detection and tracking. Lane marking detection along with vehicle positioning between lane boundaries are fundamental tasks to achieve safe and reliable autonomous driving systems. Despite the development of perception senors and clarity of the lane markings on roadways, the lane detection rem...
Chapter
Artificial Intelligence (AI) powered building control allows deriving policies that are more flexible and energy efficient than standard control. However, there are challenges: environment interaction is used to train Reinforcement Learning (RL) agents but for building control it is often not possible to use a physical environment, and creating hig...
Chapter
By using communication between multiple agents in multi-agent environments, one can reduce the effects of partial observability by combining one agent’s observation with that of others in the same dynamic environment. While a lot of successful research has been done towards communication learning in cooperative settings, communication learning in m...
Article
Full-text available
Topological data analysis is a recent and fast growing field that approaches the analysis of datasets using techniques from (algebraic) topology. Its main tool, persistent homology (PH), has seen a notable increase in applications in the last decade. Often cited as the most favourable property of PH and the main reason for practical success are the...
Preprint
Full-text available
In this paper, we study and present a management and orchestration framework for vehicular communications, which enables service continuity for the vehicle via an optimized application-context relocation approach. To optimize the transfer of the application-context for Connected and Automated Mobility (CAM) services, our MEC orchestrator performs p...
Chapter
Embodied AI, learning through interaction with a physical environment, typically requires large amounts of interaction with the environment in order to learn how to solve new tasks. Training can be done in parallel, using simulated environments. However, once deployed in e.g., a real-world setting, it is not yet clear how an agent can quickly adapt...
Article
Indoor temperature modeling is a crucial part towards efficient Heating, Ventilation and Air Conditioning (HVAC) systems. Data-driven black-box approaches have been an attractive way to develop such models due to their unique feature of not requiring detailed knowledge about the target zone. However, the noisy and non-linear nature of the problem r...
Article
Full-text available
While IEEE 802.15.4e Time-Slotted Channel Hopping (TSCH) networks should be equipped to deal with the hard wireless challenges of industrial environments, the sensor networks are often still limited by the characteristics of the used physical (PHY) layer. Therefore, the TSCH community has recently started shifting research efforts to the support of...
Article
Full-text available
Batteryless Internet-of-Things (IoT) devices need to schedule tasks on very limited energy budgets from intermittent energy harvesting. Creating an energy-aware scheduler allows the device to schedule tasks in an efficient manner to avoid power loss during execution. To achieve this, we need insight in the Worst-Case Energy Consumption (WCEC) of ea...
Article
Full-text available
IEEE 802.11 (Wi-Fi) is one of the technologies that provides high performance with a high density of connected devices to support emerging demanding services, such as virtual and augmented reality. However, in highly dense deployments, Wi-Fi performance is severely affected by interference. This problem is even worse in new standards, such as 802.1...
Article
Full-text available
This paper presents the first comprehensive tutorial on a promising research field located at the frontier of two well-established domains, neurosciences and wireless communications, motivated by the ongoing efforts to define the (). In particular, this tutorial first provides a novel integrative approach that bridges the gap between these two seem...
Article
Full-text available
We propose a spiking neural network (SNN) approach for radar-based hand gesture recognition (HGR), using frequency modulated continuous wave (FMCW) millimeter-wave radar. After pre-processing the range-Doppler or micro-Doppler radar signal, we use a signal-to-spike conversion scheme that encodes radar Doppler maps into spike trains. The spike train...
Conference Paper
Full-text available
In this paper, we study and present a management and orchestration framework for vehicular communications, which enables service continuity for the vehicle via an optimized application-context relocation approach. To optimize the transfer of the application-context for Connected and Automated Mobility (CAM) services, our MEC orchestrator performs p...
Article
Full-text available
With the emergence of 5G networks and the stringent Quality of Service (QoS) requirements of Mission-Critical Applications (MCAs), co-existing networks are expected to deliver higher-speed connections, enhanced reliability, and lower latency. IEEE 802.11 networks, which co-exist with 5G, continue to be the access choice for indoor networks. However...
Article
Full-text available
The numerous applications of industrial automation have always posed many challenges for wireless connectivity. In the last decade, IEEE 802.15.4e Time-Slotted Channel Hopping (TSCH) networks have provided high reliability and low-power operation in such challenging industrial environments. Typically, TSCH networks employ one modulation at the phys...
Chapter
Predicting cycling race results has always been a task left to experts with a lot of domain knowledge. This is largely due to the fact that the outcomes of cycling races can be rather surprising and depend on an extensive set of parameters. Examples of such factors are, among others, the preparedness of a rider, the weather, the team strategy, and...
Article
Full-text available
This paper presents the first comprehensive tutorial on a promising research field located at the frontier of two well-established domains: Neurosciences and wireless communications , motivated by the ongoing efforts to define how the sixth generation of mobile networks (6G) will be. In particular, this tutorial first provides a novel integrative a...
Conference Paper
Recently, the operation of LTE in unlicensed bands has been proposed to cope with the ever-increasing mobile traffic demand. However, the deployment of LTE in such bands implies sharing spectrum with mature technologies such as Wi-Fi. Several studies have discussed this coexistence problem by suggesting that LTE implements different adaptation mech...
Article
Full-text available
Wireless network technologies are becoming more and more popular. Because of this, important parts of the wireless spectrum become overloaded. Static spectrum allocation, which has been the norm for decades, is not suitable anymore. To maintain the high demand for spectrum and the continuous development of new wireless technologies, there is a need...
Article
Full-text available
Wireless network technologies are becoming more and more popular. Because of this, important parts of the wireless spectrum become overloaded. Static spectrum allocation, which has been the norm for decades, is not suitable anymore. To maintain the high demand for spectrum and the continuous development of new wireless technologies, there is a need...
Article
Full-text available
Today’s and tomorrow’s networks are becoming increasingly complex and heterogeneous with a large diversity of devices and technologies. To meet growing demand, and support client mobility there is need for intelligent mechanisms like multi-technology load balancing and handovers. Current solutions, like Multipath Transmission Control Protocol (MPTC...
Article
Full-text available
Since the early days of wireless communication, wireless spectrum has been allocated according to a static frequency plan, whereby most of the spectrum is licensed for exclusive use by specific services or radio technologies. While some spectrum bands are overcrowded, many other bands are heavily underutilized. As a result, there is a shortage of a...
Preprint
Building Reinforcement Learning (RL) algorithms which are able to adapt to continuously evolving tasks is an open research challenge. One technology that is known to inherently handle such non-stationary input patterns well is Hierarchical Temporal Memory (HTM), a general and biologically plausible computational model for the human neocortex. As th...
Conference Paper
The synergy of 5G and Multi-access Edge Computing (MEC) technologies brings significant benefits to vehicular networks nowadays, providing means for achieving enhanced Quality of Service (QoS), and Quality of Experience (QoE) of wide variety of vehicular applications. Although beneficial in terms of latency reduction, the edge of the architecture f...
Conference Paper
Full-text available
Industrial Internet of Things (IoT) calls for not only highly reliable, quasi-deterministic and low-power networks, but also for more flexible and programmable networks to cope with operator's dynamics demands. Software Defined Networking (SDN) offers the high levels of flexibility and programmability that traditional distributed protocols cannot o...
Article
Recently, network services are increasingly connecting computational elements within and across datacenters. In the Network Functions Virtualization (NFV) environment, to successfully orchestrate a network service, first a VNF-Forwarding Graph (VNF-FG) must be composed that realizes the required functionality. Second, this VNF-FG must be embedded o...
Article
Full-text available
As the number of devices connected to the internet and the amount of data they generate increases, the wireless spectrum is becoming an essential and scarce resource. Most connected devices use wireless technologies that use the industrial, scientific, and medical (ISM) radio bands. As a result, different technologies are interfering with each othe...
Preprint
Full-text available
This paper presents the first comprehensive tutorial on a promising research field located at the frontier of two well-established domains: Neurosciences and wireless communications, motivated by the ongoing efforts to define how the sixth generation of mobile networks (6G) will be. In particular, this tutorial first provides a novel integrative ap...
Article
In this letter, we propose an airtime-based RA model for network slicing in IEEE 802.11 RAN. We formulate this problem as a QCQP, where the overall queueing delay of the system is minimized while strict URLLC constraints are respected. We evaluated our model using three different solvers where the optimal and feasible sets of airtime configurations...
Conference Paper
Full-text available
Low-power wireless mesh networks provide connectivity for a wide range of applications in industrial scenarios. For many years, IEEE 802.15.4e Time-Slotted Channel Hopping (TSCH) networks have proven their efficiency in such environments, providing high reliability and low-power operation. TSCH networks run on top of one physical (PHY) layer and ar...