544 citations
- Intel (United States)US7 papers
- University College CorkIE3 papers
- University College DublinIE2 papers
- Association of Electronic and Information TechnologiesES1 paper
- Barcelona Supercomputing CenterES1 paper
- Berlin Institute for the Foundations of Learning and DataDE1 paper
- BOKU UniversityAT1 paper
- Dublin City UniversityIE1 paper
- Fraunhofer Institute for Telecommunications, Heinrich Hertz InstituteDE1 paper
- Free University of Bozen-BolzanoIT1 paper
- Imperial College LondonGB1 paper
- Institut national de recherche en sciences et technologies du numériqueFR1 paper
11 papers
Enhanced chemical vapour deposition of monolayer MoS2 films via a clean promoter
Lulin Wang, Yue Sun, Kaushik Kannan +10
Two-dimensional (2D) transition metal dichalcogenides (TMDCs), exemplified by molybdenum disulfide (MoS2), have shown exceptional potential for data-centred, energy-efficient elect…
Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions
Luca Longo, Mario Brcic, Federico Cabitza +16
As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount. In respo…
PROMPT: Learning Dynamic Resource Allocation Policies for Network Applications
Drew Penney, Bin Li, Jaroslaw Sydir +5
A growing number of service providers are exploring methods to improve server utilization and reduce power consumption by co-scheduling high-priority latency-critical workloads wit…
High-dimensional Convolutional Networks for Geometric Pattern Recognition
Christopher Choy, Junha Lee, Rene Ranftl +2
Many problems in science and engineering can be formulated in terms of geometric patterns in high-dimensional spaces. We present high-dimensional convolutional networks (ConvNets)…
Exploring the Vision Processing Unit as Co-processor for Inference
Sergio Rivas-Gomez, Antonio J. Peña, David Moloney +2
The success of the exascale supercomputer is largely debated to remain dependent on novel breakthroughs in technology that effectively reduce the power consumption and thermal diss…
A Comparison of Reinforcement Learning Techniques for Fuzzy Cloud Auto-Scaling
Hamid Arabnejad, Claus Pahl, Pooyan Jamshidi +1
A goal of cloud service management is to design self-adaptable auto-scaler to react to workload fluctuations and changing the resources assigned. The key problem is how and when to…