D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 32 Citations 4,695 246 World Ranking 7518 National Ranking 210

Overview

What is he best known for?

The fields of study he is best known for:

  • Computer network
  • Artificial intelligence
  • The Internet

Antonio Liotta focuses on Computer network, Quality of experience, Artificial intelligence, Quality of service and Multimedia. His research ties Distributed computing and Computer network together. He works mostly in the field of Quality of experience, limiting it down to topics relating to Service and, in certain cases, Software deployment, System integration, Middleware and Interoperability, as a part of the same area of interest.

His Artificial intelligence study focuses on Deep learning in particular. His work on Boltzmann machine as part of general Deep learning study is frequently linked to Electric power system, bridging the gap between disciplines. His work deals with themes such as Mobile phone, Service quality, Predictive modelling, Resource and Mobile QoS, which intersect with Multimedia.

His most cited work include:

  • On-Line Building Energy Optimization Using Deep Reinforcement Learning (164 citations)
  • Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science (148 citations)
  • An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0 (111 citations)

What are the main themes of his work throughout his whole career to date?

His scientific interests lie mostly in Computer network, Artificial intelligence, Distributed computing, Multimedia and Quality of experience. His Computer network research is multidisciplinary, incorporating perspectives in Wireless and The Internet. Antonio Liotta studies Deep learning which is a part of Artificial intelligence.

His Deep learning research integrates issues from Artificial neural network and Reinforcement learning. His Distributed computing research includes themes of Scalability, Key, Mobile computing and Network monitoring. The study incorporates disciplines such as Packet loss, Video quality, Subjective video quality and Service in addition to Quality of experience.

He most often published in these fields:

  • Computer network (28.17%)
  • Artificial intelligence (19.50%)
  • Distributed computing (17.65%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (19.50%)
  • Deep learning (9.60%)
  • Computer network (28.17%)

In recent papers he was focusing on the following fields of study:

His primary areas of investigation include Artificial intelligence, Deep learning, Computer network, Data mining and Anomaly detection. Antonio Liotta is interested in Artificial neural network, which is a field of Artificial intelligence. His work is dedicated to discovering how Deep learning, Reinforcement learning are connected with Supervised learning and other disciplines.

The various areas that he examines in his Computer network study include Jitter and Cluster analysis. Antonio Liotta interconnects Latency, Quality of experience, Multimedia, Throughput and Transmission delay in the investigation of issues within Jitter. His research in Cluster analysis focuses on subjects like Discriminative model, which are connected to Node.

Between 2018 and 2021, his most popular works were:

  • On-Line Building Energy Optimization Using Deep Reinforcement Learning (164 citations)
  • An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0 (111 citations)
  • Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks (33 citations)

In his most recent research, the most cited papers focused on:

  • Computer network
  • Artificial intelligence
  • The Internet

Antonio Liotta mainly investigates Artificial intelligence, Wireless sensor network, Computer network, Key and Software deployment. His work in the fields of Artificial intelligence, such as Deep learning, Image restoration and Image formation, overlaps with other areas such as Underwater. His study in Deep learning is interdisciplinary in nature, drawing from both Synthetic aperture radar and Industrial engineering.

His Wireless sensor network research incorporates elements of Real-time computing, Enhanced Data Rates for GSM Evolution and Edit distance. As part of his studies on Computer network, Antonio Liotta frequently links adjacent subjects like Service provider. As a member of one scientific family, Antonio Liotta mostly works in the field of Software deployment, focusing on World population and, on occasion, Computer security.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science

Decebal Constantin Mocanu;Elena Mocanu;Peter Stone;Phuong H. Nguyen.
Nature Communications (2018)

232 Citations

On-Line Building Energy Optimization Using Deep Reinforcement Learning

Elena Mocanu;Decebal Constantin Mocanu;Phuong H. Nguyen;Antonio Liotta.
IEEE Transactions on Smart Grid (2019)

199 Citations

An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0

Pasquale Pace;Gianluca Aloi;Raffaele Gravina;Giuseppe Caliciuri.
IEEE Transactions on Industrial Informatics (2019)

160 Citations

On management technologies and the potential of Web services

G. Pavlou;P. Flegkas;S. Gouveris;A. Liotta.
IEEE Communications Magazine (2004)

153 Citations

QoE-aware QoS management

Florence Agboma;Antonio Liotta.
advances in mobile multimedia (2008)

147 Citations

Predicting quality of experience in multimedia streaming

Vlado Menkovski;Adetola Oredope;Antonio Liotta;Antonio Cuadra Sánchez.
advances in mobile multimedia (2009)

121 Citations

An adaptive multi-constraint partitioning algorithm for offloading in pervasive systems

S. Ou;K. Yang;A. Liotta.
ieee international conference on pervasive computing and communications (2006)

118 Citations

Exploiting agent mobility for large-scale network monitoring

A. Liotta;G. Pavlou;G. Knight.
IEEE Network (2002)

109 Citations

Stable clustering through mobility prediction for large-scale multihop intelligent ad hoc networks

S. Sivavakeesar;G. Pavlou;A. Liotta.
wireless communications and networking conference (2004)

105 Citations

Towards Multi-layer Interoperability of Heterogeneous IoT Platforms: The INTER-IoT Approach

Giancarlo Fortino;Claudio Savaglio;Carlos E. Palau;Jara Suarez de Puga.
the internet of things (2018)

100 Citations

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Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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