3 Search Results for "Ayala, José Luis"

Document
Vision
DOI: 10.4230/TGDK.1.1.8
Machine Learning and Knowledge Graphs: Existing Gaps and Future Research Challenges

Authors: Claudia d'Amato, Louis Mahon, Pierre Monnin, and Giorgos Stamou

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
The graph model is nowadays largely adopted to model a wide range of knowledge and data, spanning from social networks to knowledge graphs (KGs), representing a successful paradigm of how symbolic and transparent AI can scale on the World Wide Web. However, due to their unprecedented volume, they are generally tackled by Machine Learning (ML) and mostly numeric based methods such as graph embedding models (KGE) and deep neural networks (DNNs). The latter methods have been proved lately very efficient, leading the current AI spring. In this vision paper, we introduce some of the main existing methods for combining KGs and ML, divided into two categories: those using ML to improve KGs, and those using KGs to improve results on ML tasks. From this introduction, we highlight research gaps and perspectives that we deem promising and currently under-explored for the involved research communities, spanning from KG support for LLM prompting, integration of KG semantics in ML models to symbol-based methods, interpretability of ML models, and the need for improved benchmark datasets. In our opinion, such perspectives are stepping stones in an ultimate view of KGs as central assets for neuro-symbolic and explainable AI.
Cite as

Claudia d'Amato, Louis Mahon, Pierre Monnin, and Giorgos Stamou. Machine Learning and Knowledge Graphs: Existing Gaps and Future Research Challenges. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 8:1-8:35, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{damato_et_al:TGDK.1.1.8,
  author =	{d'Amato, Claudia and Mahon, Louis and Monnin, Pierre and Stamou, Giorgos},
  title =	{{Machine Learning and Knowledge Graphs: Existing Gaps and Future Research Challenges}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{8:1--8:35},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.8},
  URN =		{urn:nbn:de:0030-drops-194824},
  doi =		{10.4230/TGDK.1.1.8},
  annote =	{Keywords: Graph-based Learning, Knowledge Graph Embeddings, Large Language Models, Explainable AI, Knowledge Graph Completion \& Curation}
}
Document
DOI: 10.4230/DagSemProc.07041.11
Thermal Characterization and Thermal Management in Processor-Based Systems

Authors: José Luis Ayala, Anya Apavatjrut, David Atienza, Marisa López-Vallejo, and Carlos A. López-Barrio

Published in: Dagstuhl Seminar Proceedings, Volume 7041, Power-aware Computing Systems (2007)

Abstract
The register file is one of the hottest devices in processor-based systems. Leakage reduction techniques and DTM mechanisms require a thermal characterization of the hardware. This paper presents a thermal model to analyze the temperature evolution in the shared register files found on VLIW systems. The use of this model allows the analysis of several factors that have an strong impact on the heat transfer. The results obtained can be used in the design of temperature-aware compilers and place&route tools.
Cite as

José Luis Ayala, Anya Apavatjrut, David Atienza, Marisa López-Vallejo, and Carlos A. López-Barrio. Thermal Characterization and Thermal Management in Processor-Based Systems. In Power-aware Computing Systems. Dagstuhl Seminar Proceedings, Volume 7041, pp. 1-10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)

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@InProceedings{ayala_et_al:DagSemProc.07041.11,
  author =	{Ayala, Jos\'{e} Luis and Apavatjrut, Anya and Atienza, David and L\'{o}pez-Vallejo, Marisa and L\'{o}pez-Barrio, Carlos A.},
  title =	{{Thermal Characterization and Thermal Management in Processor-Based Systems}},
  booktitle =	{Power-aware Computing Systems},
  pages =	{1--10},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{7041},
  editor =	{Luca Benini and Naehyuck Chang and Ulrich Kremer and Christian W. Probst},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.07041.11},
  URN =		{urn:nbn:de:0030-drops-11103},
  doi =		{10.4230/DagSemProc.07041.11},
  annote =	{Keywords: Thermal characterization, thermal model, register file}
}
Document
DOI: 10.4230/DagSemProc.05141.4
Compiler-Driven Power Optimizations in the Register File of Processor-Based Systems

Authors: José Luis Ayala and Marisa Lópes-Vallejo

Published in: Dagstuhl Seminar Proceedings, Volume 5141, Power-aware Computing Systems (2005)

Abstract
The complexity of the register file is currently one of the main factors on determining the cycle time of high performance wide-issue microprocessors due to its access time and size. Both parameters are directly related to the number of read and write ports of the register file and can be managed from a code compilation-level. Therefore, it is a priority goal to reduce this complexity in order to allow the efficient implementation of complex superscalar machines. This work presents a modified register assignment and a banked architecture which efficiently reduce the number of required ports. Also, the effect of the loop unrollling optimization performed by the compiler is analyzed and several power-efficient modifications to this mechanism are proposed. Both register assignment and loop unrolling mechanisms are modified to improve the energy savings while avoiding a hard performance impact.
Cite as

José Luis Ayala and Marisa Lópes-Vallejo. Compiler-Driven Power Optimizations in the Register File of Processor-Based Systems. In Power-aware Computing Systems. Dagstuhl Seminar Proceedings, Volume 5141, pp. 1-17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2005)

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@InProceedings{ayala_et_al:DagSemProc.05141.4,
  author =	{Ayala, Jos\'{e} Luis and L\'{o}pes-Vallejo, Marisa},
  title =	{{Compiler-Driven Power Optimizations in the Register File of Processor-Based Systems}},
  booktitle =	{Power-aware Computing Systems},
  pages =	{1--17},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2005},
  volume =	{5141},
  editor =	{Luca Benini and Ulrich Kremer and Christian W. Probst and Peter Schelkens},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.05141.4},
  URN =		{urn:nbn:de:0030-drops-3053},
  doi =		{10.4230/DagSemProc.05141.4},
  annote =	{Keywords: Register file, power reduction, compiler optimization, loop unrolling, banked architecture}
}
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