Results 31 to 40 of about 6,753,811 (352)
Triplet Loss Network for Unsupervised Domain Adaptation
Algorithms, 2019 Domain adaptation is a sub-field of transfer learning that aims at bridging the dissimilarity gap between different domains by transferring and re-using the knowledge obtained in the source domain to the target domain.
Imad Eddine Ibrahim Bekkouch +4 more
doaj +1 more source
Jurnal Sistem Informasi, 2015 In supporting the implementation of ICT service management, Pusat Sistem Informasi dan Teknologi Keuangan (Pusintek) already have the Sistem Pengelolaan Layanan Teknologi Informasi dan Komunikasi (Sipelantik) application.
Andrianto Susilo +2 more
doaj +3 more sources
Metaheuristics for the Minimum Time Cut Path Problem with Different Cutting and Sliding Speeds
Algorithms, 2021 The problem of efficiently cutting smaller two-dimensional pieces from a larger surface is recurrent in several manufacturing settings. This problem belongs to the domain of cutting and packing (C&P) problems.
Bonfim Amaro Junior +4 more
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Involvement of NRF2 in Breast Cancer and Possible Therapeutical Role of Polyphenols and Melatonin
Molecules, 2021 Oxidative stress is defined as a disturbance in the prooxidant/antioxidant balance in favor of the former and a loss of control over redox signaling processes, leading to potential biomolecular damage.
Alev Tascioglu Aliyev +4 more
doaj +1 more source
Representation of probabilistic scientific knowledge [PDF]
Journal of Biomedical Semantics, 2013 The theory of probability is widely used in biomedical research for data analysis and modelling. In previous work the probabilities of the research hypotheses have been recorded as experimental metadata. The ontology HELO is designed to support probabilistic reasoning, and provides semantic descriptors for reporting on research that involves operations
Soldatova, LN +3 more
openaire +6 more sources
KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation [PDF]
Transactions of the Association for Computational Linguistics, 2019 Pre-trained language representation models (PLMs) cannot well capture factual knowledge from text. In contrast, knowledge embedding (KE) methods can effectively represent the relational facts in knowledge graphs (KGs) with informative entity embeddings ...
Xiaozhi Wang +5 more
semanticscholar +1 more source
, 1997 How do people know as much as they do with as little information as they get? The problem takes many forms; learning vocabulary from text is an especially dramatic and convenient case for research.
T. Landauer, S. Dumais
semanticscholar +1 more source
Representation Learning of Knowledge Graphs via Fine-Grained Relation Description Combinations
IEEE Access, 2019 Knowledge representation learning attempts to represent entities and relations of knowledge graph in a continuous low-dimensional semantic space. However, most of the existing methods such as TransE, TransH, and TransR usually only utilize triples of ...
Ming He, Xiangkun Du, Bo Wang
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Bio-Inspired Approaches to Safety and Security in IoT-Enabled Cyber-Physical Systems
Sensors, 2020 Internet of Things (IoT) and Cyber-Physical Systems (CPS) have profoundly influenced the way individuals and enterprises interact with the world. Although attacks on IoT devices are becoming more commonplace, security metrics often focus on software ...
Anju P. Johnson +2 more
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Leveraging Abstract Meaning Representation for Knowledge Base Question Answering [PDF]
Findings, 2020 Knowledge base question answering (KBQA)is an important task in Natural Language Processing. Existing approaches face significant challenges including complex question understanding, necessity for reasoning, and lack of large end-to-end training datasets.
Pavan Kapanipathi +29 more
semanticscholar +1 more source