Zobrazeno 1 - 10
of 562
pro vyhledávání: '"Smyth, Barry"'
Autor:
Cunningham, Padraig, Smyth, Barry
There has been some concern about the impact of predatory publishers on scientific research for some time. Recently, publishers that might previously have been considered `predatory' have established their bona fides, at least to the extent that they
Externí odkaz:
http://arxiv.org/abs/2408.10262
Representation learning has emerged as a powerful paradigm for extracting valuable latent features from complex, high-dimensional data. In financial domains, learning informative representations for assets can be used for tasks like sector classifica
Externí odkaz:
http://arxiv.org/abs/2407.18645
In the extensive recommender systems literature, novelty and diversity have been identified as key properties of useful recommendations. However, these properties have received limited attention in the specific sub-field of research paper recommender
Externí odkaz:
http://arxiv.org/abs/2309.14984
The financial domain has proven to be a fertile source of challenging machine learning problems across a variety of tasks including prediction, clustering, and classification. Researchers can access an abundance of time-series data and even modest pe
Externí odkaz:
http://arxiv.org/abs/2305.00245
Autor:
D'Amico, Edoardo, Muhammad, Khalil, Tragos, Elias, Smyth, Barry, Hurley, Neil, Lawlor, Aonghus
Publikováno v:
LNCS,volume 13980, pp 249-263, 2023
Graph Convolutional Networks (GCN) have been recently employed as core component in the construction of recommender system algorithms, interpreting user-item interactions as the edges of a bipartite graph. However, in the absence of side information,
Externí odkaz:
http://arxiv.org/abs/2303.15946
Industry classification schemes provide a taxonomy for segmenting companies based on their business activities. They are relied upon in industry and academia as an integral component of many types of financial and economic analysis. However, even mod
Externí odkaz:
http://arxiv.org/abs/2211.06378
When studying large research corpora, "distant reading" methods are vital to understand the topics and trends in the corresponding research space. In particular, given the recognised benefits of multidisciplinary research, it may be important to map
Externí odkaz:
http://arxiv.org/abs/2203.12504
Identifying meaningful relationships between the price movements of financial assets is a challenging but important problem in a variety of financial applications. However with recent research, particularly those using machine learning and deep learn
Externí odkaz:
http://arxiv.org/abs/2202.08968
Financial forecasting has been an important and active area of machine learning research because of the challenges it presents and the potential rewards that even minor improvements in prediction accuracy or forecasting may entail. Traditionally, fin
Externí odkaz:
http://arxiv.org/abs/2201.01770
Food-choices and eating-habits directly contribute to our long-term health. This makes the food recommender system a potential tool to address the global crisis of obesity and malnutrition. Over the past decade, artificial-intelligence and medical re
Externí odkaz:
http://arxiv.org/abs/2110.07045