Results 11 to 20 of about 1,865,545 (267)
Encoding Prior Knowledge with Eigenword Embeddings [PDF]
Transactions of the Association for Computational Linguistics, 2021 Canonical correlation analysis (CCA) is a method for reducing the dimension of data represented using two views. It has been previously used to derive word embeddings, where one view indicates a word, and the other view indicates its context. We describe a way to incorporate prior knowledge into CCA, give a theoretical justification for it, and test ...
Dominique Osborne +2 more
doaj +5 more sources
CoRR, 2021 Humans and animals have a natural ability to quickly adapt to their surroundings, but machine-learning models, when subjected to changes, often require a complete retraining from scratch. We present Knowledge-adaptation priors (K-priors) to reduce the cost of retraining by enabling quick and accurate adaptation for a wide-variety of tasks and models ...
Mohammad Emtiyaz Khan, Siddharth Swaroop
openaire +4 more sources
Adapting prior knowledge activation: Mobilisation, perspective taking, and learners’ prior knowledge [PDF]
Computers in Human Behavior, 2011 This study investigates the effects of two prior knowledge activation strategies, namely, mobilisation and perspective taking, on learning. It is hypothesised that the effectiveness of these strategies is influenced by learners' prior domain knowledge.
Sandra A. J. Wetzels +2 more
openaire +2 more sources
Prior Knowledge for Part Correspondence [PDF]
Computer Graphics Forum, 2011 AbstractClassical approaches to shape correspondence base their computation purely on the properties, in particular geometric similarity, of the shapes in question. Their performance still falls far short of that of humans in challenging cases where corresponding shape parts may differ significantly in geometry or even topology.
Oliver van Kaick +6 more
openaire +2 more sources
Memory, Novelty and Prior Knowledge [PDF]
Trends in Neurosciences, 2018 Over the 40 years that TINS has been in existence, there has been substantial progress in understanding the types, organisation, and neural mechanisms of memory. The selectivity of memory maintenance and retention remains a puzzle, and we here summarise two contributions of our own research to this enigma: the striking impact of the novelty and ...
Fernandez, G.S.E. +2 more
openaire +2 more sources
Prior knowledge and exemplar frequency [PDF]
Memory & Cognition, 2008 New concepts can be learned by statistical associations, as well as by relevant existing knowledge. We examined the interaction of these two processes by manipulating exemplar frequency and thematic knowledge and considering their interaction through computational modeling. Exemplar frequency affects category learning, with high-frequency items learned
Harlan D, Harris +2 more
openaire +2 more sources
Incorporation of prior knowledge and habits while solving anagrams
Journal of Eye Movement Research, 2022 Games and puzzles provide a valuable context for examining human problem- solving behavior. We recorded and analyzed the sequence of letters viewed by the participants of our study while they were solving anagram puzzles. The goal was to examine and
Jesse Murray +4 more
doaj +1 more source
Activating students’ prior knowledge of basic science concepts on animal and human system organ
Biosfer, 2020 This study aimed to analyze students' prior knowledge of basic science subjects, especially in organ systems concepts in animals and humans. This research was conducted on the lecture of Basic Science toward 46 students in Science Education class.
Mochammad Ahied +3 more
doaj +1 more source
Community Detection with Prior Knowledge [PDF]
Proceedings of the 2013 SIAM International Conference on Data Mining, 2013 The problem of community detection is a challenging one because of the presence of hubs and noisy links, which tend to create highly imbalanced graph clusters. Often, these resulting clusters are not very intuitive and difficult to interpret. With the growing availability of network information, there is a significant amount of prior knowledge ...
Karthik Subbian +3 more
openaire +2 more sources
Frontiers in Physics, 2023 Prohibited item detection in X-ray images is an effective measure to maintain public safety. Recent prohibited item detection methods based on deep learning has achieved impressive performance.
Jinwen Chen +4 more
doaj +1 more source