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Metrically conditioned /a/-syncope in Modern Hebrew compounds
In Modern Hebrew, some, but not all, nominals exhibit obligatory /a/-syncope in open syllables if they are antepretonic in a simple (nominal) word....
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Meta-learning for heterogeneous treatment effect estimation with closed-form solvers
This article proposes a meta-learning method for estimating the conditional average treatment effect (CATE) from a few observational data. The...
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Generative adversarial meta-learning knowledge graph completion for large-scale complex knowledge graphs
In the study of large-scale complex knowledge graphs, due to the incompleteness of knowledge and the existence of low-frequency knowledge samples,...
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Leveraging transformers architectures and augmentation for efficient classification of fasteners and natural language searches
A primary concern in the realm of mechanical engineering is to ensure the efficient and effective data entry of hardware devices. Fasteners are...
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Evaluating feature attribution methods in the image domain
Feature attribution maps are a popular approach to highlight the most important pixels in an image for a given prediction of a model. Despite a...
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Advances in information retrieval collection on the European conference on information retrieval 2023
This paper introduces the Collection on ECIR 2023. The 45th European Conference on Information Retrieval (ECIR 2023) was held in Dublin, Ireland,...
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Sports recommender systems: overview and research directions
Sports recommender systems receive an increasing attention due to their potential of fostering healthy living, improving personal well-being, and...
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Language change and the Degree Semantics Parameter
Beck et al. (
2009 ) and much follow-up research (including Bochnak2015 ; Bowler2016 ; Deal and Hohaus2019 ) argue that languages systematically differ...
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Classification with costly features in hierarchical deep sets
Classification with costly features (CwCF) is a classification problem that includes the cost of features in the optimization criteria. Individually...
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Fast computation of General SimRank on heterogeneous information network
Similarity computation is a fundamental aspect of information network analysis, underpinning many research tasks including information retrieval,...
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Aspect sentiment triplet extraction based on data augmentation and task feedback
Aspect sentiment triplet extraction (ASTE), which focuses on mining the triplets (aspect, opinion, sentiment), is a complex and integrated subtask in...
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Navigation method for autonomous mobile robots based on ROS and multi-robot improved Q-learning
Recently, path planning of multi-autonomous mobile robot systems is one of the interesting topics in scientific research due to its complexity and...
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A novel approach for locating and hunting dynamic targets in unknown environments
Hunting a dynamic target that exhibits random and unexpected behavior in an unknown environment poses significant challenges. In this research paper,...
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Graph-based dynamic attribute clip** for conversational recommendation
Conversational recommender systems (CRS) enable traditional recommender systems to interact with users by asking questions about their preferences...
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Potential factors-embedding group recommendation for online education
Online education platform urgently needs recommendation methods to service learning groups. The existing group recommendation methods rely on member...
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Selective ensemble of doubly weighted fuzzy extreme learning machine for tumor classification
Malignant epithelial cell tumor also known as cancer is a deadly disease requiring a very costly and complex treatment. Early and accurate diagnosis...
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CoMadOut—a robust outlier detection algorithm based on CoMAD
Unsupervised learning methods are well established in the area of anomaly detection and achieve state of the art performances on outlier datasets....
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Bcubed revisited: elements like me
BCubed is a mathematically clean, elegant and intuitively well behaved external performance metric for clustering tasks. BCubed compares a predicted...
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Temporal validity reassessment: commonsense reasoning about information obsoleteness
It is useful for machines to know whether text information remains valid or not for various applications including text comprehension, story...
