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Found 7 papers, 3 papers with code
Semantic Novelty Detection in Natural Language Descriptions
This paper proposes to study a fine-grained semantic novelty detection task, which can be illustrated with the following example.
Zero-Shot Aspect-Based Sentiment Analysis
Aspect-based sentiment analysis (ABSA) typically requires in-domain annotated data for supervised training/fine-tuning.
Minimum Wasserstein Distance Estimator under Finite Location-scale Mixtures
Do we gain anything by learning finite location-scale mixtures via a minimum Wasserstein distance estimator (MWDE)?
Distributed Learning of Finite Gaussian Mixtures
Experiments based on simulated and real-world data show that the proposed split-and-conquer approach has comparable statistical performance with the global estimator based on the full dataset, if the latter is feasible.
A Knowledge-Driven Approach to Classifying Object and Attribute Coreferences in Opinion Mining
Classifying and resolving coreferences of objects (e. g., product names) and attributes (e. g., product aspects) in opinionated reviews is crucial for improving the opinion mining performance.
Gaussian Mixture Reduction with Composite Transportation Divergence
Although existing clustering-based methods are known for their satisfactory performance and computational efficiency, their convergence properties and optimal targets remain unknown.
Consistency of the MLE under mixture models
The large-sample properties of likelihood-based statistical inference under mixture models have received much attention from statisticians.
Statistics Theory Statistics Theory 62F12
