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Position Score Weighting Technique for Mining Web Content Outliers
, 2013 Wan Rusila Wan Zulkifeli +2 more
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Variability in gastrointestinal multiplex PCR panel ordering in urgent care: a potential diagnostic stewardship target. [PDF]
Microbiol SpectrJenkins TC +7 more
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Proceedings of the International Conference on Artificial Intelligence, Information Processing and Cloud Computing, 2019
Outlier detection is a fundamental issue in data mining and machine learning. Most methods calculate outlier score for each object and then threshold the scores to detect outliers. Most widely used thresholding techniques are based on statistics like standard deviation around mean, median absolute deviation and interquartile range. Unfortunately, these
Jiawei Yang +2 more
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Outlier detection is a fundamental issue in data mining and machine learning. Most methods calculate outlier score for each object and then threshold the scores to detect outliers. Most widely used thresholding techniques are based on statistics like standard deviation around mean, median absolute deviation and interquartile range. Unfortunately, these
Jiawei Yang +2 more
openaire +2 more sources
A critical overview of outlier detection methods
Computer Science Review, 2020A. Smiti
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Outlier and influence diagnostics for meta-analysis
Research Synthesis Methods, 2010Wolfgang Viechtbauer, Mike W-L Cheung
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On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study
Data Mining and Knowledge Discovery, 2016Arthur Zimek +2 more
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A comparative evaluation of outlier detection algorithms: Experiments and analyses
Pattern Recognition, 2018Rémi Domingues, Maurizio Filippone
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QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs
Neural Information Processing SystemsWe introduce QuaRot, a new Quantization scheme based on Rotations, which is able to quantize LLMs end-to-end, including all weights, activations, and KV cache in 4 bits.
Saleh Ashkboos +8 more
semanticscholar +1 more source