Zobrazeno 1 - 10
of 65
pro vyhledávání: '"Cao, Steven"'
While analytics of sleep electroencephalography (EEG) holds certain advantages over other methods in clinical applications, high variability across subjects poses a significant challenge when it comes to deploying machine learning models for classifi
Externí odkaz:
http://arxiv.org/abs/2310.02398
Given only a few observed entries from a low-rank matrix $X$, matrix completion is the problem of imputing the missing entries, and it formalizes a wide range of real-world settings that involve estimating missing data. However, when there are too fe
Externí odkaz:
http://arxiv.org/abs/2306.04049
The dominant approach in probing neural networks for linguistic properties is to train a new shallow multi-layer perceptron (MLP) on top of the model's internal representations. This approach can detect properties encoded in the model, but at the cos
Externí odkaz:
http://arxiv.org/abs/2104.03514
We propose a method for unsupervised parsing based on the linguistic notion of a constituency test. One type of constituency test involves modifying the sentence via some transformation (e.g. replacing the span with a pronoun) and then judging the re
Externí odkaz:
http://arxiv.org/abs/2010.03146
Validating a blockchain incurs heavy computation, communication, and storage costs. As a result, clients with limited resources, called light nodes, cannot verify transactions independently and must trust full nodes, making them vulnerable to securit
Externí odkaz:
http://arxiv.org/abs/2010.00217
We propose procedures for evaluating and strengthening contextual embedding alignment and show that they are useful in analyzing and improving multilingual BERT. In particular, after our proposed alignment procedure, BERT exhibits significantly impro
Externí odkaz:
http://arxiv.org/abs/2002.03518
Autor:
Wei, Hongjiang, Cao, Steven, Zhang, Yuyao, Guan, Xiaojun, Yan, Fuhua, Yeom, Kristen W., Liu, Chunlei
Quantitative susceptibility mapping (QSM) estimates the underlying tissue magnetic susceptibility from MRI gradient-echo phase signal and typically requires several processing steps. These steps involve phase unwrapping, brain volume extraction, back
Externí odkaz:
http://arxiv.org/abs/1905.05953
We show that constituency parsing benefits from unsupervised pre-training across a variety of languages and a range of pre-training conditions. We first compare the benefits of no pre-training, fastText, ELMo, and BERT for English and find that BERT
Externí odkaz:
http://arxiv.org/abs/1812.11760
Autor:
Wakeland-Hart, Cheyenne D., Cao, Steven A., deBettencourt, Megan T., Bainbridge, Wilma A., Rosenberg, Monica D.
Publikováno v:
In Cognition October 2022 227
Autor:
Richard, Erin L., McEvoy, Linda K., Cao, Steven Y., Oren, Eyal, Alcaraz, John E., LaCroix, Andrea Z., Salem, Rany M.
Publikováno v:
In Journal of the Neurological Sciences 15 November 2021 430