Zobrazeno 1 - 10
of 56
pro vyhledávání: '"Mancenido, Michelle"'
To enhance the generalization of machine learning models to unseen data, techniques such as dropout, weight decay ($L_2$ regularization), and noise augmentation are commonly employed. While regularization methods (i.e., dropout and weight decay) are
Externí odkaz:
http://arxiv.org/abs/2410.14602
As machine learning models continue to swiftly advance, calibrating their performance has become a major concern prior to practical and widespread implementation. Most existing calibration methods often negatively impact model accuracy due to the lac
Externí odkaz:
http://arxiv.org/abs/2410.10864
As crowdsourcing emerges as an efficient and cost-effective method for obtaining labels for machine learning datasets, it is important to assess the quality of crowd-provided data, so as to improve analysis performance and reduce biases in subsequent
Externí odkaz:
http://arxiv.org/abs/2404.17582
Maps are crucial in conveying geospatial data in diverse contexts such as news and scientific reports. This research, utilizing thematic maps, probes deeper into the underexplored intersection of text framing and map types in influencing map interpre
Externí odkaz:
http://arxiv.org/abs/2403.08260
Autor:
Kim, Nayoung, Cohen, Myke C., Ba, Yang, Pan, Anna, Bhatti, Shawaiz, Salehi, Pouria, Sung, James, Blasch, Erik, Mancenido, Michelle V., Chiou, Erin K.
Designing for AI trustworthiness is challenging, with a lack of practical guidance despite extensive literature on trust. The Multisource AI Scorecard Table (MAST), a checklist rating system, addresses this gap in designing and evaluating AI-enabled
Externí odkaz:
http://arxiv.org/abs/2401.13850
Publikováno v:
ASONAM 2024
The abundance of social media data has presented opportunities for accurately determining public and group-specific stances around policy proposals or controversial topics. In contrast with sentiment analysis which focuses on identifying prevailing e
Externí odkaz:
http://arxiv.org/abs/2309.15176
With social media being a major force in information consumption, accelerated propagation of fake news has presented new challenges for platforms to distinguish between legitimate and fake news. Effective fake news detection is a non-trivial task due
Externí odkaz:
http://arxiv.org/abs/2202.08159
Neural network-based embeddings have been the mainstream approach for creating a vector representation of the text to capture lexical and semantic similarities and dissimilarities. In general, existing encoding methods dismiss the punctuation as insi
Externí odkaz:
http://arxiv.org/abs/2101.03029
Face images are rich data items that are useful and can easily be collected in many applications, such as in 1-to-1 face verification tasks in the domain of security and surveillance systems. Multiple methods have been proposed to protect an individu
Externí odkaz:
http://arxiv.org/abs/2009.14376
Autor:
De Alcaraz-Fossoul, Josep, Wang, Yue, Liu, Ruoqian, Mancenido, Michelle, Marshall, Pamela Ann, Núñez, Celeste, Broatch, Jennifer, Ferry, Lara
Publikováno v:
In Forensic Science International: Genetics July 2023 65
