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1. X-Ray Spectroscopy in the Microcalorimeter Era. III. Line Formation under Case A, Case B, Case C, and Case D in H- and He-like Iron for a Photoionized Cloud

   https://doi.org/10.3847/1538-4357/abed4a  

   Chakraborty, P ; Ferland, G. J. ; Chatzikos, M. ; Guzmán, F. ; Su, Y. ( April 2021 , The Astrophysical Journal)

   null (Ed.)
2. Strengthening Low-resource Neural Machine Translation through Joint Learning: The Case of Farsi-Spanish [Strengthening Low-resource Neural Machine Translation through Joint Learning: The Case of Farsi-Spanish]

   https://doi.org/10.5220/0010362604750481  

   Ahmadnia, Benyamin ; Aranovich, Raul ; Dorr, Bonnie ( January 2021 , Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 1: NLPinAI)

   null (Ed.)

   This paper describes a systematic study of an approach to Farsi-Spanish low-resource Neural Machine Translation (NMT) that leverages monolingual data for joint learning of forward and backward translation models. As is standard for NMT systems, the training process begins using two pre-trained translation models that are iteratively updated by decreasing translation costs. In each iteration, either translation model is used to translate monolingual texts from one language to another, to generate synthetic datasets for the other translation model. Two new translation models are then learned from bilingual data along with the synthetic texts. The key distinguishing feature between our approach and standard NMT is an iterative learning process that improves the performance of both translation models, simultaneously producing a higher-quality synthetic training dataset upon each iteration. Our empirical results demonstrate that this approach outperforms baselines. 

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3. Filling The Gaps in Microservice Frontend Communication: Case for New Frontend Patterns [Filling The Gaps in Microservice Frontend Communication: Case for New Frontend Patterns]

   https://doi.org/10.5220/0011812500003488  

   Abdelfattah, Amr ; Cerny, Tomas ( January 2023 , 13th International Conference on Cloud Computing and Services Science (CLOSER 2023))
4. When Simple Statistical Algorithms Outperform Deep Learning: A Case of Keystroke Dynamics [When Simple Statistical Algorithms Outperform Deep Learning: A Case of Keystroke Dynamics]

   https://doi.org/10.5220/0011684100003411  

   Wahab, Ahmed ; Hou, Daqing ( January 2023 , Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods ICPRAM)

   Keystroke dynamics has gained relevance over the years for its potential in solving practical problems like online fraud and account takeovers. Statistical algorithms such as distance measures have long been a common choice for keystroke authentication due to their simplicity and ease of implementation. However, deep learning has recently started to gain popularity due to their ability to achieve better performance. When should statistical algorithms be preferred over deep learning and vice-versa? To answer this question, we set up experiments to evaluate two state-of-the-art statistical algorithms: Scaled Manhattan and the Instance-based Tail Area Density (ITAD) metric, with a state-of-the-art deep learning model called TypeNet, on three datasets (one small and two large). Our results show that on the small dataset, statistical algorithms significantly outperform the deep learning approach (Equal Error Rate (EER) of 4.3% for Scaled Manhattan / 1.3% for ITAD versus 19.18% for TypeNet ). However, on the two large datasets, the deep learning approach performs better (22.9% & 28.07% for Scaled Manhattan / 12.25% & 20.74% for ITAD versus 0.93% & 6.77% for TypeNet). 

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5. Abstract ergative Case without morphological case

   Drummond, Emily ( December 2022 , Proceedings of NELS)

   Bakay, Özge ; Pratley, Breanna ; Neu, Eva ; Deal, Peyton (Ed.)

   The existence and nature of abstract Case has been debated in recent years (McFadden 2004, Landau 2006, Markman 2009), particularly in languages that show no morphological case marking (Diercks 2012, Sheehan & van der Wal 2016). Using data from original fieldwork, I argue that Nukuoro (Polynesian-Outlier) instantiates abstract ergative Case without morphological case or agreement. Nukuoro shows a range of syntactic phenomena indicative of abstract Case, including object shift and pseudo noun incorporation (e.g., Massam 2001), syntactic ergativity in A'-movement, and alternative licensing in tenseless clauses. This pattern provides support for modern theories of Case (Legate 2008), which cleave the assignment of abstract Case from its realization in the morphology; additionally, this pattern differs from other documented examples of unrealized abstract Case by having an ergative alignment, rather than a nominative one (Halpert 2016, Sheehan & van der Wal 2016). 

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