Search Results - "Dras, Mark"

Native Language Identification With Classifier Stacking and Ensembles by Malmasi, Shervin, Dras, Mark

“…Ensemble methods using multiple classifiers have proven to be among the most successful approaches for the task of Native Language Identification (NLI),…”
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Using corpora from Natural Language Processing for investigating crosslinguistic influence by Liu, Yitao, Dras, Mark

“…Language transfer or crosslinguistic influence (CLI), referring to the influence of an L1 on the learning of an L2, is a significant aspect of Second Language…”
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Using machine learning to study the effect of medication adherence in Opioid Use Disorder by Warren, David, Marashi, Amir, Siddiqui, Arwa, Eijaz, Asim Adnan, Pradhan, Pooja, Lim, David, Call, Gary, Dras, Mark

“…Opioid Use Disorder (OUD) and opioid overdose (OD) impose huge social and economic burdens on society and health care systems. Research suggests that…”
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Image Captioning using Facial Expression and Attention by Mohamad Nezami, Omid, Dras, Mark, Wan, Stephen, Paris, Cecile

“…Benefiting from advances in machine vision and natural language processing techniques, current image captioning systems are able to generate detailed visual…”
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Identifying Which Relational Cues Users Find Helpful to Allow Tailoring of e-Coach Dialogues by Salman, Sana, Richards, Deborah, Dras, Mark

“…Relational cues are extracts from actual verbal dialogues that help build the therapist–patient working alliance and stronger bond through the depiction of…”
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Trends in Opioid Medication Adherence During the COVID-19 Pandemic: Retrospective Cohort Study by Marashi, Amir, Warren, David, Call, Gary, Dras, Mark

“…Background The recent pandemic had the potential to worsen the opioid crisis through multiple effects on patients’ lives, such as the disruption of care. In…”
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Conversation dynamics in a multiplayer video game with knowledge asymmetry by Simpson, James, Nalepka, Patrick, Kallen, Rachel W, Dras, Mark, Reichle, Erik D, Hosking, Simon G, Best, Christopher, Richards, Deborah, Richardson, Michael J

“…Despite the challenges associated with virtually mediated communication, remote collaboration is a defining characteristic of online multiplayer gaming…”
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Siamese networks for large-scale author identification by Saedi, Chakaveh, Dras, Mark

“…•Deep learning Siamese architectures perform well on author identification.•They can identify texts by previously unseen authors.•There is an unexpected…”
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Pick-Object-Attack: Type-specific adversarial attack for object detection by Mohamad Nezami, Omid, Chaturvedi, Akshay, Dras, Mark, Garain, Utpal

“…Many recent studies have shown that deep neural models are vulnerable to adversarial samples: images with imperceptible perturbations, for example, can fool…”
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Clinical named entity recognition and relation extraction using natural language processing of medical free text: A systematic review by Fraile Navarro, David, Ijaz, Kiran, Rezazadegan, Dana, Rahimi-Ardabili, Hania, Dras, Mark, Coiera, Enrico, Berkovsky, Shlomo

“…•Clinical information extraction tasks have evolved steadily, with machine learning methods and transformer models gaining track recently.•There are few…”
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Deep reinforcement learning guided graph neural networks for brain network analysis by Zhao, Xusheng, Wu, Jia, Peng, Hao, Beheshti, Amin, Monaghan, Jessica J.M., McAlpine, David, Hernandez-Perez, Heivet, Dras, Mark, Dai, Qiong, Li, Yangyang, Yu, Philip S., He, Lifang

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Elemental psychopathology: distilling constituent symptoms and patterns of repetition in the diagnostic criteria of the DSM-5 by Forbes, Miriam K, Neo, Bryan, Nezami, Omid Mohamed, Fried, Eiko I, Faure, Katherine, Michelsen, Brier, Twose, Maddison, Dras, Mark

“…The features hundreds of diagnoses comprising a multitude of symptoms, and there is considerable repetition in the symptoms among diagnoses. This repetition…”
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Predicting Suicidal Behavior Without Asking About Suicidal Ideation: Machine Learning and the Role of Borderline Personality Disorder Criteria by Horvath, Adam, Dras, Mark, Lai, Catie C.W., Boag, Simon

“…Objective Identifying predictors contributing to suicide risk could help prevent suicides via targeted interventions. However, using only known risk factors…”
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Assessing Team Effectiveness by How Players Structure Their Search in a First‐Person Multiplayer Video Game by Nalepka, Patrick, Prants, Matthew, Stening, Hamish, Simpson, James, Kallen, Rachel W., Dras, Mark, Reichle, Erik D., Hosking, Simon G., Best, Christopher, Richardson, Michael J.

“…People working as a team can achieve more than when working alone due to a team's ability to parallelize the completion of tasks. In collaborative search…”
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Gauging situation awareness by the complexity of personnel movement by Nalepka, Patrick, Stening, Hamish, Simpson, James, Kallen, Rachel W., Dras, Mark, Reichle, Erik D., Hosking, Simon G., Best, Christopher, Richardson, Michael J.

“…Ten teams consisted of three team members, who all participated as ground personnel tasked in retrieving the targets, and the remaining ten teams consisted of…”
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What Learned Representations and Influence Functions Can Tell Us About Adversarial Examples by Tonni, Shakila Mahjabin, Dras, Mark

“…Adversarial examples, deliberately crafted using small perturbations to fool deep neural networks, were first studied in image processing and more recently in…”
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Suspiciousness of Adversarial Texts to Human by Tonni, Shakila Mahjabin, Faustini, Pedro, Dras, Mark

“…Adversarial examples pose a significant challenge to deep neural networks (DNNs) across both image and text domains, with the intent to degrade model…”
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Seeing the Forest through the Trees: Data Leakage from Partial Transformer Gradients by Li, Weijun, Xu, Qiongkai, Dras, Mark

“…Recent studies have shown that distributed machine learning is vulnerable to gradient inversion attacks, where private training data can be reconstructed by…”
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Siamese Networks for Large-Scale Author Identification by Saedi, Chakaveh, Dras, Mark

“…Authorship attribution is the process of identifying the author of a text. Approaches to tackling it have been conventionally divided into classification-based…”
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Augmentation of Electronic Medical Record Data for Deep Learning by Kennedy, Georgina, Dras, Mark, Gallego, Blanca

“…Data imbalance is a well-known challenge in the development of machine learning models. This is particularly relevant when the minority class is the class of…”
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