204 citations · 218 across the 17 of their papers we have counts for
17 papers
Investigating the Influence of Prompt and Response Languages on LLM Content Generation
Thi Thanh Nhan Nguyen, Mai Khoi Tieu, Michael A. Riegler +2
This study examines how prompt and response language influence the behavior of large language models. Using five models, we evaluated answers to 68 non translation questions across…
Energy-Conscious LLM Decoding: Impact of Text Generation Strategies on GPU Energy Consumption
Alireza Nik, Michael A. Riegler, Pål Halvorsen
Decoding strategies significantly influence the quality and diversity of the generated text in Large Language Models (LLMs), yet their impact on computational resources, particular…
DPERC: Direct Parameter Estimation for Mixed Data
Tuan L. Vo, Quan Huu Do, Uyen Dang +4
The covariance matrix is a foundation in numerous statistical and machine-learning applications such as Principle Component Analysis, Correlation Heatmap, etc. However, missing val…
Principal Components for Neural Network Initialization
Nhan Phan, Thu Nguyen, Uyen Dang +2
Principal Component Analysis (PCA) is a commonly used tool for dimension reduction and denoising. Therefore, it is also widely used on the data prior to training a neural network.…
Missing data imputation for noisy time-series data and applications in healthcare
Lien P. Le, Xuan-Hien Nguyen Thi, Thu Nguyen +3
Healthcare time series data is vital for monitoring patient activity but often contains noise and missing values due to various reasons such as sensor errors or data interruptions.…
Comparative Analysis of Audio Feature Extraction for Real-Time Talking Portrait Synthesis
Pegah Salehi, Sajad Amouei Sheshkal, Vajira Thambawita +5
This paper examines the integration of real-time talking-head generation for interviewer training, focusing on overcoming challenges in Audio Feature Extraction (AFE), which often…
Enhancing Structured-Data Retrieval with GraphRAG: Soccer Data Case Study
Zahra Sepasdar, Sushant Gautam, Cise Midoglu +2
Extracting meaningful insights from large and complex datasets poses significant challenges, particularly in ensuring the accuracy and relevance of retrieved information. Tradition…
Explainability of Machine Learning Models under Missing Data
Tuan L. Vo, Thu Nguyen, Luis M. Lopez-Ramos +3
Missing data is a prevalent issue that can significantly impair model performance and explainability. This paper briefly summarizes the development of the field of missing data wit…
Classifying Dry Eye Disease Patients from Healthy Controls Using Machine Learning and Metabolomics Data
Sajad Amouei Sheshkal, Morten Gundersen, Michael Alexander Riegler +3
Dry eye disease is a common disorder of the ocular surface, leading patients to seek eye care. Clinical signs and symptoms are currently used to diagnose dry eye disease. Metabolom…
SoccerNet-Echoes: A Soccer Game Audio Commentary Dataset
Sushant Gautam, Mehdi Houshmand Sarkhoosh, Jan Held +7
The application of Automatic Speech Recognition (ASR) technology in soccer offers numerous opportunities for sports analytics. Specifically, extracting audio commentaries with ASR…
Advancing sleep detection by modelling weak label sets: A novel weakly supervised learning approach
Matthias Boeker, Vajira Thambawita, Michael Riegler +2
Understanding sleep and activity patterns plays a crucial role in physical and mental health. This study introduces a novel approach for sleep detection using weakly supervised lea…
Imputation using training labels and classification via label imputation
Thu Nguyen, Tuan L. Vo, Pål Halvorsen +1
Missing data is a common problem in practical data science settings. Various imputation methods have been developed to deal with missing data. However, even though the labels are a…
GastroVision: A Multi-class Endoscopy Image Dataset for Computer Aided Gastrointestinal Disease Detection
Debesh Jha, Vanshali Sharma, Neethi Dasu +8
Integrating real-time artificial intelligence (AI) systems in clinical practices faces challenges such as scalability and acceptance. These challenges include data availability, bi…
Validating polyp and instrument segmentation methods in colonoscopy through Medico 2020 and MedAI 2021 Challenges
Debesh Jha, Vanshali Sharma, Debapriya Banik +30
Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps. However, detecting polyps durin…
Correlation visualization under missing values: a comparison between imputation and direct parameter estimation methods
Nhat-Hao Pham, Khanh-Linh Vo, Mai Anh Vu +4
Correlation matrix visualization is essential for understanding the relationships between variables in a dataset, but missing data can pose a significant challenge in estimating co…
Understanding metric-related pitfalls in image analysis validation
Annika Reinke, Minu D. Tizabi, Michael Baumgartner +75
Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation int…
Conditional expectation with regularization for missing data imputation
Mai Anh Vu, Thu Nguyen, Tu T. Do +5
Missing data frequently occurs in datasets across various domains, such as medicine, sports, and finance. In many cases, to enable proper and reliable analyses of such data, the mi…