Transforming tabular data into images via enhanced spatial relationships for CNN processing by Hameedah A. Alenizy, Jawad Berri

“…This paper introduces an original approach that transforms tabular data into a format suitable for CNN processing. …”
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Automation of Tabular Application Formation by S. V. Zykin

Subjects: “…tabular applications…”
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Research on Fine-Tuning Optimization Strategies for Large Language Models in Tabular Data Processing by Xiaoyong Zhao, Xingxin Leng, Lei Wang, Ningning Wang

“…Despite their impressive performance across various language tasks, these models still encounter challenges when processing tabular data. This study investigates the optimization of fine-tuning strategies for LLMs specifically in the context of tabular data processing. …”
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Advanced solar radiation prediction using combined satellite imagery and tabular data processing by Mohammed Attya, O. M. Abo-Seida, H. M. Abdulkader, Amgad M. Mohammed

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SynC2S: An Efficient Method for Synthesizing Tabular Data With a Learnable Pre-Processing by Jiwoo Kim, Seri Park, Junsung Koh, Dongha Kim

“…In this study, we propose an efficient and theoretically principled method based on a deep generative model to effectively generate high-quality synthetic tabular data. First, we introduce a novel technique called C2Smap–a learnable pre-processing method that automatically transforms continuous distributions into simpler and easily generatable forms. …”
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From Tables to Computer Vision: Transforming HPDC Process Data into Images for CNN-Based Deep Learning by A. Burzyńska

“…The proposed study is founded on two principal pillars: the transformation of process tabular data (generated using the Conditional Tabular Generative Adversarial Network (CTGAN)), involving the mapping of features onto a fixed grid in a heatmap structure, and the configuration of the CNN algorithm to extract complex patterns in the data that are not readily apparent in the original tabular format. …”
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TabMoE: A General Framework for Diverse Table-Based Reasoning with Mixture-of-Experts by Jie Wu, Mengshu Hou

Subjects: “…tabular data…”
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PROCESS RENOVATION: CASE STUDY OF A LIQUIDITY PLANNING PROCESS OF THE NATIONAL BUDGET IN SLOVENIA by Marjeta Horjak, Anja Gartner

“…Theoretical findings are presented for the case study of the liquidity planning process of the national budget. They present the renovation process and the effects of the improvements achieved using the Object-Oriented Method (TAD) approach, which is based on a tabular representation, and the Aris method for the graphic depiction of the model of the business process flow based on the BPMN standard for business process modelling. …”
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Towards automated detection of adversarial attacks on tabular data by Piotr Biczyk, Łukasz Wawrowski

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Investigating imperceptibility of adversarial attacks on tabular data: An empirical analysis by Zhipeng He, Chun Ouyang, Laith Alzubaidi, Alistair Barros, Catarina Moreira

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Scoring System for Quantifying the Privacy in Re-Identification of Tabular Datasets by Jakob Folz, Manjitha D. Vidanalage, Robert Aufschlager, Amar Almaini, Michael Heigl, Dalibor Fiala, Martin Schramm

“…However, correlation-only and uniformity-only risk required significantly more processing time, while Markov Model risk incurred the highest computational cost. …”
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DEVELOPMENT OF TABULAR METHOD FOR CALCULATION OF PRIMITIVE FUNCTION IN MODULAR CODE by Vitaly V. Grankin

“…The item dwells on the solution for tabular calculation of primitive function in modular code, both in view of hardware costs and in view of the processing speed.…”
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A Comparison of AutoML Hyperparameter Optimization Tools For Tabular Data by Prativa Pokhrel, Alina Lazar

“…The performance of machine learning (ML) methods for classification and regression tasks applied to tabular datasets is sensitive to hyperparameters values. …”
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Enhancing RAG Performance by Representing Hierarchical Nodes in Headers for Tabular Data by Minchae Song

“…This study introduced hierarchical node-based header representation models designed to enhance the processing and integration of external table data, addressing the key limitations of existing RAG techniques when working with structured table sources. …”
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Counterfactual and Prototypical Explanations for Tabular Data via Interpretable Latent Space by Simone Piaggesi, Francesco Bodria, Riccardo Guidotti, Fosca Giannotti, Dino Pedreschi

“…However, with increased performance has come an increase in the complexity of the black-box models adopted by the AI systems, making them entirely obscure for the decision process adopted. Explainable AI is a field that seeks to make AI decisions more transparent by producing explanations. …”
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GlassBoost: A Lightweight and Explainable Classification Framework for Tabular Datasets by Ehsan Namjoo, Alison N. O’Connor, Jim Buckley, Conor Ryan

“…This model compression yields a transparent, IF–THEN rule-based decision process that remains faithful to the original high-performing model. …”
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Inflationary Processes in Russia Amid the COVID-19 Pandemic by Dz. I. Ramazanov, E. Yu. Onopyuk

“…The article examines inflationary processes in Russia and the impact of the coronavirus recession on them. …”
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Implementation of flexible DEA structure in the management of business processes by Šegrt Slobodan, Tomić Radoljub, Anđelković Maja

“…The research results in this paper are presented in tabular and graphical form.…”
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Application of Markov processes for analysis and control of aircraft maintainability by Yu. M. Chinyuchin, A. S. Solov'ev

“…The process of aircraft operation involves constant effects of various factors on its components leading to accidental or systematic changes in their technical condition. …”
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Bridging the Gap Between Tabular Information Requirements and the Information Delivery Specification (IDS) by Simon Fischer, Harald Urban, Christian Schranz, Gerhard Zucker

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