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arXiv 2025年

作者： Shi, Ruxue Wang, Yili Du, Mengnan Shen, Xu Wang, Xin Jilin University Changchun China Department of Data Science New Jersey Institute of Technology Newark United States

Tabular data remains one of the most prevalent and critical data formats across diverse real-world applications. However, its effective use in machine learning (ML) is often constrained by challenges such as data scarcity, privacy concerns, and class imbalance. Synthetic data generation has emerged as a promising solution, leveraging generative models to learn the distribution of real datasets and produce high-fidelity, privacy-preserving samples. Various generative paradigms have been explored, including energy-based models (EBMs), variational autoencoders (VAEs), generative adversarial networks (GANs), large language models (LLMs), and diffusion models. While several surveys have investigated synthetic tabular data generation, most focus on narrow subdomains or specific generative methods, such as GANs, diffusion models, or privacy-preserving techniques. This limited scope often results in fragmented insights, lacking a comprehensive synthesis that bridges diverse approaches. In particular, recent advances driven by LLMs and diffusion-based models remain underexplored. This gap hinders a holistic understanding of the field’s evolution, methodological interplay, and open challenges. To address this, our survey provides a unified and systematic review of synthetic tabular data generation. Our contributions are threefold: (1) we propose a comprehensive taxonomy that organizes existing methods into traditional approaches, diffusion-based methods, and LLM-based models, and provide an in-depth comparative analysis;(2) we detail the complete pipeline for synthetic tabular data generation, including data synthesis, post-processing, and evaluation;(3) we identify major challenges, explore real-world applications, and outline open research questions and future directions to guide future work in this rapidly evolving area. Copyright © 2025, The Authors. All rights reserved.

关键词： Hydrographic surveys

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State Reconstruction: Generating a Reference for Improved Diagnostics

State Reconstruction: Generating a Reference for Improved Di...

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International Conference on Prognostics and Health Management, PHM

作者： Yan Li Navid Zaman Jacek Stecki Chris Stecki Department of data science PHM Technology Melbourne Australia PHM Technology Melbourne Australia

Mechanical systems across most industries are mortal instruments, they will fail due to use or otherwise. Staying ahead of such catastrophes are crucial, especially in mission critical scenarios where loss of life is a very real danger. In such cases, corrective maintenance is too risky and scheduled maintenance is often costly; thus the collective shift towards predictive maintenance. Until recent advancements in artificial intelligence and sensor networks, such a strategy would not be so achievable. The ‘predictive’ aspect of thus type of maintenance implies that anomalies and failures are expected to be forecast ahead of occurrence - this can be accomplished with well placed sensors and sufficiently trained correlation methods. However, aspects such as shifting operating modes and varying sensor ranges make it difficult to make predictions solely using raw sensor data. This paper will outline methods and technologies to estimate healthy states of the monitored system to aid in the detection of failures before they affect function. Mechanical systems across most industries are mortal instruments, they will fail due to use or otherwise. Staying ahead of such catastrophes are crucial, especially in mission critical scenarios where loss of life is a very real danger. In such cases, corrective maintenance is too risky and scheduled maintenance is often costly; thus the collective shift towards predictive maintenance. Until recent advancements in artificial intelligence and sensor networks, such a strategy would not be so achievable. The ‘predictive’ aspect of thus type of maintenance implies that anomalies and failures are expected to be forecast ahead of occurrence - this can be accomplished with well placed sensors and sufficiently trained correlation methods. However, aspects such as shifting operating modes and varying sensor ranges make it difficult to make predictions solely using raw sensor data. This paper will outline methods and technologies to estimate heal

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ExPO: Explainable Phonetic Trait-Oriented Network for Speaker Verification

arXiv

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arXiv 2025年

作者： Ma, Yi Wang, Shuai Liu, Tianchi Li, Haizhou The Department of Electrical and Computer Engineering National University of Singapore 119077 Singapore The Institute for Infocomm Research A*STAR 138632 Singapore Shenzhen Research Institute of Big data School of Data Science The Chinese University of Hong Kong Shenzhen518172 China

In speaker verification, we use computational method to verify if an utterance matches the identity of an enrolled speaker. This task is similar to the manual task of forensic voice comparison, where linguistic analysis is combined with auditory measurements to compare and evaluate voice samples. Despite much success, we have yet to develop a speaker verification system that offers explainable results comparable to those from manual forensic voice comparison. A novel approach, Explainable Phonetic Trait-Oriented (ExPO) network, is proposed in this paper to introduce the speaker’s phonetic trait which describes the speaker’s characteristics at the phonetic level, resembling what forensic comparison does. ExPO not only generates utterance-level speaker embeddings but also allows for fine-grained analysis and visualization of phonetic traits, offering an explainable speaker verification process. Furthermore, we investigate phonetic traits from within-speaker and between-speaker variation perspectives to determine which trait is most effective for speaker verification, marking an important step towards explainable speaker verification. Our code is available at https://***/mmmmayi/ExPO. Copyright © 2025, The Authors. All rights reserved.

关键词： Linguistics

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Guidelines for dopant selection in Cu catalysts to promote the electrochemical CO_(2)reduction reaction for ethylene production

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Journal of Energy Chemistry 2025年第4期103卷 674-681页

作者： Dogyeong Kim Seohyeon Ka Man Ho Han Woong Kim Seung-Ho Yu Jae-Young Choi Keun Hwa Chae Hyung-Suk Oh Woong Hee Lee Clean Energy Research Center Korea Institute of Science and Technology(KIST)Hwarang-ro 14-gil 5Seongbuk-guSeoul 02792Republic of Korea Department of Chemical and Biological Engineering Korea University145Anam-roSeongbuk-guSeoul 02841Republic of Korea Department of Materials Science and Engineering Korea UniversityAnamdong-5-GaSeoul 02841Republic of Korea School of Advanced Materials Science and Engineering Sungkyunkwan University2066Seobu-roJangan-guSuwon-siGyeonggi-do16419Republic of Korea KIST-SKKU Carbon-Neutral Research Center Sungkyunkwan University 2066 Seobu-roJangan-guSuwon 16419Republic of Korea Analysis&Data Center Korea Institute of Science and Technology5 Hwarang-ro 14-gilSeongbuk-guSeoul 02792Republic of Korea Division of Energy and Environmental Technology KIST SchoolKorea University of Science and Technology(UST)Seoul 02792Republic of Korea

To develop an efficient electrochemical CO_(2)reduction reaction(CO_(2)RR)for the production of C_(2)chemicals,improvements in the Cu catalyst are *** is widely used for catalyst enhancement;however,only a few elements have been *** study proposes guidelines for the selection of Cu catalyst dopants to promote ethylene *** was hypothesized that the dopant chemical state highly influences the CO_(2)RR catalytic *** the case of dopants possessing a standard reduction potential within the CO_(2)RR potential region(e.g.,Mn and Ni),low Faradaic efficiency(FE)toward ethylene production was obtained owing to the presence of a metallic dopant(10.7%for Ni dopant).In contrast,a low standard reduction potential led to a stable high oxidation state for the dopant,yielding abundant Cu^(δ+)species with modified electronic structures and enhancing the CO_(2)RR catalytic activity for ethylene production(42.1%for Hf dopant).We expected that a dopant with a low standard reduction potential is difficult to reduce,which leads to a stable Cu-O-X bond and induces a stable Cu^(δ+)*** study provides insights into how to select dopant for various catalyst to enhance CO_(2)RR catalytic activity.

关键词： CO_(2)reduction reaction Catalytic selectivity Dopant Cu species Ethylene production

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Value Identification in Multistakeholder Recommender Systems for Humanities and Historical Research: The Case of the Digital Archive *** 2

Value Identification in Multistakeholder Recommender Systems...

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2nd Workshop on the Normative Design and Evaluation of Recommender Systems, NORMalize 2024

作者： Atzenhofer-Baumgartner, Florian Geiger, Bernhard C. Vogeler, Georg Kowald, Dominik Institute of Interactive Systems and Data Science Graz University of Technology Graz Austria Department of Digital Humanities University of Graz Graz Austria Know Center Research GmbH Graz Austria Signal Processing and Speech Communication Laboratory Graz University of Technology Graz Austria

Recommender systems remain underutilized in humanities and historical research, despite their potential to enhance the discovery of cultural records. This paper offers an initial value identification of the multiple stakeholders that might be impacted by recommendations in ***, a digital archive for historical legal documents. Specifically, we discuss the diverse values and objectives of its stakeholders, such as editors, aggregators, platform owners, researchers, publishers, and funding agencies. These in-depth insights into the potentially conflicting values of stakeholder groups allow designing and adapting recommender systems to enhance their usefulness for humanities and historical research. Additionally, our findings will support deeper engagement with additional stakeholders to refine value models and evaluation metrics for recommender systems in the given domains. Our conclusions are embedded in and applicable to other digital archives and a broader cultural heritage context. © 2024 Copyright for this paper by its authors.

关键词： Embedded systems

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Enhanced Image Retrieval Through the Integration of Dense Global Descriptors and Structural Masks

Enhanced Image Retrieval Through the Integration of Dense Gl...

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International Conference on big data and Smart Computing (bigCOMP)

作者： Gunho Lee Ryong Lee Rae-Young Jang Gunwoo Lee Myung-Seok Choi Department of Artificial Intelligence Data Research Korea Institute of Science and Technology Information Daejeon Republic of Korea

Similar image retrieval identifies and ranks images from a database based on visual characteristics such as color, texture, and shape to match a given sample image, providing results with the closest resemblance. Hence, it's crucial to have a thorough understanding of the content in images. In this paper, we propose a method to utilize structural information based on an image segmentation model. Significantly, the structural information can provide novel insights into aspects of images that conventional dense global descriptors may overlook, as it can clarify the shapes of objects and their backgrounds, offering a complementary perspective. Specifically, our method combines structural information with global descriptors, allowing both the detailed shapes and broader features of images to be captured in a manner that users can control. In the experiments, we evaluate the extent to which this integrated approach enhances the performance of similarity search tasks.

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PointFaceFormer: Local and Global Attention Based Transformer for 3D Point Cloud Face Recognition

PointFaceFormer: Local and Global Attention Based Transforme...

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International Conference on Automatic Face and Gesture Recognition

作者： Ziqi Gao Qiufu Li Gui Wang Linlin Shen Computer Vision Institute Shenzhen University China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Department of Computer Science University of Nottingham Ningbo China

ISBN: (数字)9798350394948

ISBN: (纸本)9798350394955

Existing 3D point cloud-based facial recognition struggles to fully leverage both global and local information inherent in the 3D point cloud data. In this paper, we introduce the PointFaceFormer, the first Transformer model designed for 3D point cloud face recognition. It incorporates an attention mechanism based on dot product and cosine functions to construct a similarity Transformer architecture, which effectively extracts both local and global features from the point cloud data. Experimental results demonstrate that PointFaceFormer achieves a recognition accuracy of 89.08% and a verification accuracy of 76.93% on the large-scale facial point cloud dataset Lock3DFace, which is a new state-of-the-art in 3D face recognition. Furthermore, PointFaceFormer exhibits excellent generalization performance on cross-quality datasets. Additionally, we validate the effectiveness of the attention mechanism through ablation experiments, which justify the effectiveness of the proposed modules.

关键词： Point cloud compression Solid modeling Three-dimensional displays Attention mechanisms Accuracy Face recognition Transformers

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Noise robust Mongolian speech data augmentation model structure 22

Noise robust Mongolian speech data augmentation model struct...

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22nd Chinese National Conference on Computational Linguistics, CCL 2023

作者： Zhiqiang, Ma Jiaqi, Sun Jinyi, Li Jiatai, Wang College of Data Science and Application Inner Mongolia University of Technology Huhhot010000 China Inner Mongolia Autonomous Region Software Service Engineering Technology Research Center Based on Big Data Huhhot010000 China

ISBN: (纸本)9781713876229

There is a lack of phonetic diversity in Mongolian corpus. Although manpower and funds spent on data collection can increase the number of phonetic sounds to some extent, the whole process needs a lot of time. data augmentation can solve the problem of data scarcity, but the environmental noise contained in the training data of the data augmentation model cannot be controlled, resulting in background noise in the augmentation speech. In this paper, a speech data augmentation method combining TTS and speech enhancement is proposed. Based on the speech spectrum graph, speech enhancement is carried out from two dimensions: frequency domain and time domain. Multiple experiments show that the qualified rate of Mongolian augmented speech reaches 70%, the CBAK and COVL of augmented speech decrease by 0.66 and 0.81, and WER and SER decrease by 2.75% and 2.05%, respectively. © 2023 China National Conference on Computational Linguistics.

关键词： Frequency domain analysis

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Identifying State-Specific Customer Churn Patterns using DM Techniques

Identifying State-Specific Customer Churn Patterns using DM ...

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2021 International Conference on data Analytics for Business and Industry, ICDABI 2021

作者： Khalid, Aisha Khedr, Ahmed Abdulrahman, Hajar Zeki, Ahmed M. University of Bahrain Big Data Science Analytics College of Science Sakhir Bahrain University of Bahrain College of Information Technology Department of Information Systems Sakhir Bahrain

ISBN: (纸本)9781665416566

Customers are the key to the success and growth of any business. In today's rapid and competitive market, customer churn is one of the essential elements and concerns for the development of telecommunication companies. Customer churn is when a customer moves from one service provider to another. Retaining these customers is a critical task, due to loss of revenue and the high cost of acquiring new customers. This research aims at studying the patterns leading to churn behavior, from an online dataset on Kaggle, by using three data Mining techniques: Decision Tree with reported accuracy of 86%, k-means with 4,686 sums of squared errors within cluster, and with Apriori, with confidence factors ranging from 90% to 100%. It was concluded that the total day charge and the number of times a customer called the Customer Service were the main factors leading to customer churn. Furthermore, analyzing customer churn on a state level could lead to unique findings that could identify the behavior of customers for a given region or state. © 2021 IEEE.

关键词： Decision trees

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THE FUNDAMENTAL LIMITS OF RECOVERING PLANTED SUBGRAPHS

arXiv

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arXiv 2025年

作者： Lee, Daniel Z. Pernice, Francisco Rajaraman, Amit Zadik, Ilias CSAIL Massachusetts Institute of Technology United States Department of Statistics and Data Science Yale University United States

Given an arbitrary subgraph H "Hn and p "pn P p0, 1q, the planted subgraph model is defined as follows. A statistician observes the union of the "signal," which is a random "planted" copy H∗ of H, together with random noise in the form of an instance of an Erdős–Rényi graph Gpn, pq. Their goal is to then recover the planted H∗ from the observed graph. Our focus in this work is to understand the minimum mean squared error (MMSE), defined in terms of recovering the edges of H∗, as a function of p and H, for sufficiently large n. A recent paper [MNS`23] characterizes the graphs for which the limiting (as n grows) MMSE curve undergoes a sharp phase transition from 0 to 1 as p increases, a behavior known as the all-or-nothing phenomenon, up to a mild density assumption on H. However, their techniques fail to describe the MMSE curves for graphs that do not display such a sharp phase transition. In this paper, we provide a formula for the limiting MMSE curve for any graph H "Hn, up to the same mild density assumption. This curve is expressed in terms of a variational formula over pairs of subgraphs of H, and is inspired by the celebrated subgraph expectation thresholds from the probabilistic combinatorics literature [KK07]. Furthermore, we give a polynomial-time description of the optimizers of this variational problem. This allows one to efficiently approximately compute the MMSE curve for any dense graph H when n is large enough. The proof relies on a novel graph decomposition of H as well as a new minimax theorem which may be of independent interest. Our results generalize to the setting of minimax rates of recovering arbitrary monotone boolean properties planted in random noise, where the statistician observes the union of a planted minimal element A Ď rNs of a monotone property and a random BerppqbN vector. In this setting, we provide a variational formula inspired by the so-called "fractional" expectation threshold [Tal10], again describing the MMSE curve (in this c

关键词： Mean square error

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