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Time series analysis is used to understand and predict dynamic processes, including evolving demands in business, weather, markets, and biological rhythms. Exponential smoothing is used in all these domains to obtain simple interpretable…

Machine Learning · Statistics 2017-10-02 Avner Abrami , Aleksandr Y. Aravkin , Younghun Kim

User data confidentiality protection is becoming a rising challenge in the present deep learning research. Without access to data, conventional data-driven model compression faces a higher risk of performance degradation. Recently, some…

Machine Learning · Computer Science 2022-01-28 Yuhang Li , Feng Zhu , Ruihao Gong , Mingzhu Shen , Xin Dong , Fengwei Yu , Shaoqing Lu , Shi Gu

We introduce TableLLM, a robust large language model (LLM) with 8 billion parameters, purpose-built for proficiently handling tabular data manipulation tasks, whether they are embedded within documents or spreadsheets, catering to…

Computation and Language · Computer Science 2025-02-18 Xiaokang Zhang , Sijia Luo , Bohan Zhang , Zeyao Ma , Jing Zhang , Yang Li , Guanlin Li , Zijun Yao , Kangli Xu , Jinchang Zhou , Daniel Zhang-Li , Jifan Yu , Shu Zhao , Juanzi Li , Jie Tang

Access to data and data processing, including the use of machine learning techniques, has become significantly easier and cheaper in recent years. Nevertheless, solutions that can be widely adopted by regulators for market monitoring and…

Machine Learning · Computer Science 2022-04-08 Celso H. H. Ribas , José C. M. Bermudez

Spreadsheets are software programs which are typically created by end-users and often used for business-critical tasks. Many studies indicate that errors in spreadsheets are very common. Thus, a number of vendors offer auditing tools which…

Software Engineering · Computer Science 2012-12-03 Daniel Kulesz , Sebastian Zitzelsberger

Risk management is a fundamental discipline in project management, which includes, among others, quantitative risk analysis. Throughout several years of teaching, we have observed difficulties in students performing Monte Carlo Simulation…

Risk Management · Quantitative Finance 2024-06-03 Fernando Acebes , David Curto , Juan de Anton , Felix Villafanez

Excel is a pervasive yet often complex tool, particularly for novice users, where runtime errors arising from logical mistakes or misinterpretations of functions pose a significant challenge. While large language models (LLMs) offer…

The Big Data landscape poses challenges in managing diverse data formats, requiring efficient storage and processing for high-quality analysis. Effective metadata management is crucial for organizing, accessing, and reusing data within…

Databases · Computer Science 2025-03-21 Claudia Diamantini , Alessandro Mele , Domenico Potena , Cristina Rossetti , Emanuele Storti

Spreadsheets are ubiquitous in business with the financial sector particularly heavily reliant on the technology. It is known that the level of spreadsheet error can be high and that it is often necessary to review spreadsheets based on a…

Software Engineering · Computer Science 2009-08-11 Leslie Bradley , Kevin McDaid

Spreadsheets are critical to data-centric tasks, with rich, structured layouts that enable efficient information transmission. Given the time and expertise required for manual spreadsheet layout design, there is an urgent need for automated…

Artificial Intelligence · Computer Science 2025-09-10 Qin Chen , Yuanyi Ren , Xiaojun Ma , Mugeng Liu , Han Shi , Dongmei Zhang

A multiverse analysis evaluates all combinations of "reasonable" analytic decisions to promote robustness and transparency, but can lead to a combinatorial explosion of analyses to compute. Long delays before assessing results prevent users…

Human-Computer Interaction · Computer Science 2023-05-16 Yang Liu , Tim Althoff , Jeffrey Heer

Tables are an extremely powerful visual and interactive tool for structuring and manipulating data, making spreadsheet programs one of the most popular computer applications. In this paper we introduce and address the task of recommending…

Information Retrieval · Computer Science 2019-07-26 Shuo Zhang , Krisztian Balog

The exponential growth of data in current times and the demand to gain information and knowledge from the data present new challenges for database researchers. Known database systems and algorithms are no longer capable of effectively…

Databases · Computer Science 2017-12-06 Yaron Gonen

Hazard models are the most commonly used tool to analyse time-to-event data. If more than one time scale is relevant for the event under study, models are required that can incorporate the dependence of a hazard along two (or more) time…

Methodology · Statistics 2025-01-14 Angela Carollo , Paul H. C. Eilers , Hein Putter , Jutta Gampe

Data processing systems impose multiple views on data as it is processed by the system. These views include spreadsheets, databases, matrices, and graphs. The common theme amongst these views is the need to store and operate on data as…

Databases · Computer Science 2015-01-26 Jeremy Kepner , Julian Chaidez , Vijay Gadepally , Hayden Jansen

The use of models, even if efficient, must be accompanied by an understanding at all levels of the process that transforms data (upstream and downstream). Thus, needs increase to define the relationships between individual data and the…

Machine Learning · Statistics 2022-09-02 Dimitri Delcaillau , Antoine Ly , Alize Papp , Franck Vermet

Tables form a central component in both exploratory data analysis and formal reporting procedures across many industries. These tables are often complex in their conceptual structure and in the computations that generate their individual…

Computation · Statistics 2023-06-30 Gabriel Becker , Adrian Waddell

It is widely documented that the absence of a structured approach to spreadsheet engineering is a key factor in the high level of spreadsheet errors. In this paper we propose and investigate the application of Test-Driven Development to the…

Software Engineering · Computer Science 2024-12-31 Alan Rust , Brian Bishop , Kevin McDaid

A consistent theme in software experimentation at Microsoft has been solving problems of experimentation at scale for a diverse set of products. Running experiments at scale (i.e., many experiments on many users) has become state of the art…

Applications · Statistics 2019-12-03 Craig Boucher , Ulf Knoblich , Daniel Miller , Sasha Patotski , Amin Saied , Venky Venkateshaiah

Mathematical models are essential for understanding and making predictions about systems arising in nature and engineering. Yet, mathematical models are a simplification of true phenomena, thus making predictions subject to uncertainty.…

Numerical Analysis · Mathematics 2023-03-03 Mark Hobbs , Hussein Rappel , Tim Dodwell