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Boosted decision trees are a very powerful machine learning technique. After introducing specific concepts of machine learning in the high-energy physics context and describing ways to quantify the performance and training quality of…

Data Analysis, Statistics and Probability · Physics 2022-06-22 Yann Coadou

This paper explores the current trending research areas in the field of Computer Science (CS) and investigates the factors contributing to their emergence. Leveraging a comprehensive dataset comprising papers, citations, and funding…

Human-Computer Interaction · Computer Science 2023-08-03 Mohammed Almutairi , Ozioma Collins Oguine

Data is evolving with the rapid progress of population and communication for various types of devices such as networks, cloud computing, Internet of Things (IoT), actuators, and sensors. The increment of data and communication content goes…

Machine Learning · Computer Science 2021-02-05 Swarajya Lakshmi V Papineni , Snigdha Yarlagadda , Harita Akkineni , A. Mallikarjuna Reddy

Learning neural subset selection tasks, such as compound selection in AI-aided drug discovery, have become increasingly pivotal across diverse applications. The existing methodologies in the field primarily concentrate on constructing…

Machine Learning · Computer Science 2024-06-11 Binghui Xie , Yatao Bian , Kaiwen zhou , Yongqiang Chen , Peilin Zhao , Bo Han , Wei Meng , James Cheng

Data mining methods have been widely applied in financial markets, with the purpose of providing suitable tools for prices forecasting and automatic trading. Particularly, learning methods aim to identify patterns in time series and, based…

Machine Learning · Statistics 2013-01-22 Marcelo S. Lauretto , Barbara B. C. Silva , Pablo M. Andrade

We investigate at decision trees that incorporate both traditional queries based on one attribute and queries based on hypotheses about the values of all attributes. Such decision trees are similar to ones studied in exact learning, where…

Computational Complexity · Computer Science 2022-03-18 Mohammad Azad , Igor Chikalov , Shahid Hussain , Mikhail Moshkov , Beata Zielosko

With the explosion of applications of Data Science, the field is has come loose from its foundations. This article argues for a new program of applied research in areas familiar to researchers in Bayesian methods in AI that are needed to…

Machine Learning · Computer Science 2023-07-04 John Mark Agosta , Robert Horton

Mutual information has been successfully adopted in filter feature-selection methods to assess both the relevancy of a subset of features in predicting the target variable and the redundancy with respect to other variables. However,…

Machine Learning · Computer Science 2019-07-18 Mario Beraha , Alberto Maria Metelli , Matteo Papini , Andrea Tirinzoni , Marcello Restelli

Data-driven algorithm design is a paradigm that uses statistical and machine learning techniques to select from a class of algorithms for a computational problem an algorithm that has the best expected performance with respect to some…

Machine Learning · Computer Science 2024-06-05 Hongyu Cheng , Sammy Khalife , Barbara Fiedorowicz , Amitabh Basu

Valuing mineral assets is a challenging task that is highly dependent on the supply (geological) uncertainty surrounding resources and reserves, and the uncertainty of demand (commodity prices). In this work, a graph-based reasoning,…

Artificial Intelligence · Computer Science 2022-12-09 Yassine Yaakoubi , Hager Radi , Roussos Dimitrakopoulos

Current evaluation functions for heuristic planning are expensive to compute. In numerous planning problems these functions provide good guidance to the solution, so they are worth the expense. However, when evaluation functions are…

Artificial Intelligence · Computer Science 2014-01-17 Tomas De la Rosa , Sergio Jimenez , Raquel Fuentetaja , Daniel Borrajo

For delivering products or services to their clients, organizations execute manifold business processes. During such execution, upcoming process tasks need to be allocated to internal resources. Resource allocation is a complex…

Software Engineering · Computer Science 2024-03-29 Luise Pufahl , Sven Ihde , Fabian Stiehle , Mathias Weske , Ingo Weber

The study of intelligent systems explains behaviour in terms of economic rationality. This results in an optimization principle involving a function or utility, which states that the system will evolve until the configuration of maximum…

Information Theory · Computer Science 2024-06-18 Pedro Hack

Decision Focused Learning has emerged as a critical paradigm for integrating machine learning with downstream optimisation. Despite its promise, existing methodologies predominantly rely on probabilistic models and focus narrowly on task…

Machine Learning · Computer Science 2025-03-21 Keivan Shariatmadar , Neil Yorke-Smith , Ahmad Osman , Fabio Cuzzolin , Hans Hallez , David Moens

Cone distribution functions from statistics are turned into Multi-Criteria Decision Making tools. It is demonstrated that this procedure can be considered as an upgrade of the weighted sum scalarization insofar as it absorbs a whole…

Artificial Intelligence · Computer Science 2024-01-17 Andreas H Hamel , Daniel Kostner

We review the role of information and learning in the stability and optimization of queueing systems. In recent years, techniques from supervised learning, bandit learning and reinforcement learning have been applied to queueing systems…

Machine Learning · Computer Science 2021-10-12 Neil Walton , Kuang Xu

State-of-the-art results in typical classification tasks are mostly achieved by unexplainable machine learning methods, like deep neural networks, for instance. Contrarily, in this paper, we investigate the application of rule learning…

Machine Learning · Computer Science 2024-03-11 Albert Nössig , Tobias Hell , Georg Moser

Rough set theory is a new method that deals with vagueness and uncertainty emphasized in decision making. Data mining is a discipline that has an important contribution to data analysis, discovery of new meaningful knowledge, and autonomous…

Databases · Computer Science 2013-11-19 Thabet Slimani

We address the practical problems of estimating the information relations that characterize large networks. Building on methods developed for analysis of the neural code, we show that reliable estimates of mutual information can be obtained…

Information Theory · Computer Science 2007-07-13 Noam Slonim , Gurinder S. Atwal , Gasper Tkacik , William Bialek

Data and knowledge representation are fundamental concepts in machine learning. The quality of the representation impacts the performance of the learning model directly. Feature learning transforms or enhances raw data to structures that…

Artificial Intelligence · Computer Science 2021-04-26 Filipe Alves Neto Verri , Renato Tinós , Liang Zhao
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