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Based on decision trees, many fields have arguably made tremendous progress in recent years. In simple words, decision trees use the strategy of "divide-and-conquer" to divide the complex problem on the dependency between input features and…

Machine Learning · Computer Science 2021-01-22 Jinxiong Zhang

Peer reviews, evaluations, and selections are a fundamental aspect of modern science. Funding bodies the world over employ experts to review and select the best proposals from those submitted for funding. The problem of peer selection,…

Computer Science and Game Theory · Computer Science 2019-05-01 Haris Aziz , Omer Lev , Nicholas Mattei , Jeffrey S. Rosenschein , Toby Walsh

In this opening talk I first describe how we are entering a data-rich era, and what clues we might soon have to physics beyond the SM (on a time scale of several years). Then we turn to a number of the basic issues we hope to explain, and…

High Energy Physics - Phenomenology · Physics 2007-05-23 Gordon L. Kane

Feature selection techniques are essential for high-dimensional data analysis. In the last two decades, their popularity has been fuelled by the increasing availability of high-throughput biomolecular data where high-dimensionality is a…

Quantitative Methods · Quantitative Biology 2024-01-18 Pengyi Yang , Hao Huang , Chunlei Liu

We consider different choice procedures such as scoring rules, rules, using majority relation, value function and tournament matrix, which are used in social and multi-criteria choice problems. We focus on the study of the properties that…

Optimization and Control · Mathematics 2016-11-03 Sergey Shvydun

The ethical concept of fairness has recently been applied in machine learning (ML) settings to describe a wide range of constraints and objectives. When considering the relevance of ethical concepts to subset selection problems, the…

Artificial Intelligence · Computer Science 2020-02-11 Margaret Mitchell , Dylan Baker , Nyalleng Moorosi , Emily Denton , Ben Hutchinson , Alex Hanna , Timnit Gebru , Jamie Morgenstern

In recent years, spiking neural networks (SNNs) have received extensive attention in brain-inspired intelligence due to their rich spatially-temporal dynamics, various encoding methods, and event-driven characteristics that naturally fit…

Neural and Evolutionary Computing · Computer Science 2022-10-18 Duzhen Zhang , Shuncheng Jia , Qingyu Wang

The notion of a simplicial set originated in algebraic topology, and has also been utilized extensively in category theory, but until relatively recently was not used outside of those fields. However, with the increasing prominence of…

Algebraic Topology · Mathematics 2024-11-28 Julia E. Bergner

We study selection principles related to bornological covers in a topological space $X$ following the work of Aurichi et al., 2019, where selection principles have been investigated in the function space $C_\mathfrak{B}(X)$ endowed with the…

General Topology · Mathematics 2025-11-07 Debraj Chandra , Subhankar Das , Nur Alam

CONTENTS: Lecce Workshop presentations available online; Borel cardinalities below c_0; Hereditarily non-topologizable groups; A hodgepodge of sets of reals; Random gaps; Covering a bounded set of functions by an increasing chain of…

General Topology · Mathematics 2008-12-31 Boaz Tsaban

Fast growing scientific topics have famously been key harbingers of the new frontiers of science, yet, large-scale analyses of their genesis and impact are rare. We investigate one possible factor connected with a topic's extraordinary…

Digital Libraries · Computer Science 2021-11-17 Ching Jin , Yifang Ma , Brian Uzzi

This is a brief review, in relatively non-technical terms, of recent advances in the theory of random field geometry. These advances have provided a collection of explicit new formulae describing mean values of a variety of geometric…

Probability · Mathematics 2008-05-08 Robert J Adler

We point out that the "additivity principle" and "scaling hypothesis" postulated by Bodineau and Derrida in Phys. Rev. Lett 92, 180601 (2004), follow naturally from the saddle point evaluation of a diffusive field theory.

Statistical Mechanics · Physics 2007-05-23 Eugene V. Sukhorukov , Andrew N. Jordan

Consensus clustering fuses diverse basic partitions (i.e., clustering results obtained from conventional clustering methods) into an integrated one, which has attracted increasing attention in both academic and industrial areas due to its…

Machine Learning · Computer Science 2019-06-04 Hongfu Liu , Zhiqiang Tao , Zhengming Ding

We give a characterization of completely regular topological spaces. Applying some recent results for supinf problems in completely regular topological spaces we establish a variational principle for saddle points. Well-posedness of saddle…

Optimization and Control · Mathematics 2024-08-05 D. Kamburova , R. Marinov , N. Zlateva

Computer Science education has been evolving over the years to reflect applied realities. Until about a decade ago, theory of computation, algorithm design and system software dominated the curricula. Most courses were considered core and…

Computers and Society · Computer Science 2022-08-10 Sreekrishnan Venkateswaran

Science, being a social enterprise, is subject to fragmentation into groups that focus on specialized areas or topics. Often new advances occur through cross-fertilization of ideas between sub-fields that otherwise have little overlap as…

Physics and Society · Physics 2012-08-17 Raj Kumar Pan , Sitabhra Sinha , Kimmo Kaski , Jari Saramäki

This is a survey paper about a selection of results in complex algebraic geometry that appeared in the recent and less recent litterature, and in which rational homogeneous spaces play a prominent r{\^o}le. This selection is largely…

Algebraic Geometry · Mathematics 2020-02-03 Laurent Manivel

The field of computational statistics refers to statistical methods or tools that are computationally intensive. Due to the recent advances in computing power some of these methods have become prominent and central to modern data analysis.…

Methodology · Statistics 2020-04-27 Suneel Babu Chatla , Chun-houh Chen , Galit Shmueli

Diffusion models, which leverage stochastic processes to capture complex data distributions effectively, have shown their performance as generative models, achieving notable success in image-related tasks through iterative denoising…

Machine Learning · Computer Science 2024-08-21 Toshihide Ubukata , Jialong Li , Kenji Tei