A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
ION-C solves overlapping network integration problems efficiently.
We prove that the refined approach -- our extension of the Yakovenko et al. formalism -- is universal in the sense that it describes well both household incomes in the European Union and the individual incomes in the United States for social classes of any income. This formalism allowed the study of the impact of the r…
The study analyzes sentiment of European tweets during the pandemic.
Study compares two market clearing methods for European power markets.
Examines insurance market development and similarity post-2004 EU enlargement.
Bayesian approach learns causal concepts from diverse social surveys.
We give a general overview of the influence of William Thurston on the French mathematical school and we show how some of the major problems he solved are rooted in the French mathematical tradition. At the same time, we survey some of Thurston's major results and their impact. The final version of this paper will appe…
Unified survey of treatment effect heterogeneity and uplift modeling methods.
Survey on curvature bounds and isoperimetric inequalities.
This paper surveys options pricing under arithmetic Brownian motion and derives formulas for various types of options.
Survey of Optimal Transport for model calibration.
Data mining revealed a cluster of economic, psychological, social and cultural indicators that in combination predicted corruption and wealth of European nations. This prosperity syndrome of self-reliant citizens, efficient division of labor, a sophisticated scientific community, and respect for the law, was clearly di…
Investors prioritize ESG in crypto-assets, showing higher exposure than traditional assets.
Modeling European spot power markets with game theory for Nash equilibria.
Deciding effective and timely preventive measures against complex social problems affecting relatively low income geographies is a difficult challenge. There is a strong need to adopt intelligent automation based solutions with low cost imprints to tackle these problems at larger scales. Starting with the hypothesis th…
Understanding tie strength in social networks, and the factors that influence it, have received much attention in a myriad of disciplines for decades. Several models incorporating indicators of tie strength have been proposed and used to quantify relationships in social networks, and a standard set of structural networ…
This survey outlines methods to ensure fairness in machine learning.
Opinion polls have been the bridge between public opinion and politicians in elections. However, developing surveys to disclose people's feedback with respect to economic issues is limited, expensive, and time-consuming. In recent years, social media such as Twitter has enabled people to share their opinions regarding …
Spatial machine learning improves poverty targeting in Indonesia.
This work surveys algorithmic recourse, aiming to clarify definitions and solutions.
The proliferation of fake news on social media has opened up new directions of research for timely identification and containment of fake news, and mitigation of its widespread impact on public opinion. While much of the earlier research was focused on identification of fake news based on its contents or by exploiting …
Graphs arise naturally in many real-world applications including social networks, recommender systems, ontologies, biology, and computational finance. Traditionally, machine learning models for graphs have been mostly designed for static graphs. However, many applications involve evolving graphs. This introduces import…
New method improves active statistical inference by reducing noise.
The paper tackles robust classification trees for distribution shifts, improving accuracy in public health and social work.
The increasing accessibility of data provides substantial opportunities for understanding user behaviors. Unearthing anomalies in user behaviors is of particular importance as it helps signal harmful incidents such as network intrusions, terrorist activities, and financial frauds. Many visual analytics methods have bee…
In general, anomaly detection is the problem of distinguishing between normal data samples with well defined patterns or signatures and those that do not conform to the expected profiles. Financial transactions, customer reviews, social media posts are all characterized by relational information. In these networks, fra…
Social network analysis is an important problem in data mining. A fundamental step for analyzing social networks is to encode network data into low-dimensional representations, i.e., network embeddings, so that the network topology structure and other attribute information can be effectively preserved. Network represen…
Survey data imputation methods impact feature selection and importance assessment.
Study finds ESG investments more resilient than traditional equity indices during market turmoil.
In recent years, we have been faced with a series of natural disasters causing a tremendous amount of financial, environmental, and human losses. The unpredictable nature of natural disasters' behavior makes it hard to have a comprehensive situational awareness (SA) to support disaster management. Using opinion surveys…
Machine learning algorithms for prediction are increasingly being used in critical decisions affecting human lives. Various fairness formalizations, with no firm consensus yet, are employed to prevent such algorithms from systematically discriminating against people based on certain attributes protected by law. The aim…
Quantum mechanics models human perception and decision-making, offering a new approach to understanding social dynamics.
This article provides the first survey of computational models of emotion in reinforcement learning (RL) agents. The survey focuses on agent/robot emotions, and mostly ignores human user emotions. Emotions are recognized as functional in decision-making by influencing motivation and action selection. Therefore, computa…
Graph kernels have attracted a lot of attention during the last decade, and have evolved into a rapidly developing branch of learning on structured data. During the past 20 years, the considerable research activity that occurred in the field resulted in the development of dozens of graph kernels, each focusing on speci…
Study on insurance risk management and sustainable development.
This survey clarifies dynamic network terminology and reviews GNN models for dynamic networks.
With the widespread use of information technologies, information networks are becoming increasingly popular to capture complex relationships across various disciplines, such as social networks, citation networks, telecommunication networks, and biological networks. Analyzing these networks sheds light on different aspe…
Study highlights fairness issues in travel behavior prediction models.
Fuzzy Forests reduces feature space in high-dimensional survey data.
This study uses Twitter to analyze traveler behavior in Manhattan.
Complex analysis aids in studying minimal surfaces.
New estimator improves statistical validity of synthetic data integration.
Social media services such as Twitter are a valuable source of information for decision support systems. Many studies have shown that this also holds for the medical domain, where Twitter is considered a viable tool for public health officials to sift through relevant information for the early detection, management, an…
Estimates social network structure from random walk subgraphs.
Bitcoin price prediction models fail to outperform a simple 'today's price' baseline, especially at longer horizons.
Survey of robust clustering methods for hotspot detection.
Innovation is among the key factors driving a country's economic and social growth. But what are the factors that make a country innovative? How do they differ across different parts of the world and different stages of development? In this work done in collaboration with the World Economic Forum (WEF), we analyze the …
AI enhances ESG practices in finance, but requires careful consideration.