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.
Blockchain fan tokens boost sports fan engagement by 50%.
Study shows impersonators generate fake engagement on Instagram.
Technology has had an unquestionable impact on the way people watch sports. Along with this technological evolution has come a higher standard to ensure a good viewing experience for the casual sports fan. It can be argued that the pervasion of statistical analysis in sports serves to satiate the fan's desire for detai…
The paper analyzes sports commentary to automatically recognize events and extract insights.
Inefficient markets allow investors to consistently outperform the market. To demonstrate that inefficiencies exist in sports betting markets, we created a betting algorithm that generates above market returns for the NFL, NBA, NCAAF, NCAAB, and WNBA betting markets. To formulate our betting strategy, we collected and …
This paper optimizes sports betting strategies using neural networks and portfolio theory.
Investigates sports betting strategies using modern portfolio theory and Kelly criterion.
Wearables like smartwatches which are embedded with sensors and powerful processors, provide a strong platform for development of analytics solutions in sports domain. To analyze players' games, while motion sensor based shot detection has been extensively studied in sports like Tennis, Golf, Baseball; Table Tennis and…
Paper simplifies complex sports analytics models for better understanding.
Over the past two decades, Machine Learning (ML) techniques have been increasingly utilized for the purpose of predicting outcomes in sport. In this paper, we provide a review of studies that have used ML for predicting results in team sport, covering studies from 1996 to 2019. We sought to answer five key research que…
Framework for real-time win probability and player ability in sports.
Operationalizes engagement as human behavior, linking theory and data.
Mathematical models reveal key factors for engaging Gen Z at work.
Paper proposes a method to aggregate customer engagement data for better ranking of e-commerce results.
FATE predicts user engagement on social apps with explainable explanations.
A simplified Bayesian approach for online sports rating.
Study improves engagement prediction in educational videos.
A dataset for evaluating engagement with scientific video lectures.
Tennis is a popular sport worldwide, boasting millions of fans and numerous national and international tournaments. Like many sports, tennis has benefitted from the popularity of rigorous record-keeping of game and player information, as well as the growth of machine learning methods for use in sports analytics. Of par…
The study analyzes games and social hierarchies, incorporating luck and depth of competition.
Improved trajectory prediction for team sports using sparse outputs.
While mobile social apps have become increasingly important in people's daily life, we have limited understanding on what motivates users to engage with these apps. In this paper, we answer the question whether users' in-app activity patterns help inform their future app engagement (e.g., active days in a future time w…
We propose a multimodal approach for detection of students' behavioral engagement states (i.e., On-Task vs. Off-Task), based on three unobtrusive modalities: Appearance, Context-Performance, and Mouse. Final behavioral engagement states are achieved by fusing modality-specific classifiers at the decision level. Various…
Topologically and geometrically engaging actions have proved to be useful to obtain rigidity results for semisimple Lie group actions. We show that the action of a simple noncompact Lie group on a compact manifold preserving a unimodular rigid geometric structure of algebraic type (e.g. a connection together with a vol…
New methods for skill rating in sports using state-space models.
The health outcomes of high-need patients can be substantially influenced by the degree of patient engagement in their own care. The role of care managers includes that of enrolling patients into care programs and keeping them sufficiently engaged in the program, so that patients can attain various goals. The attainmen…
To investigate the detection of students' behavioral engagement (On-Task vs. Off-Task), we propose a two-phase approach in this study. In Phase 1, contextual logs (URLs) are utilized to assess active usage of the content platform. If there is active use, the appearance information is utilized in Phase 2 to infer behavi…
New framework optimizes for 'value' rather than engagement.
D2KLab's approach predicts tweet engagement using two stages.
Study analyzes factors influencing healthcare providers' engagement with SMS campaigns.
This short note is intended as a "Letter to the Editor" Perspective in order that it serves as a contribution, in view of reaching the physics community caring about rare events and scaling laws and unexpected findings, on a domain of wide interest: sport and money. It is apparent from the data reported and discussed b…
BBE simulates betting exchanges to generate synthetic data for AI research.
Study user engagement in mobile health apps for health workers in resource-poor settings.
Machine learning predicts US will win most Olympic medals in 2020.
In-game win probability models, which provide a sports team's likelihood of winning at each point in a game based on historical observations, are becoming increasingly popular. In baseball, basketball and American football, they have become important tools to enhance fan experience, to evaluate in-game decision-making,…
Sporting events are extremely complex and require a multitude of metrics to accurate describe the event. When making multiple predictions, one should make them from a single source to keep consistency across the predictions. We present a multi-task learning method of generating multiple predictions for analysis via a s…
Twitter releases dataset to study user engagement on Home Timeline, focusing on privacy.
Personal assistant AI systems such as Siri, Cortana, and Alexa have become widely used as a means to accomplish tasks through natural language commands. However, components in these systems generally rely on supervised machine learning algorithms that require large amounts of hand-annotated training data, which is expe…
The Web has enabled one of the most visible recent developments in education---the deployment of massive open online courses. With their global reach and often staggering enrollments, MOOCs have the potential to become a major new mechanism for learning. Despite this early promise, however, MOOCs are still relatively u…
Study proposes new methods to convert betting odds into accurate probabilities for sports forecasting.
Data-driven approaches which aim to identify and predict player engagement are becoming increasingly popular in games industry contexts. This is due to the growing practice of tracking and storing large volumes of in-game telemetries coupled with a desire to tailor the gaming experience to the end-user's needs. These a…
BBE simulates sports betting exchanges for data generation.
In this paper we present the first results of a pilot experiment in the capture and interpretation of multimodal signals of human experts engaged in solving challenging chess problems. Our goal is to investigate the extent to which observations of eye-gaze, posture, emotion and other physiological signals can be used t…
The paper proposes a survival model to optimize mobile notification delivery times.
Unmanned Aerial Vehicles (UAVs), autonomously-guided aircraft, are widely used for tasks involving surveillance and reconnaissance. A version of the pursuit-evasion problems centered around UAVs and its variants has been extensively studied in recent years due to numerous breakthroughs in AI. We present an approach to …
Decentralized prediction markets use AMMs to pool and withdraw liquidity, improving financial properties.
Inspired by applications in sports where the skill of players or teams competing against each other varies over time, we propose a probabilistic model of pairwise-comparison outcomes that can capture a wide range of time dynamics. We achieve this by replacing the static parameters of a class of popular pairwise-compari…
New approach to disentangle utility from impulse in recommendation systems.