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.
Models predict fire and other emergencies in Edmonton.
Unsupervised learning filters tweets for emergency services during crises.
The virtualization of compute and network resources enables an unseen flexibility for deploying network services. A wide spectrum of emerging technologies allows an ever-growing range of orchestration possibilities in cloud-based environments. But in this context it remains challenging to rhyme dynamic cloud configurat…
The key characteristic of a true free market economy is that exchanges are entirely voluntary. When there is a monopoly in the creation of currency as we have in today's markets, you no longer have a true free market. Features of the current economic system such as central banking and taxation would be nonexistent in a…
Experts predict significant adoption of decentralized finance by 2034, with traditional finance adapting.
Machine learning simplifies finance, but faces challenges.
This work analyzes how users and services adapt to reduce risk, leading to specialization.
Unstructured data refers to information that does not have a predefined data model or is not organized in a pre-defined manner. Loosely speaking, unstructured data refers to text data that is generated by humans. In after-sales service businesses, there are two main sources of unstructured data: customer complaints, wh…
Study maps research streams in biodiversity finance, identifies key areas.
Digital Financial Services continue to expand and replace the delivery of traditional banking services to the customers through innovative technologies to meet the growing complex needs and globalization challenges. These diversified digital products help the organizations (service providers) to improve their firm perf…
Recently, the online car-hailing service, Didi, has emerged as a leader in the sharing economy. Used by passengers and drivers extensive, it becomes increasingly important for the car-hailing service providers to minimize the waiting time of passengers and optimize the vehicle utilization, thus to improve the overall u…
This paper evaluates investment risks in LATAM AI startups using DCF method.
Decentralized finance uses blockchain for $70B in assets, differing from traditional finance.
Crowdsourced data helps detect incidents faster, balancing accuracy and practicality.
The widespread mobile devices facilitated the emergence of many new applications and services. Among them are location-based services (LBS) that provide services based on user's location. Several techniques have been presented to enable LBS even in indoor environments where Global Positioning System (GPS) has low local…
An evolutionary game model analyzes e-commerce and traditional retail trends during the pandemic.
DeepPPMNet forecasts EMS demand and performs causal analyses for policy-making.
Proposes a framework for energy-efficient AIGC workload scheduling in cloud data centers.
Developed a cost and revenue model for HEMS to estimate breakeven transport volumes under different reimbursement and labor cost assumptions.
Deep learning (DL) training-as-a-service (TaaS) is an important emerging industrial workload. The unique challenge of TaaS is that it must satisfy a wide range of customers who have no experience and resources to tune DL hyper-parameters, and meticulous tuning for each user's dataset is prohibitively expensive. Therefo…
New approach uses deep reinforcement learning for vehicle dispatching, reducing waiting times.
Orchestrating the Twin Transition in GBS: A Socio-Technical Framework
Study detects and mitigates stealthy DDoS attacks in IoT networks.
With the emergence of the Hospital Readmission Reduction Program of the Center for Medicare and Medicaid Services on October 1, 2012, forecasting unplanned patient readmission risk became crucial to the healthcare domain. There are tangible works in the literature emphasizing on developing readmission risk prediction m…
Examines AI regulation in finance, highlighting risks and gaps in current laws.
Paper uses deep reinforcement learning for network slicing and traffic prediction.
Automated service classification plays a crucial role in service discovery, selection, and composition. Machine learning has been widely used for service classification in recent years. However, the performance of conventional machine learning methods highly depends on the quality of manual feature engineering. In this…
OTT services are replacing traditional telecom services, affecting revenue streams.
Economic complexity reflects the amount of knowledge that is embedded in the productive structure of an economy. By combining tools from network science and econometrics, a robust and stable relationship between a country's productive structure and its economic growth has been established. Here we report that not only …
Study improves forecasting of ED crowding using advanced ML models.
AI in finance uses quantum logic for better decision-making.
This papers presents a deep learning-based framework to predict crowdsourced service availability spatially and temporally. A novel two-stage prediction model is introduced based on historical spatio-temporal traces of mobile crowdsourced services. The prediction model first clusters mobile crowdsourced services into r…
Modeling investor behavior from financial advisor notes using NLP.
This paper presents approaches to determine a network based pricing for 3D printing services in the context of a two-sided manufacturing-as-a-service marketplace. The intent is to provide cost analytics to enable service bureaus to better compete in the market by moving away from setting ad-hoc and subjective prices. A…
This paper tackles fair same-day delivery service by optimizing regional service rates.
DeepSIP predicts network failures' impact using CNN from syslog and traffic data.
Service system dynamics occur at the interplay between customer behaviour and a service provider's response. This kind of dynamics can effectively be modeled within the framework of queuing theory where customers' arrivals are described by point process models. However, these approaches are limited by parametric assump…
AI enhances financial forecasting with challenges in regulation and privacy.
Proposes FairDRL-ST for fair spatio-temporal mobility prediction.
Mobile gaming has emerged as a promising market with billion-dollar revenues. A variety of mobile game platforms and services have been developed around the world. One critical challenge for these platforms and services is to understand user churn behavior in mobile games. Accurate churn prediction will benefit many st…
CovidCare uses EMR data to predict patient outcomes in emerging epidemics.
An online learning framework optimizes pricing and capacity in service systems.
Twitter is recently being used during crises to communicate with officials and provide rescue and relief operation in real time. The geographical location information of the event, as well as users, are vitally important in such scenarios. The identification of geographic location is one of the challenging tasks as the…
Agent-to-agent finance aims to manage payments and trust for AI agents.
Pakistan examines digital mergers using traditional competition tools.
The Social Internet of Things (SIoT), integration of the Internet of Things and Social Networks paradigms, has been introduced to build a network of smart nodes that are capable of establishing social links. In order to deal with misbehaving service provider nodes, service requestor nodes must evaluate their trustworth…
AI agent predicts industry and product/service codes for companies.
I present a web service for querying an embedding of entities in the Wikidata knowledge graph. The embedding is trained on the Wikidata dump using Gensim's Word2Vec implementation and a simple graph walk. A REST API is implemented. Together with the Wikidata API the web service exposes a multilingual resource for over …