Mobile crowdsourcing has become easier thanks to the widespread of smartphones capable of seamlessly collecting and pushing the desired data to cloud services. However, the success of mobile crowdsourcing relies on balancing the supply and demand by first accurately forecasting spatially and temporally the supply-deman…
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arXiv research
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.
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48 results for “service gaps”
Two neural network models analyze bus system efficiency and demand.
problem Identify service gaps and quantify demand in public transportation.
method Two neural network models considering demographic data and metrics.
result Models can generalize to other cities' bus systems.
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…
Examines AI regulation in finance, highlighting risks and gaps in current laws.
problem Rapid AI adoption in finance introduces risks and compliance challenges.
method Reviews current legislation, industry guidelines, and real-world use cases.
result Need for adaptive, technology-neutral policies to balance innovation and consumer protection.
Optimizes task allocation for financial analysts to balance work efficiency and well-being.
problem Balancing business goals with financial analysts' well-being in error resolution tasks.
method Used a Genetic Algorithm (GA) to optimize task allocation considering both business goals and analyst well-being.
result GA model outperforms existing methods and is applicable to various real-world scenarios.
Model analyzes mortgage relief during financial hardship.
problem Understanding and optimizing mortgage relief during financial distress.
method Agent-based model of households and servicers.
result Model replicates real-world mortgage studies and provides fine-grained insights.
Assessing the Solvency of Virtual Asset Service Providers: Are Current Standards Sufficient?q-fin.GN
The paper assesses VASPs' solvency using multiple data sources.
problem Insolvency risk in VASPs without systematic auditing.
method Cross-referencing cryptoasset wallets, balance sheets, and supervisory data.
result Inconsistent data between DLT transactions and balance sheets for some VASPs.
Study uncovers financial trends from cross-lingual news data.
problem Understanding financial dynamics across diverse global economies.
method Sentiment analysis, NER, and semantic textual similarity for news articles.
result Meaningful correlation between stock price movements and cross-linguistic news sentiments.
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.
problem OTT services are reducing traditional telecom revenue streams.
method Quantitative analysis of mobile user trends and revenue changes.
result OTT services are becoming more prevalent and impacting telecom revenue.
The Impact of Services on Economic Complexity: Service Sophistication as Route for Economic Growthecon.GN
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 …
The paper bounds generalization errors for deep neural networks with Markov datasets.
problem Bounding generalization errors for deep learning with Markov datasets.
method Developed new symmetrization inequalities for Markov chains, using spectral gap of the infinitesimal generator.
result Derived upper bounds on generalization errors for deep neural networks with Markov datasets.
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…
Network Based Pricing for 3D Printing Services in Two-Sided Manufacturing-as-a-Service Marketplacecs.LG
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.
problem Fairness in same-day delivery service for different neighborhoods.
method Partition service area into regions, use multi-objective Markov decision process and deep Q-learning.
result Our approach maximizes fairness across all regions while maintaining overall service rate.
DeepSIP predicts network failures' impact using CNN from syslog and traffic data.
problem Predicting service impact from network failures.
method Temporal multimodal CNN for predicting time to recovery and traffic loss.
result DeepSIP reduced prediction error by approximately 50%.
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…
An online learning framework optimizes pricing and capacity in service systems.
problem Optimizing pricing and capacity in dynamic service systems.
method Gradient-based Online Learning in Queue (GOLiQ) framework.
result GOLiQ achieves logarithmic regret bound and improves service provider's performance.
This work analyzes how users and services adapt to reduce risk, leading to specialization.
problem Adaptation of users and services to reduce risk affects learning and performance.
method Analyzed a class of dynamics where users allocate participation and services update parameters.
result Repeated myopic updates with multiple learners lead to better outcomes than repeated risk minimization.
Proposes FairDRL-ST for fair spatio-temporal mobility prediction.
problem Fairness concerns in spatio-temporal AI applications.
method Disentangled representation learning, adversarial learning.
result Achieves fairness in spatio-temporal mobility prediction without performance loss.
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 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.
problem Manual curation of company data is expensive and prone to errors.
method Hierarchical multi-class industry code classifier with multi-label product/service code classifier.
result High accuracy (92-96%) achieved with limited labeled data.
Optimizes antenna tilt for better QoS in cellular networks.
problem Hard to learn optimal antenna tilt policies in real networks due to risk and simulation gap.
method Uses off-policy Contextual Multi-Armed-Bandit (CMAB) techniques to learn from existing data.
result Trained policies show consistent improvements over existing logging policies.
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 …
Policy certifies inventory levels meeting service requirements.
problem Maintaining stock levels meeting service requirements despite unknown demand.
method Data-driven order policy using online learning and integral action.
result Valid inference method for finite samples.
Since time immemorial, people have been looking for ways to organize scientific knowledge into some systems to facilitate search and discovery of new ideas. The problem was partially solved in the pre-Internet era using library classifications, but nowadays it is nearly impossible to classify all scientific and popular…
We aim to predict and explain service failures in supply-chain networks, more precisely among last-mile pickup and delivery services to customers. We analyze a dataset of 500,000 services using (1) supervised classification with Random Forests, and (2) Association Rules. Our classifier reaches an average sensitivity of…
This study develops an online predictive optimization framework for dynamically operating a transit service in an area of crowd movements. The proposed framework integrates demand prediction and supply optimization to periodically redesign the service routes based on recently observed demand. To predict demand for the …
TIMeSynC combines financial service interactions for intent prediction.
problem Aligning and learning from multi-domain, multi-resolution sequences for accurate intent prediction.
method An encoder-decoder transformer model addressing sequence alignment, temporal dynamics, and dynamic/static sequence combination.
result Significant improvement in intent prediction over existing methods.
Computable contracts simplify financial transactions and reduce legal costs.
problem Difficulty in querying, executing, and analyzing text-based financial contracts.
method Develop a Contract Definition Language and illustrate use cases.
result Substantial improvements in customer experience and cost reduction.
Paper introduces privacy-preserving deep-learning service.
problem Privacy loss in deep-learning-as-a-service.
method Homomorphic Encryption tailored for CNNs.
result Effectiveness of proposed privacy-preserving architecture.
Machine learning methods are widely used for a variety of prediction problems. \emph{Prediction as a service} is a paradigm in which service providers with technological expertise and computational resources may perform predictions for clients. However, data privacy severely restricts the applicability of such services…
The writers propose a mathematical Method for deriving risk weights which describe how a borrower's income, relative to their debt service obligations (serviceability) affects the probability of default of the loan. The Method considers the borrower's income not simply as a known quantity at the time the loan is made, …
Study uses CNN to analyze images of SMEs for bankruptcy risk.
problem Lack of data for risk analysis of SMEs.
method Created images for each SME, trained CNN on these images.
result CNN achieved 97.8% accuracy in predicting bankruptcy.
LightAutoML automates ML for a large financial services company.
problem Building high-quality ML models for a complex financial ecosystem.
method Developed an AutoML system tailored to a large European financial services company's unique requirements.
result LightAutoML outperformed experienced data scientists and other open-source solutions.
Graph learning categorizes DeFi services into similar functionalities.
problem Identifying similar financial services in decentralized finance protocols.
method Graph representation learning (GRL) to categorize smart contract blocks into clusters.
result Purity of clustering reaches .888 in the best-case scenario.
AI enhances financial services but humans are irreplaceable for empathy, presence, and ethics.
problem AI's limitations in financial services, especially with small datasets and human judgment.
method EPOCH framework highlighting five irreplaceable human capabilities: Empathy, Presence, Opinion, Creativity, and Hope.
result Humans are essential for trust, innovation, and consumer experience in financial services.
The professional services sector is at a turning point, with some industries showing growth opportunities.
problem Identifying growth opportunities in the professional services sector after decades of growth.
method A simple framework applied to the US economic context to diagnose growth opportunities.
result The professional services sector is expected to stall at a national level, but some industries still offer growth opportunities.
With the widespread use of machine learning (ML) techniques, ML as a service has become increasingly popular. In this setting, an ML model resides on a server and users can query it with their data via an API. However, if the user's input is sensitive, sending it to the server is undesirable and sometimes even legally …
Classification-as-a-Service (CaaS) is widely deployed today in machine intelligence stacks for a vastly diverse set of applications including anything from medical prognosis to computer vision tasks to natural language processing to identity fraud detection. The computing power required for training complex models on l…
The authors characterize flexibility in power and energy markets considering time, spatiality, resource, and risk.
problem Evaluating and maximizing flexibility in power systems and markets.
method Characterization of flexibility dimensions (time, spatiality, resource, risk) and their interrelations with flexibility assets, products, and services.
result Flexibility should be evaluated based on multiple dimensions for efficient power systems and markets.
Study on electronic banking satisfaction in Nigeria.
problem Limited research on factors enhancing end users' satisfaction in electronic banking.
method Empirical analysis of factors influencing electronic banking user satisfaction.
result Factors influencing electronic banking user satisfaction and their relationship with satisfaction.
Recently, mobile operators in many developing economies have launched "Mobile Money" platforms that deliver basic financial services over the mobile phone network. While many believe that these services can improve the lives of the poor, a consistent difficulty has been identifying individuals most likely to benefit fr…
Framework optimizes targeting high-need individuals while estimating treatment effects.
problem Balancing resource allocation to high-need individuals with evaluating treatment effects.
method Proposes a framework to design randomized allocation rules that balance targeting high-need recipients with learning treatment effects.
result Optimized policies can significantly mitigate the tradeoff between targeting high-need individuals and estimating treatment effects.
Radio on Free Space Optics (RoFSO), as a universal platform for heterogeneous wireless services, is able to transmit multiple radio frequency signals at high rates in free space optical networks. This paper investigates the optimal design of power allocation for Wavelength Division Multiplexing (WDM) transmission in Ro…
Money was invented to address the difficulty in the double coincidence of wants between the supply and demand when people exchanged their goods and services. There are two information states in society: one is the initial state that people have goods and services due to division of labor; the other is the final state t…