On-device research index

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.

168,742 papers · 148 categories

Trend · papers per month

count % of corpus

6 results for “User-centric”

Online Learning with Probing for Sequential User-Centric Selectioncs.LG

OLPA optimizes online user-centric selection with probing, achieving near-optimal regret bounds.

problem Sequential decision-making with unknown resources and rewards.

method Probing-augmented user-centric selection (PUCS) framework, greedy probing algorithm, OLPA algorithm.

result OLPA achieves a near-optimal regret bound of

\mathcal{O}(\sqrt{T} + \ln^{2} T)

for online settings.

online learning sequential decision-making probing user-centric selection regret bound

2025-07-27abs ↗pdf ↗

UCFE: A User-Centric Financial Expertise Benchmark for Large Language Modelsq-fin.CP

UCFE benchmarks LLMs in financial tasks with human feedback.

problem Evaluating LLMs' financial task performance and user satisfaction.

method Hybrid approach combining human expert evaluations and dynamic interactions.

result Significant alignment between benchmark scores and human preferences (Pearson correlation coefficient of 0.78).

Large Language Models Financial Expertise User Satisfaction Hybrid Evaluation Human Feedback

2024-10-17abs ↗pdf ↗

Individual Mobility Prediction: An Interpretable Activity-based Hidden Markov Approachcs.LG

Study develops a new model for predicting individual mobility based on activity patterns.

problem Existing mobility prediction methods overlook underlying activity patterns.

method Activity-based hidden Markov model (IOHMM) using transit smart card data.

result Proposed model achieves similar prediction performance to LSTM but also provides behavioral insights.

mobility prediction hidden Markov model activity-based transportation behavioral interpretation

2021-01-11abs ↗pdf ↗

BehavDT: A Behavioral Decision Tree Learning to Build User-Centric Context-Aware Predictive Modelcs.LG

Proposes BehavDT model for context-aware user behavior prediction.

problem Building a context-aware predictive model based on diverse user behavioral activities.

method Introduces BehavDT, a behavioral decision tree that considers user behavior-oriented generalization.

result BehavDT model outperforms traditional machine learning approaches in predicting user diverse behaviors considering multi-dimensional contexts.

Behavioral Decision Tree Context-Aware Predictive Model User-centric Smartphone Data Decision Tree

2019-12-17abs ↗pdf ↗

Fusing Multifaceted Transaction Data for User Modeling and Demographic Predictioncs.SI

Inferring user characteristics such as demographic attributes is of the utmost importance in many user-centric applications. Demographic data is an enabler of personalization, identity security, and other applications. Despite that, this data is sensitive and often hard to obtain. Previous work has shown that purchase …

2017-12-19abs ↗pdf ↗

A General Framework for Scalable UE-AP Association in User-Centric Cell-Free Massive MIMO based on Recurrent Neural Networkscs.LG

Study improves scalability of cell-free massive MIMO networks by optimizing UE-AP association.

problem Optimizing UE-AP association in cell-free massive MIMO networks.

method Deep learning algorithm using Bidirectional Long Short-Term Memory cells and hybrid probabilistic weight updating.

result Enhanced scalability without retraining, robust against pilot contamination.

cell-free massive MIMO UE-AP association scalability deep learning recurrent neural networks

2025-03-06abs ↗pdf ↗