:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Jin, Jiahui, Hong, Yi, Xu, Guandong, Zhang, Jinghui, Tang, Jun, Wang, Hancheng
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Computers and Society
Online Access:	https://arxiv.org/abs/2411.01134
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Network-Based Transfer Learning Helps Improve Short-Term Crime Prediction Accuracy
by: Wu, Jiahui, et al.
Published: (2024)

Improving the Fairness of Deep-Learning, Short-term Crime Prediction with Under-reporting-aware Models
by: Wu, Jiahui, et al.
Published: (2024)

Deep Learning Based Crime Prediction Models: Experiments and Analysis
by: Utsha, Rittik Basak, et al.
Published: (2024)

Machine Learning for Public Good: Predicting Urban Crime Patterns to Enhance Community Safety
by: Gupta, Sia, et al.
Published: (2024)

Crime Hotspot Prediction Using Deep Graph Convolutional Networks
by: Zubair, Tehreem, et al.
Published: (2025)

Comprehensive Monitoring of Air Pollution Hotspots Using Sparse Sensor Networks
by: Bhardwaj, Ankit, et al.
Published: (2024)

Unmasking COVID-19 Vulnerability in Nigeria: Mapping Risks Beyond Urban Hotspots
by: Wafula, Sheila, et al.
Published: (2025)

CrimeAlarm: Towards Intensive Intent Dynamics in Fine-grained Crime Prediction
by: Hu, Kaixi, et al.
Published: (2024)

Efficient and Personalized Mobile Health Event Prediction via Small Language Models
by: Wang, Xin, et al.
Published: (2024)

Predicting Human Mobility during Extreme Events via LLM-Enhanced Cross-City Learning
by: Tang, Yinzhou, et al.
Published: (2025)

Decision-centric fairness: Evaluation and optimization for resource allocation problems
by: De Vos, Simon, et al.
Published: (2025)

Enhancing Binary Encoded Crime Linkage Analysis Using Siamese Network
by: Zhan, Yicheng, et al.
Published: (2025)

Evaluating LLMs for Demographic-Targeted Social Bias Detection: A Comprehensive Benchmark Study
by: Majumdar, Ayan, et al.
Published: (2025)

Advancing Crime Linkage Analysis with Machine Learning: A Comprehensive Review and Framework for Data-Driven Approaches
by: Lima, Vinicius, et al.
Published: (2024)

A Question-centric Multi-experts Contrastive Learning Framework for Improving the Accuracy and Interpretability of Deep Sequential Knowledge Tracing Models
by: Zhang, Hengyuan, et al.
Published: (2024)

Divide-Conquer Transformer Learning for Predicting Electric Vehicle Charging Events Using Smart Meter Data
by: Ke, Fucai, et al.
Published: (2024)

Outlier Detection Bias Busted: Understanding Sources of Algorithmic Bias through Data-centric Factors
by: Ding, Xueying, et al.
Published: (2024)

Revisiting the Predictability of Performative, Social Events
by: Perdomo, Juan C.
Published: (2025)

CityLearn v2: Energy-flexible, resilient, occupant-centric, and carbon-aware management of grid-interactive communities
by: Nweye, Kingsley, et al.
Published: (2024)

An ExplainableFair Framework for Prediction of Substance Use Disorder Treatment Completion
by: Lucas, Mary M., et al.
Published: (2024)

Predictive Hotspot Mapping for Data-driven Crime Prediction
by: Sriram, Karthik, et al.
Published: (2026)

Time Series Analysis for Education: Methods, Applications, and Future Directions
by: Mao, Shengzhong, et al.
Published: (2024)

Quantifying Holistic Review: A Multi-Modal Approach to College Admissions Prediction
by: Zeng, Jun-Wei, et al.
Published: (2025)

Carbon Emission Prediction in China Considering New Quality Productive Forces Using a Deep & Corss Learning Modeling Framework
by: Xie, Haijin, et al.
Published: (2025)

Smartphone App Usage Prediction Using Points of Interest
by: Yu, Donghan, et al.
Published: (2017)

OpenCarbonEval: A Unified Carbon Emission Estimation Framework in Large-Scale AI Models
by: Yu, Zhaojian, et al.
Published: (2024)

Addressing Polarization and Unfairness in Performative Prediction
by: Jin, Kun, et al.
Published: (2024)

FlashST: A Simple and Universal Prompt-Tuning Framework for Traffic Prediction
by: Li, Zhonghang, et al.
Published: (2024)

TNANet: A Temporal-Noise-Aware Neural Network for Suicidal Ideation Prediction with Noisy Physiological Data
by: Liu, Niqi, et al.
Published: (2024)

Identifying Dealbreakers and Robust Policies for the Energy Transition Amid Unexpected Events
by: Coppitters, Diederik, et al.
Published: (2025)

ThinkTank-ME: A Multi-Expert Framework for Middle East Event Forecasting
by: Li, Haoxuan, et al.
Published: (2026)

The future of human-centric eXplainable Artificial Intelligence (XAI) is not post-hoc explanations
by: Swamy, Vinitra, et al.
Published: (2023)

Predicting and Understanding College Student Mental Health with Interpretable Machine Learning
by: Chowdhury, Meghna Roy, et al.
Published: (2025)

Causal Explainability of Machine Learning in Heart Failure Prediction from Electronic Health Records
by: Hou, Yina, et al.
Published: (2025)

Inference-Time Rule Eraser: Fair Recognition via Distilling and Removing Biased Rules
by: Zhang, Yi, et al.
Published: (2024)

Enhancing Collaborative Filtering-Based Course Recommendations by Exploiting Time-to-Event Information with Survival Analysis
by: Gharahighehi, Alireza, et al.
Published: (2025)

Personality Analysis from Online Short Video Platforms with Multi-domain Adaptation
by: An, Sixu, et al.
Published: (2024)

DisenGCD: A Meta Multigraph-assisted Disentangled Graph Learning Framework for Cognitive Diagnosis
by: Yang, Shangshang, et al.
Published: (2024)

Enhancing Multi-Attribute Fairness in Healthcare Predictive Modeling
by: Wang, Xiaoyang, et al.
Published: (2025)

AdvKT: An Adversarial Multi-Step Training Framework for Knowledge Tracing
by: Fu, Lingyue, et al.
Published: (2025)