Transfer Learning for Assessing Heavy Metal Pollution in Seaports Sediments
Fuente:
arXiv
Saved in:
| Main Authors: | Lai, Tin, Farid, Farnaz, Kuan, Yueyang, Zhang, Xintian |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Predict-then-Optimize for Seaport Power-Logistics Scheduling: Generalization across Varying Tasks Stream
by: Pu, Chuanqing, et al.
Published: (2025)
by: Pu, Chuanqing, et al.
Published: (2025)
Edge Caching Optimization with PPO and Transfer Learning for Dynamic Environments
by: Niknia, Farnaz, et al.
Published: (2024)
by: Niknia, Farnaz, et al.
Published: (2024)
Smart Ensemble Learning Framework for Predicting Groundwater Heavy Metal Pollution
by: Ansah-Narh, T., et al.
Published: (2026)
by: Ansah-Narh, T., et al.
Published: (2026)
Towards Neural Architecture Search for Transfer Learning in 6G Networks
by: Orucu, Adam, et al.
Published: (2024)
by: Orucu, Adam, et al.
Published: (2024)
Convolutional versus Dense Neural Networks: Comparing the Two Neural Networks Performance in Predicting Building Operational Energy Use Based on the Building Shape
by: Nazari, Farnaz, et al.
Published: (2021)
by: Nazari, Farnaz, et al.
Published: (2021)
Efficient Deep Learning for Short-Term Solar Irradiance Time Series Forecasting: A Benchmark Study in Ho Chi Minh City
by: Hoang, Tin
Published: (2025)
by: Hoang, Tin
Published: (2025)
Assessing Pre-Trained Models for Transfer Learning Through Distribution of Spectral Components
by: Zhang, Tengxue, et al.
Published: (2024)
by: Zhang, Tengxue, et al.
Published: (2024)
Assessing Electricity Service Unfairness with Transfer Counterfactual Learning
by: Wei, Song, et al.
Published: (2023)
by: Wei, Song, et al.
Published: (2023)
Non-Stationary Bandit Learning via Predictive Sampling
by: Liu, Yueyang, et al.
Published: (2022)
by: Liu, Yueyang, et al.
Published: (2022)
Can Explainable AI Assess Personalized Health Risks from Indoor Air Pollution?
by: Sarkar, Pritisha, et al.
Published: (2025)
by: Sarkar, Pritisha, et al.
Published: (2025)
Beyond Activation Alignment: The Geometry of Neural Sensitivity
by: Yavari, Amirhossein, et al.
Published: (2026)
by: Yavari, Amirhossein, et al.
Published: (2026)
Assessing and Predicting Air Pollution in Asia: A Regional and Temporal Study (2018-2023)
by: Rahman, Anika, et al.
Published: (2025)
by: Rahman, Anika, et al.
Published: (2025)
Federated Learning for Privacy-Preserving Medical AI
by: Hoang, Tin
Published: (2026)
by: Hoang, Tin
Published: (2026)
In-Context Linear Regression Demystified: Training Dynamics and Mechanistic Interpretability of Multi-Head Softmax Attention
by: He, Jianliang, et al.
Published: (2025)
by: He, Jianliang, et al.
Published: (2025)
Transferable Graph Condensation from the Causal Perspective
by: Du, Huaming, et al.
Published: (2026)
by: Du, Huaming, et al.
Published: (2026)
Automatic Cross-Domain Transfer Learning for Linear Regression
by: Liu, Xinshun, et al.
Published: (2020)
by: Liu, Xinshun, et al.
Published: (2020)
A New Perspective To Understanding Multi-resolution Hash Encoding For Neural Fields
by: Luo, Steven Tin Sui
Published: (2025)
by: Luo, Steven Tin Sui
Published: (2025)
Adaptive Weighted LSSVM for Multi-View Classification
by: Lighvan, Farnaz Faramarzi, et al.
Published: (2025)
by: Lighvan, Farnaz Faramarzi, et al.
Published: (2025)
From Data Leak to Secret Misses: The Impact of Data Leakage on Secret Detection Models
by: Soltaniani, Farnaz, et al.
Published: (2026)
by: Soltaniani, Farnaz, et al.
Published: (2026)
Adaptive Unknown Fault Detection and Few-Shot Continual Learning for Condition Monitoring in Ultrasonic Metal Welding
by: Eslaminia, Ahmadreza, et al.
Published: (2026)
by: Eslaminia, Ahmadreza, et al.
Published: (2026)
Assessing Foundation Models' Transferability to Physiological Signals in Precision Medicine
by: Christenson, Matthias, et al.
Published: (2024)
by: Christenson, Matthias, et al.
Published: (2024)
A Comprehensive Analysis on the Learning Curve in Kernel Ridge Regression
by: Cheng, Tin Sum, et al.
Published: (2024)
by: Cheng, Tin Sum, et al.
Published: (2024)
Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R
by: Guerrero, Pablo Robin, et al.
Published: (2025)
by: Guerrero, Pablo Robin, et al.
Published: (2025)
Training Machine Learning Models on Human Spatio-temporal Mobility Data: An Experimental Study [Experiment Paper]
by: Liu, Yueyang, et al.
Published: (2025)
by: Liu, Yueyang, et al.
Published: (2025)
Predicting Air Pollution in Cork, Ireland Using Machine Learning
by: Rashidunnabi, Md, et al.
Published: (2025)
by: Rashidunnabi, Md, et al.
Published: (2025)
Unlock the Correlation between Supervised Fine-Tuning and Reinforcement Learning in Training Code Large Language Models
by: Chen, Jie, et al.
Published: (2024)
by: Chen, Jie, et al.
Published: (2024)
Mode-Shape Expansion Using Physics-Constrained Gaussian Process Regression
by: Ghahari, Farid
Published: (2026)
by: Ghahari, Farid
Published: (2026)
Improved Graph-based semi-supervised learning Schemes
by: Bozorgnia, Farid
Published: (2024)
by: Bozorgnia, Farid
Published: (2024)
Shared DIFF Transformer
by: Cang, Yueyang, et al.
Published: (2025)
by: Cang, Yueyang, et al.
Published: (2025)
Multi-Task Learning for Metal Alloy Property Prediction: An Empirical Study of Negative Transfer and Mitigation Strategies
by: Kang, Sungwoo
Published: (2025)
by: Kang, Sungwoo
Published: (2025)
AED: An black-box NLP classifier model attacker
by: Liu, Yueyang, et al.
Published: (2021)
by: Liu, Yueyang, et al.
Published: (2021)
GCN-RL Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learning
by: Wang, Hanrui, et al.
Published: (2020)
by: Wang, Hanrui, et al.
Published: (2020)
Fractional Heat Kernel for Semi-Supervised Graph Learning with Small Training Sample Size
by: Bozorgnia, Farid, et al.
Published: (2025)
by: Bozorgnia, Farid, et al.
Published: (2025)
Graph-Based Semi-Supervised Segregated Lipschitz Learning
by: Bozorgnia, Farid, et al.
Published: (2024)
by: Bozorgnia, Farid, et al.
Published: (2024)
Wasserstein Transfer Learning
by: Zhang, Kaicheng, et al.
Published: (2025)
by: Zhang, Kaicheng, et al.
Published: (2025)
Missing Data Imputation using Neural Cellular Automata
by: Luu, Tin, et al.
Published: (2025)
by: Luu, Tin, et al.
Published: (2025)
A Model Ensemble-Based Post-Processing Framework for Fairness-Aware Prediction
by: Zhao, Zhouting, et al.
Published: (2026)
by: Zhao, Zhouting, et al.
Published: (2026)
Selecting Subsets of Source Data for Transfer Learning with Applications in Metal Additive Manufacturing
by: Tang, Yifan, et al.
Published: (2024)
by: Tang, Yifan, et al.
Published: (2024)
Complete Chess Games Enable LLM Become A Chess Master
by: Zhang, Yinqi, et al.
Published: (2025)
by: Zhang, Yinqi, et al.
Published: (2025)
Exploring Open-world Continual Learning with Knowns-Unknowns Knowledge Transfer
by: Li, Yujie, et al.
Published: (2025)
by: Li, Yujie, et al.
Published: (2025)
Similar Items
-
Predict-then-Optimize for Seaport Power-Logistics Scheduling: Generalization across Varying Tasks Stream
by: Pu, Chuanqing, et al.
Published: (2025) -
Edge Caching Optimization with PPO and Transfer Learning for Dynamic Environments
by: Niknia, Farnaz, et al.
Published: (2024) -
Smart Ensemble Learning Framework for Predicting Groundwater Heavy Metal Pollution
by: Ansah-Narh, T., et al.
Published: (2026) -
Towards Neural Architecture Search for Transfer Learning in 6G Networks
by: Orucu, Adam, et al.
Published: (2024) -
Convolutional versus Dense Neural Networks: Comparing the Two Neural Networks Performance in Predicting Building Operational Energy Use Based on the Building Shape
by: Nazari, Farnaz, et al.
Published: (2021)