Instruct: Given the title of a scientific paper, retrieve paper titles that are cited by the given paper.
Query: A Machine Learning Approach for Air Quality Prediction: Model Regularization and Optimization
Applying machine learning techniques on air quality data for real-time decision support
An online air pollution forecasting system using neural networks
HazeEst: Machine Learning Based Metropolitan Air Pollution Estimation From Fixed and Mobile Sensors
A Consistent Regularization Approach for Structured Prediction
Urban Air Pollution Monitoring System With Forecasting Models
Predicting and analyzing water quality using Machine Learning: A comprehensive model
Residual Autoencoder-LSTM for City Region Vehicle Emission Pollution Prediction
Regularization methods for neural networks and related models
Atmospheric Temperature Prediction using Support Vector Machines
A Hybrid ARIMA and Neural Network Model to Forecast Particulate Matter Concentration in Changsha , China
Comparison of neural network models with ARIMA and regression models for prediction of Houston's daily maximum ozone concentrations
Regularized extreme learning machine for regression with missing data
A Methodology for Building Regression Models using Extreme Learning Machine: OP-ELM
Reynolds-Averaged Turbulence Modeling Using Type I and Type II Machine Learning Frameworks with Deep Learning
Shrink Globally, Act Locally: Sparse Bayesian Regularization and Prediction
Machine Learning-augmented Predictive Modeling of Turbulent Separated Flows over Airfoils
Forecasting of ozone concentration in smart city using deep learning
Deep Air : Forecasting Air Pollution in Beijing , China
A Partition-Based Framework for Building and Validating Regression Models
Linear prediction models with graph regularization for web-page categorization
PCANet-II: When PCANet Meets the Second Order Pooling
dRMT: Disaggregated Programmable Switching
Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering
MHC class II proteins and disease: a structural perspective
Organic Control of Traffic Lights