Learning Both Dynamic-Shared and Dynamic-Specific Patterns for Chaotic Time-Series Prediction

Robust manifold broad learning system for large-scale noisy chaotic time series prediction: A perturbation perspective

(2019) Shoubo Feng et al.   NEURAL NETWORKS

Flow Prediction in Spatio-Temporal Networks Based on Multitask Deep Learning

(2019) Junbo Zhang et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Co-evolutionary multi-task learning for dynamic time series prediction

(2018) Rohitash Chandra et al.   APPLIED SOFT COMPUTING

Recurrent Air Quality Predictor Based on Meteorology- and Pollution-Related Factors

(2018) Ke Gu et al.   IEEE Transactions on Industrial Informatics

Multi-Target Regression via Robust Low-Rank Learning

(2018) Xiantong Zhen et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Robust Regression Estimation Based on Low-Dimensional Recurrent Neural Networks

(2018) Youshen Xia et al.   IEEE Transactions on Neural Networks and Learning Systems

Multitarget Sparse Latent Regression

(2018) Xiantong Zhen et al.   IEEE Transactions on Neural Networks and Learning Systems

Nonuniform State Space Reconstruction for Multivariate Chaotic Time Series

(2018) Min Han et al.   IEEE Transactions on Cybernetics

Adaptive Granulation-Based Prediction for Energy System of Steel Industry

(2018) Tianyu Wang et al.   IEEE Transactions on Cybernetics

High-Order Temporal Correlation Model Learning for Time-Series Prediction

(2018) Peiguang Jing et al.   IEEE Transactions on Cybernetics

Electricity Demand Forecasting by Multi-Task Learning

(2018) Jean-Baptiste Fiot et al.   IEEE Transactions on Smart Grid

Structured Manifold Broad Learning System: A Manifold Perspective for Large-Scale Chaotic Time Series Analysis and Prediction

(2018) Min Han et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Universal Approximation Capability of Broad Learning System and Its Structural Variations

(2018) C. L. Philip Chen et al.   IEEE Transactions on Neural Networks and Learning Systems

Hierarchical Feature Selection for Random Projection

(2018) Qi Wang et al.   IEEE Transactions on Neural Networks and Learning Systems

Online Multi-Task Learning Framework for Ensemble Forecasting

(2017) Jianpeng Xu et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Algorithm-Dependent Generalization Bounds for Multi-Task Learning

(2017) Tongliang Liu et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Feature Selection Based on Structured Sparsity: A Comprehensive Study

(2017) Jie Gui et al.   IEEE Transactions on Neural Networks and Learning Systems

The chaotic dynamics of high-dimensional systems

(2016) Marjan Abdechiri et al.   NONLINEAR DYNAMICS

Multi-task support vector machines for feature selection with shared knowledge discovery

(2016) Sen Wang et al.   SIGNAL PROCESSING

Multiple/Single-View Human Action Recognition via Part-Induced Multitask Structural Learning

(2015) An-An Liu et al.   IEEE Transactions on Cybernetics

Statistical analysis of autoregressive fractionally integrated moving average models in R

(2013) Javier E. Contreras-Reyes et al.   COMPUTATIONAL STATISTICS

A Convex Formulation for Learning a Shared Predictive Structure from Multiple Tasks

(2012) Jianhui Chen et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

A feasible method for optimization with orthogonality constraints

(2012) Zaiwen Wen et al.   MATHEMATICAL PROGRAMMING

Chaotic Time Series Prediction Based on a Novel Robust Echo State Network

(2012) Decai Li et al.   IEEE Transactions on Neural Networks and Learning Systems

Extreme Learning Machine for Regression and Multiclass Classification

(2011) Guang-Bin Huang et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS

Convex multi-task feature learning

(2008) Andreas Argyriou et al.   MACHINE LEARNING