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Anomaly detection in dynamic attributed networks

Neural computing & applications, 2021-03, Vol.33 (6), p.2125-2136

2021

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Nonparallel Support Vector Ordinal Regression

IEEE transactions on cybernetics, 2017-10, Vol.47 (10), p.3306-3317

2017

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Forward Prediction and Inverse Design of Nanophotonic Devices Based on Capsule Network

IEEE photonics journal, 2022-08, Vol.14 (4), p.1-8

2022

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A Survey on Feature Selection

Procedia computer science, 2016, Vol.91, p.919-926

2016

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Learning With Label Proportions via NPSVM

IEEE transactions on cybernetics, 2017-10, Vol.47 (10), p.3293-3305

2017

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Feature Selection With \ell Regularization

IEEE transaction on neural networks and learning systems, 2018-10, Vol.29 (10), p.4967-4982

2018

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Learning Robust Auto-Encoders With Regularizer for Linearity and Sparsity

IEEE access, 2019, Vol.7, p.17195-17206

2019

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Graph-Based Clustering via Group Sparsity and Manifold Regularization

IEEE access, 2019, Vol.7, p.172123-172135

2019

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Nonsmooth Penalized Clustering via \ell Regularized Sparse Regression

IEEE transactions on cybernetics, 2017-06, Vol.47 (6), p.1423-1433

2017

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A Brief Survey on Learning Based Methods for Vehicle Routing Problems

Procedia computer science, 2023, Vol.221, p.773-780

2023

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Optimality Conditions and a Smoothing Trust Region Newton Method for NonLipschitz Optimization

SIAM journal on optimization, 2013-01, Vol.23 (3), p.1528-1552

2013

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A NEW TRUST-REGION ALGORITHM FOR NONLINEAR CONSTRAINED OPTIMIZATION

Journal of computational mathematics, 2010, Vol.28 (1), p.72-86

2010

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Sparse optimization guided pruning for neural networks

Neurocomputing (Amsterdam), 2024-03, Vol.574, p.127280, Article 127280

2024

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Feature Selection of Network Data VIA ℓ2,p Regularization

Cognitive computation, 2020-11, Vol.12 (6), p.1217-1232

2020

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Two New Decomposition Algorithms for Training Bound-Constrained Support Vector Machines

Foundations of computing and decision sciences, 2015-03, Vol.40 (1), p.67-86

2015

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A Brief Survey on Graph Anomaly Detection

Procedia computer science, 2024, Vol.242, p.1263-1270

2024

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Knowledge Graph Embedding by Double Limit Scoring Loss

IEEE transactions on knowledge and data engineering, 2022-12, Vol.34 (12), p.5825-5839

2022

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DigGCN: Learning Compact Graph Convolutional Networks via Diffusion Aggregation

IEEE transactions on cybernetics, 2022-02, Vol.52 (2), p.912-924

2022

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A brief survey on Computational Gromov-Wasserstein distance

Procedia computer science, 2022, Vol.199, p.697-702

2022

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Adaboost-LLP: A Boosting Method for Learning With Label Proportions

IEEE transaction on neural networks and learning systems, 2018-08, Vol.29 (8), p.3548-3559

2018

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Fast kernel extreme learning machine for ordinal regression

Knowledge-based systems, 2019-08, Vol.177, p.44-54

2019

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A Brief Survey of Distribution Robust Graph Neural Networks

Procedia computer science, 2024, Vol.242, p.1281-1286

2024

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A unified pre-training and adaptation framework for combinatorial optimization on graphs

Science China. Mathematics, 2024-06, Vol.67 (6), p.1439-1456

2024

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A fast algorithm for nonsmooth penalized clustering

Neurocomputing (Amsterdam), 2018-01, Vol.273, p.583-592

2018

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Feature selection with MCP \[^2\] regularization

Neural computing & applications, 2019-10, Vol.31 (10), p.6699-6709

2019

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Anomaly detection in dynamic attributed networks

Nonparallel Support Vector Ordinal Regression

Forward Prediction and Inverse Design of Nanophotonic Devices Based on Capsule Network

A Survey on Feature Selection

Learning With Label Proportions via NPSVM

Feature Selection With \ell Regularization

Learning Robust Auto-Encoders With Regularizer for Linearity and Sparsity

Graph-Based Clustering via Group Sparsity and Manifold Regularization

Nonsmooth Penalized Clustering via \ell Regularized Sparse Regression

A Brief Survey on Learning Based Methods for Vehicle Routing Problems

Optimality Conditions and a Smoothing Trust Region Newton Method for NonLipschitz Optimization

A NEW TRUST-REGION ALGORITHM FOR NONLINEAR CONSTRAINED OPTIMIZATION

Sparse optimization guided pruning for neural networks

Feature Selection of Network Data VIA ℓ2,p Regularization

Two New Decomposition Algorithms for Training Bound-Constrained Support Vector Machines

A Brief Survey on Graph Anomaly Detection

Knowledge Graph Embedding by Double Limit Scoring Loss

DigGCN: Learning Compact Graph Convolutional Networks via Diffusion Aggregation

A brief survey on Computational Gromov-Wasserstein distance

Adaboost-LLP: A Boosting Method for Learning With Label Proportions

Fast kernel extreme learning machine for ordinal regression

A Brief Survey of Distribution Robust Graph Neural Networks

A unified pre-training and adaptation framework for combinatorial optimization on graphs

A fast algorithm for nonsmooth penalized clustering

Feature selection with MCP \[^2\] regularization

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