Shiliang Sun
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Shiliang Suncomputer-science Degrees
Computer Science
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Machine Learning
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Computer Science
Shiliang Sun's Degrees
- Bachelors Computer Science Peking University
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(Suggest an Edit or Addition)Shiliang Sun's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- A survey of multi-view machine learning (2013) (730)
- A bayesian network approach to traffic flow forecasting (2006) (598)
- Multi-view learning overview: Recent progress and new challenges (2017) (582)
- A review of natural language processing techniques for opinion mining systems (2017) (366)
- A Survey of Optimization Methods From a Machine Learning Perspective (2019) (238)
- A review of optimization methodologies in support vector machines (2011) (216)
- A survey of multi-source domain adaptation (2015) (197)
- An adaptive k-nearest neighbor algorithm (2010) (136)
- An experimental evaluation of ensemble methods for EEG signal classification (2007) (126)
- Network-Scale Traffic Modeling and Forecasting with Graphical Lasso (2011) (122)
- Variational Inference for Infinite Mixtures of Gaussian Processes With Applications to Traffic Flow Prediction (2011) (119)
- Adaptive feature extraction for EEG signal classification (2006) (113)
- PAC-bayes bounds with data dependent priors (2012) (107)
- Multi-view Laplacian Support Vector Machines (2011) (107)
- A subject transfer framework for EEG classification (2012) (102)
- Multiview Uncorrelated Discriminant Analysis (2016) (94)
- Multitask learning for EEG-based biometrics (2008) (86)
- Sparse Semi-supervised Learning Using Conjugate Functions (2010) (85)
- A Survey on Multiview Clustering (2017) (84)
- Consensus and complementarity based maximum entropy discrimination for multi-view classification (2016) (83)
- Multitask multiclass support vector machines: Model and experiments (2013) (82)
- Robust Co-Training (2011) (73)
- Traffic Flow Forecasting Using a Spatio-temporal Bayesian Network Predictor (2005) (73)
- Neural network multitask learning for traffic flow forecasting (2008) (73)
- Multi-View Maximum Entropy Discrimination (2013) (71)
- A review of adaptive feature extraction and classification methods for EEG-based brain-computer interfaces (2014) (70)
- The Selective Random Subspace Predictor for Traffic Flow Forecasting (2007) (69)
- Joint Type Inference on Entities and Relations via Graph Convolutional Networks (2019) (68)
- Multiple-view multiple-learner active learning (2010) (64)
- Multitask Twin Support Vector Machines (2012) (58)
- Multi-source Transfer Learning with Multi-view Adaboost (2012) (58)
- A Survey on Multi-View Clustering (2022) (57)
- High-Order Gaussian Process Dynamical Models for Traffic Flow Prediction (2016) (56)
- A review of Nyström methods for large-scale machine learning (2015) (53)
- Multiple-View Multiple-Learner Semi-Supervised Learning (2011) (53)
- Manifold Partition Discriminant Analysis (2017) (52)
- Alternative Multiview Maximum Entropy Discrimination (2016) (52)
- Multiview Learning With Generalized Eigenvalue Proximal Support Vector Machines (2019) (49)
- Active learning with extremely sparse labeled examples (2010) (49)
- Multi-view Laplacian twin support vector machines (2014) (49)
- PAC-Bayes analysis of multi-view learning (2014) (46)
- Multi-view clustering ensembles (2013) (45)
- A Bayesian network approach to time series forecasting of short-term traffic flows (2004) (45)
- Manifold-preserving graph reduction for sparse semi-supervised learning (2014) (44)
- Extracting Entities and Relations with Joint Minimum Risk Training (2018) (43)
- PAC-Bayes bounds for stable algorithms with instance-dependent priors (2018) (43)
- Multi-View Support Vector Machines with the Consensus and Complementarity Information (2020) (43)
- Multi-view twin support vector machines (2015) (42)
- The random electrode selection ensemble for EEG signal classification (2008) (42)
- Multitask centroid twin support vector machines (2015) (39)
- An Algorithm on Multi-View Adaboost (2010) (38)
- Semi-supervised multi-view maximum entropy discrimination with expectation Laplacian regularization (2019) (36)
- Hierarchical Multi-view Fisher Discriminant Analysis (2009) (35)
- A review of deterministic approximate inference techniques for Bayesian machine learning (2013) (34)
- Soft Margin Consistency Based Scalable Multi-View Maximum Entropy Discrimination (2016) (33)
- The Extreme Energy Ratio Criterion for EEG Feature Extraction (2008) (33)
- Short-term traffic flow forecasting using Sampling Markov Chain method with incomplete data (2004) (33)
- Assessing features for electroencephalographic signal categorization (2005) (32)
- Variational Dependent Multi-output Gaussian Process Dynamical Systems (2014) (31)
- A Visual Attention Based Approach to Text Extraction (2010) (31)
- Local within-class accuracies for weighting individual outputs in multiple classifier systems (2010) (30)
- Semi-supervised feature extraction for EEG classification (2013) (29)
- Multi-view Transfer Learning with Adaboost (2011) (29)
- Multi-view learning for visual violence recognition with maximum entropy discrimination and deep features (2019) (28)
- View Construction for Multi-view Semi-supervised Learning (2011) (28)
- Multiview Uncorrelated Locality Preserving Projection (2020) (28)
- Cross-domain representation-learning framework with combination of class-separate and domain-merge objectives (2012) (27)
- Weighted Data Normalization Based on Eigenvalues for Artificial Neural Network Classification (2009) (27)
- Bayesian Network Methods for Traffic Flow Forecasting with Incomplete Data (2004) (27)
- Policy-based reinforcement learning for time series anomaly detection (2020) (26)
- Multi-kernel maximum entropy discrimination for multi-view learning (2016) (26)
- Kernel regression with sparse metric learning (2013) (25)
- An optimal kernel feature extractor and its application to EEG signal classification (2006) (25)
- Traffic flow forecasting based on multitask ensemble learning (2009) (24)
- General multi-view semi-supervised least squares support vector machines with multi-manifold regularization (2020) (24)
- Hierarchical Distance Metric Learning for Large Margin Nearest Neighbor Classification (2011) (23)
- Multi-View Representation Learning With Deep Gaussian Processes (2020) (23)
- Infinite mixtures of multivariate Gaussian processes (2013) (23)
- Multitask multiclass privileged information support vector machines (2012) (23)
- Multiview Machine Learning (2019) (22)
- An empirical evaluation of linear and nonlinear kernels for text classification using Support Vector Machines (2010) (22)
- Subspace ensembles for classification (2007) (21)
- Extreme energy difference for feature extraction of EEG signals (2010) (21)
- Modeling and recognizing human trajectories with beta process hidden Markov models (2015) (21)
- Active learning of Gaussian processes with manifold-preserving graph reduction (2014) (21)
- Nonparametric Sparse Matrix Decomposition for Cross-View Dimensionality Reduction (2017) (20)
- Hybrid neural conditional random fields for multi-view sequence labeling (2020) (20)
- An Accelerated Linearly Convergent Stochastic L-BFGS Algorithm (2019) (20)
- Kernel Regression with a Mahalanobis Metric for Short-Term Traffic Flow Forecasting (2008) (19)
- Semisupervised Support Vector Machines With Tangent Space Intrinsic Manifold Regularization (2016) (19)
- Learning On-Line Classification via Decorrelated LMS Algorithm: Application to Brain-Computer Interfaces (2005) (19)
- Trajectory-based human activity recognition with hierarchical dirichlet process hidden Markov models (2013) (19)
- Transfer Learning with Part-Based Ensembles (2013) (18)
- Nonlinear Combination of Multiple Kernels for Support Vector Machines (2010) (18)
- Text detection in nature scene images using two-stage nontext filtering (2015) (17)
- Incomplete multi-view clustering with cosine similarity (2021) (17)
- Transferable Discriminative Dimensionality Reduction (2011) (17)
- Multi-link traffic flow forecasting using neural networks (2010) (17)
- Domain Adaptation with Twin Support Vector Machines (2018) (16)
- General multi-view learning with maximum entropy discrimination (2019) (16)
- Adaptive EEG signal classification using stochastic approximation methods (2008) (16)
- Multi-view uncorrelated linear discriminant analysis with applications to handwritten digit recognition (2014) (15)
- LCBM: A Multi-View Probabilistic Model for Multi-Label Classification (2020) (15)
- Probabilistic inference of Bayesian neural networks with generalized expectation propagation (2020) (15)
- Tangent space intrinsic manifold regularization for data representation (2013) (15)
- Ensemble Learning Methods for Classifying EEG Signals (2007) (15)
- Multitask Multiclass Support Vector Machines (2011) (14)
- Gaussian process versus margin sampling active learning (2015) (14)
- An Improved Random Subspace Method and Its Application to EEG Signal Classification (2007) (14)
- Ensembles of Feature Subspaces for Object Detection (2009) (14)
- PAC-Bayes bounds for twin support vector machines (2017) (12)
- A Centroid k-Nearest Neighbor Method (2010) (12)
- Dynamical ensemble learning with model-friendly classifiers for domain adaptation (2012) (12)
- A Multitask Learning Approach to Face Recognition Based on Neural Networks (2008) (12)
- Online Anomaly Detection with Sparse Gaussian Processes (2019) (11)
- Improved Margin Sampling for Active Learning (2014) (11)
- Semantic Features for Multi-view Semi-supervised and Active Learning of Text Classification (2008) (10)
- The stochastic approximation method for adaptive Bayesian classifiers: towards online brain–computer interfaces (2011) (10)
- Promoting active learning with mixtures of Gaussian processes (2020) (10)
- Multi-view Regularized Gaussian Processes (2017) (10)
- Hierarchical Large Margin Nearest Neighbor Classification (2010) (10)
- Variational Mixtures of Gaussian Processes for Classification (2017) (10)
- Energy feature extraction of EEG signals and a case study (2008) (9)
- Neural Langevin Dynamical Sampling (2020) (9)
- Semi-supervised feature extraction with local temporal regularization for EEG classification (2011) (8)
- Single-task and multitask sparse Gaussian processes (2013) (8)
- Multiview Variational Sparse Gaussian Processes (2020) (8)
- ASHF-Net: Adaptive Sampling and Hierarchical Folding Network for Robust Point Cloud Completion (2021) (8)
- On the On-line Learning Algorithms for EEG Signal Classification in Brain Computer Interfaces (2005) (8)
- Adversarial robustness and attacks for multi-view deep models (2021) (8)
- Applying a multitask feature sparsity method for the classification of semantic relations between nominals (2012) (7)
- Evolutionary classifier ensembles for semi-supervised learning (2010) (7)
- GNN-XML: Graph Neural Networks for Extreme Multi-label Text Classification (2020) (7)
- RL-VAEGAN: Adversarial defense for reinforcement learning agents via style transfer (2021) (7)
- Location Dependent Dirichlet Processes (2017) (7)
- Variational multimodal machine translation with underlying semantic alignment (2021) (7)
- Multi-view Gaussian processes with posterior consistency (2021) (6)
- Sparse Multimodal Gaussian Processes (2017) (6)
- Short-Term Traffic Flow Forecasting Using Expanded Bayesian Network for Incomplete Data (2004) (6)
- Spatial Filter Selection with LASSO for EEG Classification (2010) (6)
- Local Tangent Space Discriminant Analysis (2016) (6)
- Semi-supervised Multitask Learning via Self-training and Maximum Entropy Discrimination (2012) (5)
- Attentive multi-view reinforcement learning (2020) (5)
- Sparse Gaussian processes with manifold-preserving graph reduction (2014) (5)
- Dynamical Sampling with Langevin Normalization Flows (2019) (5)
- High Reliable Multi-View Semi-Supervised Learning with Extremely Sparse Labeled Data (2008) (4)
- Multi-view Opinion Mining with Deep Learning (2018) (4)
- Part-Based Transfer Learning (2011) (4)
- Revisiting Gaussian Process Dynamical Models (2015) (4)
- Large-scale Opinion Relation Extraction with Distantly Supervised Neural Network (2017) (3)
- Generalizing expectation propagation with mixtures of exponential family distributions and an application to Bayesian logistic regression (2019) (3)
- A Learning Error Analysis for Structured Prediction with Approximate Inference (2017) (3)
- A semi-supervised classification method based on transduction of labeled data (2004) (3)
- TiRGN: Time-Guided Recurrent Graph Network with Local-Global Historical Patterns for Temporal Knowledge Graph Reasoning (2022) (3)
- Alpha-divergence minimization with mixed variational posterior for Bayesian neural networks and its robustness against adversarial examples (2021) (3)
- Sparse Kernel Regression for Traffic Flow Forecasting (2011) (3)
- Multi-view Deep Gaussian Processes (2018) (3)
- Multi-view multi-label active learning with conditional Bernoulli mixtures (2018) (3)
- BGNN-XML: Bilateral Graph Neural Networks for Extreme Multi-label Text Classification (2022) (3)
- Multi-view Learning and Deep Learning for Microscopic Neuroblastoma Pathology Image Diagnosis (2018) (3)
- Multiview Transfer Learning and Multitask Learning (2019) (3)
- Key Course Selection for Academic Early Warning Based on Gaussian Processes (2016) (3)
- Feature selection for ensembles using Non-dominated Sorting in Genetic Algorithms (2010) (3)
- Multiview Clustering (2019) (2)
- Off-line Signature Verification Based on Multitask Learning (2011) (2)
- Deep multi-view multiclass twin support vector machines (2022) (2)
- Active Learning Methods with Deep Gaussian Processes (2018) (2)
- Multiview Deep Learning (2019) (2)
- Semisupervised Tangent Space Discriminant Analysis (2015) (2)
- An Online Learning Algorithm for Bilinear Models (2015) (2)
- Conditional Random Fields for Multiview Sequential Data Modeling (2020) (2)
- Educational and Non-educational Text Classification Based on Deep Gaussian Processes (2017) (1)
- Stick-Breaking Dependent Beta Processes with Variational Inference (2020) (1)
- Key Course Selection in Academic Warning with Sparse Regression (2016) (1)
- Multi-view multi-label active learning with conditional Bernoulli mixtures (2022) (1)
- Weighting Individual Classifiers by Local Within-Class Accuracies (2009) (1)
- Semismooth Newton Algorithm for Efficient Projections onto ℓ1, ∞-norm Ball (2020) (1)
- Uncorrelated transferable feature extraction for signal classification in brain-computer interfaces (2015) (1)
- Supervised Bayesian sparse coding for classification (2014) (1)
- Multi-view Deep Gaussian Process with a Pre-training Acceleration Technique (2020) (1)
- PAC-Bayes Analysis for Twin Support Vector Machines (2015) (1)
- Discussion of ‘ Stability Selection ’ , by Nicolai Meinshausen and Peter Bühlmann (2010) (1)
- Sequential training of semi-supervised classification based on sparse Gaussian process regression (2012) (1)
- Multi-View Deep Attention Network for Reinforcement Learning (Student Abstract) (2020) (1)
- Using a Random Subspace Predictor to Integrate Spatial and Temporal Information for Traffic Flow Forecasting (2005) (1)
- Decomposed slice sampling for factorized distributions (2020) (1)
- DetexNet: Accurately Diagnosing Frequent and Challenging Pediatric Malignant Tumors (2020) (1)
- Multiview learning with variational mixtures of Gaussian processes (2020) (1)
- A Theory of Kernel Extreme Energy Difference for Feature Extraction of EEG Signals (2009) (1)
- Multi-task Sparse Gaussian Processes with Improved Multi-task Sparsity Regularization (2014) (1)
- Adversarial Attacks for Multi-view Deep Models (2020) (0)
- Enhancing Unsupervised Domain Adaptation via Semantic Similarity Constraint for Medical Image Segmentation (2022) (0)
- Local Tangent Space Discriminant Analysis (2015) (0)
- Adversarially Training MCMC with Non-Volume-Preserving Flows (2022) (0)
- Anchor-based incomplete multi-view spectral clustering (2022) (0)
- Kernel Local Fisher Discriminant Analysis-Based Prediction on Protein O-Glycosylation Sites Using SVM (2015) (0)
- Multiview Subspace Learning (2019) (0)
- Multiview Supervised Learning (2019) (0)
- Semi-supervised feature extraction for EEG classification (2012) (0)
- L G ] 2 4 D ec 2 01 7 Neural Network Multitask Learning for Traffic Flow Forecasting (2018) (0)
- Semismooth Newton Algorithm for Efficient Projections onto $\ell_{1, \infty}$-norm Ball (2020) (0)
- View Construction (2019) (0)
- Multiview Semi-supervised Learning (2019) (0)
- Importance Weighted Extreme Energy Ratio for EEG Classification (2010) (0)
- L G ] 3 A pr 2 01 8 1 A Survey on MultiView Clustering (2018) (0)
- Sparse uncorrelated cross-domain feature extraction for signal classification in brain-computer interfaces (2015) (0)
- A Variant of Gaussian Process Dynamical Systems (2019) (0)
- L G ] 2 4 D ec 2 01 7 Weighted Data Normalization Based on Eigenvalues for Artificial Neural Network Classification (2018) (0)
- A Theoretical Derivation of the Kernel Extreme Energy Ratio Method for EEG Feature Extraction (2008) (0)
- Multiview Active Learning (2019) (0)
- Intelligent Educational Data Analysis with Gaussian Processes (2018) (0)
- A survey of multi-view machine learning (2013) (0)
- Variational hidden conditional random fields with beta processes (2017) (0)
- SagaNet: A Small Sample Gated Network for Pediatric Cancer Diagnosis (2021) (0)
- Active learning of Gaussian processes with manifold-preserving graph reduction (2014) (0)
- Variational Beta Process Hidden Markov Models with Shared Hidden States for Trajectory Recognition (2021) (0)
- Multi-view Defense with Adversarial Autoencoders (2021) (0)
- Classifying EEG signals in Fisher discriminant spaces by random electrode selection (2008) (0)
- Adversarial Attack with Pattern Replacement (2019) (0)
- Variational Langevin Hamiltonian Monte Carlo for Distant Multi-modal Sampling (2019) (0)
- Performance Improvement of Traffic Flow Prediction Model using Combination of Support Vector Machine and Rough Set (2018) (0)
- Bayesian Adversarial Attack on Graph Neural Networks (Student Abstract) (2020) (0)
- A Conditional Random Fields Based Framework for Multiview Sequential Data Modeling (2019) (0)
- INTRINSIC MANIFOLD REGULARIZATION FOR DATA REPRESENTATION (2013) (0)
- A review of deterministic approximate inference techniques for Bayesian machine learning (2013) (0)
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