Liang Zhao

ORCID

Publication Activity (10 Years)

Years Active: 2000-2023
Publications (10 Years): 64

Top Venues

Instituto Tecnológico de Aeronáutica, São José dos Campos, São Paulo, Brazil (PHD)

Education History

Instituto Tecnológico de Aeronáutica, São José dos Campos, São Paulo, Brazil

PHD

Publications

Jiang Liu, Donghong Ji, Jingye Li, Dongdong Xie, Chong Teng, Liang Zhao, Fei Li
TOE: A Grid-Tagging Discontinuous NER Model Enhanced by Embedding Tag/Word Relations and More Fine-Grained Tags. IEEE ACM Trans. Audio Speech Lang. Process. 31 (2023)
Esteban Wilfredo Vilca Zuñiga, Caetano Mazzoni Ranieri, Liang Zhao, Jó Ueyama, Yu-tao Zhu, Donghong Ji
Maximizing portfolio profitability during a cryptocurrency downtrend: A Bitcoin Blockchain transaction-based approach. INNS DLIA@IJCNN (2023)
Sérgio Baldo Júnior, Murillo G. Carneiro, João-Batista Destro-Filho, Liang Zhao, Renato Tinós
Classification of coma etiology using convolutional neural networks and long-short term memory networks. IJCNN (2023)
Leandro Anghinoni, Yu-tao Zhu, Donghong Ji, Liang Zhao
TransGNN: A Transductive Graph Neural Network with Graph Dynamic Embedding. IJCNN (2023)
Jianglong Yan, Leandro Anghinoni, Yu-tao Zhu, Weiguang Liu, Gen Li, Qiusheng Zheng, Liang Zhao
Characterizing data patterns with core-periphery network modeling. J. Comput. Sci. 66 (2023)
Luan V. C. Martins, Adriana Passos Bueno, Alexandre Defelicibus, Rodrigo D. Drummond, Renan Valieris, Yu-Tao Zhu, Israel Tojal da Silva, Liang Zhao
WSI2ML - An Open-Source Whole Slide Image Annotation Software for Machine Learning Applications. WebMedia (2023)
Didier A. Vega-Oliveros, Liang Zhao, Anderson Rocha, Lilian Berton
Link Prediction Based on Stochastic Information Diffusion. IEEE Trans. Neural Networks Learn. Syst. 33 (8) (2022)
Adriano Henrique Cantão, Alessandra Alaniz Macedo, Liang Zhao, José Augusto Baranauskas
Feature Ranking from Random Forest Through Complex Network's Centrality Measures - A Robust Ranking Method Without Using Out-of-Bag Examples. ADBIS (2022)
Laercio de Oliveira Junior, Florian Stelzer, Liang Zhao
Clustered and deep echo state networks for signal noise reduction. Mach. Learn. 111 (8) (2022)
Tiago Colliri, Liang Zhao
Stock market trend detection and automatic decision-making through a network-based classification model. Nat. Comput. 20 (4) (2021)
Breno Nunes, Tiago Colliri, Marcelo Lauretto, Weiguang Liu, Liang Zhao
Anomaly Detection in Brazilian Federal Government Purchase Cards Through Unsupervised Learning Techniques. BRACIS (2) (2021)
Tiago Colliri, Marcia Minakawa, Liang Zhao
Detecting Early Signs of Insufficiency in COVID-19 Patients from CBC Tests Through a Supervised Learning Approach. BRACIS (2) (2021)
Tiago Colliri, Weiguang Liu, Liang Zhao
An Optimized Modularity-Based High Level Classification Model. IJCNN (2020)
Benjamin Miranda Tabak, Thiago C. Silva, Liang Zhao, Ahmet Sensoy
Applications of Machine Learning Methods in Complex Economics and Financial Networks. Complex. 2020 (2020)
Moshé Cotacallapa, Lilian Berton, Leonardo N. Ferreira, Marcos G. Quiles, Liang Zhao, Elbert E. N. Macau, Didier A. Vega-Oliveros
Measuring the engagement level in encrypted group conversations by using temporal networks. IJCNN (2020)
Fabricio A. Breve, Marcos G. Quiles, Liang Zhao, Elbert E. N. Macau
Chaotic Phase Synchronization and Desynchronization in an Oscillator Network for Object Selection. CoRR (2020)
Rafael D. Rodrigues, Liang Zhao, Qiusheng Zheng, Junbao Zhang
A tourist walk approach for internal and external outlier detection. Neurocomputing 393 (2020)
Leonardo N. Ferreira, Didier Augusto Vega-Oliveros, Moshé Cotacallapa, Manoel F. Cardoso, Marcos G. Quiles, Liang Zhao, Elbert E. N. Macau
Chronnet: a network-based model for spatiotemporal data analysis. CoRR (2020)
Matheus A. De Castro Santos, Didier Augusto Vega-Oliveros, Liang Zhao, Lilian Berton
Classifying El Niño-Southern Oscillation Combining Network Science and Machine Learning. IEEE Access 8 (2020)
Fabricio Aparecido Breve, Liang Zhao, Marcos Gonçalves Quiles
Particle Competition and Cooperation for Semi-Supervised Learning with Label Noise. CoRR (2020)
Tiago Colliri, Alexandre C. B. Delbem, Liang Zhao
Predicting the Evolution of COVID-19 Cases and Deaths Through a Correlations-Based Temporal Network. BRACIS (2) (2020)
Leonardo N. Ferreira, Didier Augusto Vega-Oliveros, Liang Zhao, Manoel F. Cardoso, Elbert E. N. Macau
Global fire season severity analysis and forecasting. Comput. Geosci. 134 (2020)
Murillo G. Carneiro, Ran Cheng, Liang Zhao, Yaochu Jin
Particle swarm optimization for network-based data classification. Neural Networks 110 (2019)
Xubo Gao, Qiusheng Zheng, Filipe Alves Neto Verri, Rafael D. Rodrigues, Liang Zhao
Particle Competition for Multilayer Network Community Detection. ICMLC (2019)
Didier Augusto Vega-Oliveros, Moshé Cotacallapa, Leonardo N. Ferreira, Marcos G. Quiles, Liang Zhao, Elbert E. N. Macau, Manoel F. Cardoso
From spatio-temporal data to chronological networks: an application to wildfire analysis. SAC (2019)
Tiago Colliri, Liang Zhao
A Network-Based Model for Optimizing Returns in the Stock Market. BRACIS (2019)
Leandro Anghinoni, Liang Zhao, Donghong Ji, Heng Pan
Time series trend detection and forecasting using complex network topology analysis. Neural Networks 117 (2019)
Thiago Henrique Cupertino, Murillo Guimarães Carneiro, Qiusheng Zheng, Junbao Zhang, Liang Zhao
A scheme for high level data classification using random walk and network measures. Expert Syst. Appl. 92 (2018)
Filipe Alves Neto Verri, Roberto Alves Gueleri, Qiusheng Zheng, Junbao Zhang, Liang Zhao
Network community detection via iterative edge removal in a flocking-like system. CoRR (2018)
Didier Augusto Vega-Oliveros, Moshé Cotacallapa, Leonardo N. Ferreira, Marcos G. Quiles, Liang Zhao, Elbert E. N. Macau, Manoel F. Cardoso
From spatio-temporal data to chronological networks: An application to wildfire analysis. CoRR (2018)
Leandro Anghinoni, Liang Zhao, Qiusheng Zheng, Junbo Zhang
Time Series Trend Detection and Forecasting Using Complex Network Topology Analysis. IJCNN (2018)
Filipe Alves Neto Verri, Renato Tinós, Liang Zhao
Feature Learning in Feature-Sample Networks Using Multi-Objective Optimization. CEC (2018)
Renato Tinós, Liang Zhao, Francisco Chicano, L. Darrell Whitley
NK Hybrid Genetic Algorithm for Clustering. IEEE Trans. Evol. Comput. 22 (5) (2018)
Murillo G. Carneiro, Liang Zhao
Analysis of Graph Construction Methods in Supervised Data Classification. BRACIS (2018)
Murillo Guimarães Carneiro, Liang Zhao
Organizational Data Classification Based on the Importance Concept of Complex Networks. IEEE Trans. Neural Networks Learn. Syst. 29 (8) (2018)
Tiago Colliri, Donghong Ji, Heng Pan, Liang Zhao
A Network-Based High Level Data Classification Technique. IJCNN (2018)
Filipe Alves Neto Verri, Paulo Roberto Urio, Liang Zhao
Network Unfolding Map by Vertex-Edge Dynamics Modeling. IEEE Trans. Neural Networks Learn. Syst. 29 (2) (2018)
João Roberto Bertini Jr., Maria do Carmo Nicoletti, Liang Zhao
Attribute-based Decision Graphs: A framework for multiclass data classification. Neural Networks 85 (2017)
Murillo G. Carneiro, Thiago Henrique Cupertino, Ran Cheng, Yaochu Jin, Liang Zhao
Nature-Inspired Graph Optimization for Dimensionality Reduction. ICTAI (2017)
Murillo G. Carneiro, Thiago Henrique Cupertino, Liang Zhao, João Luís Garcia Rosa
Semi-supervised Semantic Role Labeling for Brazilian Portuguese. J. Inf. Data Manag. 8 (2) (2017)
Thiago Ferreira Covoes, Liang Zhao
Low and high level classification using stacking. IJCNN (2017)
Rafael D. Rodrigues, Liang Zhao, Qiusheng Zheng, Junbao Zhang
Structural outlier detection: A tourist walk approach. ICNC-FSKD (2017)
Filipe Alves Neto Verri, Renato Tinós, Liang Zhao
Feature learning in feature-sample networks using multi-objective optimization. CoRR (2017)
Murillo G. Carneiro, João Luís Garcia Rosa, Qiusheng Zheng, Xiaoming Liu, Liang Zhao
Improving semantic role labeling using high-level classification in complex networks. ICNC-FSKD (2017)
Paulo Roberto Urio, Filipe Alves Neto Verri, Liang Zhao
Semi-Supervised Classification by Particle Competition in Complex Network's Edges. Int. J. Pattern Recognit. Artif. Intell. 30 (9) (2016)
João Roberto Bertini Jr., Maria do Carmo Nicoletti, Liang Zhao
An embedded imputation method via Attribute-based Decision Graphs. Expert Syst. Appl. 57 (2016)
Filipe Alves Neto Verri, Liang Zhao
Random Walk in Feature-Sample Networks for Semi-supervised Classification. BRACIS (2016)
Filipe Alves Neto Verri, Paulo Roberto Urio, Liang Zhao
Network Unfolding Map by Edge Dynamics Modeling. CoRR (2016)
Renato Tinós, Liang Zhao, Francisco Chicano, L. Darrell Whitley
A New Evaluation Function for Clustering: The NK Internal Validation Criterion. GECCO (2016)
Andres Eduardo Coca Salazar, Liang Zhao
Musical rhythmic pattern extraction using relevance of communities in networks. Inf. Sci. 329 (2016)
Fabio Alessandro Oliveira da Silva, Liang Zhao
A Network of Neural Oscillators for Fractal Pattern Recognition. Neural Process. Lett. 44 (1) (2016)
Andres Eduardo Coca Salazar, Liang Zhao
Musical Scales Recognition via Deterministic Walk in a Graph. BRACIS (2016)
Bilzã Araújo, Liang Zhao
Data heterogeneity consideration in semi-supervised learning. Expert Syst. Appl. 45 (2016)
Alcides X. Benicasa, Marcos G. Quiles, Thiago C. Silva, Liang Zhao, Roseli A. F. Romero
An object-based visual selection framework. Neurocomputing 180 (2016)
Murillo G. Carneiro, Liang Zhao, Ran Cheng, Yaochu Jin
Network structural optimization based on swarm intelligence for highlevel classification. IJCNN (2016)
Leonardo Nascimento Ferreira, Liang Zhao
Time series clustering via community detection in networks. Inf. Sci. 326 (2016)
Fabricio A. Breve, Marcos G. Quiles, Liang Zhao
Interactive Image Segmentation of Non-contiguous Classes Using Particle Competition and Cooperation. ICCSA (1) (2015)
Thiago Christiano Silva, Liang Zhao
High-level pattern-based classification via tourist walks in networks. Inf. Sci. 294 (2015)
Fabricio A. Breve, Liang Zhao, Marcos G. Quiles
Particle competition and cooperation for semi-supervised learning with label noise. Neurocomputing 160 (2015)
Leonardo Nascimento Ferreira, Liang Zhao
A Time Series Clustering Technique based on Community Detection in Networks. INNS Conference on Big Data (2015)
Paulo Roberto Urio, Filipe Alves Neto Verri, Liang Zhao
Semi-supervised learning by edge domination in complex networks. ICNC (2015)
Fabricio A. Breve, Marcos Gonçalves Quiles, Liang Zhao
Interactive image segmentation using particle competition and cooperation. IJCNN (2015)
Thiago Henrique Cupertino, Liang Zhao, Murillo G. Carneiro
Network-based supervised data classification by using an heuristic of ease of access. Neurocomputing 149 (2015)
Leonardo Nascimento Ferreira, Liang Zhao
Time Series Clustering via Community Detection in Networks. CoRR (2015)
Leonardo Nascimento Ferreira, Liang Zhao
Detecting Time Series Periodicity Using Complex Networks. BRACIS (2014)
Murillo G. Carneiro, Thiago Henrique Cupertino, Liang Zhao
K-associated optimal network for graph embedding dimensionality reduction. IJCNN (2014)
Fabio Alessandro Oliveira da Silva, Liang Zhao
Recognizing Fractal Patterns Using a Ring of Phase Oscillators. BRACIS (2014)
João Roberto Bertini Jr., Maria do Carmo Nicoletti, Liang Zhao
Imputation of missing data supported by Complete p-Partite attribute-based Decision Graphs. IJCNN (2014)
Roberto Alves Gueleri, Thiago Henrique Cupertino, André Carlos Ponce de Leon Ferreira de Carvalho, Liang Zhao
A flocking-like technique to perform semi-supervised learning. IJCNN (2014)
Murillo G. Carneiro, João Luís Garcia Rosa, Alneu de Andrade Lopes, Liang Zhao
Network-based data classification: combining K-associated optimal graphs and high-level prediction. J. Braz. Comput. Soc. 20 (1) (2014)
Fabiano Berardo de Sousa, Liang Zhao
Evaluating and Comparing the IGraph Community Detection Algorithms. BRACIS (2014)
Andres Eduardo Coca Salazar, Liang Zhao
Rhythmic Pattern Extraction by Community Detection in Complex Networks. BRACIS (2014)
Thiago Henrique Cupertino, Roberto Alves Gueleri, Liang Zhao
A semi-supervised classification technique based on interacting forces. Neurocomputing 127 (2014)
Alcides Xavier Benicasa, Marcos G. Quiles, Thiago C. Silva, Liang Zhao, Roseli A. Francelin Romero
An Object-Based Visual Selection Model Combining Physical Features and Memory. BRACIS (2014)
Xiaoming Liang, Liang Zhao
Effect of nonidentical signal phases on signal amplification of two coupled excitable neurons. Neurocomputing 127 (2014)
Fabio Willian Zamoner, Liang Zhao
A Network-Based Semi-supervised Outlier Detection Technique Using Particle Competition and Cooperation. BRACIS (2013)
João Roberto Bertini Jr., Liang Zhao, Alneu de Andrade Lopes
An incremental learning algorithm based on the K-associated graph for non-stationary data classification. Inf. Sci. 246 (2013)
Thiago C. Silva, Liang Zhao, Thiago Henrique Cupertino
Handwritten Data Clustering Using Agents Competition in Networks. J. Math. Imaging Vis. 45 (3) (2013)
Thiago Henrique Cupertino, Liang Zhao
Semi-Supervised Learning Using Random Walk Limiting Probabilities. ISNN (2) (2013)
Xiaoming Liang, Liang Zhao
Phase-Noise-Induced Resonance in Arrays of Coupled Excitable Neural Models. IEEE Trans. Neural Networks Learn. Syst. 24 (8) (2013)
Thiago Christiano Silva, Liang Zhao
Uncovering overlapping cluster structures via stochastic competitive learning. Inf. Sci. 247 (2013)
João Roberto Bertini Jr., Maria do Carmo Nicoletti, Liang Zhao
Attribute-based Decision Graphs for multiclass data classification. IEEE Congress on Evolutionary Computation (2013)
Alcides Xavier Benicasa, Marcos G. Quiles, Liang Zhao, Roseli A. F. Romero
Top-Down Biasing and Modulation for Object-Based Visual Attention. ICONIP (3) (2013)
Thiago Henrique Cupertino, Liang Zhao
Bias-Guided Random Walk for Network-Based Data Classification. ISNN (2) (2013)
Bilzã Araújo, Liang Zhao
Detecting and labeling representative nodes for network-based semi-supervised learning. IJCNN (2013)
Thiago Henrique Cupertino, Thiago C. Silva, Liang Zhao
Classification of multiple observation sets via network modularity. Neural Comput. Appl. 23 (7-8) (2013)
João R. Bertini, Maria do Carmo Nicoletti, Liang Zhao
Ensemble of complete P-partite graph classifiers for non-stationary environments. IEEE Congress on Evolutionary Computation (2013)
Thiago Christiano Silva, Liang Zhao
High Level Pattern Classification via Tourist Walks in Networks CoRR (2013)
João Roberto Bertini Jr., Liang Zhao
A Purity Measure Based Transductive Learning Algorithm. ISNN (2) (2013)
Fabricio A. Breve, Liang Zhao
Fuzzy community structure detection by particle competition and cooperation. Soft Comput. 17 (4) (2013)
Filipe Alves Neto, Liang Zhao
High level data classification based on network entropy. IJCNN (2013)
Thiago Henrique Cupertino, Jean Huertas, Liang Zhao
Data clustering using controlled consensus in complex networks. Neurocomputing 118 (2013)
Andres E. Coca, Débora C. Corrêa, Liang Zhao
Computer-aided music composition with LSTM neural network and chaotic inspiration. IJCNN (2013)
Fabiano Berardo de Sousa, Liang Zhao
Investigation of complex dynamics in a recurrent neural network with network community structure and asymmetric weight matrix. IJCNN (2013)
Thiago C. Silva, Liang Zhao
Preventing Error Propagation in Semi-supervised Learning. ISNN (1) (2012)
Xiaoming Liang, Liang Zhao
Firing Activity Induced by Nonidentical Signal Phases in Two Coupled Excitable Neurons. SBRN (2012)
Xiaoming Liang, Liang Zhao, Zonghua Liu
Enhancing Weak Signal Transmission Through a Feedforward Network. IEEE Trans. Neural Networks Learn. Syst. 23 (9) (2012)
Bilzã Araújo, Liang Zhao
Robustness Analysis of Network-Based Semi-supervised Learning Algorithms. SBRN (2012)
Fabricio A. Breve, Liang Zhao
Particle Competition and Cooperation to Prevent Error Propagation from Mislabeled Data in Semi-supervised Learning. SBRN (2012)
Thiago Christiano Silva, Liang Zhao
Stochastic Competitive Learning in Complex Networks. IEEE Trans. Neural Networks Learn. Syst. 23 (3) (2012)

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Publication Activity (10 Years)

Top Topics

Top Venues

Liang Zhao