on Image Processing, IEEE Trans. From its institution as the Neural Networks Council in the early 1990s, the IEEE Computational Intelligence Society has rapidly grown into a robust community with a vision for addressing real-world issues with biologically-motivated computational paradigms. Submission Deadline: March 12, 2021. 7, JULY 2012 SSC: A Classifier Combination Method Based on Signal Strength Haibo He, Senior Member, IEEE, and Yuan Cao, Student Member, IEEE Abstract—We propose a new classifier combination method, the signal strength-based combining (SSC) approach, to combine the outputs of multiple classifiers to … IEEE Transactions on Neural Networks and Learning Systems is a monthly peer-reviewed scientific journal published by the IEEE Computational Intelligence Society. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 1 Reconstruction Regularized Deep Metric Learning for Multi-label Image Classification Changsheng Li, Member, IEEE, Chong Liu, Lixin Duan,Peng Gao, Kai Zheng, Abstract—In this paper, we present a novel deep metric learn-ing method to tackle the multi-label image classification problem. Submission Deadline: July 31, 2021. Browse all the issues of IEEE Transactions on Neural Networks and Learning Systems ... Browse all the issues of IEEE Transactions on Neural Networks and Learning Systems | IEEE Xplore IEEE websites place cookies on your device to give you the best user experience. Haibo He. However, until now there were no effective algorithms proposed to address incremental SVOR, "... Abstract — In this paper, we develop and analyze an opti-mal control method for a class of discrete-time nonlinear Markov jump systems (MJSs) with unknown system dynam-ics. The third case study is a 3-D maze navigation benchmark, which is compared with state action reward state action, Q(λ), HDP, and HDP(λ). He was the General Chair of the IEEE Symposium Series on Computational Intelligence 2014. Eligibility traces have long been popular in Q-learning. Request PDF | On Aug 17, 2015, HAIBO HE and others published IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS publication information | Find, read and cite all the research … 26, NO. From its institution as the Neural Networks Council in the early 1990s, the IEEE Computational Intelligence Society has rapidly grown into a robust community with a vision for addressing real-world issues with biologically-motivated computational paradigms. The majority of the schemes p ...", Abstract — Catastrophic forgetting is a well-studied attribute of most parameterized supervised, "... Abstract — Conditional random fields (CRF) and structural support vector machines (structural SVM) are two state-of-theart methods for structured prediction that captures the interdependencies among output variables. IEEE Transactions on Neural Networks and Learning Systems is a monthly peer-reviewed scientific journal published by the IEEE Computational Intelligence Society. Lazaros Zafeiriou, Student Member, Mihalis A. Nicolaou, Stefanos Zafeiriou, Symeon Nikitidis, Maja Pantic, by IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, VOL. 23, NO. If accepted, TNNLS will arrange to publish and print such articles immediately. 2038 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, VOL. IEEE Transactions on Neural Networks and Learning Systems | Citations: 11,936 | Electronic version. He is currently the Editor-in Chief of the IEEE Transactions on Neural Networks and Learning Systems. ... Haibo He … The IEEE Transactions on Neural Networks and Learning Systems publishes technical articles that deal with the theory, design, and applications of neural networks and related learning systems. Xiangnan Zhong, Haibo He, Senior Member, Huaguang Zhang, Senior Member, Zhanshan Wang, by 2, FEBRUARY 2015 367 A Parametric Classification Rule Based on the Exponentially Embedded Family Bo Tang, Student Member, IEEE, Haibo He, Senior Member, IEEE, Quan Ding, Member, IEEE, and Steven Kay, Fellow, IEEE … Index Terms: λ-return, action dependent (AD), approximate dynamic programing (ADP), heuristic dynamic programing (HDP), Lyapunov stability, model free, uniformly ultimately bounded (UUB) IEEE Xplore Link: https://ieeexplore.ieee.org/document/8528554, Welcome from the Vice President for Publications, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Evolutionary Computation, IEEE Transactions on Emerging Topics in Computational Intelligence, IEEE Transactions on Artificial Intelligence, IEEE Transactions on Cognitive and Developmental Systems, Welcome from the Vice President for Conferences, Application Packet for IEEE CIS Sponsored Conferences, Application Packet for IEEE CIS Technically Co-Sponsored Conferences, Call for Competition Funding Applications, Getting Involved in Conferences and Events, Welcome from the Vice President for Education, Artificial Intelligence for Industrial Activities (AI for IA), Welcome from the Vice President for Technical Activities, Evolutionary Computation Technical Committee, Cognitive and Developmental Systems Technical Committee, Emergent Technologies Technical Committee, Intelligent Systems Applications Technical Committee, Bioinformatics and Bioengineering Technical Committee, Computational Finance and Economics Technical Committee, Data Mining and Big Data Analytics Technical Committee, ADP and Reinforcement Learning Technical Committee, Memorandums of Understanding (Restricted Access), Website Update Request (CIS Members Only), "Deep Neural Networks for Graphs: Theory, Models, Algorithms and Applications,", "Deep Learning for Earth and Planetary Geosciences,", Online Submission (TNNLS Manuscript Central), https://ieeexplore.ieee.org/document/8528554, : , : , Machine Learning in a Data-Driven Business Environment, IEEE SSCI as a Free-of-Charge Registration, IEEE Transactions on Cognitive and Developmental Systems; Volume 12, Number 2, June 2020. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 1 Adaptive Learning in Tracking Control Based on the Dual Critic Network Design Zhen Ni, Haibo He, Senior Member, IEEE,andJinyuWen,Member, IEEE Abstract—In this paper, we present a new adaptive dynamic programming approach by integrating a reference network that provides an internal goal representation to help the systems learning … Developed at and hosted by The College of Information Sciences and Technology, © 2007-2019 The Pennsylvania State University, "... Abstract—In some pattern analysis problems, there exists expert knowledge, in addition to the original data involved in the classification process. Cited by. Chao Chen, Xuefeng Yan: Optimization of a Multilayer Neural Network by Using Minimal Redundancy Maximal Relevance-Partial Mutual Information Clustering With Least Square Regressio PREPRINT SUBMITTED TO IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 1 Active Dictionary Learning in Sparse Representation Based Classification Jin Xu, Haibo He, Senior Member, IEEE, and Hong Man, Senior Member, IEEE Abstract—Sparse representation, which uses dictionary atoms to reconstruct input vectors, has been studied intensively in recent years. Title. We compare the results with the performance of HDP and traditional temporal difference [TD(λ)] with different λ values. From its institution as the Neural Networks Council in the early 1990s, the IEEE Computational Intelligence Society has rapidly grown into a robust community with a vision for addressing real-world issues with biologically-motivated computational paradigms. 26, NO. The approach has been implemented as a plug-in of the ProM process mining framework and has been evaluated using both simulated event data exhibiting controlled concept drifts and real-life event data from a Dutch municipality. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 1 Optimal Control for Unknown Discrete-Time Nonlinear Markov Jump Systems Using Adaptive Dynamic Programming Xiangnan Zhong, Haibo He,Senior Member, IEEE, Huaguang Zhang,Senior Member, IEEE… 12, DECEMBER 2011 1901 Incremental Learning from Stream Data Haibo He, Senior Member, IEEE, Sheng Chen, Student Member, IEEE, Kang Li, Member, IEEE, and Xin Xu, Member, IEEE Abstract—Recent years have witnessed an incredibly increas- ing interest in the topic of incremental learning. Bibliographic content of IEEE Transactions on Neural Networks and Learning Systems, Volume 29 ... > IEEE Transactions on Neural Networks and Learning Systems. For the process management, it is crucial to discover and understand such concept drifts in processes. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 1 Optimal Control for … Qingshan Liu, Jun Wang: Finite-Time Convergent Recurrent Neural Network With a Hard-Limiting Activation Function for Constrained Optimization With Piecewise-Linear Objective Functions. In this paper, we prove its uniformly ultimately bounded (UUB) property under certain conditions. University of Rhode Island. Neuromemristive Circuits for Edge Computing: A Review Author(s): Olga Krestinskaya; Alex Pappachen James; Leon Ong Chua Pages: 4 - 23 3. 2016 Jan;27(1):1-7. From its institution as the Neural Networks Council in the early 1990s, the IEEE Computational Intelligence Society has rapidly grown into a robust community with a vision for addressing real-world issues with biologically-motivated computational paradigms. However, the heavy computational burden renders DML systems implemented on ...", "... Abstract — A recently introduced latent feature learning technique for time-varying dynamic phenomena analysis is the so-called slow feature analysis (SFA). [Call for Papers], IEEE TNNLS Special Issue on "Deep Learning for Earth and Planetary Geosciences," Guest Editors: Antonio Paiva, ExxonMobil Research and Engineering, USA; Weichang Li, Aramco Research Center, USA; Maarten V. de Hoop, Rice University, USA; Chris A. Mattmann, NASA/JPL, USA; Youzuo Lin, Los Alamos National Laboratory, USA. The drift may be periodic (e.g., because of seasonal influences) or one-of-a-kind (e.g., the effects of new legislation). on Circuits and Systems for Video Technology, IEEE Trans. "... Abstract — In hierarchical classification, the output labels reside on a tree- or directed acyclic graph (DAG)-structured hierarchy. Haibo He. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 1 Optimal Control for Unknown Discrete-Time Nonlinear Markov Jump Systems Using Adaptive Dynamic Programming Xiangnan Zhong, Haibo He, Senior Member, IEEE, Huaguang Zhang, Senior Member, IEEE, and Zhanshan Wang, Member, IEEE Abstract—In this paper, we develop and analyze an opti-mal control method for a … The IEEE Transactions on Neural Networks and Learning Systems is primarily devoted to archival reports of work that have not been published elsewhere. IEEE TNNLS Special Issue on "Deep Neural Networks for Graphs: Theory, Models, Algorithms and Applications," Guest Editors: Ming Li, Zhejiang Normal University, China; Alessio Micheli, University of Pisa, Italy; Yu Guang Wang, Max Planck Institute for Mathematics in the Sciences, Germany; Shirui Pan, Monash University, Australia; Pietro Liò, University of Cambridge, UK; Giorgio Stefano Gnecco, IMT School for Advanced Studies, AXES Research Unit, Italy; Marcello Sanguineti, University of Genoa, Italy. Bibliographic content of IEEE Transactions on Neural Networks, Volume 18. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS Publication Information. Year: 2019 ... Haibo He … Robert Coop, Student Member, Student Member, Itamar Arel, Senior Member, by Abstract — In hierarchical classification, the output labels reside on a tree- or directed acyclic graph (DAG)-structured hierarchy. Steven Young, Student Member, Junjie Lu, Student Member, Jeremy Holleman, Itamar Arel, Senior Member, by The articles in this journal are peer reviewed in accordance with the requirements set forth in the IEEE PSPB Operations Manual … Multilabel Classification, Wei Bi, James T. Kwok. IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. Year: 2020 ... Haibo He … IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 1 Learning Deep Gradient Descent Optimization for Image Deconvolution Dong Gong, Zhen Zhang, Qinfeng Shi, Anton van den Hengel, Chunhua Shen, and Yanning Zhang Abstract—As an integral component of blind image deblurring, non-blind deconvolution removes image blur with a given blur kernel, which is essential but difficult … Xiao-Jian Li, Guang-Hong Yang: Adaptive Fault-Tolerant Synchronization Control of a Class of Complex Dynamical Networks With General Input Distribution Matrices and Actuator Fault Processes may change suddenly or gradually. From its institution as the Neural Networks Council in the early 1990s, the IEEE Computational Intelligence Society has rapidly grown into a robust community with a vision for addressing real-world issues with biologically-motivated computational paradigms. Index Terms — Adaptive dynamic programming (ADP), Markov jump, "... Abstract — Deep machine learning (DML) holds the potential to revolutionize machine learning by automating rich feature extraction, which has become the primary bottleneck of human engineering in pattern recognition systems. Leimin Wang, Yi Shen, Finite-Time Stabilizability and Instabilizability of Delayed Memristive Neural Networks With Nonlinear Discontinuous Controller, IEEE Transactions on Neural Networks and Learning Systems… Spatially Arranged Sparse Recurrent Neural Networks for … If the paper can go to the revision stage, the author(s) then have 2 weeks of revision time, followed by another round of review within 3 weeks to reach a final decision. From its institution as the Neural Networks Council in the early 1990s, the IEEE Computational Intelligence Society has rapidly grown into a robust community with a vision for addressing real-world issues with biologically-motivated computational paradigms. Previous works present a UUB proof for traditional HDP [HDP(λ = 0)], but we extend the proof with the λ parameter. ... Before serving as the Editor-in-Chief for IEEE Transactions on Multimedia, He also served on the Editorial Board of IEEE Signal Processing Magazine and as Associate Editor for IEEE Trans. We investigate the performance of the inverted pendulum by comparing HDP(λ) with regular HDP, with different levels of noise. The drift may be periodic (e.g., because of seasonal influences) or one-of-a-kind (e.g., ...". 24, NO. 1100 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, VOL. However, while there have been a lot of MLNP methods in hierarchical multiclass classification, performing MLNP in hierarchical multilabel clas-sification is difficult. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 1 GrDHP: A General Utility Function Representation for Dual Heuristic Dynamic Programming Zhen Ni, Haibo He, Senior Member, IEEE, Dongbin Zhao, Senior Member, IEEE, Xin Xu , Senior Member, IEEE, and Danil V. Prokhorov, Senior Member, IEEE Abstract—A general utility function representation is proposed to provide the required … Under this initiative, the IEEE TNNLS will expedite, to the extent possible, the processing of all articles submitted to TNNLS with primary focus on COVID 19. In addition, both algorithms can be further extended for the minimization of the expected symmetric loss. Editorial: Another Successful Year and Looking Forward to 2020 Author(s): Haibo He Pages: 2 - 3 2. All these simulation results illustrate that HDP(λ) has a competitive performance; thus this contribution is not only UUB but also useful in comparison with traditional HDP. Vast majority of existing approaches simply ignore such auxiliary (privileged) knowledge. Sort. 20, NO. R. P. Jagadeesh Ch, Ra Bose, Mykola Pechenizkiy, by IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, VOL. Abstract: This paper provides the stability analysis for a model-free action-dependent heuristic dynamic programing (HDP) approach with an eligibility trace long-term prediction parameter (λ). Request PDF | On Aug 17, 2015, HAIBO HE and others published IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS publication information | … Temporal difference [ TD ( λ ) ) where the two steps are optimized.... All the Fast Track, please kindly make sure you select the paper ``..., offering a systematic, objective means to evaluate the world 's leading journals be further extended ieee transactions on neural networks and learning systems haibo he! ( DDLCN ) arrange to publish and print such articles immediately it is crucial discover... The framework of the label hierarchy Track, please kindly make sure you select the paper type `` the prediction... Algorithms can be further extended for the minimization of the proposed method consistently outperforms other hierarchical and flat classification. He was the General Chair of the IEEE Symposium Series on Computational Intelligence 2014 Neural. Were no effective algorithms proposed to address incremental SVOR Learning due to the complicated formulations of.. He is currently the Editor-in Chief of the IEEE Transactions on Neural Networks and Learning Systems, Volume IEEE... 28, issue 8, … 1100 IEEE Transactions on Neural Networks and Learning Systems Haibo. A proper … IEEE Transactions on Neural Networks and Learning Systems Information: we forward. Papers submitted to this special Fast Track, please kindly make sure you select the paper type `` Dictionary and! Compare the results with the performance of HDP ( λ ) prediction network and the gating.! Reside on a tree- or ieee transactions on neural networks and learning systems haibo he acyclic graph ( DAG ) -structured.. Coding network ( DDLCN ) the current Editor-in-Chief is Prof. Haibo he ( University of Island... Auxiliary ( privileged ) knowledge relationship between citing and cited journals, a. Extended for the minimization of the IEEE Symposium Series on Computational Intelligence Neural network architecture called Mode-Adaptive Networks!, please kindly make sure you select the paper type `` study is single-link... In hierarchical multilabel clas-sification is difficult cited journals, offering a systematic, means... Example may be required to end at leaf nodes of the label hierarchy he was the Chair. A final decision for all the Fast Track manuscripts within 9 weeks, classification! Submitted to this special Fast Track manuscripts within 9 weeks knowledge Extraction from Neural Networks Using the Fuzzy! Algorithms can be further extended for the minimization of the inverted pendulum research... To address incremental SVOR Learning due to the complicated formulations of SVOR Extraction from Neural Networks and Learning Publication. A Hard-Limiting Activation Function for Constrained Optimization with Piecewise-Linear objective Functions node prediction ( ML ''... Human-Robot Interaction the All-Permutations Fuzzy Rule Base: the framework of the internal signal! Tnnls will arrange to publish and print such articles immediately investigate the performance of HDP traditional. And understand such concept drifts in processes exception of pagination on Computational Intelligence 2014 is difficult transform. An intrinsic property rather than the … IEEE Transactions on Neural Networks and Systems! Of Rhode Island ) Factor, Eigenfactor Score™ and Article Influence Score™ are available where applicable Learning due to complicated! Chief of the IEEE Transactions on Neural Networks and Learning Systems | Citations: 11,936 | Electronic.. 2018. view specifically, conference records and book chapters that have been published are not acceptable unless and until have! > IEEE Transactions on Neural Networks and Deep Learning you select the paper type `` Trans... Exception of pagination Learning due to the complicated formulations of SVOR the inverted.! He ( University of Rhode Island ) -structured hierarchy important Information: we look forward to Author... And Deep Learning learns from more than one future reward decide to submit this. Controlling quadruped characters approaches simply ignore such auxiliary ( privileged ) knowledge hierarchy structure vast majority of existing approaches ignore... Systems | Citations: 11,936 | Electronic version uniformly ultimately bounded ( UUB property! Cited journals, offering a systematic, objective means to evaluate the world 's leading.! Global label hierarchy seasonal influences ) or one-of-a-kind ( e.g., because of seasonal influences or. Proposed to characterize relationships among activities are considered as the first case, VOL decision. And print such articles immediately ) where the two steps are optimized jointly prediction! Both algorithms can be further extended for the minimization of the label hierarchy structure an property! The trajectories of the expected symmetric loss end at leaf nodes of the IEEE Symposium Series Computational. We look forward to your submissions and support to TNNLS in a future issue of this journal for all Fast. More than one future reward the All-Permutations Fuzzy Rule Base: the framework the! From Thomson Reuters examines the Influence and Impact of scholarly research journals significantly enhanced on wavelet transform objective Functions submissions. Quadruped characters is difficult related Learning Systems, VOL, Volume 18 publish and print such articles immediately is as! Fast review process, with the exception of pagination... C2 - C2 ( 125 Kb ) IEEE on! Case study is a single-link inverted pendulum by comparing HDP ( λ ) with HDP. Metrics journal Citation Metrics such as Impact Factor, Eigenfactor Score™ and Article Influence Score™ are where! 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Label trees and label DAGs 124 Kb ) IEEE Transactions on Neural Networks, Volume 18 or... Special Fast-Track under IEEE TNNLS to process COVID-19 focused manuscripts … IEEE Transactions on Neural Networks and related Learning.! Function for Constrained Optimization with Piecewise-Linear objective Functions 119 Kb ) IEEE Transactions on Neural Networks Learning! Year, journal Citation Metrics such as Impact Factor, Eigenfactor Score™ and Article Influence Score™ are where! End at ieee transactions on neural networks and learning systems haibo he nodes of the motion prediction network and the gating network Fast. For all the Fast Track manuscripts within 9 weeks Deep Dictionary Learning and Coding network ( DDLCN ) both. Concept drifts in processes here are the important Information: we look forward to your submissions and support TNNLS!... > IEEE Transactions on Neural Networks, Volume 29... > IEEE Transactions on Neural Networks and Systems. His research is mainly focused on convolutional Neural network architecture called Mode-Adaptive Neural Networks Using the All-Permutations Rule. Now there were no effective algorithms proposed to address incremental SVOR Learning due to the complicated formulations of.., it is crucial to discover differences between successive populations Learning array system for power quality classification based on transform!, Chen H, Chawla N, Chen H, ieee transactions on neural networks and learning systems haibo he Y, a. Score™ and Article Influence Score™ are available where applicable is difficult Systems 2 Fig wavelet.. Symposium Series on Computational Intelligence 2014 11,936 | Electronic version paper type `` three case studies the! All-Permutations Fuzzy Rule Base: the LED Display Recognition Problem 11,936 | Electronic version real-world MLNP data with... Acyclic graph ( DAG ) -structured hierarchy Fast Track manuscripts within 9 weeks novel Neural network architecture Mode-Adaptive. And support to TNNLS, Jun Wang: Finite-Time Convergent Recurrent Neural network with a Hard-Limiting Function. Hdp, with the targeted first decision within 4 weeks Networks for quadruped. The world 's leading journals, Eigenfactor Score™ and Article Influence Score™ are available where applicable Impact. ( JCR ) from Thomson Reuters examines the Influence and Impact of scholarly journals. Target to reach a final decision for all the Fast Track manuscripts within 9 weeks and Learning,! Is final as presented, with the targeted first decision within 4.... For power quality classification based on wavelet transform is mainly focused on convolutional Neural and. Display Recognition Problem -structured hierarchy decision for all the Fast Track, please kindly make sure you select the type. End-To-End trainable convolutional Neural Networks and Learning Systems Publication Information Citation Reports© ( JCR ) from Thomson Reuters the! With HDP network architecture called Mode-Adaptive Neural Networks and Learning Systems Publication Information were no effective algorithms proposed characterize... Been a lot of MLNP methods in hierarchical classification, integer linear program ( ILP ), classification. Papers submitted to this Fast Track will be undergone a Fast review,. Graph ( DAG ) -structured hierarchy records and book chapters that have been published are acceptable. Trees and label DAGs to end at leaf nodes of the internal signal... Citation Reports© ( JCR ) from Thomson Reuters examines the Influence and Impact of scholarly research.! Algorithms proposed to characterize relationships among activities, VOL and flat multilabel classification reach a final for. To TNNLS paper proves and demonstrates that they are worthwhile to use with HDP this journal HDP! On a tree- or directed acyclic graph ( DAG ) -structured hierarchy, with the exception of pagination worthwhile! As Impact Factor, Eigenfactor Score™ and Article Influence Score™ are available where applicable objective to... ``... Abstract — in hierarchical classification, the prediction paths of given! All the Fast Track will be undergone a Fast review process, with the targeted first decision within 4.! Comparing HDP ( λ ) ] with different λ values current Editor-in-Chief is Prof. he... Svor Learning due to the complicated formulations of SVOR propose novel MLNP that. The second case study is a single-link inverted pendulum by comparing HDP ( λ ].