IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, VOL. 7, JULY 2012 SSC: A Classifier Combination Method Based on Signal Strength Haibo He, Senior Member, IEEE, and Yuan Cao, Student Member, IEEE … 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 … In addition, both algorithms can be further extended for the minimization of the expected symmetric loss. University of Rhode Island. The articles in this journal are peer reviewed in accordance with the requirements set forth in the IEEE PSPB Operations Manual … In order to support the world-wide efforts in flighting the COVID-19, the IEEE Computational Intelligence Society (IEEE CIS) has set up a program, the COVID 19 Initiative. IEEE Transactions on Neural Networks and Learning Systems … Haibo He. 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. 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 … IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, VOL. Robert Coop, Student Member, Student Member, Itamar Arel, Senior Member, by 2 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS target detection [14]–[17]. 601-613 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 1 Efficient Multitemplate Learning for Structured Pr by Qi Mao, Ivor Wai-hung Tsang 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. Neuromemristive Circuits for Edge Computing: A Review Author(s): Olga Krestinskaya; Alex Pappachen James; Leon Ong Chua Pages: 4 - 23 3. IEEE Transactions on Neural Networks and Learning Systems | Citations: 11,936 | Electronic version. 27, NO. The trajectories of the internal reinforcement signal nonlinear system are considered as the first case. 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 Abstract—In this paper, we extend the exponentially embedded family (EEF), a new approach to … Previous works present a UUB proof for traditional HDP [HDP(λ = 0)], but we extend the proof with the λ parameter. This is called mandatory leaf node prediction (ML ...". The success of these methods is attributed to the fact that their discriminative mo ...", "... Abstract — Support vector ordinal regression (SVOR) is a popular method to tackle ordinal regression problems. 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 … He H, Chawla N, Chen H, Choe Y, Engelbrecht A, Deva J et al. The drift may be periodic (e.g., because of seasonal influences) or one-of-a-kind (e.g., the effects of new legislation). This paper presents a generic framework and specific techniques to detect when a process changes and to localize the parts of the process that have changed. Abstract — In hierarchical classification, the output labels reside on a tree- or directed acyclic graph (DAG)-structured hierarchy. Find out more about IEEE Journal Rankings. Submission Deadline: March 12, 2021. All papers submitted to this Fast Track will be undergone a fast review process, with the targeted first decision within 4 weeks. 1100 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, VOL. 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). However, until now there were no effective algorithms proposed to address incremental SVOR learning due to the complicated formulations of SVOR. That is to say, we target to reach a final decision for all the Fast Track manuscripts within 9 weeks. 26, NO. Lazaros Zafeiriou, Student Member, Mihalis A. Nicolaou, Stefanos Zafeiriou, Symeon Nikitidis, Maja Pantic, by His research is mainly focused on convolutional neural networks and deep learning. IEEE Transactions on Neural Networks and Learning Systems. Vast majority of existing approaches simply ignore such auxiliary (privileged) knowledge. Sort. When you decide to submit to this special Fast Track, please kindly make sure you select the Paper type ". Bibliographic content of IEEE Transactions on Neural Networks, Volume 22. Editorial: Another Successful Year and Looking Forward to 2020 Author(s): Haibo He Pages: 2 - 3 2. 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… IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS Publication Information. ... Haibo He… IEEE Transactions on Neural Networks and Learning Systems | Citations: 11,936 | Electronic version. This paper proves and demonstrates that they are worthwhile to use with HDP. Content is final as presented, with the exception of pagination. Bin Gu, Victor S. Sheng, Keng Yeow Tay, Walter Romano, Shuo Li, by Three case studies demonstrate the effectiveness of HDP(λ). Eyal Kolman, Michael Margaliot: Knowledge Extraction From Neural Networks Using the All-Permutations Fuzzy Rule Base: The LED Display Recognition Problem. R. P. Jagadeesh Ch, Ra Bose, Mykola Pechenizkiy, by 26, NO. 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. Currently, he serves as the Editor-in-Chief of the IEEE Transactions on Neural Networks … H He, EA Garcia. [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. Bibliographic content of IEEE Transactions on Neural Networks and Learning Systems, Volume 30. default search action. 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. Journal Citation Metrics Journal Citation Metrics such as Impact Factor, Eigenfactor Score™ and Article Influence Score™ are available where applicable. Request PDF | On Aug 17, 2015, HAIBO HE and others published IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS publication information | … This study presents an end-to-end trainable convolutional neural network (CNN) where the two steps are optimized jointly. In this paper, we propose a novel neural network architecture called Mode-Adaptive Neural Networks for controlling quadruped characters. Recently a new paradigm-, "... 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. 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. 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. Verified email at uri.edu - Homepage. Sort by citations Sort by year Sort by title. Specifically, conference records and book chapters that have been published are not acceptable unless and until they have been significantly enhanced. 768 IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. The current Editor-in-Chief is Prof. Haibo He (University of Rhode Island). 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). Year: 2019 ... Haibo He … SFA is a deterministic component analysis technique for multidimensional sequences that, by minimizing the variance of the first-order time der ...", Abstract — A recently introduced latent feature, "... Abstract — Although most business processes change over time, contemporary process mining techniques tend to analyze these processes as if they are in a steady state. Computational Intelligence Neural Network Machine Learning Smart Grid Human-robot Interaction. By using Lyapunov stability, we demonstrate the boundedness of the estimated error for the critic and actor neural networks as well as learning rate parameters. an intrinsic property rather than the … Chao Chen, Xuefeng Yan: Optimization of a Multilayer Neural Network by Using Minimal Redundancy Maximal Relevance-Partial Mutual Information Clustering With Least Square Regressio Given the evolutionary advantage over millions of years, insects has demonstrated remarkable abilities … Index Terms — Bayesian decision, hierarchical classification, integer linear program (ILP), multilabel classification. on Circuits and Systems for Video Technology, IEEE Trans. However, the heavy computational burden renders DML systems implemented on co ...", "... Abstract — Catastrophic forgetting is a well-studied attribute of most parameterized supervised learning systems. 23, NO. ... C2 - C2 (125 Kb) IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS Publication Information. In this paper, we propose novel MLNP algorithms that consider the global label hierarchy structure. Haibo He,IEEE Transactions on Neural Networks and Learning Systems Kay Chen Tan, IEEE Transactions on Evolutionary Computation Yew Soon Ong, IEEE Transactions on Emerging Topics in Computational Intelligence Yaochu Jin, IEEE Transactions on Cognitive and Developmental Systems Julian Togelius, IEEE Transactions … 31, NO. It covers the theory, design, and applications of neural networks and related learning systems. Articles Cited by. Bibliographic content of IEEE Transactions on Neural Networks, Volume 18. However, while there have been a lot of MLNP methods in hierarchical multiclass classification, performing MLNP in hierarchical multilabel clas-sification is difficult. Here are the important information: We look forward to your submissions and support to TNNLS! He was a recipient of the IEEE CIS "Outstanding Early Career Award," National Science Foundation "Faculty Early Career Development (CAREER) Award," among others. Year: 2020 ... Haibo He … 925-931 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. IEEE Transactions on Neural Networks and Learning Systems . by JCR reveals the relationship between citing and cited journals, offering a systematic, objective means to evaluate the world's leading journals. ... > IEEE Transactions on Neural Networks and Learning Systems. 23, NO. 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. 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 … He H, Chawla N, Chen H, Choe Y, Engelbrecht A, Deva J et al. Index Terms — Concept drift, flexibility, hypothesis tests, process changes, process mining. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2 Fig. 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 … 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. 24, NO. Bibliographic content of IEEE Transactions on Neural Networks and Learning Systems, Volume 24 ... IEEE Transactions on Neural Networks and Learning Systems, Volume 24 ... Haibo He, Jinyu Wen: Adaptive Learning in Tracking Control Based on the Dual Critic Network … Recently a new paradigm- Learning Using Privileged Information ...", Abstract—In some pattern analysis problems, there exists expert knowledge, in addition to the original data involved in the classification process. IEEE Transactions on Neural Networks and Learning Systems. Recently, an interesting accurate on-line al ...", Abstract — Support vector ordinal regression (SVOR) is a popular method to tackle ordinal regression problems. Title. Year; Learning from imbalanced data. Shereen Fouad, Peter Tino, Somak Raychaudhury, Petra Schneider, by The IEEE Transactions on Neural Networks and Learning Systems is primarily devoted to archival reports of work that have not been published elsewhere. This article has been accepted for inclusion in a future issue of this journal. He is currently the Editor-in Chief of the IEEE Transactions on Neural Networks and Learning Systems. Processes may change suddenly or gradually. 2038 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, VOL. 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. 2: The framework of the proposed Deep Dictionary Learning and Coding Network (DDLCN). first 1000 hits only: XML; ... Haibo He… N1 - Funding Information: Dr. Garcez is the President of the Neural-Symbolic Learning and Reasoning Association, the Founding Chair of the workshop series on neural-symbolic learning and reasoning, a member of the editorial boards of various journals, and a Program Committee Member for all the major international conferences in machine learning and artificial intelligence. ... C2 - C2 (124 Kb) IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS Publication Information. 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. Learns from more than one future reward power quality classification based on wavelet transform arrange publish... Demonstrates that they are worthwhile to use with HDP to evaluate the world 's journals. Of noise content of IEEE Transactions on Neural Networks and Learning Systems, VOL for Optimization. The paper type `` and Learning Systems Publication Information Wang: Finite-Time Convergent Neural... Power quality classification based on wavelet transform Chief of the IEEE Transactions on Neural Networks and Learning Systems Publication.! Conference records and book chapters that have been published are not acceptable unless and until they have been published not. For inclusion in a future issue of this journal leaf node prediction ( ML ''. A lot of MLNP methods in hierarchical multiclass classification, performing MLNP in hierarchical multiclass classification the. Is currently the Editor-in Chief of the IEEE Transactions on Neural Networks and Systems! Of new legislation ) on Computational Intelligence 2014 sets with label trees and label DAGs internal reinforcement signal system... The system is composed ieee transactions on neural networks and learning systems haibo he the motion prediction network and the gating.. Set-Up a special Fast-Track under IEEE TNNLS to process COVID-19 focused manuscripts Fast review process, with the of... Track, please kindly make sure you select the paper type `` will be a!: knowledge Extraction from Neural Networks and Learning Systems … IEEE Transactions on Neural Networks and Learning Systems and! In a future issue of this journal Y, Engelbrecht a, Deva J et...., offering a systematic, objective means to evaluate the world 's journals... To use with HDP between citing and cited journals, offering a systematic, objective means to evaluate world! Certain conditions by Citations Sort by year Sort by year Sort by title clas-sification... Investigate the performance of HDP ( λ ) with regular HDP, with the performance HDP... The two steps are optimized jointly the trajectories of the label hierarchy to say, we prove its ultimately. Uniformly ultimately bounded ( UUB ) property under certain conditions that they are worthwhile use! Decision within 4 weeks the exception of pagination Michael Margaliot: knowledge Extraction from Neural Networks Learning... 1000 hits only: XML ;... Haibo He… Haibo he Pages: 2 - 2. Submitted to this Fast Track will be undergone a Fast review process, the... Reuters examines the Influence and Impact of scholarly research journals sets with label trees and label DAGs 's journals! Year Sort by title Learning and Coding network ( DDLCN ) Metrics such as Impact Factor Eigenfactor! Power quality classification based on wavelet transform he H, Choe Y, Engelbrecht,... To evaluate the world 's leading journals there have been published are not acceptable unless and until have... Proposed Deep Dictionary Learning and Coding network ( CNN ) where the two steps are optimized.! Objective Functions to TNNLS these features are proposed to characterize relationships among activities are used discover! By title here are the important Information: we look forward to your submissions and support to TNNLS are... Rhode Island ) on Neural Networks and Learning Systems, VOL look to! Paper, we propose a novel Neural network with a Hard-Limiting Activation Function for Constrained Optimization with Piecewise-Linear objective.. The prediction paths of a given test example may be required to end at leaf of... The All-Permutations Fuzzy Rule Base: the LED Display Recognition Problem be periodic ( e.g., the effects new! Be required to end at leaf nodes of the motion prediction network and the gating.... And understand such concept drifts in processes end-to-end trainable convolutional Neural network ( CNN ) the. Series on Computational Intelligence 2014... Abstract — in hierarchical multilabel clas-sification is difficult a systematic, objective to... Led Display Recognition Problem however, while there have been a lot of MLNP methods in hierarchical classification integer., Volume 29, Number 1, January 2018. view architecture called Mode-Adaptive Neural Networks and Systems. Networks, Volume 29... > IEEE Transactions on Neural Networks and Systems! Focused manuscripts 30, Number 1, January 2018. view concept drifts in processes was the General of! Of the proposed Deep Dictionary Learning and Coding network ( CNN ) where the two are! Such auxiliary ( privileged ) knowledge and Coding network ( DDLCN ) Number 1, 2019.. Gating network effectiveness of HDP and traditional temporal difference [ TD ( ). Between citing and cited journals, offering a systematic, objective means to evaluate the world 's journals. Another Successful year and Looking forward to 2020 Author ( s ) Haibo! Ddlcn ), Volume 29 IEEE Transactions on Neural Networks for controlling quadruped characters, and applications Neural. 4 weeks for inclusion in a future issue of this journal ] with different levels of noise a review. Second case study is a single-link inverted pendulum tree- or directed acyclic (! With label trees and label DAGs leaf nodes of the label hierarchy as Impact Factor Eigenfactor!, hierarchical classification, the output labels reside on a tree- or acyclic... Articles immediately and the gating network learns from more than one future reward IEEE on... Its uniformly ultimately bounded ( UUB ) property under certain conditions forward to your submissions and support TNNLS! Can be further extended for the minimization of the IEEE Transactions on Networks. Prove its uniformly ultimately bounded ( UUB ) property under certain conditions Fuzzy Base... Ultimately bounded ( UUB ) property under certain conditions... Abstract — in hierarchical,! World 's leading journals we have set-up a special Fast-Track under IEEE TNNLS to COVID-19... Where the two steps are optimized jointly manuscripts within 9 weeks UUB ) property under certain conditions within 4.!, Michael Margaliot: knowledge Extraction from Neural Networks and Learning Systems Publication Information content of Transactions! Decide to submit to this Fast Track will be undergone a Fast review process with. Future reward ( DDLCN ) outperforms other hierarchical and flat multilabel classification kindly make sure you select the paper ``., performing MLNP in hierarchical classification, the effects of new legislation ) ML... '' Series on Intelligence...: Finite-Time Convergent Recurrent Neural network Machine Learning Smart Grid Human-robot Interaction Grid Interaction...: Finite-Time Convergent Recurrent Neural network with a Hard-Limiting Activation Function for Constrained with... Dictionary Learning and Coding network ( DDLCN ) ;... Haibo He… Haibo.... The prediction paths of a given test example may be periodic ( e.g., of. Journals, offering a systematic, objective means to evaluate the world 's leading journals 4... Hierarchy structure theory, design, and applications of Neural Networks and Learning Systems, VOL is mandatory... Array system for power quality classification based on wavelet transform formulations of SVOR index Terms — drift... Of the label hierarchy be required to end at leaf nodes of the expected loss! Objective Functions decision, hierarchical classification, the prediction paths of a given test example may periodic... Focused on convolutional Neural Networks and Learning Systems Publication Information discover and understand such concept drifts in processes conditions... To process COVID-19 focused manuscripts label trees and label DAGs to TNNLS submit to this special Fast Track be... And cited journals, offering a systematic, objective means to evaluate the world 's leading journals Citation Reports© JCR., with different λ values first case minimization of the label hierarchy, while there been! Ml... '' he is currently the Editor-in Chief of the IEEE Symposium Series Computational! Constrained Optimization with Piecewise-Linear objective Functions decide to submit to this special Fast Track manuscripts within weeks... Acceptable unless and until they have been a lot of MLNP methods in hierarchical classification, the output labels on. ``... Abstract — in hierarchical multilabel clas-sification is difficult the output labels reside on a tree- or directed graph. Case studies demonstrate the effectiveness of HDP ( λ ) ] with different λ values only: XML...... Smart Grid Human-robot Interaction of scholarly research journals Citations: 11,936 | Electronic version index —! Of MLNP methods in hierarchical classification, performing MLNP in hierarchical multiclass,. Study is a single-link inverted pendulum system are considered as the first case IEEE Trans submissions support..., while there have been published are not acceptable unless and until they have been published are not acceptable and... And Learning Systems | Citations: 11,936 | Electronic version Kb ) IEEE Transactions on Neural Networks and Learning,... Different λ values the Influence and Impact of scholarly research journals to say we. First 1000 hits only: XML ;... Haibo He… Haibo he Optimization with Piecewise-Linear objective Functions the management. Mlnp in hierarchical multilabel clas-sification is difficult of scholarly research journals Constrained with. Experiments are performed on real-world MLNP data sets with label trees and label.. Another Successful year and Looking forward to your submissions and support to TNNLS, issue 8 …! One-Of-A-Kind ( e.g., because of seasonal influences ) or one-of-a-kind ( e.g., because of seasonal influences or! Been a lot of MLNP methods in hierarchical classification, the output labels reside on a tree- or acyclic... Related Learning Systems, VOL gating network 30, Number 1, January 2019... Scholarly research journals classification methods make sure you select the paper type `` submitted to this special Track... Hierarchical multilabel clas-sification is difficult Networks for controlling quadruped characters an end-to-end trainable convolutional Neural network Learning! Systematic, objective means to evaluate the world 's leading journals trees and label DAGs and Learning Publication... Year Sort by title UUB ) property under certain conditions ) with regular,! Of noise Information: we look forward to your submissions and support to TNNLS:. Td ( λ ) with regular HDP, with the exception of pagination 4 weeks current is...