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Introduction to the Special Issue on Tensor Decomposition for Signal Processing and Machine Learning

Hongyang Chen, Sergiy A. Vorobyov, Hing Cheung So, Fauzia Ahmad, Fatih Porikli
2021 IEEE Journal on Selected Topics in Signal Processing  
Introduction to the Special Issue on Tensor Decomposition for Signal Processing and Machine Learning T ENSOR decomposition, also called tensor factorization, is useful for representing and analyzing multi-dimensional  ...  This special issue (SI) covers a broad array of research on tensor methods, tensor decompositions for signal processing and machine learning, and their applications in wireless communications, radar, biomedicine  ... 
doi:10.1109/jstsp.2021.3065184 fatcat:qbvihejwkfaa5hoztety77pnwi

Introduction to the Special Issue on New Approaches to Statistical Speech and Text Processing

2008 IEEE Transactions on Audio, Speech, and Language Processing  
Renals is an Associate Editor of IEEE SIGNAL PROCESSING LETTERS, and was previously on the IEEE SPS Technical Committee on Machine Learning and Signal Processing.  ...  Her research interests include natural language processing, information retrieval, and machine learning.  ...  Introduction to the Special Issue on New Approaches to Statistical Speech and Text Processing D RAMATIC advances in automatic speech recognition technology in recent years have enabled serious growth in  ... 
doi:10.1109/tasl.2008.2004251 fatcat:jnfnhcxs6reqtggf4nikgygmvy

Preface–Special Issue on Mathematical Optimization: Past, Present and Future

Zai-Wen Wen, Ya-Xiang Yuan
2020 Journal of the Operations Research Society of China  
The success of large-scale optimization in machine learning and signal processing certainly provides a very exciting paradigm on "Modeling + algorithms + computing power".  ...  Making the best use of vastly parallel computation to qualitatively transform optimization is promising. How can optimization help machine learning, signal processing, statistics, and engineering?  ...  The success of large-scale optimization in machine learning and signal processing certainly provides a very exciting paradigm on "Modeling + algorithms + computing power".  ... 
doi:10.1007/s40305-020-00310-z fatcat:hzioj3ugg5cy5cckvxoovwerg4

A Comprehensive Survey on Machine Learning for Signal Processing: Evolution, Applications and Research Opportunities

Padma Charan Sahu, Dr. Ratnakar Dash
2020 Zenodo  
Right now, will profit by a thorough conversation on the distinctive learning ideal models and ML methods applied to crucial issues in signal processing, including estimation of Bit Error rate, Signal  ...  Without a doubt, ML has been applied to different unremarkable and complex issues emerging in signal processing activity and the executives.  ...  Machine Learning for Signal Processing In 1959, Arthur Samuel instituted the expression "Machine Learning", as the field of study that enables PCs to learn without being unequivocally customized.  ... 
doi:10.5281/zenodo.3834084 fatcat:5dn4p7qgoneqpmp46i2rdivn7q

Guest Editors' Introduction: Neural Networks For Signal Processing

A.G. Constantinides, S. Haykin, Yu Hen Hu, Jenq-neng Hwang, S. Katagiri, Sun-yuan Kung, T.A. Poggio
1997 IEEE Transactions on Signal Processing  
Based on the subject area of interest, the accepted papers are grouped into the following categories: • nonlinear signal learning and processing: theory and algorithms; • signal prediction and filtering  ...  P ROGRESS in the theory and design of neural networks has expanded on many fronts during the past ten years. Much of that progress has a direct bearing on signal processing.  ... 
doi:10.1109/tsp.1997.650089 fatcat:se3mm23wzna73iwb6to666b2re

07-1345-C16

2021 Biomedical Engineering  
However, machine learning also allows for evaluating signals that lack rules for manual scoring.  ...  Since the process is time consuming and subjective, automated classifiers or recommender systems could improve efficiency and objectivity of the evaluation.  ...  However, machine learning also allows for evaluating signals that lack rules for manual scoring.  ... 
doi:10.1515/bmt-2021-6069 pmid:34598378 fatcat:absdz4zxcnhqhk4l2uoitgwxqu

Guest Editorial: Introduction to the Special Issue on Machine Learning for Microarray Bioinformatics

Man Wai Mak, Ahmed Tewfik, Lai Wan Chan, Chun Chung Keith Chan
2007 Journal of Signal Processing Systems  
This special issue showcases various machine learning approaches to meeting this challenge. The areas in which this special issue is focusing on can be categorized as follows.  ...  One of the main challenges in computational biology is the revelation and interpretation of the rich genomic information underlying cancer biology and to facilitating molecular classification and prediction  ...  This special issue showcases various machine learning approaches to meeting this challenge. The areas in which this special issue is focusing on can be categorized as follows. 1.  ... 
doi:10.1007/s11265-007-0125-y fatcat:autxxx4iibg7nizsrtjbtfbrq4

IEEE Journal of Selected Topics in Signal Processing Special Issue on Recent Advances in Automotive Radar Signal Processing

2020 IEEE Signal Processing Magazine  
In particular, machine learning and deep learning applications are increasingly used. This special issue targets novel technical contributions.  ...  detection • Interference detection and mitigation • Enhanced object and scene classification • Machine learning and deep learning applications (point cloud segmentation, occupancy grid calculation, 3D  ... 
doi:10.1109/msp.2020.2999221 fatcat:3asddcjzjzfopa4nm74r7z4ygm

Editorial: Introduction to the Issue on Distributed Machine Learning for Wireless Communication

Ping Yang, Octavia A. Dobre, Ming Xiao, Marco Di Renzo, Jun Li, Tony Q. S. Quek, Zhu Han
2022 IEEE Journal on Selected Topics in Signal Processing  
Editorial: Introduction to the Issue on Distributed Machine Learning for Wireless Communication I.  ...  Currently, most wireless network machine learning solutions require the training data and learning process to be centralized in one or more data centers.  ... 
doi:10.1109/jstsp.2022.3165356 fatcat:dab46w4tone55oow6gquetnp6m

Introduction to the Issue on Statistical Learning Methods for Speech and Language Processing

Xiaodong He, Li Deng, Roland Kuhn, Helen Meng, Samy Bengio
2010 IEEE Journal on Selected Topics in Signal Processing  
Introduction to the Issue on Statistical Learning Methods for Speech and Language Processing I N the past few years, significant progress has been made in both research and commercial applications of speech  ...  Another focus of this special issue is on the cross-fertilization of learning approaches to speech and language processing problems.  ... 
doi:10.1109/jstsp.2010.2086910 fatcat:wyezgqd235ffvp3zkklwo4tlge

Special Issue on Signal Processing and Machine Learning for Biomedical Data

Giuseppe Raso, Donato Cascio
2021 Applied Sciences  
This Special Issue is focused on advanced techniques in signal processing, analysis, modelling, and classification, applied to a variety of medical diagnostic problems [...]  ...  Introduction This Special Issue is focused on advanced techniques in signal processing, analysis, modelling, and classification, applied to a variety of medical diagnostic problems.  ...  Furthermore, the introduction of new techniques and methodologies for diagnostic purposes, especially in the field of medical imaging, requires new signal processing and machine learning methods.  ... 
doi:10.3390/app11083399 fatcat:zxywfeynhjch7ilytlemjuoyci

Survey on Neural Network Architectures with Deep Learning

Smys S., Joy Iong Zong Chen, Subarna Shakya
2020 Journal of Soft Computing Paradigm  
In particular deep learning is one of the cost efficient, effective supervised learning model, which can be applied to various complicated issues.  ...  In the present research era, machine learning is an important and unavoidable zone where it provides better solutions to various domains.  ...  Introduction Machine learning is a popular approach in present research environment as it deals various applications in image processing, signal processing and other data analysis [1] .  ... 
doi:10.36548/jscp.2020.3.007 fatcat:saxneqmonvdy7iv6qzkpkoii3y

Paradigm Shifts in Video Technologies: Introduction to T-CSVT Future Special Issues

2014 IEEE transactions on circuits and systems for video technology (Print)  
Advanced developments in machine learning may lead to a mass-knowledge based visual signal processing, communication, and computing systems, instead of traditional memoryless or memory-based signal processing  ...  A new theory on distributed coding and distributed processing is also emerging to enable independent compression and processing of visual signals with significantly reduced communication overhead, but  ...  Furthermore, we are calling for proposals on special issues on machine learning in visual computing and other areas that may result paradigm shifts in video technologies.  ... 
doi:10.1109/tcsvt.2014.2332410 fatcat:zdevzkgx6bdkxik5wcxbh2ad3i

Data Analytics on Graphs Part II: Signals on Graphs

Ljubiša Stanković, Danilo Mandic, Miloš Daković, Miloš Brajović, Bruno Scalzo, Shengxi Li, Anthony G. Constantinides
2020 Foundations and Trends® in Machine Learning  
Information for Librarians Foundations and Trends R in Machine Learning, 2020, Volume 13, 6 issues.  ...  Part II embarks on these concepts to address the algorithmic and practical issues related to data/signal processing on graphs, with the focus on the analysis and estimation of both deterministic and random  ... 
doi:10.1561/2200000078-2 fatcat:2toioxxi75clplxyktcflfixjq

AI and the Singularity: A Fallacy or a Great Opportunity?

Adriana Braga, Robert Logan
2019 Information  
We have invited a group of scholars to address this question, whose positions on the Singularity range from advocates to skeptics.  ...  The reader will find a cogent summary of the issues faced by researchers who are working to develop the field of artificial intelligence and in particular artificial general intelligence.  ...  Introduction We made a call for papers that either support or criticize the lead paper for this Special Issue entitled The Emperor of Strong AI Has no Clothes: Limits to Artificial Intelligence.  ... 
doi:10.3390/info10020073 fatcat:ewcmu7tzkfa7ljfauugcv4sevy
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