S. Kung

发表

Generalized principal components analysis and its application in approximate stochastic realization

K. Arun, S. Kung, 1986 .

Principal Component Neural Networks: Theory and Applications

Sun-Yuan Kung, Konstantinos I. Diamantaras, S. Kung, 1996 .

A Toeplitz approximation approach to coherent source direction finding

Sun-Yuan Kung, R. Foka, C. Lo, 1986, ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing.

State-space and singular-value decomposition-based approximation methods for the harmonic retrieval problem

K. Arun, S. Kung, D. B. Rao, 1983 .

Neural networks for signal processing : proceedings of the 1991 IEEE workshop

F. Fallside, Sun-Yuan Kung, J. A.A. Sorenson, 1991 .

Cross-Scale Residual Network: A General Framework for Image Super-Resolution, Denoising, and Deblocking

S. Kung, Yuan Zhou, Xiaoting Du, 2021, IEEE Transactions on Cybernetics.

Optimal Hankel-norm model reductions: Multivariable systems

S. Kung, D. Lin, 1980 .

Cost-effective kernel ridge regression implementation for keystroke-based active authentication system

Sun-Yuan Kung, J. Morris Chang, Pei-Yuan Wu, 2017, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Kernel Methods and Machine Learning

S. Kung, 2014 .

VLSI and Modern Signal Processing

T. Kailath, H. Whitehouse, S. Kung, 1984 .

A Unified Systolic Architecture for Artificial Neural Networks

Jenq-Neng Hwang, Sun-Yuan Kung, Jenq-Neng Hwang, 1989, J. Parallel Distributed Comput..

Parallel architectures for artificial neural nets

S. Y. Kung, J. N. Hwang, Jenq-Neng Hwang, 1988, IEEE 1988 International Conference on Neural Networks.

Balanced approximation of stochastic systems

K. Arun, S. Kung, 1990 .

Neural networks for extracting unsymmetric principal components

S. Kung, K. Diamantaras, 1991, Neural Networks for Signal Processing Proceedings of the 1991 IEEE Workshop.

A self-stabilized minor subspace rule

S. Amari, S. Douglas, S. Kung, 1998, IEEE Signal Processing Letters.

Biometric Authentication: A Machine Learning Approach

Sun-Yuan Kung, Man-Wai Mak, S. H. Lin, 2004 .

Gradient adaptation under unit-norm constraints

S. Amari, S. Douglas, S. Kung, 1998, Ninth IEEE Signal Processing Workshop on Statistical Signal and Array Processing (Cat. No.98TH8381).

A neural network learning algorithm for adaptive principal component extraction (APEX)

Sun-Yuan Kung, Konstantinos I. Diamantaras, S. Kung, 1990, International Conference on Acoustics, Speech, and Signal Processing.

An algebraic projection analysis for optimal hidden units size and learning rates in back-propagation learning

S. Y. Kung, J. N. Hwang, Jenq-Neng Hwang, 1988, IEEE 1988 International Conference on Neural Networks.

Environment adaptation for robust speaker verification by cascading maximum likelihood linear regression and reinforced learning

Sun-Yuan Kung, Man-Wai Mak, Kwok-Kwong Yiu, 2007, Comput. Speech Lang..

Parallel algorithms/architectures for neural networks

Jenq-Neng Hwang, Sun-Yuan Kung, Jenq-Neng Hwang, 1989, J. VLSI Signal Process..

Multikernel Least Mean Square Algorithm

Sun-Yuan Kung, Danilo P. Mandic, Felipe A. Tobar, 2014, IEEE Transactions on Neural Networks and Learning Systems.

On two-dimensional Markov spectral estimation

R. Chellappa, S. Kung, Y. Hu, 1983 .

Guest Editorial Applications Of Artificial Neural Networks To Image Processing

Aggelos K. Katsaggelos, Rama Chellappa, Sun-Yuan Kung, 1998, IEEE Trans. Image Process..

Improved Pisarenko's sinusoidal spectrum estimate via SVD subspace approximation methods

S. Kung, Y. Hu, 1982, 1982 21st IEEE Conference on Decision and Control.

Real-Time Configuration for Fault-Tolerant VLSI Array Processors

Chein-Wei Jen, Sun-Yuan Kung, Chih-Wei Jim Chang, 1986, RTSS.

CLAss-Specific Subspace Kernel Representations and Adaptive Margin Slack Minimization for Large Scale Classification

Sun-Yuan Kung, Yinan Yu, Konstantinos I. Diamantaras, 2018, IEEE Transactions on Neural Networks and Learning Systems.

New Results in 2-D Systems Theory. Part III. Recursive Realization and Estimation Algorithms for 2-D Systems.

Sun-Yuan Kung, B. Levy, M. Morf, 1977 .

A Unification of Edmonds ’ Routing Theorem and Ahlswede et al ’ s Network Coding Theorem

K. Jain, S. Kung, Yunnan Wu, 2005 .

A Unification of Menger ’ s and Edmonds ’ Graph Theorems and Ahlswede et al ’ s Network Coding Theorem

K. Jain, S. Kung, Yunnan Wu, 2004 .

GOASVM: a subcellular location predictor by incorporating term-frequency gene ontology into the general form of Chou's pseudo-amino acid composition.

S. Kung, M. Mak, Shibiao Wan, 2013, Journal of theoretical biology.

Editorial: IEEE Transactions on Sustainable Computing, Special Issue on Smart Data and Deep Learning in Sustainable Computing

Sun-Yuan Kung, Meikang Qiu, Qing Yang, 2019, IEEE Trans. Sustain. Comput..

GOP-INTERLACED CODING SCHEME FOR ENHANCING COARSE-GRAIN PARALLELISM AND ERROR CONCEALMENT

S. Kung, Yen-kuang Chen, M. Chang, 1998 .

A probabilistic DBNN with applications to sensor fusion and object recognition

S. Kung, Long-Ji Lin, Shang-Hung Lin, 1995, Proceedings of 1995 IEEE Workshop on Neural Networks for Signal Processing.

Conditional random fields for the prediction of signal peptide cleavage sites

Sun-Yuan Kung, Man-Wai Mak, S. Kung, 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

HybridGO-Loc: Mining Hybrid Features on Gene Ontology for Predicting Subcellular Localization of Multi-Location Proteins

Sun-Yuan Kung, Shibiao Wan, Man-Wai Mak, 2014, PloS one.

Allpass vs. unit-norm constraints in contrast-based blind deconvolution

S. Douglas, S. Kung, 1999, Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468).

Data privacy protection by kernel subspace projection and generalized eigenvalue decomposition

Sun-Yuan Kung, Konstantinos I. Diamantaras, S. Kung, 2016, 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP).

mLASSO-Hum: A LASSO-based interpretable human-protein subcellular localization predictor.

Sun-Yuan Kung, Shibiao Wan, Man-Wai Mak, 2015, Journal of theoretical biology.

Adaptive notch filtering for the retrieval of sinusoids in noise

S. Kung, D. B. Rao, 1984 .

Discriminative mining of gene microarray data

Sun-Yuan Kung, Robert Clarke, Jianhua Xuan, 2001, Neural Networks for Signal Processing XI: Proceedings of the 2001 IEEE Signal Processing Society Workshop (IEEE Cat. No.01TH8584).

Quanti cation and Segmentation of BrainTissues from MR Images : A ProbabilisticNeural Network

S. Kung, T. Adal, ApproachYue, 1998 .

Transcriptional Network Analysis Identifies BACH1 as a Master Regulator of Breast Cancer Bone Metastasis

S. Kung, Yibin Kang, I. Tagkopoulos, 2012, The Journal of Biological Chemistry.

Breast Cancer Bone Metastasis Identifies BACH 1 as a Master Regulator of Transcriptional Network Analysis

S. Kung, Yibin Kang, I. Tagkopoulos, 2012 .

Emergence of predictive capacity within microbial genetic networks

Sun-Yuan Kung, Ilias Tagkopoulos, Saeed Tavazoie, 2008 .

Classification of Temporal Gene Expression Data Using Wavelet Domain Feature in Kernel SVM

S. Kung, S. Fattah, M. Maksud, 2014 .

Coding and comparison of DAG's as a novel neural structure with applications to on-line handwriting recognition

Sun-Yuan Kung, I-Jong Lin, S. Kung, 1997, IEEE Trans. Signal Process..

Model-based Neural Networks for Image Processing

Sun-Yuan Kung, Lin Guan, S. Kung, 1997, IEEE Signal Process. Mag..

Algorithm/Architecture Coexploration

He Lin, Gwo Lee, Sun Kung, 2012 .

IWQoS 2004 Table of Contents Session 1: Ad Hoc Wireless, Mobile and Sensor Networks

Yunnan Wu, Sun-Yuan Kung, Vishal Misra, 2004 .

Multimedia Signal Processing Technical Committee of the IEEE Signal Processing Society In Cooperation With Digital Signal Processing Technical Committee Image and Multidimensional Signal Processing Technical Committee Speech Processing Technical Committee New Jersey Center for Multimedia Research

Sun-Yuan Kung, Tsuhan Chen, Amy R. Reibman, 1997 .

Neural networks for signal processing - Guest editors' introduction

Jenq-Neng Hwang, Sun-Yuan Kung, Shigeru Katagiri, 1997 .

FEATURESELECTIONFOR PAIRWISESCORINGKERNELSWITH APPLICATIONSTO PROTEINSUBCELLULARLOCALIZATION

S. Kung, 2007 .

Semi-Supervised Few-Shot Learning from A Dependency-Discriminant Perspective

S. Kung, Zejiang Hou, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Cost-Effective Kernel Ridge Regression Implementation for Keystroke-Based Active Authentication System

S. Kung, Pei-Yuan Wu, Chi-Chen Fang, 2014, IEEE Transactions on Cybernetics.

Intelligent Multimedia Processing

Jenq-Neng Hwang, Sun-Yuan Kung, Ling Guan, 2001 .

Multi-Dimensional Vision Transformer Compression via Dependency Guided Gaussian Process Search

S. Kung, Zejiang Hou, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

DESIGNING VLSI SIGNAL PROCESSING CHIPS USING DATA DEPENDENCE GRAPHS.

Sun-Yuan Kung, John V. McCanny, J. G. McWhirter, 1987 .

J an 2 01 5 EFFICIENT DIVIDE-AND-CONQUER CLASSIFICATION BASED ON FEA TURE-SPACE DECOMPOSITION

S. Kung, Xiangyang Ji, Qi Guo, 2015 .

MILAN: Masked Image Pretraining on Language Assisted Representation

S. Kung, Yuan Xie, Fei Sun, 2022, ArXiv.

A new identification and model reduction algorithm via singular value decomposition

Sun-Yuan Kung, S. Kung, 1978 .

A Two-Variable Approach to the Reduction Problem with Hankel Criterion Model Norm

Y. Genin, S. Kung, 1981 .

Optimal Hankel-norm model reductions-scalar systems

Sun-Yuan Kung, S. Kung, 1980 .

Systolic Arrays

Sun-Yuan Kung, Yu Hen Hu, S. Kung, 2018, Handbook of Signal Processing Systems.

Parameter Efficient Dynamic Convolution via Tensor Decomposition

S. Kung, Zejiang Hou, 2021, BMVC.

Parallel and pipelined VLSI implementation of a staged decoder for BCM signals

Giuseppe Caire, Sun-Yuan Kung, Javier Ventura-Traveset, 1995, J. VLSI Signal Process..

A Principal Component Clustering Approach to Object-Oriented Motion Segmentation and Estimation

Sun-Yuan Kung, Yen-Kuang Chen, Yun-Ting Lin, 1997, J. VLSI Signal Process..

Face recognition/detection by probabilistic decision-based neural network

Sun-Yuan Kung, Shang-Hung Lin, Long-Ji Lin, 1997, IEEE Trans. Neural Networks.

Class-Discriminative CNN Compression pdf

David Wentzlaff, Yuchen Liu, S. Y. Kung, 2021, 2022 26th International Conference on Pattern Recognition (ICPR).

Rethinking Class-Discrimination Based CNN Channel Pruning pdf

David Wentzlaff, Yuchen Liu, S. Y. Kung, 2020, ArXiv.

Low-energy Formulations of Support Vector Machine Kernel Functions for Biomedical Sensor Applications

Sun-Yuan Kung, Naveen Verma, Kyong-Ho Lee, 2012, Journal of Signal Processing Systems.

Fast subcellular localization by cascaded fusion of signal-based and homology-based methods

Sun-Yuan Kung, Man-Wai Mak, Wei Wang, 2011, Proteome Science.

A kernel-based core growing clustering method

Jin-Shiuh Taur, Tzuen Wuu Hsieh, S. Y. Kung, 2009 .

Information Exchange in Wireless Networks with Network Coding and Physical-layer Broadcast

Yunnan Wu, Sun-Yuan Kung, Philip A. Chou, 2004 .

Scalable Kernel Learning Via the Discriminant Information

S. Kung, Zejiang Hou, Mert Al, 2019, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Methodical Design and Trimming of Deep Learning Networks: Enhancing External BP Learning with Internal Omnipresent-supervision Training Paradigm

Zejiang Hou, Yuchen Liu, Sun-Yuan Kung, 2019, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Gradient Adaptive Paraunitary Filter Banks for Spatio-Temporal Subspace Analysis and Multichannel Blind Deconvolution

Sun-Yuan Kung, Shun-ichi Amari, Scott C. Douglas, 2004, J. VLSI Signal Process..

Adaptive paraunitary filter banks for principal and minor subspace analysis

Sun-Yuan Kung, Shun-ichi Amari, Scott C. Douglas, 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

Gradient Adaptive Algorithms for Contrast-Based Blind Deconvolution

Sun-Yuan Kung, Scott C. Douglas, S. Douglas, 2000, J. VLSI Signal Process..

On gradient adaptation with unit-norm constraints

Sun-Yuan Kung, Shun-ichi Amari, Scott C. Douglas, 2000, IEEE Trans. Signal Process..

Design of estimation/deflation approaches to independent component analysis

S. Douglas, S. Kung, S.C. Douglas, 1998, Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284).

Kuicnet Algorithms for Blind Deconvolution

Scott C. Douglas, S. Douglas, S. Kung, 1998, Neural Networks for Signal Processing VIII. Proceedings of the 1998 IEEE Signal Processing Society Workshop (Cat. No.98TH8378).

Extraction of independent components from hybrid mixture: KuicNet learning algorithm and applications

Sun-Yuan Kung, Cristina Mejuto, S. Kung, 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

Neural Networks for Intelligent Multimedia Processing

Sun-Yuan Kung, Jenq-Neng Hwang, S. Kung, 1997, Neural Networks for Signal Processing VII. Proceedings of the 1997 IEEE Signal Processing Society Workshop.

HGC: Hierarchical Group Convolution for Highly Efficient Neural Network pdf

Yuan Zhou, Sun-Yuan Kung, Xukai Xie, 2019, ArXiv.

Estimation of elliptical basis function parameters by the EM algorithm with application to speaker verification

Sun-Yuan Kung, Man-Wai Mak, S. Kung, 2000, IEEE Trans. Neural Networks Learn. Syst..

Decision-based neural networks with signal/image classification applications

Sun-Yuan Kung, Jin-Shiuh Taur, S. Kung, 1995, IEEE Trans. Neural Networks.

Molecular Bases of Disease

S. Kung, Yibin Kang, Qifeng Yang, 2013 .

Speeding up subcellular localization by extracting informative regions of protein sequences for profile alignment

Sun-Yuan Kung, Wei Wang, Man-Wai Mak, 2010, 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

PairProSVM: Protein Subcellular Localization Based on Local Pairwise Profile Alignment and SVM

Sun-Yuan Kung, Man-Wai Mak, Jian Guo, 2008, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Accurate detection of aneuploidies in array CGH and gene expression microarray data

Sun-Yuan Kung, Olga G. Troyanskaya, Chad L. Myers, 2004, Bioinform..

Image Restoration via Multi-prior Collaboration

Sun-Yuan Kung, Feng Jiang, Shengping Zhang, 2014, ACCV.

CLAss-Specific Subspace Kernel Representations and Adaptive Margin Slack Minimization for Large Scale Classification

Sun-Yuan Kung, Yinan Yu, Konstantinos I. Diamantaras, 2018, IEEE Trans. Neural Networks Learn. Syst..

Multi-class biclustering and classification based on modeling of gene regulatory networks

Sun-Yuan Kung, Ilias Tagkopoulos, Nikolai Slavov, 2005, Fifth IEEE Symposium on Bioinformatics and Bioengineering (BIBE'05).

Fusion of Conditional Random Field and SignalP for Protein Cleavage Site Prediction

Sun-Yuan Kung, Man-Wai Mak, Wei Wang, 2009 .

Embedded Computing for Fluorescence Confocal Endomicroscopy Imaging

Sun-Yuan Kung, Seah Hock Soon, Malini Olivo, 2009, J. Signal Process. Syst..

Gram-LocEN: Interpretable prediction of subcellular multi-localization of Gram-positive and Gram-negative bacterial proteins

Sun-Yuan Kung, Shibiao Wan, Man-Wai Mak, 2017 .

Ensemble Linear Neighborhood Propagation for Predicting Subchloroplast Localization of Multi-Location Proteins.

Sun-Yuan Kung, Shibiao Wan, Man-Wai Mak, 2016, Journal of proteome research.

Mem-mEN: Predicting Multi-Functional Types of Membrane Proteins by Interpretable Elastic Nets

Sun-Yuan Kung, Shibiao Wan, Man-Wai Mak, 2016, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Mem-ADSVM: A two-layer multi-label predictor for identifying multi-functional types of membrane proteins.

Sun-Yuan Kung, Shibiao Wan, Man-Wai Mak, 2016, Journal of theoretical biology.

Sparse regressions for predicting and interpreting subcellular localization of multi-label proteins

Sun-Yuan Kung, Shibiao Wan, Man-Wai Mak, 2016, BMC Bioinformatics.

mPLR-Loc: an adaptive decision multi-label classifier based on penalized logistic regression for protein subcellular localization prediction.

Sun-Yuan Kung, Shibiao Wan, Man-Wai Mak, 2015, Analytical biochemistry.

R3P-Loc: a compact multi-label predictor using ridge regression and random projection for protein subcellular localization.

Sun-Yuan Kung, Shibiao Wan, Man-Wai Mak, 2014, Journal of theoretical biology.

GOASVM: Protein subcellular localization prediction based on Gene ontology annotation and SVM

Sun-Yuan Kung, Shibiao Wan, Man-Wai Mak, 2012, ICASSP.

2011 Ieee International Workshop on Machine Learning for Signal Processing Protein Subcellular Localization Prediction Based on Profile Alignment and Gene Ontology

Sun-Yuan Kung, Shibiao Wan, Man-Wai Mak, 2022 .

Fusion of cleavage site detection and pairwise alignment for fast subcellular localization

Sun-Yuan Kung, Man-Wai Mak, S. Kung, 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

Wavefront Array Processor: Language, Architecture, and Applications

D. V. Bhaskar Rao, K. S. Arun, Sun-Yuan Kung, 1982, IEEE Transactions on Computers.

PDA-SVM Hybrid: A Unified Model for Kernel-Based Supervised Classification

Sun-Yuan Kung, Man-Wai Mak, S. Kung, 2011, J. Signal Process. Syst..

Capacity bound analysis for FIR Be/spl acute/zout equalizers in ISI MIMO channels

Sun-Yuan Kung, Xinying Zhang, S. Kung, 2005, IEEE Transactions on Signal Processing.

A recursive QR approach to semi-blind equalization of time-varying MIMO channels

Sun-Yuan Kung, Xinying Zhang, Chad L. Myers, 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Achievable capacity with sequential equalizers in Rayleigh fading MIMO channels

Sun-Yuan Kung, Xinying Zhang, S. Kung, 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).

Bezout space-time precoders and equalizers for MIMO channels

Yunnan Wu, Sun-Yuan Kung, Xinying Zhang, 2002, IEEE Trans. Signal Process..

On Practical Design for Joint Distributed Source and Network Coding

Yunnan Wu, Sun-Yuan Kung, Zixiang Xiong, 2009, IEEE Transactions on Information Theory.

Minimum-energy multicast in mobile ad hoc networks using network coding

Yunnan Wu, Sun-Yuan Kung, Philip A. Chou, 2004, Information Theory Workshop.

Cross-correlation neural network models

Sun-Yuan Kung, Konstantinos I. Diamantaras, S. Kung, 1994, IEEE Trans. Signal Process..

Multi-Dimensional Dynamic Model Compression for Efficient Image Super-Resolution

S. Kung, Zejiang Hou, 2022, 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

Content-Aware GAN Compression

Zhe L. Lin, Zhe Lin, Federico Perazzi, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Hyperspectral and Multispectral Image Fusion Based on Local Low Rank and Coupled Spectral Unmixing

Sun-Yuan Kung, Yuan Zhou, Chunping Hou, 2017, IEEE Transactions on Geoscience and Remote Sensing.

VLSI Array processors

S. Kung, S. Kung, 1985, IEEE ASSP Magazine.

A novel three-class ROC method for eQTL analysis

Yeung Sam Hung, S. Y. Kung, Weichao Xu, 2010, 2010 International Conference on Machine Learning and Cybernetics.

MILAN: Masked Image Pretraining on Language Assisted Representation

S. Kung, Yuan Xie, Fei Sun, 2022, ArXiv.

Wavefront Array Processors-Concept to Implementation

Jenq-Neng Hwang, Sun-Yuan Kung, Sheng-Chun Lo, 1987, Computer.

Improving kernel-energy trade-offs for machine learning in implantable and wearable biomedical applications

Sun-Yuan Kung, Naveen Verma, Kyong-Ho Lee, 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Progressive Learning for Unsupervised Change Detection on Aerial Images

S. Kung, Xiangrui Li, Keran Chen, 2023, IEEE Transactions on Geoscience and Remote Sensing.

Image super-resolution based on dense convolutional auto-encoder blocks

Yuan Zhou, Xukai Xie, Sun-Yuan Kung, 2021, Neurocomputing.

mGOASVM: Multi-label protein subcellular localization based on gene ontology and support vector machines

Sun-Yuan Kung, Shibiao Wan, Man-Wai Mak, 2012, BMC Bioinformatics.

Ring systolic designs for artificial neural nets

Jenq-Neng Hwang, Sun-Yuan Kung, Jenq-Neng Hwang, 1988, Neural Networks.

Few-Shot Learning Via Dependency Maximization and Instance Discriminant Analysis

Sun-Yuan Kung, Zejiang Hou, S. Kung, 2021, 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP).

Optimal Systolic Design for the Transitive Closure and the Shortest Path Problems

Sun-Yuan Kung, Paul S. Lewis, Sheng-Chun Lo, 1987, IEEE Transactions on Computers.

Distributed utility maximization for network coding based multicasting: a shortest path approach

Yunnan Wu, Sun-Yuan Kung, S. Kung, 2006, IEEE Journal on Selected Areas in Communications.

Distributed Utility Maximization for Network Coding Based Multicasting: A Critical Cut Approach

Yunnan Wu, Sun-Yuan Kung, Mung Chiang, 2006, 2006 4th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks.

A classification scheme for ‘high-dimensional-small-sample-size’ data using soda and ridge-SVM with microwave measurement applications

Sun-Yuan Kung, Yinan Yu, Tomas McKelvey, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

Testing for Acceptance–Rejection

S. Y. Kung, Shang‐Hung Lin, S. Kung, 1999 .

Semi-Supervised Salient Object Detection Using a Linear Feedback Control System Model

Sun-Yuan Kung, Yuan Zhou, Chunping Hou, 2019, IEEE Transactions on Cybernetics.

CHEX: CHannel EXploration for CNN Model Compression

S. Kung, Xiaolong Ma, Minghai Qin, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Compressive Privacy: From Information\/Estimation Theory to Machine Learning [Lecture Notes]

S.Y. Kung, S. Kung, S. Kung, 2017, IEEE Signal Processing Magazine.

Cross-Layer Network Lifetime Maximization in Underwater Wireless Sensor Networks

Yuan Zhou, Sun-Yuan Kung, Yu Hen Hu, 2020, IEEE Systems Journal.

Frame-rate up-conversion using transmitted true motion vectors

Sun-Yuan Kung, Anthony Vetro, Huifang Sun, 1998, 1998 IEEE Second Workshop on Multimedia Signal Processing (Cat. No.98EX175).

Temporal Action Localization Using Long Short-Term Dependency pdf

Sun-Yuan Kung, Hongru Li, Yuan Zhou, 2019, IEEE Transactions on Multimedia.

Meta-Learning with Attention for Improved Few-Shot Learning

Sun-Yuan Kung, Anwar Elwalid, Zejiang Hou, 2021, ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

TRUE MOTION ESTIMATION — THEORY, APPLICATION, AND IMPLEMENTATION

Sun-Yuan Kung, Yen-Kuang Chen, Huifang Sun, 2004 .

A feature tracking algorithm using neighborhood relaxation with multi-candidate pre-screening

Sun-Yuan Kung, Yen-Kuang Chen, Yun-Ting Lin, 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

Applying articulatory features to telephone-based speaker verification

Sun-Yuan Kung, Man-Wai Mak, Ka-Yee Leung, 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Variable-phase-shift-based RF-baseband codesign for MIMO antenna selection

A.F. Molisch, Xinying Zhang, Sun-Yuan Kung, 2005, IEEE Transactions on Signal Processing.

Toeplitz eigensystem solver

Yu Hen Hu, Sun-Yuan Kung, S. Kung, 1985, IEEE Trans. Acoust. Speech Signal Process..

A delay damage model selection algorithm for NARX neural networks

Sun-Yuan Kung, C. Lee Giles, Tsungnan Lin, 1997, IEEE Trans. Signal Process..

Salient Object Detection via Fuzzy Theory and Object-Level Enhancement

Sun-Yuan Kung, Yuan Zhou, Jianjun Lei, 2019, IEEE Transactions on Multimedia.

Fault-Tolerant Array Processors Using Single-Track Switches

Sun-Yuan Kung, Chih-Wei Jim Chang, Shiann-Ning Jean, 1989, IEEE Trans. Computers.

Quantitative Analysis of MR Brain Image Sequences by Adaptive Self-Organizing Finite Mixtures

Sun-Yuan Kung, Yue Joseph Wang, Tülay Adali, 1998, J. VLSI Signal Process..

Quantification and segmentation of brain tissues from MR images: a probabilistic neural network approach

Sun-Yuan Kung, Yue Joseph Wang, Tülay Adali, 1998, IEEE Trans. Image Process..

Privacy-preserving PCA on horizontally-partitioned data

Sun-Yuan Kung, J. Morris Chang, Pei Yuan Wu, 2017, 2017 IEEE Conference on Dependable and Secure Computing.

Methodology, Techniques and Applications: Coding of Video and Multimedia Content

Sun-Yuan Kung, Ling Guan, Yifeng He, 2012 .

Message from the program chairs of HPCC 2015

Jack Dongarra, Tarek El-Ghazawi, Meikang Qiu, 2015, IEEE International Conference on High Performance Computing and Communications.

Multi-Dimensional Model Compression of Vision Transformer pdf

Sun-Yuan Kung, Zejiang Hou, S. Kung, 2021, 2022 IEEE International Conference on Multimedia and Expo (ICME).

Hidden Markov models for character recognition

Sun-Yuan Kung, J. A. Vlontzos, S. Kung, 1989, International Conference on Acoustics, Speech, and Signal Processing,.

Multi-scale Generative Adversarial Networks for Crowd Counting

Sun-Yuan Kung, Yuan Zhou, Jianxing Yang, 2018, 2018 24th International Conference on Pattern Recognition (ICPR).

Low-energy Formulations of Support Vector Machine Kernel Functions for Biomedical Sensor Applications

S. Kung, N. Verma, Kyong-Ho Lee, 2012, Journal of Signal Processing Systems.

Feature Selection for Genomic Signal Processing: Unsupervised, Supervised, and Self-Supervised Scenarios

Sun-Yuan Kung, Man-Wai Mak, Yuhui Luo, 2010, J. Signal Process. Syst..

A Solution to the Curse of Dimensionality Problem in Pairwise Scoring Techniques

Sun-Yuan Kung, Man-Wai Mak, S. Kung, 2006, ICONIP.

Quantum Computer-Aided Design Automation

S. Kung, Yao-Hsin Chou, Shu-Yu Kuo, 2023, IEEE Nanotechnology Magazine.

Dynamic resource allocation via video content and short-term traffic statistics

Min Wu, Sun-Yuan Kung, Robert A. Joyce, 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

A two-variable approach to the model reduction problem with Hankel norm criterion

Y. Genin, Y. Genin, S. Kung, 1981 .

Digital neural networks

Sun-Yuan Kung, S. Kung, 1993, Prentice Hall Information and System Sciences Series.

Adaptive Principal component EXtraction (APEX) and applications

S.Y. Kung, K.I. Diamantaras, J.S. Taur, 1994, IEEE Trans. Signal Process..

Truncation of protein sequences for fast profile alignment with application to subcellular localization

Sun-Yuan Kung, Wei Wang, Man-Wai Mak, 2010, 2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Soft-Root-Sign Activation Function pdf

Dandan Li, Yuan Zhou, Shuwei Huo, 2020, ArXiv.

A state-space formulation for optimal Hankel-norm approximations

Sun-Yuan Kung, S. Kung, D. Lin, 1981 .

A Novel Multi-Stage Training Approach for Human Activity Recognition From Multimodal Wearable Sensor Data Using Deep Neural Network

Shaikh Anowarul Fattah, Sun-Yuan Kung, Tanvir Mahmud, 2021, IEEE Sensors Journal.

Benchmark data for identifying multi-functional types of membrane proteins

Sun-Yuan Kung, Shibiao Wan, Man-Wai Mak, 2016, Data in brief.

Ensemble random projection for multi-label classification with application to protein subcellular localization

Sun-Yuan Kung, Yue Wang, Shibiao Wan, 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

An ensemble classifier with random projection for predicting multi-label protein subcellular localization

Sun-Yuan Kung, Yue Wang, Shibiao Wan, 2013, 2013 IEEE International Conference on Bioinformatics and Biomedicine.

Sun-Yuan Kung, Shibiao Wan, Man-Wai Mak, 2013 .

Adaptive thresholding for multi-label SVM classification with application to protein subcellular localization prediction

Sun-Yuan Kung, Shibiao Wan, Man-Wai Mak, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

Semi-supervised saliency classifier based on a linear feedback control system model

Sun-Yuan Kung, Yuan Zhou, Shuwei Huo, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Cross-Layer Design for Network Lifetime Maximization in Underwater Wireless Sensor Networks

Sun-Yuan Kung, Yuan Zhou, Boyu Wang, 2018, 2018 IEEE International Conference on Communications (ICC).

Profit Improvement in Wireless Video Broadcasting System: A Marginal Principle Approach

Sun-Yuan Kung, Yiqiang Chen, Wen Ji, 2015, IEEE Transactions on Mobile Computing.

Exploring Highly Efficient Compact Neural Networks For Image Classification

Yuan Zhou, S. Y. Kung, Xukai Xie, 2020, 2020 IEEE International Conference on Image Processing (ICIP).

A Compressive Privacy approach to Generalized Information Bottleneck and Privacy Funnel problems

S. Y. Kung, S. Kung, 2017, J. Frankl. Inst..

Collaborative PCA/DCA Learning Methods for Compressive Privacy

Sun-Yuan Kung, J. Morris Chang, Pei Yuan Wu, 2017, ACM Trans. Embed. Comput. Syst..

Discriminant component analysis for privacy protection and visualization of big data

Sun-Yuan Kung, S. Kung, 2017, Multimedia Tools and Applications.

Network planning in wireless ad hoc networks: a cross-Layer approach

Yunnan Wu, Sun-Yuan Kung, Qian Zhang, 2005, IEEE Journal on Selected Areas in Communications.

A Low-Cost Time-Hopping Impulse Radio System for High Data Rate Transmission

Alexander M. Haimovich, Makoto Miyake, H. Vincent Poor, 2005, EURASIP J. Adv. Signal Process..

Semisupervised Learning Based on a Novel Iterative Optimization Model for Saliency Detection

Sun-Yuan Kung, Yuan Zhou, Wei Xiang, 2019, IEEE Transactions on Neural Networks and Learning Systems.

Sparse regressions for predicting and interpreting subcellular localization of multi-label proteins

S. Kung, M. Mak, Shibiao Wan, 2016, BMC Bioinformatics.

Computational intelligence approach for gene expression data mining and classification

Sun-Yuan Kung, Jianhua Xuan, Yue Joseph Wang, 2003, 2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698).

Exploiting Operation Importance for Differentiable Neural Architecture Search pdf

Yuan Zhou, Xukai Xie, Sun-Yuan Kung, 2019, IEEE Transactions on Neural Networks and Learning Systems.

Discriminatory Mining of Gene Expression Microarray Data

Jianhua Xuan, Junying Zhang, Javed I. Khan, 2003, J. VLSI Signal Process..

Probabilistic principal component subspaces: a hierarchical finite mixture model for data visualization

Sun-Yuan Kung, Yue Joseph Wang, Matthew T. Freedman, 2000, IEEE Trans. Neural Networks Learn. Syst..

On Programming Languages for VLSI Array Processors

S. Y. Kung, S. Kung, 1986, Photonics West - Lasers and Applications in Science and Engineering.

On VLSI array architectures for digital image processing

Sun-Yuan Kung, S. Kung, 1986, ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing.

On programming VLSI concurrent array processors

Sun-Yuan Kung, Armin B. Cremers, A. Cremers, 1984, Integr..

DFT-based hybrid antenna selection schemes for spatially correlated MIMO channels

Sun-Yuan Kung, Andreas F. Molisch, Jinyun Zhang, 2003, 14th IEEE Proceedings on Personal, Indoor and Mobile Radio Communications, 2003. PIMRC 2003..

Phase-shift-based antenna selection for MIMO channels

Sun-Yuan Kung, Andreas F. Molisch, Xinying Zhang, 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).

CovSegNet: A Multi Encoder–Decoder Architecture for Improved Lesion Segmentation of COVID-19 Chest CT Scans pdf

Shaikh Anowarul Fattah, Sun-Yuan Kung, Tanvir Mahmud, 2020, IEEE Transactions on Artificial Intelligence.

Large-scale image colorization based on divide-and-conquer support vector machines

S. Kung, Seungmin Rho, Bo-Wei Chen, 2016, The Journal of Supercomputing.

Feature reduction based on Sum-Of-SNR (SOSNR) optimization

Sun-Yuan Kung, Yinan Yu, Tomas McKelvey, 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Kernel SODA: A Feature Reduction Technique Using Kernel Based Analysis

Sun-Yuan Kung, Yinan Yu, Tomas McKelvey, 2013, 2013 12th International Conference on Machine Learning and Applications.

On efficient learning and classification kernel methods

Sun-Yuan Kung, Pei Yuan Wu, S. Kung, 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Kernel Approaches to Unsupervised and Supervised Machine Learning

Sun-Yuan Kung, S. Kung, 2009, PCM.

Kernel Methods and Machine Learning: References

S. Kung, 2014 .

Efficient Divide-And-Conquer Classification Based on Feature-Space Decomposition pdf

Sun-Yuan Kung, Feng Jiang, Xiangyang Ji, 2015, ArXiv.

Optical interconnections for VLSI systems

F.J. Leonberger, J.W. Goodman, Sun-Yuan Kung, 1984, Proceedings of the IEEE.

Comb Convolution for Efficient Convolutional Architecture pdf

Sun-Yuan Kung, Yuan Zhou, Dandan Li, 2019, ArXiv.

Low-power SVM classifiers for sound event classification on mobile devices

Sun-Yuan Kung, Man-Wai Mak, S. Kung, 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

A Feature-map Discriminant Perspective for Pruning Deep Neural Networks pdf

Zejiang Hou, Sun-Yuan Kung, S. Kung, 2020, ArXiv.

Efficient Image Super Resolution Via Channel Discriminative Deep Neural Network Pruning

Zejiang Hou, Sun-Yuan Kung, S. Kung, 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Augment deep BP-parameter learning with local XAI-structural learning

Sun-Yuan Kung, Zejiang Hou, S. Kung, 2020, Commun. Inf. Syst..

Semi-Supervised Few-Shot Learning Via Dependency Maximization and Instance Discriminant Analysis

S. Kung, Zejiang Hou, 2022, Journal of Signal Processing Systems.

Perturbation regulated kernel regressors for supervised machine learning

Sun-Yuan Kung, Pei Yuan Wu, S. Kung, 2012, 2012 IEEE International Workshop on Machine Learning for Signal Processing.

Efficient Divide-and-Conquer Classification Based on Parallel Feature-Space Decomposition for Distributed Systems

Sun-Yuan Kung, Seungmin Rho, Feng Jiang, 2015, IEEE Systems Journal.

Parameter design tradeoff between prediction performance and training time for Ridge-SVM

Sun-Yuan Kung, Rasmus Rothe, Yinan Yu, 2013, 2013 IEEE International Workshop on Machine Learning for Signal Processing (MLSP).

A Linear Systolic Array for Real-Time Morphological Image Processing

Sun-Yuan Kung, Konstantinos I. Diamantaras, S. Kung, 1997, J. VLSI Signal Process..

Transductive Learning for Multi-Label Protein Subchloroplast Localization Prediction

Sun-Yuan Kung, Shibiao Wan, Man-Wai Mak, 2017, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Supervising Nyström Methods via Negative Margin Support Vector Selection pdf

Sun-Yuan Kung, Mert Al, Thee Chanyaswad, 2018, ArXiv.

Kernel Methods and Machine Learning

S. Kung, 2014 .

Algorithms/applications/architectures of artificial neural nets

Jenq-Neng Hwang, Sun-Yuan Kung, Jenq-Neng Hwang, 1988 .

A unified modeling of neural networks architectures

S. Y. Kung, J. N. Hwang, S. Kung, 1991 .

Multiclass Ridge-adjusted Slack Variable Optimization using selected basis for fast classification

Sun-Yuan Kung, Yinan Yu, Konstantinos I. Diamantaras, 2014, 2014 22nd European Signal Processing Conference (EUSIPCO).

Impulse radio pulse shaping for ultra-wide bandwidth (UWB) systems

Yunnan Wu, Sun-Yuan Kung, Andreas F. Molisch, 2003, 14th IEEE Proceedings on Personal, Indoor and Mobile Radio Communications, 2003. PIMRC 2003..

BAWGNet: Boundary aware wavelet guided network for the nuclei segmentation in histopathology images

S. Kung, S. Fattah, Tamjid Imtiaz, 2023, Comput. Biol. Medicine.

Integrated fast implementation of mathematical morphology operations in image processing

Sun-Yuan Kung, Konstantinos I. Diamantaras, K. H. Zimmermann, 1990, IEEE International Symposium on Circuits and Systems.

Volume rendering by wavefront architecture

S. Y. Kung, Shang-Hung Lin, S. Kung, 1993, Proceedings of International Conference on Application Specific Array Processors (ASAP '93).

A unification of network coding and tree-packing (routing) theorems

Yunnan Wu, Sun-Yuan Kung, Kamal Jain, 2006, TNET.

On supercomputing with systolic/wavefront array processors

Sun-Yuan Kung, S. Kung, 1984 .

A highly concurrent algorithm and pipeleined architecture for solving Toeplitz systems

Sun-Yuan Kung, Yu Hu, S. Kung, 1983 .

Object-based scene segmentation combining motion and image cues

Sun-Yuan Kung, Yen-Kuang Chen, Yun-Ting Lin, 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

Motion-based segmentation by principal singular vector (PSV) clustering method

Sun-Yuan Kung, Yen-Kuang Chen, Yun-Ting Lin, 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

Super-resolution Imaging Based on Global Interpolation and Structural Similarities

Sun-Yuan Kung, Ying Chen, Yuan Zhou, 2018, 2018 24th International Conference on Pattern Recognition (ICPR).

Differential mutual information forward search for multi-kernel discriminant-component selection with an application to privacy-preserving classification

Sun-Yuan Kung, J. Morris Chang, Mert Al, 2017, 2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP).

WAVEFRONT ARRAY PROCESSOR: ARCHITECTURE, LANGUAGE AND APPLICATIONS.

Sun-Yuan Kung, K. S. Arun, R. J. Gal-Ezer, 1982 .

Multimedia Signal Processors: An Architectural Platform with Algorithmic Compilation

Sun-Yuan Kung, Yen-Kuang Chen, S. Kung, 1998, J. VLSI Signal Process..

Adversarial Learning for Multiscale Crowd Counting Under Complex Scenes

Yuan Zhou, Hongru Li, Sun-Yuan Kung, 2020, IEEE Transactions on Cybernetics.

Bezout equalization for STBC-MIMO systems

Yunnan Wu, Sun-Yuan Kung, Xinying Zhang, 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

A recursive QR approach to adaptive equalization of time-varying MIMO channels

Sun-Yuan Kung, Xinying Zhang, Chad L. Myers, 2005, Commun. Inf. Syst..

Semantic Relevance Learning for Video-Query Based Video Moment Retrieval

S. Kung, Yuan Zhou, Shuwei Huo, 2023, IEEE Transactions on Multimedia.

Adaptive Irregular Graph Construction-Based Salient Object Detection

Sun-Yuan Kung, Yuan Zhou, Tianhao Zhang, 2020, IEEE Transactions on Circuits and Systems for Video Technology.

Extraction of Video Objects via Surface Optimization and Voronoi Order

Sun-Yuan Kung, I-Jong Lin, S. Kung, 2001, J. VLSI Signal Process..

Dynamic programming implementation on array processor architectures

Sun-Yuan Kung, Konstantinos I. Diamantaras, W. H. Chou, 1996, J. VLSI Signal Process..

Timing Analysis and Design Optimization of VLSI Data Flow Arrays

Sun-Yuan Kung, Paul S. Lewis, Sheng-Chun Lo, 1986, ICPP.

A Wavefront Array Processor Using Dataflow Processing Elements

John A. Vlontzos, Sun-Yuan Kung, S. Kung, 1987, ICS.

Maximum Likelihood and Maximum a Posteriori Adaptation for Distributed Speaker Recognition Systems

Sun-Yuan Kung, Man-Wai Mak, Chin-Hung Sit, 2004, ICBA.

Extraction of Speaker Features from Different Stages of DSR Front-Ends for Distributed Speaker Verification

Sun-Yuan Kung, Man-Wai Mak, Chin-Hung Sit, 2005, Int. J. Speech Technol..

Hierarchically Aggregated Residual Transformation for Single Image Super Resolution

Sun-Yuan Kung, Zejiang Hou, S. Kung, 2021, 2020 25th International Conference on Pattern Recognition (ICPR).

Data mapping by probabilistic modular networks and information-theoretic criteria

Sun-Yuan Kung, Huai Li, Yue Joseph Wang, 1998, IEEE Trans. Signal Process..

A Kernel Discriminant Information Approach to Non-linear Feature Selection

Zejiang Hou, S. Y. Kung, S. Kung, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Trend and Challenge on System-on-a-Chip Designs

Sun-Yuan Kung, Yen-Kuang Chen, S. Kung, 2008, J. Signal Process. Syst..

Support vector analysis of large-scale data based on kernels with iteratively increasing order

S. Kung, Seungmin Rho, Bo-Wei Chen, 2016, The Journal of Supercomputing.

A fast rate-optimized motion estimation algorithm for low-bit-rate video coding

Sun-Yuan Kung, Yen-Kuang Chen, John C.-H. Ju, 1999, IEEE Trans. Circuits Syst. Video Technol..

Multilayer neural networks for reduced-rank approximation

Sun-Yuan Kung, Konstantinos I. Diamantaras, S. Kung, 1994, IEEE Trans. Neural Networks.

Kernel Methods and Machine Learning: Efficient kernel methods for learning and classification

S. Y. Kung, S. Kung, 2014 .

Ridge-adjusted Slack Variable Optimization for supervised classification

Sun-Yuan Kung, Yinan Yu, Konstantinos I. Diamantaras, 2013, 2013 IEEE International Workshop on Machine Learning for Signal Processing (MLSP).

Multi-Kernel, Deep Neural Network and Hybrid Models for Privacy Preserving Machine Learning

Sun-Yuan Kung, Mert Al, Thee Chanyaswad, 2018, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).