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Anthony Kuh
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2020 – today
- 2023
- [j14]Vinay Chakravarthi Gogineni
, Stefan Werner
Communication-Efficient Online Federated Learning Strategies for Kernel Regression. IEEE Internet Things J. 10(5): 4531-4544 (2023) - [j13]François Gauthier
Asynchronous Online Federated Learning With Reduced Communication Requirements. IEEE Internet Things J. 10(23): 20761-20775 (2023) - [j12]François Gauthier
Personalized Graph Federated Learning With Differential Privacy. IEEE Trans. Signal Inf. Process. over Networks 9: 736-749 (2023) - [c53]Anthony Kuh, Tyler Baguio:
Distributed on-line anomaly detection using kernel methods. APSIPA ASC 2023: 1208-1213 - [i8]François Gauthier, Vinay Chakravarthi Gogineni, Stefan Werner, Yih-Fang Huang, Anthony Kuh:
Asynchronous Online Federated Learning with Reduced Communication Requirements. CoRR abs/2303.15226 (2023) - [i7]François Gauthier, Vinay Chakravarthi Gogineni
Personalized Graph Federated Learning with Differential Privacy. CoRR abs/2306.06399 (2023) - 2022
- [j11]Vinay Chakravarthi Gogineni
Personalized Online Federated Learning for IoT/CPS: Challenges and Future Directions. IEEE Internet Things Mag. 5(4): 78-84 (2022) - [c52]François Gauthier, Vinay Chakravarthi Gogineni
Clustered Graph Federated Personalized Learning. IEEECONF 2022: 744-748 - [c51]Vinay Chakravarthi Gogineni
Decentralized Graph Federated Multitask Learning for Streaming Data. CISS 2022: 101-106 - [c50]Vinay Chakravarthi Gogineni
Communication-Efficient Online Federated Learning Framework for Nonlinear Regression. ICASSP 2022: 5228-5232 - [c49]François Gauthier, Vinay Chakravarthi Gogineni, Stefan Werner
Resource-Aware Asynchronous Online Federated Learning for Nonlinear Regression. ICC 2022: 2828-2833 - [c48]Clyde James Felix, Japhet Ye, Anthony Kuh:
Personalized Learning Using Kernel Methods and Random Fourier Features. IJCNN 2022: 1-5 - 2021
- [j10]Anthony Kuh, Norman Abramson:
In Memoriam: Norman Abramson. IEEE Commun. Mag. 59(1): 6-7 (2021) - [c47]Anthony Kuh, Shuai Huang, Cynthia Chen:
Personalized Learning using Multiple Kernel Models. APSIPA ASC 2021: 2085-2088 - [c46]Anthony Kuh:
Real Time Kernel Learning for Sensor Networks using Principles of Federated Learning. APSIPA ASC 2021: 2089-2093 - [i6]Vinay Chakravarthi Gogineni, Stefan Werner, Yih-Fang Huang, Anthony Kuh:
Communication-Efficient Online Federated Learning Framework for Nonlinear Regression. CoRR abs/2110.06556 (2021) - [i5]François Gauthier, Vinay Chakravarthi Gogineni, Stefan Werner, Yih-Fang Huang, Anthony Kuh:
Resource-Aware Asynchronous Online Federated Learning for Nonlinear Regression. CoRR abs/2111.13931 (2021) - 2020
- [j9]Kewei Chen
Nonlinear Adaptive Filtering With Kernel Set-Membership Approach. IEEE Trans. Signal Process. 68: 1515-1528 (2020)
2010 – 2019
- 2019
- [c45]Navid Tafaghodi Khajavi, Anthony Kuh:
Decomposition of Covariance Matrix Using Cascade of Trees. APSIPA 2019: 779-783 - [c44]Navid Tafaghodi Khajavi, Anthony Kuh:
Covariance Matrix Decomposition Using Cascade of Linear Tree Transformations. GlobalSIP 2019: 1-5 - 2018
- [c43]Kewei Chen, Stefan Werner
Nonlinear Online Learning - A Kernel SMF Approach. APSIPA 2018: 218-223 - [c42]Muhammad Sharif Uddin, Anthony Kuh:
Online Unsupervised Kernel Affine Projection Algorithms. APSIPA 2018: 229-234 - [i4]Mojtaba Abolfazli, June Zhang, Anthony Kuh:
How Consumer Empathy Assist Power Grid in Demand Response. CoRR abs/1807.07170 (2018) - [i3]Navid Tafaghodi Khajavi, Anthony Kuh:
Model Approximation Using Cascade of Tree Decompositions. CoRR abs/1808.03504 (2018) - 2017
- [c41]Anthony Kuh, Muhammad Sharif Uddin, Phyllis Ng:
Online unsupervised kernel learning algorithms. APSIPA 2017: 1019-1025 - 2016
- [c40]Navid Tafaghodi Khajavi, Anthony Kuh:
The goodness of covariance selection problem from AUC bounds. Allerton 2016: 1252-1258 - [c39]Navid Tafaghodi Khajavi, Anthony Kuh:
The covariance selection quality for graphs with junction trees through AUC bounds. APSIPA 2016: 1-6 - [c38]Muhammad Sharif Uddin
Online least-squares one-class support vector machine for outlier detection in power grid data. ICASSP 2016: 2628-2632 - [c37]Seyyed A. Fatemi, Anthony Kuh, Matthias Fripp:
Solar radiation forecast under convex piecewise linear cost functions. IJCNN 2016: 4985-4990 - [c36]Seyyed A. Fatemi, Anthony Kuh, Vijay Gupta
Energy efficient scheduling algorithms for pumping water in radial networks. ITA 2016: 1-6 - [c35]Navid Tafaghodi Khajavi, Anthony Kuh:
The quality of tree approximation from AUC bounds. ITA 2016: 1-7 - [i2]Navid Tafaghodi Khajavi, Anthony Kuh:
The Quality of the Covariance Selection Through Detection Problem and AUC Bounds. CoRR abs/1605.05776 (2016) - [i1]Navid Tafaghodi Khajavi, Anthony Kuh:
The Goodness of Covariance Selection Problem from AUC Bounds. CoRR abs/1608.07015 (2016) - 2015
- [c34]Anthony Kuh:
Signal and information processing applications for the smart grid. APSIPA 2015: 1238-1243 - [c33]Matthew Motoki, Monica Umeda, Matthias Fripp, Anthony Kuh:
Approximate dynamic programming for control of a residential water heater. IJCNN 2015: 1-8 - [c32]Navid Tafaghodi Khajavi, Anthony Kuh:
Formulation of the Tree Approximation Problem as a Detection Problem and Relation between the AUC and Information Theory Divergences. INNS Conference on Big Data 2015: 257-264 - 2014
- [c31]Trevor Alexander, Anthony Kuh, Katsuhiko Hamada, Hiromu Mori, Hiroyuki Shinoda
Parallel memory-efficient processing of BCI data. APSIPA 2014: 1-9 - [c30]Seyyed A. Fatemi, Anthony Kuh, Matthias Fripp:
Online solar radiation forecasting under asymmetrie cost functions. APSIPA 2014: 1-6 - [c29]Navid Tafaghodi Khajavi, Anthony Kuh, Narayana P. Santhanam:
Spatial correlations for solar PV generation and its tree approximation analysis. APSIPA 2014: 1-5 - [c28]Sayed Pouria Talebi
A Quaternion Least Mean Phase adaptive estimator. ICASSP 2014: 6419-6423 - [c27]Seyyed A. Fatemi, Anthony Kuh:
Solar radiation forecasting under asymmetric cost functions. IJCNN 2014: 1727-1732 - 2013
- [c26]Seyyed A. Fatemi, Anthony Kuh:
Solar radiation forecasting using zenith angle. GlobalSIP 2013: 523-526 - [c25]Muhammad Sharif Uddin
Nested bounds for the constrained sensor placement problem. ICASSP 2013: 4216-4220 - [c24]Navid Tafaghodi Khajavi, Anthony Kuh:
First order Markov chain approximation of microgrid renewable generators covariance matrix. ISIT 2013: 1207-1211 - 2012
- [c23]Anthony Kuh, Chuanyi Ji, Yun Wei:
Stochastic queuing models for distributed PV energy. APSIPA 2012: 1-6 - [c22]Toshihisa Tanaka, Yoshikazu Washizawa, Anthony Kuh:
Adaptive kernel principal components tracking. ICASSP 2012: 1905-1908 - [c21]Felipe A. Tobar, Anthony Kuh, Danilo P. Mandic:
A novel augmented complex valued kernel LMS. SAM 2012: 473-476 - [c20]Muhammad Sharif Uddin
Approximate solutions and performance bounds for the sensor placement problem. SmartGridComm 2012: 31-36 - 2011
- [j8]Ying Hu, Anthony Kuh, Tao Yang, Aleksandar Kavcic:
A Belief Propagation Based Power Distribution System State Estimator. IEEE Comput. Intell. Mag. 6(3): 36-46 (2011) - [c19]Ying Hu, Anthony Kuh, Aleksandar Kavcic, Dora Nakafuji:
Real-time state estimation on micro-grids. IJCNN 2011: 1378-1385 - [c18]David E. Bakken, Anjan Bose, K. Mani Chandy, Pramod P. Khargonekar
GRIP - Grids with intelligent periphery: Control architectures for Grid2050π. SmartGridComm 2011: 7-12 - 2010
- [c17]Nathan Kowahl, Anthony Kuh:
Micro-scale smart grid optimization. IJCNN 2010: 1-8
2000 – 2009
- 2009
- [c16]Anthony Kuh, Danilo P. Mandic:
Applications of complex augmented kernels to wind profile prediction. ICASSP 2009: 3581-3584 - 2008
- [c15]Anand Sharma, Anthony Kuh:
Class document frequency as a learned feature for text categorization. IJCNN 2008: 2988-2993 - 2007
- [j7]Anthony Kuh, Philippe De Wilde
Comments on "Pruning Error Minimization in Least Squares Support Vector Machines". IEEE Trans. Neural Networks 18(2): 606-609 (2007) - [c14]Chaopin Zhu, Anthony Kuh:
Ad Hoc Sensor Network Localization using Distributed Kernel Regression Algorithms. ICASSP (2) 2007: 497-500 - 2006
- [c13]Chaopin Zhu, Anthony Kuh:
On Randomly Evolving Email Networks. CISS 2006: 894-898 - [c12]Anthony Kuh, Danilo P. Mandic:
Sequential Detection Using Least Squares Temporal Difference Methods. ICASSP (5) 2006: 701-704 - [c11]Chaopin Zhu, Anthony Kuh:
Dynamic Ad Hoc Network Localization Using Online Least Squares Kernel Subspace Methods. ISIT 2006: 630-634 - [c10]Anthony Kuh, Chaopin Zhu, Danilo P. Mandic:
Sensor Network Localization Using Least Squares Kernel Regression. KES (3) 2006: 1280-1287 - 2005
- [c9]Danilo P. Mandic, Dragan Obradovic, Anthony Kuh, Tülay Adali, Udo Trutschel, Martin Golz, Philippe De Wilde
Data Fusion for Modern Engineering Applications: An Overview. ICANN (2) 2005: 715-721 - 2004
- [c8]Chengan Guo, Anthony Kuh:
An Optimal Neural-Network Model for Learning Posterior Probability Functions from Observations. ISNN (1) 2004: 370-376
1990 – 1999
- 1999
- [c7]Chengan Guo, Anthony Kuh:
A neural-network Q-learning method for decentralized sequential detection with feedback. IJCNN 1999: 2288-2291 - [c6]Anthony Kuh:
Performance of analog neural networks subject to drifting targets and noise. IJCNN 1999: 2406-2409 - 1997
- [j6]Xiaodong Tian, Anthony Kuh:
Performance Bounds for Single Layer Threshold Networks when Tracking a Drifting Adversary. Neural Networks 10(5): 897-906 (1997) - [j5]Chengan Guo, Anthony Kuh:
Temporal difference learning applied to sequential detection. IEEE Trans. Neural Networks 8(2): 278-287 (1997) - [j4]Anthony Kuh:
Comparison of tracking algorithms for single layer threshold networks in the presence of random drift. IEEE Trans. Signal Process. 45(3): 640-649 (1997) - 1996
- [j3]Meina Xu, Anthony Kuh:
Image coding using feature map finite-state vector quantization. IEEE Signal Process. Lett. 3(7): 215-217 (1996) - 1995
- [c5]Meina Xu, Anthony Kuh:
Unsupervised Learning Applied to Image Coding. ISCAS 1995: 1632-1635 - 1993
- [c4]Jianping Huang, Anthony Kuh:
A neural network isolated word recognition system for moderate sized databases. ICNN 1993: 387-391 - 1992
- [j2]Zezhen Kuang, Anthony Kuh:
A combined self-organizing feature map and multilayer perceptron for isolated word recognition. IEEE Trans. Signal Process. 40(11): 2651-2657 (1992) - 1991
- [c3]Anthony Kuh, Thomas Petsche, Ronald L. Rivest:
Incrementally Learning Time-Varying Half Planes. NIPS 1991: 920-927 - 1990
- [c2]Anthony Kuh, Thomas Petsche, Ronald L. Rivest:
Learning Time-Varying Concepts. NIPS 1990: 183-189
1980 – 1989
- 1989
- [j1]Anthony Kuh, Bradley W. Dickinson:
Information capacity of associative memories. IEEE Trans. Inf. Theory 35(1): 59-68 (1989) - 1987
- [c1]Anthony Kuh:
Performance Measures for Associative Memories that Learn and Forget. NIPS 1987: 432-441
Coauthor Index
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last updated on 2024-09-09 01:17 CEST by the dblp team
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