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Machine Learning for Systems
2020
IEEE Micro
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"Enhancing Model Parallelism in Neural Architecture Search for Multidevice Systems" is another article that analyzes automatic optimization techniques for improving the performance of deep neural networks ...
In "RELEQ: A Reinforcement Learning Approach for Automatic Deep Quantization of Neural Networks," the authors describe a reinforcement learning mechanism to optimize deep neural network architectures. ...
doi:10.1109/mm.2020.3016551
fatcat:7lbbknjtmjamha2ek5fnc2tbem
2020 Index IEEE Transactions on Very Large Scale Integration (VLSI) Systems Vol. 28
2020
IEEE Transactions on Very Large Scale Integration (vlsi) Systems
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., Conflux-An Asynchronous Two-to-One Multiplexor for Time-Division Multiplexing and Clockless, Tokenless Readout; TVLSI Feb. 2020 503-515 Holcomb, D., see 2685-2698 Holcomb, D.E., see 1807-1820 Homayoun ...
., +, TVLSI Feb. 2020 433-442
Algorithm and Architecture of an Efficient MIMO Detector With Cross-
Level Parallel Tree-Search. ...
., +, TVLSI April 2020 954-967 Computational complexity Algorithm and Architecture of an Efficient MIMO Detector With Cross-Level Parallel Tree-Search. ...
doi:10.1109/tvlsi.2020.3041879
fatcat:33vb2eia2jfjpog4wei4peq5ge
Device and Circuit Architectures for In‐Memory Computing
2020
Advanced Intelligent Systems
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Finally, array architectures for computing are reviewed, including typical architectures for neural network accelerators, content addressable memory (CAM), and novel circuit topologies for general-purpose ...
In-memory computing (IMC) appears as a promising approach to suppress the memory bottleneck and enable higher parallelism of data processing, thanks to the memory array architecture. ...
Keywords artificial intelligence, in-memory computing, machine learning, memories, neural networks ...
doi:10.1002/aisy.202000040
fatcat:qo4yfcftdva2npkdltopwgqkby
Privacy-Preserving Cloud Computing: Ecosystem, Life Cycle, Layered Architecture and Future Roadmap
[article]
2022
arXiv
pre-print
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This paper helps to identify existing trends by establishing a layered architecture along with a life cycle and an ecosystem for privacy-preserving cloud systems in addition to identifying the existing ...
This survey paper on privacy-preserving cloud computing can help pave the way for future research in related areas. ...
and modeling error by making use of multidevice diversity. ...
arXiv:2204.11120v1
fatcat:tx75pckegjgqxg6tiibptiazbi
Improving the Performance of Whale Optimization Algorithm through OpenCL-Based FPGA Accelerator
2020
Complexity
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The proposed framework comprises two feasible parallel models called partial parallel and all-FPGA parallel, respectively. ...
System-on-Chip. ...
Exploration Phase (Searching for Preys ). In addition to exploitation phase, a stochastic searching technique is also adopted to enhance the exploration in WOA. ...
doi:10.1155/2020/8810759
fatcat:z2yil2yb5nbbjbiiuxiwodfsni
Investigations on Performance Enhancement Measures of the Bidirectional Converter in PV–Wind Interconnected Microgrid System
2019
Energies
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The wind and PV interconnected microgrid system was mathematically modeled for steady-state conditions. This hybrid microgrid model was simulated using the MATLAB/SIMULINK platform. ...
The outcomes establish that the system can be kept up in a steady-state condition under the recommended control plans when the network is changed, starting with one working condition then onto the next ...
In the proposed work for the same 3 kW system, the power factor enhancement was attained between 20% to 40%. ...
doi:10.3390/en12142672
fatcat:7fnrfrqj4bfmbe3gkdl7g73n6q
Reinforcement Learning-Empowered Mobile Edge Computing for 6G Edge Intelligence
2022
IEEE Access
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This paper provides a comprehensive research review on RL-enabled MEC and offers insight for development in this area. ...
Finally, the open challenges are discussed to provide helpful guidance for future research in RL training and learning MEC. ...
In [171] , to solve the curseof-dimensionality problem and reduce the signal overhead, an improved neural network architecture was designed for value function approximation, including local feature summation ...
doi:10.1109/access.2022.3183647
fatcat:pd5z6q4innd5jl25g4r7b4nq3i
2021 Index IEEE Transactions on Instrumentation and Measurement Vol. 70
2021
IEEE Transactions on Instrumentation and Measurement
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The Author Index contains the primary entry for each item, listed under the first author's name. ...
-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021. ...
Zhao, P., +, TIM 2021 4002811 Automatic Attention Learning Using Neural Architecture Search for Detection of Cardiac Abnormality in 12-Lead ECG. ...
doi:10.1109/tim.2022.3156705
fatcat:dmqderzenrcopoyipv3v4vh4ry
Reinforcement Learning-Empowered Mobile Edge Computing for 6G Edge Intelligence
[article]
2022
arXiv
pre-print
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This paper provides a comprehensive research review on RL-enabled MEC and offers insight for development in this area. ...
Finally, the open challenges are discussed to provide helpful guidance for future research in RL training and learning MEC. ...
In [171] , to solve the curse-ofdimensionality problem and reduce the signal overhead, an improved neural network architecture was designed for the value function approximation, including local feature ...
arXiv:2201.11410v4
fatcat:24igkq4kbrb2pjzwf3mf3n7qtq
SmartAuth: User-Centered Authorization for the Internet of Things
2017
USENIX Security Symposium
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Through the interface, security policies can be generated and enforced by enhancing existing platforms. ...
device's context (e.g., a humidity sensor in a bath room) to an activity's semantics (e.g., taking a bath) using natural language processing and program analysis. ...
Our security policy model for the smart home architecture is described in the form of a triple (E, A, T ). ...
dblp:conf/uss/TianZLWUGT17
fatcat:fnv5tm6wszgedknufzl63xmbvq
Experiments in Immersive Virtual Reality for Scientific Visualization
2002
Computers & graphics
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This article provides a snapshot of immersive virtual reality (IVR) use for scientific visualization, in the context of the evolution of computing in general and of user interfaces in particular. ...
Clearly, visualization by itself will not solve the problem of understanding truly large datasets that would overwhelm both display capacity and the human visual system. ...
As always we are deeply grateful for the superb editing of Katrina Avery. ...
doi:10.1016/s0097-8493(02)00113-9
fatcat:cvhdqfjm35gqtpsuyt5wyw6bly
Machine Learning Parallelism Could Be Adaptive, Composable and Automated
2021
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Applying parallel training systems tocomplex models adds nontrivial development overheads in addition to model prototyping, and often results in lower-than-expected performance. ...
They enable rapid compositions of parallelization strategies for unseen models, improve parallelization performance, and simplify parallel ML programming. ...
In this chapter, we co-develop representations and systems for dynamic neural network parallelisms. ...
doi:10.1184/r1/14402450
fatcat:be5w3hpokjcvplwhzqjnkz5re4
Intelligent systems and services for image and video analysis
[article]
2021
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This doctoral dissertation explores intelligent systems and services for image and video analysis. ...
The architecture is capable of extracting multi-scale image features by using blocks of parallel convolutional layers with different filter sizes. ...
Handling the pipeline execution in a highly scalable system architecture; • Task scheduling for task parallelization. ...
doi:10.26253/heal.uth.13375
fatcat:4fay4wumojfndc5b6cokz2wijq
Software and Hardware Co-design for Efficient Neural Networks
2022
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A combination of different styles of neural network compression techniques can offer multiplying gains in shrinking the memory footprints. ...
Deep Neural Networks (DNNs) offer state-of-the-art performance in many domains but this success comes at the cost of high computational and memory resources. ...
I felt I have been increditably lucky to have him as my PhD supervisor and will always be truely thankful to the amount of reserach freedom that he lets me to have in my PhD studies. ...
doi:10.17863/cam.86258
fatcat:smuvfjrmvve47cfpgooxs3tea4
Reinforcement Learning-Empowered Mobile Edge Computing for 6G Edge Intelligence
[article]
2022
Preserved Fulltext
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This paper provides a comprehensive research review on RL-enabled MEC and offers insight for development in this area. ...
Finally, the open challenges are discussed to provide helpful guidance for future research in RL training and learning MEC. ...
In [169] , to solve the curse-ofdimensionality problem and reduce the signal overhead, an improved neural network architecture was designed for the value function approximation, including local feature ...
doi:10.48550/arxiv.2201.11410
fatcat:5242ngqtgbhvdpcuhcygxdvsru
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