Results 11 to 20 of about 676,729 (299)
Spike-based dynamic computing with asynchronous sensing-computing neuromorphic chip [PDF]
Nature Communications, 2023 By mimicking the neurons and synapses of the human brain and employing spiking neural networks on neuromorphic chips, neuromorphic computing offers a promising energy-efficient machine intelligence.
Ole Richter +21 more
semanticscholar +1 more source
Proceedings of the ACM on Programming Languages, 2021 We explore asynchronous programming with algebraic effects. We complement their conventional synchronous treatment by showing how to naturally also accommodate asynchrony within them, namely, by decoupling the execution of operation calls into signalling that an operation’s implementation needs to be executed, and interrupting a running ...
Danel Ahman, Matija Pretnar
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AEGNN: Asynchronous Event-based Graph Neural Networks [PDF]
Computer Vision and Pattern Recognition, 2022 The best performing learning algorithms devised for event cameras work by first converting events into dense representations that are then processed using standard CNNs.
S. Schaefer +2 more
semanticscholar +1 more source
Mobility-Aware Cooperative Caching in Vehicular Edge Computing Based on Asynchronous Federated and Deep Reinforcement Learning [PDF]
IEEE Journal on Selected Topics in Signal Processing, 2022 Vehicular edge computing (VEC) can learn and cache most popular contents for vehicular users (VUs) in the roadside units (RSUs) to support real-time vehicular applications.
Qiong Wu +5 more
semanticscholar +1 more source
Pathways: Asynchronous Distributed Dataflow for ML [PDF]
Conference on Machine Learning and Systems, 2022 We present the design of a new large scale orchestration layer for accelerators. Our system, Pathways, is explicitly designed to enable exploration of new systems and ML research ideas, while retaining state of the art performance for current models ...
P. Barham +15 more
semanticscholar +1 more source
Asynchronous Gradient Push [PDF]
IEEE Transactions on Automatic Control, 2021 33 pages, 9 figures, accepted to IEEE Transactions on Automatic ...
Mahmoud S. Assran, Michael G. Rabbat
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Communication-Efficient Federated Deep Learning With Layerwise Asynchronous Model Update and Temporally Weighted Aggregation [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2019 Federated learning obtains a central model on the server by aggregating models trained locally on clients. As a result, federated learning does not require clients to upload their data to the server, thereby preserving the data privacy of the clients ...
Y. Chen, Xiaoyan Sun, Yaochu Jin
semanticscholar +1 more source
Combining Events and Frames Using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction [PDF]
IEEE Robotics and Automation Letters, 2021 Event cameras are novel vision sensors that report per-pixel brightness changes as a stream of asynchronous “events”. They offer significant advantages compared to standard cameras due to their high temporal resolution, high dynamic range and lack of ...
Daniel Gehrig +4 more
semanticscholar +1 more source
IEEE Transactions on Automatic Control, 2008 This paper formulates and solves a version of the widely studied Vicsek consensus problem in which each member of a group of n > 1 agents independently updates its heading at times determined by its own clock. It is not assumed that the agents' clocks are synchronized or that the "event" times between which any one agent updates its heading are ...
Cao, Ming +2 more
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End-to-End Learning of Representations for Asynchronous Event-Based Data [PDF]
IEEE International Conference on Computer Vision, 2019 Event cameras are vision sensors that record asynchronous streams of per-pixel brightness changes, referred to as "events”. They have appealing advantages over frame based cameras for computer vision, including high temporal resolution, high dynamic ...
Daniel Gehrig +3 more
semanticscholar +1 more source