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11/30/2020
ScaleNAS: One-Shot Learning of Scale-Aware Representations for Visual Recognition
Scale variance among different sizes of body parts and objects is a chal...
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07/08/2020
NASGEM: Neural Architecture Search via Graph Embedding Method
Neural Architecture Search (NAS) automates and prospers the design of ne...
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03/04/2020
Ordering Chaos: Memory-Aware Scheduling of Irregularly Wired Neural Networks for Edge Devices
Recent advances demonstrate that irregularly wired neural networks from ...
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11/21/2019
AutoShrink: A Topology-aware NAS for Discovering Efficient Neural Architecture
Resource is an important constraint when deploying Deep Neural Networks ...
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04/15/2019
Low-Power Computer Vision: Status, Challenges, Opportunities
Computer vision has achieved impressive progress in recent years. Meanwh...
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12/06/2018
Towards Leveraging the Information of Gradients in Optimization-based Adversarial Attack
In recent years, deep neural networks demonstrated state-of-the-art perf...
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11/27/2018
LEASGD: an Efficient and Privacy-Preserving Decentralized Algorithm for Distributed Learning
Distributed learning systems have enabled training large-scale models ov...
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10/20/2018
Differentiable Fine-grained Quantization for Deep Neural Network Compression
Neural networks have shown great performance in cognitive tasks. When de...
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10/03/2018
2018 Low-Power Image Recognition Challenge
The Low-Power Image Recognition Challenge (LPIRC, https://rebootingcompu...
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05/27/2017
