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06/30/2022
QUIDAM: A Framework for Quantization-Aware DNN Accelerator and Model Co-Exploration
As the machine learning and systems communities strive to achieve higher...
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06/22/2022
Play It Cool: Dynamic Shifting Prevents Thermal Throttling
Machine learning (ML) has entered the mobile era where an enormous numbe...
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04/24/2021
Width Transfer: On the (In)variance of Width Optimization
Optimizing the channel counts for different layers of a CNN has shown gr...
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08/22/2020
One Weight Bitwidth to Rule Them All
Weight quantization for deep ConvNets has shown promising results for ap...
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07/23/2020
PareCO: Pareto-aware Channel Optimization for Slimmable Neural Networks
Slimmable neural networks provide a flexible trade-off front between pre...
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02/07/2020
Improving the Adversarial Robustness of Transfer Learning via Noisy Feature Distillation
Fine-tuning through knowledge transfer from a pre-trained model on a lar...
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04/28/2019
LeGR: Filter Pruning via Learned Global Ranking
Filter pruning has shown to be effective for learning resource-constrain...
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04/05/2019
FLightNNs: Lightweight Quantized Deep Neural Networks for Fast and Accurate Inference
To improve the throughput and energy efficiency of Deep Neural Networks ...
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04/04/2019
Regularizing Activation Distribution for Training Binarized Deep Networks
Binarized Neural Networks (BNNs) can significantly reduce the inference ...
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02/08/2019
AdaScale: Towards Real-time Video Object Detection Using Adaptive Scaling
In vision-enabled autonomous systems such as robots and autonomous cars,...
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01/21/2019
Understanding the Impact of Label Granularity on CNN-based Image Classification
In recent years, supervised learning using Convolutional Neural Networks...
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10/04/2018
Domain Specific Approximation for Object Detection
There is growing interest in object detection in advanced driver assista...
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10/01/2018