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07/05/2023
Zero-Shot Neural Architecture Search: Challenges, Solutions, and Opportunities
Recently, zero-shot (or training-free) Neural Architecture Search (NAS) ...
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05/13/2023
TIPS: Topologically Important Path Sampling for Anytime Neural Networks
Anytime neural networks (AnytimeNNs) are a promising solution to adaptiv...
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01/26/2023
ZiCo: Zero-shot NAS via Inverse Coefficient of Variation on Gradients
Neural Architecture Search (NAS) is widely used to automatically design ...
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08/17/2022
Restructurable Activation Networks
Is it possible to restructure the non-linear activation functions in a d...
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12/29/2021
Super-Efficient Super Resolution for Fast Adversarial Defense at the Edge
Autonomous systems are highly vulnerable to a variety of adversarial att...
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03/17/2021
Collapsible Linear Blocks for Super-Efficient Super Resolution
With the advent of smart devices that support 4K and 8K resolution, Sing...
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08/25/2020
New Directions in Distributed Deep Learning: Bringing the Network at Forefront of IoT Design
In this paper, we first highlight three major challenges to large-scale ...
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04/07/2020
FedMAX: Mitigating Activation Divergence for Accurate and Communication-Efficient Federated Learning
In this paper, we identify a new phenomenon called activation-divergence...
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10/23/2019
EdgeAI: A Vision for Deep Learning in IoT Era
The significant computational requirements of deep learning present a ma...
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10/02/2019
Towards Unifying Neural Architecture Space Exploration and Generalization
In this paper, we address a fundamental research question of significant...
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07/26/2019
Memory- and Communication-Aware Model Compression for Distributed Deep Learning Inference on IoT
Model compression has emerged as an important area of research for deplo...
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05/17/2019
Dream Distillation: A Data-Independent Model Compression Framework
Model compression is eminently suited for deploying deep learning on IoT...
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01/20/2019
NIF: A Framework for Quantifying Neural Information Flow in Deep Networks
In this paper, we present a new approach to interpreting deep learning m...
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12/06/2018
Climate Anomalies vs Air Pollution: Carbon Emissions and Anomaly Networks
This project aims to shed light on how man-made carbon emissions are aff...
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12/01/2018
