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05/04/2023
CAMEL: Co-Designing AI Models and Embedded DRAMs for Efficient On-Device Learning
The emergence of the Internet of Things (IoT) has resulted in a remarkab...
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07/19/2022
SphereFed: Hyperspherical Federated Learning
Federated Learning aims at training a global model from multiple decentr...
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01/09/2022
A Multi-agent Reinforcement Learning Approach for Efficient Client Selection in Federated Learning
Federated learning (FL) is a training technique that enables client devi...
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10/28/2021
FAST: DNN Training Under Variable Precision Block Floating Point with Stochastic Rounding
Block Floating Point (BFP) can efficiently support quantization for Deep...
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10/27/2020
Succinct and Robust Multi-Agent Communication With Temporal Message Control
Recent studies have shown that introducing communication between agents ...
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07/13/2020
Term Revealing: Furthering Quantization at Run Time on Quantized DNNs
We present a novel technique, called Term Revealing (TR), for furthering...
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03/08/2020
On the Robustness of Cooperative Multi-Agent Reinforcement Learning
In cooperative multi-agent reinforcement learning (c-MARL), agents learn...
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12/04/2019
RTN: Reparameterized Ternary Network
To deploy deep neural networks on resource-limited devices, quantization...
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09/06/2019
Efficient Communication in Multi-Agent Reinforcement Learning via Variance Based Control
Multi-agent reinforcement learning (MARL) has recently received consider...
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05/01/2019
Full-stack Optimization for Accelerating CNNs with FPGA Validation
We present a full-stack optimization framework for accelerating inferenc...
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11/07/2018
Packing Sparse Convolutional Neural Networks for Efficient Systolic Array Implementations: Column Combining Under Joint Optimization
This paper describes a novel approach of packing sparse convolutional ne...
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02/09/2018