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06/09/2022
Quantum Policy Iteration via Amplitude Estimation and Grover Search – Towards Quantum Advantage for Reinforcement Learning
We present a full implementation and simulation of a novel quantum reinf...
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12/17/2020
FantastIC4: A Hardware-Software Co-Design Approach for Efficiently Running 4bit-Compact Multilayer Perceptrons
With the growing demand for deploying deep learning models to the "edge"...
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04/09/2020
Dithered backprop: A sparse and quantized backpropagation algorithm for more efficient deep neural network training
Deep Neural Networks are successful but highly computationally expensive...
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04/02/2020
Learning Sparse Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T)
Deep neural networks (DNN) have shown remarkable success in a variety of...
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12/18/2019
Pruning by Explaining: A Novel Criterion for Deep Neural Network Pruning
The success of convolutional neural networks (CNNs) in various applicati...
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07/27/2019
DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks
The field of video compression has developed some of the most sophistica...
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05/15/2019
DeepCABAC: Context-adaptive binary arithmetic coding for deep neural network compression
We present DeepCABAC, a novel context-adaptive binary arithmetic coder f...
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03/07/2019
Robust and Communication-Efficient Federated Learning from Non-IID Data
Federated Learning allows multiple parties to jointly train a deep learn...
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12/18/2018
Entropy-Constrained Training of Deep Neural Networks
We propose a general framework for neural network compression that is mo...
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05/27/2018
Compact and Computationally Efficient Representation of Deep Neural Networks
Dot product operations between matrices are at the heart of almost any f...
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05/22/2018