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12/29/2022
BiMLP: Compact Binary Architectures for Vision Multi-Layer Perceptrons
This paper studies the problem of designing compact binary architectures...
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04/24/2022
Source-Free Domain Adaptation via Distribution Estimation
Domain Adaptation aims to transfer the knowledge learned from a labeled ...
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06/21/2021
Federated Learning with Positive and Unlabeled Data
We study the problem of learning from positive and unlabeled (PU) data i...
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03/10/2021
Manifold Regularized Dynamic Network Pruning
Neural network pruning is an essential approach for reducing the computa...
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03/01/2021
Learning Frequency Domain Approximation for Binary Neural Networks
Binary neural networks (BNNs) represent original full-precision weights ...
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12/23/2020
A Survey on Visual Transformer
Transformer is a type of deep neural network mainly based on self-attent...
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10/21/2020
SCOP: Scientific Control for Reliable Neural Network Pruning
This paper proposes a reliable neural network pruning algorithm by setti...
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10/10/2020
Training Binary Neural Networks through Learning with Noisy Supervision
This paper formalizes the binarization operations over neural networks f...
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09/28/2020
Kernel Based Progressive Distillation for Adder Neural Networks
Adder Neural Networks (ANNs) which only contain additions bring us a new...
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05/29/2020
DC-NAS: Divide-and-Conquer Neural Architecture Search
Most applications demand high-performance deep neural architectures cost...
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05/14/2020
A Semi-Supervised Assessor of Neural Architectures
Neural architecture search (NAS) aims to automatically design deep neura...
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02/23/2020
Beyond Dropout: Feature Map Distortion to Regularize Deep Neural Networks
Deep neural networks often consist of a great number of trainable parame...
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09/30/2019
RNAS: Architecture Ranking for Powerful Networks
Neural Architecture Search (NAS) is attractive for automatically produci...
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09/30/2019
ReNAS:Relativistic Evaluation of Neural Architecture Search
An effective and efficient architecture performance evaluation scheme is...
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09/21/2019
Positive-Unlabeled Compression on the Cloud
Many attempts have been done to extend the great success of convolutiona...
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08/06/2019