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08/11/2022
MILAN: Masked Image Pretraining on Language Assisted Representation
Self-attention based transformer models have been dominating many comput...
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12/31/2021
Multi-Dimensional Model Compression of Vision Transformer
Vision transformers (ViT) have recently attracted considerable attention...
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09/07/2021
Few-shot Learning via Dependency Maximization and Instance Discriminant Analysis
We study the few-shot learning (FSL) problem, where a model learns to re...
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01/03/2021
A Novel Multi-Stage Training Approach for Human Activity Recognition from Multimodal Wearable Sensor Data Using Deep Neural Network
Deep neural network is an effective choice to automatically recognize hu...
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12/02/2020
CovSegNet: A Multi Encoder-Decoder Architecture for Improved Lesion Segmentation of COVID-19 Chest CT Scans
Automatic lung lesions segmentation of chest CT scans is considered a pi...
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07/30/2020
Privacy Enhancing Machine Learning via Removal of Unwanted Dependencies
The rapid rise of IoT and Big Data has facilitated copious data driven a...
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05/28/2020
A Feature-map Discriminant Perspective for Pruning Deep Neural Networks
Network pruning has become the de facto tool to accelerate deep neural n...
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03/01/2020
Soft-Root-Sign Activation Function
The choice of activation function in deep networks has a significant eff...
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11/24/2019
Exploiting Operation Importance for Differentiable Neural Architecture Search
Recently, differentiable neural architecture search methods significantl...
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11/04/2019
Cross-Scale Residual Network for Multiple Tasks:Image Super-resolution, Denoising, and Deblocking
In general, image restoration involves mapping from low quality images t...
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11/04/2019
Temporal Action Localization using Long Short-Term Dependency
Temporal action localization in untrimmed videos is an important but dif...
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11/01/2019
Comb Convolution for Efficient Convolutional Architecture
Convolutional neural networks (CNNs) are inherently suffering from massi...
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09/23/2019
Scalable Kernel Learning via the Discriminant Information
Kernel approximation methods have been popular techniques for scalable k...
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06/09/2019
HGC: Hierarchical Group Convolution for Highly Efficient Neural Network
Group convolution works well with many deep convolutional neural network...
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05/10/2018
Supervising Nyström Methods via Negative Margin Support Vector Selection
Pattern recognition on big data can be challenging for kernel machines a...
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02/26/2017