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06/25/2023
Adaptive Sharpness-Aware Pruning for Robust Sparse Networks
Robustness and compactness are two essential components of deep learning...
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06/14/2023
Heterogeneous Continual Learning
We propose a novel framework and a solution to tackle the continual lear...
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06/09/2023
FasterViT: Fast Vision Transformers with Hierarchical Attention
We design a new family of hybrid CNN-ViT neural networks, named FasterVi...
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04/02/2023
Recurrence without Recurrence: Stable Video Landmark Detection with Deep Equilibrium Models
Cascaded computation, whereby predictions are recurrently refined over s...
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10/13/2022
Structural Pruning via Latency-Saliency Knapsack
Structural pruning can simplify network architecture and improve inferen...
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06/20/2022
Global Context Vision Transformers
We propose global context vision transformer (GC ViT), a novel architect...
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03/22/2022
GradViT: Gradient Inversion of Vision Transformers
In this work we demonstrate the vulnerability of vision transformers (Vi...
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02/14/2022
Do Gradient Inversion Attacks Make Federated Learning Unsafe?
Federated learning (FL) allows the collaborative training of AI models w...
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12/14/2021
AdaViT: Adaptive Tokens for Efficient Vision Transformer
We introduce AdaViT, a method that adaptively adjusts the inference cost...
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10/22/2021
When to Prune? A Policy towards Early Structural Pruning
Pruning enables appealing reductions in network memory footprint and tim...
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10/20/2021
HALP: Hardware-Aware Latency Pruning
Structural pruning can simplify network architecture and improve inferen...
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10/10/2021
NViT: Vision Transformer Compression and Parameter Redistribution
Transformers yield state-of-the-art results across many tasks. However, ...
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07/13/2021
Deep Neural Networks are Surprisingly Reversible: A Baseline for Zero-Shot Inversion
Understanding the behavior and vulnerability of pre-trained deep neural ...
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04/15/2021
See through Gradients: Image Batch Recovery via GradInversion
Training deep neural networks requires gradient estimation from data bat...
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02/20/2021
MHDeep: Mental Health Disorder Detection System based on Body-Area and Deep Neural Networks
Mental health problems impact quality of life of millions of people arou...
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07/29/2020
Fully Dynamic Inference with Deep Neural Networks
Modern deep neural networks are powerful and widely applicable models th...
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04/18/2020
Efficient Synthesis of Compact Deep Neural Networks
Deep neural networks (DNNs) have been deployed in myriad machine learnin...
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12/18/2019
Dreaming to Distill: Data-free Knowledge Transfer via DeepInversion
We introduce DeepInversion, a new method for synthesizing images from th...
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10/11/2019
DiabDeep: Pervasive Diabetes Diagnosis based on Wearable Medical Sensors and Efficient Neural Networks
Diabetes impacts the quality of life of millions of people. However, dia...
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05/27/2019
Incremental Learning Using a Grow-and-Prune Paradigm with Efficient Neural Networks
Deep neural networks (DNNs) have become a widely deployed model for nume...
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01/30/2019
Hardware-Guided Symbiotic Training for Compact, Accurate, yet Execution-Efficient LSTM
Many long short-term memory (LSTM) applications need fast yet compact mo...
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12/21/2018
ChamNet: Towards Efficient Network Design through Platform-Aware Model Adaptation
This paper proposes an efficient neural network (NN) architecture design...
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05/30/2018
Grow and Prune Compact, Fast, and Accurate LSTMs
Long short-term memory (LSTM) has been widely used for sequential data m...
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05/30/2018
Grow and Prune Compact, Fast, and AccurateLSTMs
Long short-term memory (LSTM) has been widely used for sequential data m...
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11/06/2017