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09/16/2023
Accelerating In-Browser Deep Learning Inference on Diverse Edge Clients through Just-in-Time Kernel Optimizations
Web applications are increasingly becoming the primary platform for AI s...
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08/29/2023
Empowering LLM to use Smartphone for Intelligent Task Automation
Mobile task automation is an attractive technique that aims to enable vo...
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08/29/2023
Serving MoE Models on Resource-constrained Edge Devices via Dynamic Expert Swapping
Mixture of experts (MoE) is a popular technique in deep learning that im...
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08/29/2023
Generative Model for Models: Rapid DNN Customization for Diverse Tasks and Resource Constraints
Unlike cloud-based deep learning models that are often large and uniform...
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08/22/2023
PatchBackdoor: Backdoor Attack against Deep Neural Networks without Model Modification
Backdoor attack is a major threat to deep learning systems in safety-cri...
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04/15/2023
OliVe: Accelerating Large Language Models via Hardware-friendly Outlier-Victim Pair Quantization
Transformer-based large language models (LLMs) have achieved great succe...
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03/13/2023
AdaptiveNet: Post-deployment Neural Architecture Adaptation for Diverse Edge Environments
Deep learning models are increasingly deployed to edge devices for real-...
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02/07/2023
LUT-NN: Towards Unified Neural Network Inference by Table Lookup
DNN inference requires huge effort of system development and resource co...
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11/11/2022
StrokeGAN+: Few-Shot Semi-Supervised Chinese Font Generation with Stroke Encoding
The generation of Chinese fonts has a wide range of applications. The cu...
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09/22/2022
Nesting Forward Automatic Differentiation for Memory-Efficient Deep Neural Network Training
An activation function is an element-wise mathematical function and play...
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08/30/2022
ANT: Exploiting Adaptive Numerical Data Type for Low-bit Deep Neural Network Quantization
Quantization is a technique to reduce the computation and memory cost of...
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06/11/2022
Reducing Capacity Gap in Knowledge Distillation with Review Mechanism for Crowd Counting
The lightweight crowd counting models, in particular knowledge distillat...
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05/15/2022
Automation Slicing and Testing for in-App Deep Learning Models
Intelligent Apps (iApps), equipped with in-App deep learning (DL) models...
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02/14/2022
SQuant: On-the-Fly Data-Free Quantization via Diagonal Hessian Approximation
Quantization of deep neural networks (DNN) has been proven effective for...
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01/05/2022
Sample Selection with Deadline Control for Efficient Federated Learning on Heterogeneous Clients
Federated Learning (FL) trains a machine learning model on distributed c...
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12/05/2021
Boosting Mobile CNN Inference through Semantic Memory
Human brains are known to be capable of speeding up visual recognition o...
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11/22/2021
DAPPER: Performance Estimation of Domain Adaptation in Mobile Sensing
Many applications that utilize sensors in mobile devices and apply machi...
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10/13/2021
Rethinking the Representational Continuity: Towards Unsupervised Continual Learning
Continual learning (CL) aims to learn a sequence of tasks without forget...
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05/20/2021
Dual-side Sparse Tensor Core
Leveraging sparsity in deep neural network (DNN) models is promising for...
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02/04/2021
App Developer Centric Trusted Execution Environment
ARM TrustZone is the de-facto hardware TEE implementation on mobile devi...
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01/18/2021
DeepPayload: Black-box Backdoor Attack on Deep Learning Models through Neural Payload Injection
Deep learning models are increasingly used in mobile applications as cri...
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12/16/2020
StrokeGAN: Reducing Mode Collapse in Chinese Font Generation via Stroke Encoding
The generation of stylish Chinese fonts is an important problem involved...
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10/25/2019
Hardware-aware One-Shot Neural Architecture Search in Coordinate Ascent Framework
Designing accurate and efficient convolutional neural architectures for ...
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09/02/2019
Approximate Query Processing on Autonomous Cameras
Surveillance IoT cameras are becoming autonomous: they operate on batter...
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04/28/2019
Supporting Video Queries on Zero-Streaming Cameras
As low-cost surveillance cameras grow rapidly, we advocate for these cam...
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11/08/2018
A First Look at Deep Learning Apps on Smartphones
We are in the dawn of deep learning explosion for smartphones. To bridge...
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11/08/2018
When Mobile Apps Going Deep: An Empirical Study of Mobile Deep Learning
Deep learning (DL) is a game-changing technique in mobile scenarios, as ...
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12/01/2017
