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05/25/2023
FedHC: A Scalable Federated Learning Framework for Heterogeneous and Resource-Constrained Clients
Federated Learning (FL) is a distributed learning paradigm that empowers...
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04/23/2023
GACER: Granularity-Aware ConcurrEncy Regulation for Multi-Tenant Deep Learning
As deep learning continues to advance and is applied to increasingly com...
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04/01/2022
QuadraLib: A Performant Quadratic Neural Network Library for Architecture Optimization and Design Exploration
The significant success of Deep Neural Networks (DNNs) is highly promote...
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03/17/2022
A Survey of Multi-Tenant Deep Learning Inference on GPU
Deep Learning (DL) models have achieved superior performance. Meanwhile,...
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11/28/2021
Automated Runtime-Aware Scheduling for Multi-Tenant DNN Inference on GPU
With the fast development of deep neural networks (DNNs), many real-worl...
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11/28/2021
A Survey of Large-Scale Deep Learning Serving System Optimization: Challenges and Opportunities
Deep Learning (DL) models have achieved superior performance in many app...
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10/21/2021
Supporting Massive DLRM Inference Through Software Defined Memory
Deep Learning Recommendation Models (DLRM) are widespread, account for a...
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11/22/2020
Third ArchEdge Workshop: Exploring the Design Space of Efficient Deep Neural Networks
This paper gives an overview of our ongoing work on the design space exp...
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11/21/2020
Efficient Neural Network Implementation with Quadratic Neuron
Previous works proved that the combination of the linear neuron network ...
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11/08/2020
Towards Latency-aware DNN Optimization with GPU Runtime Analysis and Tail Effect Elimination
Despite the superb performance of State-Of-The-Art (SOTA) DNNs, the incr...
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08/14/2020
AntiDote: Attention-based Dynamic Optimization for Neural Network Runtime Efficiency
Convolutional Neural Networks (CNNs) achieved great cognitive performanc...
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11/17/2019
Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning
Current state-of-the-art object detectors can have significant performan...
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10/17/2019
LanCe: A Comprehensive and Lightweight CNN Defense Methodology against Physical Adversarial Attacks on Embedded Multimedia Applications
Recently, adversarial attacks can be applied to the physical world, caus...
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10/07/2019
Task-Adaptive Incremental Learning for Intelligent Edge Devices
Convolutional Neural Networks (CNNs) are used for a wide range of image-...
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08/27/2019
Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation
The state-of-art DNN structures involve intensive computation and high m...
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05/31/2019
ADMM for Efficient Deep Learning with Global Convergence
Alternating Direction Method of Multipliers (ADMM) has been used success...
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05/21/2019
DoPa: A Fast and Comprehensive CNN Defense Methodology against Physical Adversarial Attacks
Recently, Convolutional Neural Networks (CNNs) demonstrate a considerabl...
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05/10/2019
Interpreting and Evaluating Neural Network Robustness
Recently, adversarial deception becomes one of the most considerable thr...
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10/29/2018
Demystifying Neural Network Filter Pruning
Based on filter magnitude ranking (e.g. L1 norm), conventional filter pr...
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10/28/2018
Distilling Critical Paths in Convolutional Neural Networks
Neural network compression and acceleration are widely demanded currentl...
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10/17/2018
Progressive Weight Pruning of Deep Neural Networks using ADMM
Deep neural networks (DNNs) although achieving human-level performance i...
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10/12/2018
Interpretable Convolutional Filter Pruning
The sophisticated structure of Convolutional Neural Network (CNN) allows...
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09/29/2018
Interpreting Adversarial Robustness: A View from Decision Surface in Input Space
One popular hypothesis of neural network generalization is that the flat...
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09/04/2018
HASP: A High-Performance Adaptive Mobile Security Enhancement Against Malicious Speech Recognition
Nowadays, machine learning based Automatic Speech Recognition (ASR) tech...
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05/23/2018
Towards Robust Training of Neural Networks by Regularizing Adversarial Gradients
In recent years, neural networks have demonstrated outstanding effective...
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02/15/2018
