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09/16/2023
Rethinking Learning Rate Tuning in the Era of Large Language Models
Large Language Models (LLMs) represent the recent success of deep learni...
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09/06/2023
Fast and Resource-Efficient Object Tracking on Edge Devices: A Measurement Study
Object tracking is an important functionality of edge video analytic sys...
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05/10/2023
Securing Distributed SGD against Gradient Leakage Threats
This paper presents a holistic approach to gradient leakage resilient di...
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03/21/2023
STDLens: Model Hijacking-Resilient Federated Learning for Object Detection
Federated Learning (FL) has been gaining popularity as a collaborative l...
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01/15/2023
EENet: Learning to Early Exit for Adaptive Inference
Budgeted adaptive inference with early exits is an emerging technique to...
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10/24/2022
Selecting and Composing Learning Rate Policies for Deep Neural Networks
The choice of learning rate (LR) functions and policies has evolved from...
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10/22/2021
Learning Text-Image Joint Embedding for Efficient Cross-Modal Retrieval with Deep Feature Engineering
This paper introduces a two-phase deep feature engineering framework for...
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08/02/2021
Learning TFIDF Enhanced Joint Embedding for Recipe-Image Cross-Modal Retrieval Service
It is widely acknowledged that learning joint embeddings of recipes with...
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07/27/2021
Parallel Detection for Efficient Video Analytics at the Edge
Deep Neural Network (DNN) trained object detectors are widely deployed i...
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07/02/2021
Gradient-Leakage Resilient Federated Learning
Federated learning(FL) is an emerging distributed learning paradigm with...
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04/25/2021
RDMAbox : Optimizing RDMA for Memory Intensive Workloads
We present RDMAbox, a set of low level RDMA opti-mizations that provide ...
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10/20/2020
Promoting High Diversity Ensemble Learning with EnsembleBench
Ensemble learning is gaining renewed interests in recent years. This pap...
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08/03/2020
Efficient Orchestration of Host and Remote Shared Memory for Memory Intensive Workloads
Since very few contributions to the development of an unified memory orc...
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07/11/2020
Understanding Object Detection Through An Adversarial Lens
Deep neural networks based object detection models have revolutionized c...
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04/22/2020
A Framework for Evaluating Gradient Leakage Attacks in Federated Learning
Federated learning (FL) is an emerging distributed machine learning fram...
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04/09/2020
TOG: Targeted Adversarial Objectness Gradient Attacks on Real-time Object Detection Systems
The rapid growth of real-time huge data capturing has pushed the deep le...
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10/01/2019
Cross-Layer Strategic Ensemble Defense Against Adversarial Examples
Deep neural network (DNN) has demonstrated its success in multiple domai...
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08/29/2019
Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness
Ensemble learning is a methodology that integrates multiple DNN learners...
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08/21/2019
Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks
Deep neural networks (DNNs) have demonstrated impressive performance on ...
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08/18/2019
Demystifying Learning Rate Polices for High Accuracy Training of Deep Neural Networks
Learning Rate (LR) is an important hyper-parameter to tune for effective...
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10/29/2018
