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07/17/2023
Toward Scalable and Controllable AR Experimentation
To understand how well a proposed augmented reality (AR) solution works,...
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07/09/2023
Carbon-Efficient Neural Architecture Search
This work presents a novel approach to neural architecture search (NAS) ...
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06/21/2023
Opportunities of Renewable Energy Powered DNN Inference
With the proliferation of the adoption of renewable energy in powering d...
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02/22/2023
Learning Mixture Structure on Multi-Source Time Series for Probabilistic Forecasting
In many data-driven applications, collecting data from different sources...
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01/15/2023
LitAR: Visually Coherent Lighting for Mobile Augmented Reality
An accurate understanding of omnidirectional environment lighting is cru...
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01/15/2023
Multi-Camera Lighting Estimation for Photorealistic Front-Facing Mobile Augmented Reality
Lighting understanding plays an important role in virtual object composi...
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07/07/2022
Privacy-preserving Reflection Rendering for Augmented Reality
Many augmented reality (AR) applications rely on omnidirectional environ...
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04/28/2022
FuncPipe: A Pipelined Serverless Framework for Fast and Cost-efficient Training of Deep Learning Models
Training deep learning (DL) models has become a norm. With the emergence...
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10/07/2021
Multi-objective Optimization by Learning Space Partitions
In contrast to single-objective optimization (SOO), multi-objective opti...
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08/19/2021
On the Future of Cloud Engineering
Ever since the commercial offerings of the Cloud started appearing in 20...
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08/13/2021
Quantifying and Improving Performance of Distributed Deep Learning with Cloud Storage
Cloud computing provides a powerful yet low-cost environment for distrib...
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06/16/2021
Enabling Sustainable Clouds: The Case for Virtualizing the Energy System
Cloud platforms' growing energy demand and carbon emissions are raising ...
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05/30/2021
Xihe: A 3D Vision-based Lighting Estimation Framework for Mobile Augmented Reality
Omnidirectional lighting provides the foundation for achieving spatially...
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04/30/2021
Memory-Efficient Deep Learning Inference in Trusted Execution Environments
This study identifies and proposes techniques to alleviate two key bottl...
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04/16/2021
Sync-Switch: Hybrid Parameter Synchronization for Distributed Deep Learning
Stochastic Gradient Descent (SGD) has become the de facto way to train d...
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06/11/2020
Few-shot Neural Architecture Search
To improve the search efficiency for Neural Architecture Search (NAS), O...
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05/05/2020
ESG2Risk: A Deep Learning Framework from ESG News to Stock Volatility Prediction
Incorporating environmental, social, and governance (ESG) considerations...
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04/07/2020
Characterizing and Modeling Distributed Training with Transient Cloud GPU Servers
Cloud GPU servers have become the de facto way for deep learning practit...
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03/30/2020
PointAR: Efficient Lighting Estimation for Mobile Augmented Reality
We propose an efficient lighting estimation pipeline that is suitable to...
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02/16/2020
MDInference: Balancing Inference Accuracy and Latency for Mobile Applications
Deep Neural Networks (DNNs) are allowing mobile devices to incorporate a...
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02/16/2020
MDInference: Balancing Inference Accuracy andLatency for Mobile Applications
Deep Neural Networks (DNNs) are allowing mobile devices to incorporate a...
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12/05/2019
Perseus: Characterizing Performance and Cost of Multi-Tenant Serving for CNN Models
Deep learning models are increasingly used for end-user applications, su...
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09/10/2019
Characterizing the Deep Neural Networks Inference Performance of Mobile Applications
Today's mobile applications are increasingly leveraging deep neural netw...
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09/04/2019
ModiPick: SLA-aware Accuracy Optimization For Mobile Deep Inference
Mobile applications are increasingly leveraging complex deep learning mo...
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08/28/2019
Confidential Deep Learning: Executing Proprietary Models on Untrusted Devices
Performing deep learning on end-user devices provides fast offline infer...
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07/03/2019
CloudCoaster: Transient-aware Bursty Datacenter Workload Scheduling
Today's clusters often have to divide resources among a diverse set of j...
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05/28/2019
Exploring Interpretable LSTM Neural Networks over Multi-Variable Data
For recurrent neural networks trained on time series with target and exo...
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05/24/2019
Statistical embedding for directed graphs
We propose a novel statistical node embedding of directed graphs, which ...
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03/27/2019
Sensing Social Media Signals for Cryptocurrency News
The ability to track and monitor relevant and important news in real-tim...
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02/28/2019
Speeding up Deep Learning with Transient Servers
Distributed training frameworks, like TensorFlow, have been proposed as ...
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06/17/2018
Multi-variable LSTM neural network for autoregressive exogenous model
In this paper, we propose multi-variable LSTM capable of accurate foreca...
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04/14/2018
An interpretable LSTM neural network for autoregressive exogenous model
In this paper, we propose an interpretable LSTM recurrent neural network...
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02/12/2018
Predicting short-term Bitcoin price fluctuations from buy and sell orders
Bitcoin is the first decentralized digital cryptocurrency, which has sho...
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07/14/2017
Cloud-based or On-device: An Empirical Study of Mobile Deep Inference
Modern mobile applications are benefiting significantly from the advance...
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07/14/2017
