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08/11/2023
Rethinking the Localization in Weakly Supervised Object Localization
Weakly supervised object localization (WSOL) is one of the most popular ...
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07/21/2023
MAS: Towards Resource-Efficient Federated Multiple-Task Learning
Federated learning (FL) is an emerging distributed machine learning meth...
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03/02/2023
Boosting Distributed Full-graph GNN Training with Asynchronous One-bit Communication
Training Graph Neural Networks (GNNs) on large graphs is challenging due...
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02/15/2023
FedABC: Targeting Fair Competition in Personalized Federated Learning
Federated learning aims to collaboratively train models without accessin...
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12/04/2022
Toward Efficient Language Model Pretraining and Downstream Adaptation via Self-Evolution: A Case Study on SuperGLUE
This technical report briefly describes our JDExplore d-team's Vega v2 s...
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10/19/2022
Machine Learning for a Sustainable Energy Future
Transitioning from fossil fuels to renewable energy sources is a critica...
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09/07/2022
Not All Instances Contribute Equally: Instance-adaptive Class Representation Learning for Few-Shot Visual Recognition
Few-shot visual recognition refers to recognize novel visual concepts fr...
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07/09/2022
Smart Multi-tenant Federated Learning
Federated learning (FL) is an emerging distributed machine learning meth...
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05/24/2022
Optimizing Performance of Federated Person Re-identification: Benchmarking and Analysis
The increasingly stringent data privacy regulations limit the developmen...
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05/24/2022
Deep Learning Workload Scheduling in GPU Datacenters: Taxonomy, Challenges and Vision
Deep learning (DL) shows its prosperity in a wide variety of fields. The...
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04/09/2022
Divergence-aware Federated Self-Supervised Learning
Self-supervised learning (SSL) is capable of learning remarkable represe...
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04/09/2022
Federated Unsupervised Domain Adaptation for Face Recognition
Given labeled data in a source domain, unsupervised domain adaptation ha...
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10/15/2021
Carbon Neutrality in Data Center
Data centers are carbon-intensive enterprises due to their massive energ...
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09/03/2021
Characterization and Prediction of Deep Learning Workloads in Large-Scale GPU Datacenters
Modern GPU datacenters are critical for delivering Deep Learning (DL) mo...
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08/14/2021
Joint Optimization in Edge-Cloud Continuum for Federated Unsupervised Person Re-identification
Person re-identification (ReID) aims to re-identify a person from non-ov...
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08/14/2021
Collaborative Unsupervised Visual Representation Learning from Decentralized Data
Unsupervised representation learning has achieved outstanding performanc...
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08/03/2021
Are Missing Links Predictable? An Inferential Benchmark for Knowledge Graph Completion
We present InferWiki, a Knowledge Graph Completion (KGC) dataset that im...
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07/27/2021
Exploring Sequence Feature Alignment for Domain Adaptive Detection Transformers
Detection transformers have recently shown promising object detection re...
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06/06/2021
ModelCI-e: Enabling Continual Learning in Deep Learning Serving Systems
MLOps is about taking experimental ML models to production, i.e., servin...
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05/18/2021
ModelPS: An Interactive and Collaborative Platform for Editing Pre-trained Models at Scale
AI engineering has emerged as a crucial discipline to democratize deep n...
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05/17/2021
Towards Unsupervised Domain Adaptation for Deep Face Recognition under Privacy Constraints via Federated Learning
Unsupervised domain adaptation has been widely adopted to generalize mod...
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05/17/2021
EasyFL: A Low-code Federated Learning Platform For Dummies
Academia and industry have developed several platforms to support the po...
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02/05/2021
A Serverless Cloud-Fog Platform for DNN-Based Video Analytics with Incremental Learning
DNN-based video analytics have empowered many new applications (e.g., au...
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01/11/2021
On the Practicality of Differential Privacy in Federated Learning by Tuning Iteration Times
In spite that Federated Learning (FL) is well known for its privacy prot...
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11/27/2020
Learning Relation Prototype from Unlabeled Texts for Long-tail Relation Extraction
Relation Extraction (RE) is a vital step to complete Knowledge Graph (KG...
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11/25/2020
Privacy-preserving Collaborative Learning with Automatic Transformation Search
Collaborative learning has gained great popularity due to its benefit of...
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11/04/2020
InferBench: Understanding Deep Learning Inference Serving with an Automatic Benchmarking System
Deep learning (DL) models have become core modules for many applications...
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08/26/2020
Performance Optimization for Federated Person Re-identification via Benchmark Analysis
Federated learning is a privacy-preserving machine learning technique th...
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07/09/2020
Distributed Energy Trading and Scheduling among Microgrids via Multiagent Reinforcement Learning
The development of renewable energy generation empowers microgrids to ge...
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06/09/2020
Hysia: Serving DNN-Based Video-to-Retail Applications in Cloud
Combining video streaming and online retailing (V2R) has been a growing ...
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06/09/2020
MLModelCI: An Automatic Cloud Platform for Efficient MLaaS
MLModelCI provides multimedia researchers and developers with a one-stop...
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01/20/2020
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications
Generative adversarial networks (GANs) are a hot research topic recently...
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12/21/2019
Look, Read and Feel: Benchmarking Ads Understanding with Multimodal Multitask Learning
Given the massive market of advertising and the sharply increasing onlin...
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12/12/2019
A Survey of Predictive Maintenance: Systems, Purposes and Approaches
This paper provides a comprehensive literature review on Predictive Main...
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06/09/2019
Soft-ranking Label Encoding for Robust Facial Age Estimation
Automatic facial age estimation can be used in a wide range of real-worl...
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04/23/2019
Baconian: A Unified Opensource Framework for Model-Based Reinforcement Learning
Model-Based Reinforcement Learning (MBRL) is one category of Reinforceme...
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04/08/2019
Large Margin Multi-modal Multi-task Feature Extraction for Image Classification
The features used in many image analysis-based applications are frequent...
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04/08/2019
Heterogeneous Multi-task Metric Learning across Multiple Domains
Distance metric learning (DML) plays a crucial role in diverse machine l...
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04/08/2019
Transferring Knowledge Fragments for Learning Distance Metric from A Heterogeneous Domain
The goal of transfer learning is to improve the performance of target le...
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04/08/2019
Multi-view Vector-valued Manifold Regularization for Multi-label Image Classification
In computer vision, image datasets used for classification are naturally...
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04/04/2019
Cost-Sensitive Feature Selection by Optimizing F-Measures
Feature selection is beneficial for improving the performance of general...
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02/19/2019
Optimizing Network Performance for Distributed DNN Training on GPU Clusters: ImageNet/AlexNet Training in 1.5 Minutes
It is important to scale out deep neural network (DNN) training for redu...
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01/15/2019
Energy-Efficient Thermal Comfort Control in Smart Buildings via Deep Reinforcement Learning
Heating, Ventilation, and Air Conditioning (HVAC) is extremely energy-co...
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12/25/2018
JALAD: Joint Accuracy- and Latency-Aware Deep Structure Decoupling for Edge-Cloud Execution
Recent years have witnessed a rapid growth of deep-network based service...
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11/16/2018
Content-Aware Personalised Rate Adaptation for Adaptive Streaming via Deep Video Analysis
Adaptive bitrate (ABR) streaming is the de facto solution for achieving ...
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10/09/2018
Transfer Metric Learning: Algorithms, Applications and Outlooks
Distance metric learning (DML) aims to find an appropriate way to reveal...
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10/09/2018
GraphMP: I/O-Efficient Big Graph Analytics on a Single Commodity Machine
Recent studies showed that single-machine graph processing systems can b...
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05/24/2018
Intelligent Trainer for Model-Based Reinforcement Learning
Model-based deep reinforcement learning (DRL) algorithm uses the sampled...
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05/22/2018
Speeding-up Age Estimation in Intelligent Demographics System via Network Optimization
Age estimation is a difficult task which requires the automatic detectio...
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05/07/2018
