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09/19/2023
Enhanced C-V2X Mode 4 to Optimize Age of Information and Reliability for IoV
Internet of vehicles (IoV) has emerged as a key technology to realize re...
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09/19/2023
Delay-sensitive Task Offloading in Vehicular Fog Computing-Assisted Platoons
Vehicles in platoons need to process many tasks to support various real-...
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09/04/2023
Parameter and Computation Efficient Transfer Learning for Vision-Language Pre-trained Models
With ever increasing parameters and computation, vision-language pre-tra...
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08/31/2023
FedDD: Toward Communication-efficient Federated Learning with Differential Parameter Dropout
Federated Learning (FL) requires frequent exchange of model parameters, ...
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08/19/2023
User-centric AIGC products: Explainable Artificial Intelligence and AIGC products
Generative AI tools, such as ChatGPT and Midjourney, are transforming ar...
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07/24/2023
General-Purpose Multi-Modal OOD Detection Framework
Out-of-distribution (OOD) detection identifies test samples that differ ...
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06/27/2023
Approximated Prompt Tuning for Vision-Language Pre-trained Models
Prompt tuning is a parameter-efficient way to deploy large-scale pre-tra...
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06/01/2023
Adapting Pre-trained Language Models to Vision-Language Tasks via Dynamic Visual Prompting
Pre-trained language models (PLMs) have played an increasing role in mul...
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04/06/2023
Deep Reinforcement Learning Based Vehicle Selection for Asynchronous Federated Learning Enabled Vehicular Edge Computing
In the traditional vehicular network, computing tasks generated by the v...
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03/11/2023
Deep Reinforcement Learning Based Power Allocation for Minimizing AoI and Energy Consumption in MIMO-NOMA IoT Systems
Multi-input multi-out and non-orthogonal multiple access (MIMO-NOMA) int...
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01/29/2023
Unsupervised Domain Adaptation on Person Re-Identification via Dual-level Asymmetric Mutual Learning
Unsupervised domain adaptation person re-identification (Re-ID) aims to ...
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01/16/2023
HiFlash: Communication-Efficient Hierarchical Federated Learning with Adaptive Staleness Control and Heterogeneity-aware Client-Edge Association
Federated learning (FL) is a promising paradigm that enables collaborati...
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12/02/2022
Olive Branch Learning: A Topology-Aware Federated Learning Framework for Space-Air-Ground Integrated Network
The space-air-ground integrated network (SAGIN), one of the key technolo...
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12/01/2022
Symphony in the Latent Space: Provably Integrating High-dimensional Techniques with Non-linear Machine Learning Models
This paper revisits building machine learning algorithms that involve in...
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08/21/2022
CycleTrans: Learning Neutral yet Discriminative Features for Visible-Infrared Person Re-Identification
Visible-infrared person re-identification (VI-ReID) is a task of matchin...
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08/03/2022
Asynchronous Federated Learning for Edge-assisted Vehicular Networks
Vehicular networks enable vehicles support real-time vehicular applicati...
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08/03/2022
High stable and accurate vehicle selection scheme based on federated edge learning in vehicular networks
Federated edge learning (FEEL) technology for vehicular networks is cons...
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08/02/2022
Towards V2I Age-aware Fairness Access: A DQN Based Intelligent Vehicular Node Training and Test Method
Vehicles on the road exchange data with base station (BS) frequently thr...
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08/02/2022
Asynchronous Federated Learning Based Mobility-aware Caching in Vehicular Edge Computing
Vehicular edge computing (VEC) is a promising technology to support real...
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08/02/2022
Mobility-Aware Cooperative Caching in Vehicular Edge Computing Based on Asynchronous Federated and Deep Reinforcement Learning
The vehicular edge computing (VEC) can cache contents in different RSUs ...
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03/27/2022
HELoC: Hierarchical Contrastive Learning of Source Code Representation
Abstract syntax trees (ASTs) play a crucial role in source code represen...
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08/09/2021
Velocity-adaptive Access Scheme for MEC-assisted Platooning Networks: Access Fairness Via Data Freshness
Platooning strategy is an important part of autonomous driving technolog...
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07/30/2021
Decentralized Power Allocation for MIMO-NOMA Vehicular Edge Computing Based on Deep Reinforcement Learning
Vehicular edge computing (VEC) is envisioned as a promising approach to ...
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01/21/2021
Deep Reinforcement Learning with Spatio-temporal Traffic Forecasting for Data-Driven Base Station Sleep Control
To meet the ever increasing mobile traffic demand in 5G era, base statio...
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12/14/2020
FedHome: Cloud-Edge based Personalized Federated Learning for In-Home Health Monitoring
In-home health monitoring has attracted great attention for the ageing p...
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12/02/2020
Delay Sensitive Task Offloading in the 802.11p Based Vehicular Fog Computing Systems
Vehicular fog computing (VFC) is envisioned as a promising solution to p...
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11/05/2020
Time-dependent Performance Analysis of the 802.11p-based Platooning Communications Under Disturbance
Platooning is a critical technology to realize autonomous driving. Each ...
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10/28/2020
Rosella: A Self-Driving Distributed Scheduler for Heterogeneous Clusters
Large-scale interactive web services and advanced AI applications make s...
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08/05/2020
BATS: A Spectral Biclustering Approach to Single Document Topic Modeling and Segmentation
Existing topic modeling and text segmentation methodologies generally re...
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07/27/2020
Learning Task-oriented Disentangled Representations for Unsupervised Domain Adaptation
Unsupervised domain adaptation (UDA) aims to address the domain-shift pr...
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03/09/2020
DeepCP: Deep Learning Driven Cascade Prediction Based Autonomous Content Placement in Closed Social Network
Online social networks (OSNs) are emerging as the most popular mainstrea...
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02/26/2020
HFEL: Joint Edge Association and Resource Allocation for Cost-Efficient Hierarchical Federated Edge Learning
Federated Learning (FL) has been proposed as an appealing approach to ha...
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02/25/2020
Personalized Federated Learning for Intelligent IoT Applications: A Cloud-Edge based Framework
Internet of Things (IoT) have widely penetrated in different aspects of ...
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09/07/2019
A Deep Learning Framework for Pricing Financial Instruments
We propose an integrated deep learning architecture for the stock moveme...
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07/01/2019
Bandit Learning for Diversified Interactive Recommendation
Interactive recommender systems that enable the interactions between use...
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05/28/2019
Video-based Person Re-identification with Two-stream Convolutional Network and Co-attentive Snippet Embedding
Recently, the applications of person re-identification in visual surveil...
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05/28/2019
Adaptive Reduced Rank Regression
Low rank regression has proven to be useful in a wide range of forecasti...
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05/16/2019
Recent Advances in Diversified Recommendation
With the rapid development of recommender systems, accuracy is no longer...
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03/19/2019
Diversity-Promoting Deep Reinforcement Learning for Interactive Recommendation
Interactive recommendation that models the explicit interactions between...
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10/24/2018
Nonconvex and Nonsmooth Sparse Optimization via Adaptively Iterative Reweighted Methods
We present a general formulation of nonconvex and nonsmooth sparse optim...
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07/19/2018
A Swarming Approach to Optimize the One-hop Delay in Smart Driving Inter-platoon Communications
In this paper, we propose a swarming approach and optimize the one-hop d...
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07/09/2018
Towards Non-Parametric Learning to Rank
This paper studies a stylized, yet natural, learning-to-rank problem and...
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11/29/2017
Parameter-free ℓ_p-Box Decoding of LDPC Codes
The Alternating Direction Method of Multipliers (ADMM) decoding of Low D...
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06/01/2016
Improving Deep Neural Network with Multiple Parametric Exponential Linear Units
Activation function is crucial to the recent successes of deep neural ne...
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02/17/2015