Search Results for author: Qiong Wu

Found 43 papers, 13 papers with code

Cooperative Edge Caching Based on Elastic Federated and Multi-Agent Deep Reinforcement Learning in Next-Generation Network

1 code implementation18 Jan 2024 Qiong Wu, Wenhua Wang, Pingyi Fan, Qiang Fan, Huiling Zhu, Khaled B. Letaief

Finally, we propose a multi-agent deep reinforcement learning (MADRL) based algorithm to decide where the predicted popular contents are collaboratively cached among SBSs.

Federated Learning reinforcement-learning

Efficient Toxic Content Detection by Bootstrapping and Distilling Large Language Models

no code implementations13 Dec 2023 Jiang Zhang, Qiong Wu, Yiming Xu, Cheng Cao, Zheng Du, Konstantinos Psounis

Furthermore, student LMs fine-tuned with rationales extracted via DToT outperform baselines on all datasets with up to 16. 9\% accuracy improvement, while being more than 60x smaller than conventional LLMs.

In-Context Learning

URLLC-Awared Resource Allocation for Heterogeneous Vehicular Edge Computing

no code implementations30 Nov 2023 Qiong Wu, Wenhua Wang, Pingyi Fan, Qiang Fan, Jiangzhou Wang, Khaled B. Letaief

Vehicular edge computing (VEC) is a promising technology to support real-time vehicular applications, where vehicles offload intensive computation tasks to the nearby VEC server for processing.


FedDD: Toward Communication-efficient Federated Learning with Differential Parameter Dropout

no code implementations31 Aug 2023 Zhiying Feng, Xu Chen, Qiong Wu, Wen Wu, Xiaoxi Zhang, Qianyi Huang

FedDD consists of two key modules: dropout rate allocation and uploaded parameter selection, which will optimize the model parameter uploading ratios tailored to different clients' heterogeneous conditions and also select the proper set of important model parameters for uploading subject to clients' dropout rate constraints.

Federated Learning

General-Purpose Multi-Modal OOD Detection Framework

no code implementations24 Jul 2023 Viet Duong, Qiong Wu, Zhengyi Zhou, Eric Zavesky, Jiahe Chen, Xiangzhou Liu, Wen-Ling Hsu, Huajie Shao

To reach this goal, we propose a general-purpose weakly-supervised OOD detection framework, called WOOD, that combines a binary classifier and a contrastive learning component to reap the benefits of both.

Contrastive Learning Out of Distribution (OOD) Detection

Approximated Prompt Tuning for Vision-Language Pre-trained Models

no code implementations27 Jun 2023 Qiong Wu, Shubin Huang, Yiyi Zhou, Pingyang Dai, Annan Shu, Guannan Jiang, Rongrong Ji

Prompt tuning is a parameter-efficient way to deploy large-scale pre-trained models to downstream tasks by adding task-specific tokens.

Image Classification Text-to-Image Generation +1

Adapting Pre-trained Language Models to Vision-Language Tasks via Dynamic Visual Prompting

1 code implementation1 Jun 2023 Shubin Huang, Qiong Wu, Yiyi Zhou, WeiJie Chen, Rongsheng Zhang, Xiaoshuai Sun, Rongrong Ji

In addition, we also experiment DVP with the recently popular adapter approach to keep the most parameters of PLMs intact when adapting to VL tasks, helping PLMs achieve a quick shift between single- and multi-modal tasks.

Transfer Learning Visual Prompting

Deep Reinforcement Learning Based Vehicle Selection for Asynchronous Federated Learning Enabled Vehicular Edge Computing

no code implementations6 Apr 2023 Qiong Wu, Siyuan Wang, Pingyi Fan, Qiang Fan

Furthermore, as vehicles have different local training time due to various sizes of local data and their different computing capabilities, asynchronous federated learning (AFL) is employed to facilitate the RSU to update the global model immediately after receiving a local model to reduce the aggregation delay.

Edge-computing Federated Learning

Deep Reinforcement Learning Based Power Allocation for Minimizing AoI and Energy Consumption in MIMO-NOMA IoT Systems

no code implementations11 Mar 2023 Hongbiao Zhu, Qiong Wu, Qiang Fan, Pingyi Fan, Jiangzhou Wang, Zhengquan Li

It is critical to determine the optimal policy including sample collection requirements and power allocation to minimize the AoI and energy consumption of MIMO-NOMA IoT system, where the transmission rate is not a constant in the SIC process and the noise is stochastic in the MIMO-NOMA channel.

HiFlash: Communication-Efficient Hierarchical Federated Learning with Adaptive Staleness Control and Heterogeneity-aware Client-Edge Association

no code implementations16 Jan 2023 Qiong Wu, Xu Chen, Tao Ouyang, Zhi Zhou, Xiaoxi Zhang, Shusen Yang, Junshan Zhang

Federated learning (FL) is a promising paradigm that enables collaboratively learning a shared model across massive clients while keeping the training data locally.

Edge-computing Federated Learning

Olive Branch Learning: A Topology-Aware Federated Learning Framework for Space-Air-Ground Integrated Network

no code implementations2 Dec 2022 Qingze Fang, Zhiwei Zhai, Shuai Yu, Qiong Wu, Xiaowen Gong, Xu Chen

The space-air-ground integrated network (SAGIN), one of the key technologies for next-generation mobile communication systems, can facilitate data transmission for users all over the world, especially in some remote areas where vast amounts of informative data are collected by Internet of remote things (IoRT) devices to support various data-driven artificial intelligence (AI) services.

Federated Learning

Symphony in the Latent Space: Provably Integrating High-dimensional Techniques with Non-linear Machine Learning Models

no code implementations1 Dec 2022 Qiong Wu, Jian Li, Zhenming Liu, Yanhua Li, Mihai Cucuringu

This paper revisits building machine learning algorithms that involve interactions between entities, such as those between financial assets in an actively managed portfolio, or interactions between users in a social network.

Ensemble Learning Time Series Analysis

CycleTrans: Learning Neutral yet Discriminative Features for Visible-Infrared Person Re-Identification

no code implementations21 Aug 2022 Qiong Wu, Jiaer Xia, Pingyang Dai, Yiyi Zhou, Yongjian Wu, Rongrong Ji

Visible-infrared person re-identification (VI-ReID) is a task of matching the same individuals across the visible and infrared modalities.

Person Re-Identification

Higher-order accurate two-sample network inference and network hashing

1 code implementation16 Aug 2022 Meijia Shao, Dong Xia, Yuan Zhang, Qiong Wu, Shuo Chen

Two-sample hypothesis testing for network comparison presents many significant challenges, including: leveraging repeated network observations and known node registration, but without requiring them to operate; relaxing strong structural assumptions; achieving finite-sample higher-order accuracy; handling different network sizes and sparsity levels; fast computation and memory parsimony; controlling false discovery rate (FDR) in multiple testing; and theoretical understandings, particularly regarding finite-sample accuracy and minimax optimality.

Vocal Bursts Valence Prediction

Asynchronous Federated Learning for Edge-assisted Vehicular Networks

1 code implementation3 Aug 2022 Siyuan Wang, Qiong Wu, Qiang Fan, Pingyi Fan, Jiangzhou Wang

For the traditional federated learning (FL), vehicles train the data locally to obtain a local model and then upload the local model to the RSU to update the global model, thus the data privacy can be protected through sharing model parameters instead of data.

Federated Learning

Mobility-Aware Cooperative Caching in Vehicular Edge Computing Based on Asynchronous Federated and Deep Reinforcement Learning

1 code implementation2 Aug 2022 Qiong Wu, Yu Zhao, Qiang Fan, Pingyi Fan, Jiangzhou Wang, Cui Zhang

In addition, we consider the mobility of vehicles and propose a deep reinforcement learning algorithm to obtain the optimal cooperative caching location for the predicted popular contents in order to optimize the content transmission delay.

Edge-computing Federated Learning +2

Time-Dependent Performance Modeling for Platooning Communications at Intersection

no code implementations2 Aug 2022 Qiong Wu, Yu Zhao, Qiang Fan

In this paper, we construct the time-dependent model to evaluate the platooning communication performance at the intersection based on the initial movement characteristics.

Autonomous Driving

A Deep Reinforcement Learning Approach for Online Parcel Assignment

no code implementations8 Sep 2021 Hao Zeng, Qiong Wu, Kunpeng Han, Junying He, Haoyuan Hu

In this paper, we investigate the online parcel assignment (OPA) problem, in which each stochastically generated parcel needs to be assigned to a candidate route for delivery to minimize the total cost subject to certain business constraints.

Decision Making reinforcement-learning +1

Discover Cross-Modality Nuances for Visible-Infrared Person Re-Identification

1 code implementation CVPR 2021 Qiong Wu, Pingyang Dai, Jie Chen, Chia-Wen Lin, Yongjian Wu, Feiyue Huang, Bineng Zhong, Rongrong Ji

In this paper, we propose a joint Modality and Pattern Alignment Network (MPANet) to discover cross-modality nuances in different patterns for visible-infrared person Re-ID, which introduces a modality alleviation module and a pattern alignment module to jointly extract discriminative features.

Person Re-Identification

Deep Reinforcement Learning with Spatio-temporal Traffic Forecasting for Data-Driven Base Station Sleep Control

no code implementations21 Jan 2021 Qiong Wu, Xu Chen, Zhi Zhou, Liang Chen, Junshan Zhang

To meet the ever increasing mobile traffic demand in 5G era, base stations (BSs) have been densely deployed in radio access networks (RANs) to increase the network coverage and capacity.

Double Quarter Wave Crab Cavity Wire Stretching Measurement at BNL

no code implementations18 Jan 2021 Qiong Wu, Tianmu Xin, Binping Xiao

The wire stretching measurement was completed on the prototype Double Quarter Wave (DQW) crab cavity for operation practice and calibration of the measurement system.

Accelerator Physics

FedHome: Cloud-Edge based Personalized Federated Learning for In-Home Health Monitoring

1 code implementation14 Dec 2020 Qiong Wu, Xu Chen, Zhi Zhou, Junshan Zhang

In this paper, we propose FedHome, a novel cloud-edge based federated learning framework for in-home health monitoring, which learns a shared global model in the cloud from multiple homes at the network edges and achieves data privacy protection by keeping user data locally.

Human Activity Recognition Personalized Federated Learning

Delay Sensitive Task Offloading in the 802.11p Based Vehicular Fog Computing Systems

1 code implementation2 Dec 2020 Qiong Wu, Hanxu Liu, Ruhai Wang, Pingyi Fan, Qiang Fan, Zhengquan Li

Furthermore, the long-term reward of the system (i. e., jointly considers the transmission delay, computing delay, available resources, and diversity of vehicles and tasks) becomes a significantly important issue for providers.

Networking and Internet Architecture

Time-dependent Performance Analysis of the 802.11p-based Platooning Communications Under Disturbance

1 code implementation5 Nov 2020 Qiong Wu, Hongmei Ge, Pingyi Fan, Jiangzhou Wang, Qiang Fan, Zhengquan Li

However, one vehicle in platoons inevitably suffers from a disturbance resulting from the leader vehicle acceleration/deceleration, wind gust and uncertainties in a platoon control system, i. e., aerodynamics drag and rolling resistance moment etc.

Networking and Internet Architecture

Rosella: A Self-Driving Distributed Scheduler for Heterogeneous Clusters

no code implementations28 Oct 2020 Qiong Wu, Zhenming Liu

We evaluate Rosella with a variety of workloads on a 32-node AWS cluster.


BATS: A Spectral Biclustering Approach to Single Document Topic Modeling and Segmentation

no code implementations5 Aug 2020 Qiong Wu, Adam Hare, Sirui Wang, Yuwei Tu, Zhenming Liu, Christopher G. Brinton, Yanhua Li

In this work, we reexamine the inter-related problems of "topic identification" and "text segmentation" for sparse document learning, when there is a single new text of interest.

Segmentation Text Segmentation +1

DeepCP: Deep Learning Driven Cascade Prediction Based Autonomous Content Placement in Closed Social Network

no code implementations9 Mar 2020 Qiong Wu, Muhong Wu, Xu Chen, Zhi Zhou, Kaiwen He, Liang Chen

Accordingly, we further propose a novel autonomous content placement mechanism CP-GAN which adopts the generative adversarial network (GAN) for agile placement decision making to reduce the content access latency and enhance users' QoE.

Decision Making Generative Adversarial Network

HFEL: Joint Edge Association and Resource Allocation for Cost-Efficient Hierarchical Federated Edge Learning

no code implementations26 Feb 2020 Siqi Luo, Xu Chen, Qiong Wu, Zhi Zhou, Shuai Yu

We further formulate a joint computation and communication resource allocation and edge association problem for device users under HFEL framework to achieve global cost minimization.

Distributed, Parallel, and Cluster Computing

Personalized Federated Learning for Intelligent IoT Applications: A Cloud-Edge based Framework

no code implementations25 Feb 2020 Qiong Wu, Kaiwen He, Xu Chen

Internet of Things (IoT) have widely penetrated in different aspects of modern life and many intelligent IoT services and applications are emerging.

Edge-computing Human Activity Recognition +1

PD-GAN: Adversarial Learning for Personalized Diversity-Promoting Recommendation

1 code implementation IJCAI 2019 Qiong Wu, Yong liu, Chunyan Miao, Binqiang Zhao, Yin Zhao, Lu Guan

This paper proposes Personalized Diversity-promoting GAN (PD-GAN), a novel recommendation model to generate diverse, yet relevant recommendations.

Recommendation Systems

Bandit Learning for Diversified Interactive Recommendation

no code implementations1 Jul 2019 Yong Liu, Yingtai Xiao, Qiong Wu, Chunyan Miao, Juyong Zhang

Interactive recommender systems that enable the interactions between users and the recommender system have attracted increasing research attentions.

Bayesian Inference Recommendation Systems +1

Adaptive Reduced Rank Regression

1 code implementation NeurIPS 2020 Qiong Wu, Felix Ming Fai Wong, Zhenming Liu, Yanhua Li, Varun Kanade

We study the low rank regression problem $\my = M\mx + \epsilon$, where $\mx$ and $\my$ are $d_1$ and $d_2$ dimensional vectors respectively.


Video-based Person Re-identification with Two-stream Convolutional Network and Co-attentive Snippet Embedding

no code implementations28 May 2019 Peixian Chen, Pingyang Dai, Qiong Wu, Yuyu Huang

Recently, the applications of person re-identification in visual surveillance and human-computer interaction are sharply increasing, which signifies the critical role of such a problem.

Optical Flow Estimation Video-Based Person Re-Identification

Recent Advances in Diversified Recommendation

no code implementations16 May 2019 Qiong Wu, Yong liu, Chunyan Miao, Yin Zhao, Lu Guan, Haihong Tang

With the rapid development of recommender systems, accuracy is no longer the only golden criterion for evaluating whether the recommendation results are satisfying or not.

Recommendation Systems

Diversity-Promoting Deep Reinforcement Learning for Interactive Recommendation

no code implementations19 Mar 2019 Yong Liu, Yinan Zhang, Qiong Wu, Chunyan Miao, Lizhen Cui, Binqiang Zhao, Yin Zhao, Lu Guan

Interactive recommendation that models the explicit interactions between users and the recommender system has attracted a lot of research attentions in recent years.

Recommendation Systems reinforcement-learning +1

A Swarming Approach to Optimize the One-hop Delay in Smart Driving Inter-platoon Communications

no code implementations19 Jul 2018 Qiong Wu, Shuzhen Nie, Pingyi Fan, Zhengquan Li, Cui Zhang

In the second step, we first set the minimum average one-hop delay found in the first step as the initial optimization goal and then adopt the swarming approach again to get the one-hop delay of each backbone vehicle balance to the minimum average one-hop delay.

Networking and Internet Architecture

Towards Non-Parametric Learning to Rank

no code implementations9 Jul 2018 Ao Liu, Qiong Wu, Zhenming Liu, Lirong Xia

Next, we fix the problem by introducing a new algorithm with features constructed from "global information" of the data matrix.

Feature Engineering Learning-To-Rank

Parameter-free $\ell_p$-Box Decoding of LDPC Codes

1 code implementation29 Nov 2017 Qiong Wu, Fan Zhang, Hao Wang, Jun Lin, Yang Liu

The Alternating Direction Method of Multipliers (ADMM) decoding of Low Density Parity Check (LDPC) codes has received many attentions due to its excellent performance at the error floor region.

Information Theory Information Theory

Improving Deep Neural Network with Multiple Parametric Exponential Linear Units

1 code implementation1 Jun 2016 Yang Li, Chunxiao Fan, Yong Li, Qiong Wu, Yue Ming

In this paper, we first propose a new activation function, Multiple Parametric Exponential Linear Units (MPELU), aiming to generalize and unify the rectified and exponential linear units.

Computational Curiosity (A Book Draft)

no code implementations17 Feb 2015 Qiong Wu

This book discusses computational curiosity, from the psychology of curiosity to the computational models of curiosity, and then showcases several interesting applications of computational curiosity.

Recommendation Systems

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