b'Han Yu'

research

∙ 09/06/2023

Image Aesthetics Assessment via Learnable Queries

Image aesthetics assessment (IAA) aims to estimate the aesthetics of ima...

0 Zhiwei Xiong, et al. ∙

research

∙ 09/01/2023

Efficient RLHF: Reducing the Memory Usage of PPO

Reinforcement Learning with Human Feedback (RLHF) has revolutionized lan...

0 Michael Santacroce, et al. ∙

research

∙ 08/29/2023

FedLogic: Interpretable Federated Multi-Domain Chain-of-Thought Prompt Selection for Large Language Models

Leveraging “chain-of-thought (CoT)” reasoning to elicit rapid and precis...

0 Pengwei Xing, et al. ∙

research

∙ 08/24/2023

LR-XFL: Logical Reasoning-based Explainable Federated Learning

Federated learning (FL) is an emerging approach for training machine lea...

0 Yanci Zhang, et al. ∙

research

∙ 08/14/2023

Aggregating Intrinsic Information to Enhance BCI Performance through Federated Learning

Insufficient data is a long-standing challenge for Brain-Computer Interf...

0 Rui Liu, et al. ∙

research

∙ 08/07/2023

The Prospect of Enhancing Large-Scale Heterogeneous Federated Learning with Transformers

Federated learning (FL) addresses data privacy concerns by enabling coll...

0 Yulan Gao, et al. ∙

research

∙ 07/25/2023

Elastic Entangled Pair and Qubit Resource Management in Quantum Cloud Computing

Quantum cloud computing (QCC) offers a promising approach to efficiently...

0 Rakpong Kaewpuang, et al. ∙

research

∙ 07/20/2023

Fairness-Aware Client Selection for Federated Learning

Federated learning (FL) has enabled multiple data owners (a.k.a. FL clie...

0 Yuxin Shi, et al. ∙

research

∙ 07/20/2023

Flatness-Aware Minimization for Domain Generalization

Domain generalization (DG) seeks to learn robust models that generalize ...

0 Xingxuan Zhang, et al. ∙

research

∙ 07/01/2023

Hierarchical Federated Learning Incentivization for Gas Usage Estimation

Accurately estimating gas usage is essential for the efficient functioni...

0 Has Sun, et al. ∙

research

∙ 06/26/2023

Cost-Effective Task Offloading Scheduling for Hybrid Mobile Edge-Quantum Computing

In this paper, we aim to address the challenge of hybrid mobile edge-qua...

0 Ziqiang Ye, et al. ∙

research

∙ 06/16/2023

Towards Quantum Federated Learning

Quantum Federated Learning (QFL) is an emerging interdisciplinary field ...

0 Chao Ren, et al. ∙

research

∙ 05/25/2023

Meta Adaptive Task Sampling for Few-Domain Generalization

To ensure the out-of-distribution (OOD) generalization performance, trad...

0 Zheyan Shen, et al. ∙

research

∙ 05/24/2023

Rethinking the Evaluation Protocol of Domain Generalization

Domain generalization aims to solve the challenge of Out-of-Distribution...

0 Han Yu, et al. ∙

research

∙ 05/11/2023

Multi-Tier Client Selection for Mobile Federated Learning Networks

Federated learning (FL), which addresses data privacy issues by training...

0 Yulan Gao, et al. ∙

research

∙ 05/11/2023

Utility-Maximizing Bidding Strategy for Data Consumers in Auction-based Federated Learning

Auction-based Federated Learning (AFL) has attracted extensive research ...

0 Xiaoli Tang, et al. ∙

research

∙ 04/19/2023

DADFNet: Dual Attention and Dual Frequency-Guided Dehazing Network for Video-Empowered Intelligent Transportation

Visual surveillance technology is an indispensable functional component ...

0 Yu Guo, et al. ∙

research

∙ 04/10/2023

Entangled Pair Resource Allocation under Uncertain Fidelity Requirements

In quantum networks, effective entanglement routing facilitates remote e...

0 Rakpong Kaewpuang, et al. ∙

research

∙ 03/16/2023

Towards the Understanding of Receptivity and Affect in EMAs using Physiological based Machine Learning Method: Analysis of Receptivity and Affect

As mobile health (mHealth) studies become increasingly productive due to...

0 Zachary D King, et al. ∙

research

∙ 03/03/2023

Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization

Recently, flat minima are proven to be effective for improving generaliz...

0 Xingxuan Zhang, et al. ∙

research

∙ 02/27/2023

Towards Interpretable Federated Learning

Federated learning (FL) enables multiple data owners to build machine le...

0 Anran Li, et al. ∙

research

∙ 02/22/2023

Efficient Training of Large-scale Industrial Fault Diagnostic Models through Federated Opportunistic Block Dropout

Artificial intelligence (AI)-empowered industrial fault diagnostics is i...

0 Yuanyuan Chen, et al. ∙

research

∙ 02/03/2023

Clustered Embedding Learning for Recommender Systems

In recent years, recommender systems have advanced rapidly, where embedd...

0 Yizhou Chen, et al. ∙

research

∙ 01/23/2023

Optimising Event-Driven Spiking Neural Network with Regularisation and Cutoff

Spiking neural networks (SNNs), a variant of artificial neural networks ...

0 Dengyu Wu, et al. ∙

research

∙ 01/06/2023

Evolutionary Carrier Selection for Shared Truck Delivery Services

With multiple carriers in a logistics market, customers can choose the b...

0 Rakpong Kaewpuang, et al. ∙

research

∙ 12/28/2022

Towards AI-Empowered Crowdsourcing

Crowdsourcing, in which human intelligence and productivity is dynamical...

0 Shipeng Wang, et al. ∙

research

∙ 12/02/2022

Stable Learning via Sparse Variable Independence

The problem of covariate-shift generalization has attracted intensive re...

0 Han Yu, et al. ∙

research

∙ 11/21/2022

PiRL: Participant-Invariant Representation Learning for Healthcare

Due to individual heterogeneity, performance gaps are observed between g...

0 Zhaoyang Cao, et al. ∙

research

∙ 11/07/2022

FIXED: Frustratingly Easy Domain Generalization with Mixup

Domain generalization (DG) aims to learn a generalizable model from mult...

0 Wang Lu, et al. ∙

research

∙ 11/06/2022

On the Domain Adaptation and Generalization of Pretrained Language Models: A Survey

Recent advances in NLP are brought by a range of large-scale pretrained ...

0 Xu Guo, et al. ∙

research

∙ 11/01/2022

Multi-Resource Allocation for On-Device Distributed Federated Learning Systems

This work poses a distributed multi-resource allocation scheme for minim...

0 Yulan Gao, et al. ∙

research

∙ 10/22/2022

Stochastic Qubit Resource Allocation for Quantum Cloud Computing

Quantum cloud computing is a promising paradigm for efficiently provisio...

0 Rakpong Kaewpuang, et al. ∙

research

∙ 10/18/2022

Measure-Theoretic Probability of Complex Co-occurrence and E-Integral

Complex high-dimensional co-occurrence data are increasingly popular fro...

0 Jian-Yong Wang, et al. ∙

research

∙ 10/13/2022

LEAVES: Learning Views for Time-Series Data in Contrastive Learning

Contrastive learning, a self-supervised learning method that can learn r...

0 Han Yu, et al. ∙

research

∙ 10/13/2022

Empirical Evaluation of Data Augmentations for Biobehavioral Time Series Data with Deep Learning

Deep learning has performed remarkably well on many tasks recently. Howe...

0 Huiyuan Yang, et al. ∙

research

∙ 10/06/2022

Improving the Sample Efficiency of Prompt Tuning with Domain Adaptation

Prompt tuning, or the conditioning of a frozen pretrained language model...

0 Xu Guo, et al. ∙

research

∙ 09/24/2022

Cooperative Resource Management in Quantum Key Distribution (QKD) Networks for Semantic Communication

Increasing privacy and security concerns in intelligence-native 6G netwo...

0 Rakpong Kaewpuang, et al. ∙

research

∙ 09/21/2022

Towards Trustworthy AI-Empowered Real-Time Bidding for Online Advertisement Auctioning

Artificial intelligence-empowred Real-Time Bidding (AIRTB) is regarded a...

0 Xiaoli Tang, et al. ∙

research

∙ 09/16/2022

DQC^2O: Distributed Quantum Computing for Collaborative Optimization in Future Networks

With the advantages of high-speed parallel processing, quantum computers...

0 Napat Ngoenriang, et al. ∙

research

∙ 09/16/2022

Optimal Stochastic Resource Allocation for Distributed Quantum Computing

With the advent of interconnected quantum computers, i.e., distributed q...

0 Napat Ngoenriang, et al. ∙

research

∙ 08/24/2022

Adaptive Resource Allocation in Quantum Key Distribution (QKD) for Federated Learning

Increasing privacy and security concerns in intelligence-native 6G netwo...

0 Rakpong Kaewpuang, et al. ∙

research

∙ 08/17/2022

Resource Allocation in Quantum Key Distribution (QKD) for Space-Air-Ground Integrated Networks

Space-air-ground integrated networks (SAGIN) are one of the most promisi...

0 Rakpong Kaewpuang, et al. ∙

research

∙ 08/10/2022

FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through Federated Learning

Large-scale neural networks possess considerable expressive power. They ...

0 Yuanyuan Chen, et al. ∙

research

∙ 08/07/2022

Bias Reducing Multitask Learning on Mental Health Prediction

There has been an increase in research in developing machine learning mo...

17 Khadija Zanna, et al. ∙

research

∙ 04/17/2022

NICO++: Towards Better Benchmarking for Domain Generalization

Despite the remarkable performance that modern deep neural networks have...

18 Xingxuan Zhang, et al. ∙

research

∙ 02/22/2022

Semi-Supervised Learning and Data Augmentation in Wearable-based Momentary Stress Detection in the Wild

Physiological and behavioral data collected from wearable or mobile sens...

0 Han Yu, et al. ∙

research

∙ 02/16/2022

More to Less (M2L): Enhanced Health Recognition in the Wild with Reduced Modality of Wearable Sensors

Accurately recognizing health-related conditions from wearable data is c...

0 Huiyuan Yang, et al. ∙

research

∙ 02/15/2022

Towards Verifiable Federated Learning

Federated learning (FL) is an emerging paradigm of collaborative machine...

0 Yanci Zhang, et al. ∙

research

∙ 02/15/2022

Federated Graph Neural Networks: Overview, Techniques and Challenges

With its powerful capability to deal with graph data widely found in pra...

0 Rui Liu, et al. ∙

research

∙ 01/31/2022

Heterogeneous Federated Learning via Grouped Sequential-to-Parallel Training

Federated learning (FL) is a rapidly growing privacy-preserving collabor...

0 Shenglai Zeng, et al. ∙

Han Yu

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