b'Song Guo'

research

∙ 09/02/2023

GBE-MLZSL: A Group Bi-Enhancement Framework for Multi-Label Zero-Shot Learning

This paper investigates a challenging problem of zero-shot learning in t...

0 Ziming Liu, et al. ∙

research

∙ 08/07/2023

Intelligence-Endogenous Management Platform for Computing and Network Convergence

Massive emerging applications are driving demand for the ubiquitous depl...

0 Zicong Hong, et al. ∙

research

∙ 07/11/2023

Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators

Federated learning has become a popular method to learn from decentraliz...

0 Sikai Bai, et al. ∙

research

∙ 07/04/2023

SRCD: Semantic Reasoning with Compound Domains for Single-Domain Generalized Object Detection

This paper provides a novel framework for single-domain generalized obje...

0 Zhijie Rao, et al. ∙

research

∙ 06/21/2023

Adaptive DNN Surgery for Selfish Inference Acceleration with On-demand Edge Resource

Deep Neural Networks (DNNs) have significantly improved the accuracy of ...

0 Xiang Yang, et al. ∙

research

∙ 06/02/2023

On Knowledge Editing in Federated Learning: Perspectives, Challenges, and Future Directions

As Federated Learning (FL) has gained increasing attention, it has becom...

0 Leijie Wu, et al. ∙

research

∙ 06/01/2023

Dissecting Arbitrary-scale Super-resolution Capability from Pre-trained Diffusion Generative Models

Diffusion-based Generative Models (DGMs) have achieved unparalleled perf...

0 Ruibin Li, et al. ∙

research

∙ 05/19/2023

SFP: Spurious Feature-targeted Pruning for Out-of-Distribution Generalization

Model substructure learning aims to find an invariant network substructu...

1 ingchun Wang, et al. ∙

research

∙ 05/02/2023

Efficient Federated Learning with Enhanced Privacy via Lottery Ticket Pruning in Edge Computing

Federated learning (FL) is a collaborative learning paradigm for decentr...

22 Yifan Shi, et al. ∙

research

∙ 05/02/2023

MDENet: Multi-modal Dual-embedding Networks for Malware Open-set Recognition

Malware open-set recognition (MOSR) aims at jointly classifying malware ...

0 Jingcai Guo, et al. ∙

research

∙ 05/02/2023

DRPT: Disentangled and Recurrent Prompt Tuning for Compositional Zero-Shot Learning

Compositional Zero-shot Learning (CZSL) aims to recognize novel concepts...

0 Xiaocheng Lu, et al. ∙

research

∙ 05/02/2023

CNS-Net: Conservative Novelty Synthesizing Network for Malware Recognition in an Open-set Scenario

We study the challenging task of malware recognition on both known and n...

0 Jingcai Guo, et al. ∙

research

∙ 05/01/2023

Towards Unbiased Training in Federated Open-world Semi-supervised Learning

Federated Semi-supervised Learning (FedSSL) has emerged as a new paradig...

0 Jie Zhang, et al. ∙

research

∙ 04/17/2023

Prophet: Conflict-Free Sharding Blockchain via Byzantine-Tolerant Deterministic Ordering

Sharding scales throughput by splitting blockchain nodes into parallel g...

0 Zicong Hong, et al. ∙

research

∙ 03/20/2023

Offline-Online Class-incremental Continual Learning via Dual-prototype Self-augment and Refinement

This paper investigates a new, practical, but challenging problem named ...

0 Fushuo Huo, et al. ∙

research

∙ 03/14/2023

DualMix: Unleashing the Potential of Data Augmentation for Online Class-Incremental Learning

Online Class-Incremental (OCI) learning has sparked new approaches to ex...

0 Yunfeng Fan, et al. ∙

research

∙ 02/09/2023

Data Quality-aware Mixed-precision Quantization via Hybrid Reinforcement Learning

Mixed-precision quantization mostly predetermines the model bit-width se...

0 Yingchun Wang, et al. ∙

research

∙ 12/19/2022

Exploring Optimal Substructure for Out-of-distribution Generalization via Feature-targeted Model Pruning

Recent studies show that even highly biased dense networks contain an un...

0 Yingchun Wang, et al. ∙

research

∙ 12/07/2022

Efficient Stein Variational Inference for Reliable Distribution-lossless Network Pruning

Network pruning is a promising way to generate light but accurate models...

5 Yingchun Wang, et al. ∙

research

∙ 11/21/2022

Exploiting Personalized Invariance for Better Out-of-distribution Generalization in Federated Learning

Recently, data heterogeneity among the training datasets on the local cl...

0 Xueyang Tang, et al. ∙

research

∙ 11/19/2022

Decomposed Soft Prompt Guided Fusion Enhancing for Compositional Zero-Shot Learning

Compositional Zero-Shot Learning (CZSL) aims to recognize novel concepts...

0 Xiaocheng Lu, et al. ∙

research

∙ 11/15/2022

FedTune: A Deep Dive into Efficient Federated Fine-Tuning with Pre-trained Transformers

Federated Learning (FL) is an emerging paradigm that enables distributed...

0 Jinyu Chen, et al. ∙

research

∙ 11/15/2022

CaDM: Codec-aware Diffusion Modeling for Neural-enhanced Video Streaming

Recent years have witnessed the dramatic growth of Internet video traffi...

18 Qihua Zhou, et al. ∙

research

∙ 11/14/2022

Feature Correlation-guided Knowledge Transfer for Federated Self-supervised Learning

To eliminate the requirement of fully-labeled data for supervised model ...

17 YI LIU, et al. ∙

research

∙ 11/14/2022

PMR: Prototypical Modal Rebalance for Multimodal Learning

Multimodal learning (MML) aims to jointly exploit the common priors of d...

0 Yunfeng Fan, et al. ∙

research

∙ 11/13/2022

Demystify Self-Attention in Vision Transformers from a Semantic Perspective: Analysis and Application

Self-attention mechanisms, especially multi-head self-attention (MSA), h...

0 Leijie Wu, et al. ∙

research

∙ 08/24/2022

PromptFL: Let Federated Participants Cooperatively Learn Prompts Instead of Models – Federated Learning in Age of Foundation Model

Quick global aggregation of effective distributed parameters is crucial ...

0 Tao Guo, et al. ∙

research

∙ 08/21/2022

Fed-FSNet: Mitigating Non-I.I.D. Federated Learning via Fuzzy Synthesizing Network

Federated learning (FL) has emerged as a promising privacy-preserving di...

12 Jingcai Guo, et al. ∙

research

∙ 07/16/2022

A Survey on Collaborative DNN Inference for Edge Intelligence

With the vigorous development of artificial intelligence (AI), the intel...

0 Weiqing Ren, et al. ∙

research

∙ 06/17/2022

PICO: Pipeline Inference Framework for Versatile CNNs on Diverse Mobile Devices

Recent researches in artificial intelligence have proposed versatile con...

0 Xiang Yang, et al. ∙

research

∙ 06/13/2022

Accelerating Federated Learning via Sampling Anchor Clients with Large Batches

Using large batches in recent federated learning studies has improved co...

0 Feijie Wu, et al. ∙

research

∙ 05/09/2022

Layer-wised Model Aggregation for Personalized Federated Learning

Personalized Federated Learning (pFL) not only can capture the common pr...

0 Xiaosong Ma, et al. ∙

research

∙ 05/04/2022

Rethinking Classifier and Adversarial Attack

Various defense models have been proposed to resist adversarial attack a...

0 Youhuan Yang, et al. ∙

research

∙ 05/04/2022

CE-based white-box adversarial attacks will not work using super-fitting

Deep neural networks are widely used in various fields because of their ...

0 Youhuan Yang, et al. ∙

research

∙ 04/14/2022

Sign Bit is Enough: A Learning Synchronization Framework for Multi-hop All-reduce with Ultimate Compression

Traditional one-bit compressed stochastic gradient descent can not be di...

8 Feijie Wu, et al. ∙

research

∙ 03/07/2022

Towards Unbiased Multi-label Zero-Shot Learning with Pyramid and Semantic Attention

Multi-label zero-shot learning extends conventional single-label zero-sh...

0 Ziming Liu, et al. ∙

research

∙ 02/27/2022

Vertical Machine Unlearning: Selectively Removing Sensitive Information From Latent Feature Space

Recently, the enactment of privacy regulations has promoted the rise of ...

0 Tao Guo, et al. ∙

research

∙ 02/05/2022

A Coalition Formation Game Approach for Personalized Federated Learning

Facing the challenge of statistical diversity in client local data distr...

2 Leijie Wu, et al. ∙

research

∙ 12/17/2021

From Deterioration to Acceleration: A Calibration Approach to Rehabilitating Step Asynchronism in Federated Optimization

In the setting of federated optimization, where a global model is aggreg...

9 Feijie Wu, et al. ∙

research

∙ 11/04/2021

Parameterized Knowledge Transfer for Personalized Federated Learning

In recent years, personalized federated learning (pFL) has attracted inc...

9 Jie Zhang, et al. ∙

research

∙ 10/22/2021

Federated Unlearning via Class-Discriminative Pruning

We explore the problem of selectively forgetting categories from trained...

0 Junxiao Wang, et al. ∙

research

∙ 06/24/2021

Personalized Federated Learning with Clustered Generalization

We study the recent emerging personalized federated learning (PFL) that ...

1 Xueyang Tang, et al. ∙

research

∙ 04/15/2021

Serverless Federated Learning for UAV Networks: Architecture, Challenges, and Opportunities

Unmanned aerial vehicles (UAVs), or say drones, are envisioned to suppor...

0 Yuben Qu, et al. ∙

research

∙ 04/01/2021

Online Multiple Object Tracking with Cross-Task Synergy

Modern online multiple object tracking (MOT) methods usually focus on tw...

0 Song Guo, et al. ∙

research

∙ 02/01/2021

Optimizing Video Caching at the Edge: A Hybrid Multi-Point Process Approach

It is always a challenging problem to deliver a huge volume of videos ov...

0 Xianzhi Zhang, et al. ∙

research

∙ 01/31/2021

Gain without Pain: Offsetting DP-injected Nosies Stealthily in Cross-device Federated Learning

Federated Learning (FL) is an emerging paradigm through which decentrali...

0 Wenzhuo Yang, et al. ∙

research

∙ 09/25/2020

DPN: Detail-Preserving Network with High Resolution Representation for Efficient Segmentation of Retinal Vessels

Retinal vessels are important biomarkers for many ophthalmological and c...

0 Song Guo, et al. ∙

research

∙ 08/10/2020

Scalable and Communication-efficient Decentralized Federated Edge Learning with Multi-blockchain Framework

The emerging Federated Edge Learning (FEL) technique has drawn considera...

0 Jiawen Kang, et al. ∙

research

∙ 07/07/2020

A Survey of State-of-the-Art on Blockchains: Theories, Modelings, and Tools

To draw a roadmap of current research activities of the blockchain commu...

0 Huawei Huang, et al. ∙

research

∙ 04/30/2020

A Novel Perspective to Zero-shot Learning: Towards an Alignment of Manifold Structures via Semantic Feature Expansion

Zero-shot learning aims at recognizing unseen classes (no training examp...

6 Jingcai Guo, et al. ∙

Song Guo

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