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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...
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08/07/2023
Intelligence-Endogenous Management Platform for Computing and Network Convergence
Massive emerging applications are driving demand for the ubiquitous depl...
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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...
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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...
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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 ...
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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...
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06/01/2023
Dissecting Arbitrary-scale Super-resolution Capability from Pre-trained Diffusion Generative Models
Diffusion-based Generative Models (DGMs) have achieved unparalleled perf...
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05/19/2023
SFP: Spurious Feature-targeted Pruning for Out-of-Distribution Generalization
Model substructure learning aims to find an invariant network substructu...
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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...
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05/02/2023
MDENet: Multi-modal Dual-embedding Networks for Malware Open-set Recognition
Malware open-set recognition (MOSR) aims at jointly classifying malware ...
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05/02/2023
DRPT: Disentangled and Recurrent Prompt Tuning for Compositional Zero-Shot Learning
Compositional Zero-shot Learning (CZSL) aims to recognize novel concepts...
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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...
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05/01/2023
Towards Unbiased Training in Federated Open-world Semi-supervised Learning
Federated Semi-supervised Learning (FedSSL) has emerged as a new paradig...
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04/17/2023
Prophet: Conflict-Free Sharding Blockchain via Byzantine-Tolerant Deterministic Ordering
Sharding scales throughput by splitting blockchain nodes into parallel g...
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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 ...
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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...
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02/09/2023
Data Quality-aware Mixed-precision Quantization via Hybrid Reinforcement Learning
Mixed-precision quantization mostly predetermines the model bit-width se...
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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...
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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...
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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...
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11/19/2022
Decomposed Soft Prompt Guided Fusion Enhancing for Compositional Zero-Shot Learning
Compositional Zero-Shot Learning (CZSL) aims to recognize novel concepts...
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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...
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11/15/2022
CaDM: Codec-aware Diffusion Modeling for Neural-enhanced Video Streaming
Recent years have witnessed the dramatic growth of Internet video traffi...
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11/14/2022
Feature Correlation-guided Knowledge Transfer for Federated Self-supervised Learning
To eliminate the requirement of fully-labeled data for supervised model ...
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11/14/2022
PMR: Prototypical Modal Rebalance for Multimodal Learning
Multimodal learning (MML) aims to jointly exploit the common priors of d...
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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...
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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 ...
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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...
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07/16/2022
A Survey on Collaborative DNN Inference for Edge Intelligence
With the vigorous development of artificial intelligence (AI), the intel...
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06/17/2022
PICO: Pipeline Inference Framework for Versatile CNNs on Diverse Mobile Devices
Recent researches in artificial intelligence have proposed versatile con...
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06/13/2022
Accelerating Federated Learning via Sampling Anchor Clients with Large Batches
Using large batches in recent federated learning studies has improved co...
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05/09/2022
Layer-wised Model Aggregation for Personalized Federated Learning
Personalized Federated Learning (pFL) not only can capture the common pr...
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05/04/2022
Rethinking Classifier and Adversarial Attack
Various defense models have been proposed to resist adversarial attack a...
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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 ...
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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...
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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...
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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 ...
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02/05/2022
A Coalition Formation Game Approach for Personalized Federated Learning
Facing the challenge of statistical diversity in client local data distr...
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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...
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11/04/2021
Parameterized Knowledge Transfer for Personalized Federated Learning
In recent years, personalized federated learning (pFL) has attracted inc...
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10/22/2021
Federated Unlearning via Class-Discriminative Pruning
We explore the problem of selectively forgetting categories from trained...
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06/24/2021
Personalized Federated Learning with Clustered Generalization
We study the recent emerging personalized federated learning (PFL) that ...
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04/15/2021
Serverless Federated Learning for UAV Networks: Architecture, Challenges, and Opportunities
Unmanned aerial vehicles (UAVs), or say drones, are envisioned to suppor...
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04/01/2021
Online Multiple Object Tracking with Cross-Task Synergy
Modern online multiple object tracking (MOT) methods usually focus on tw...
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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...
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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...
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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...
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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...
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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...
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04/30/2020
