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09/21/2023
MarkNerf:Watermarking for Neural Radiance Field
A watermarking algorithm is proposed in this paper to address the copyri...
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09/19/2023
Steganography for Neural Radiance Fields by Backdooring
The utilization of implicit representation for visual data (such as imag...
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09/12/2023
Hierarchical Conditional Semi-Paired Image-to-Image Translation For Multi-Task Image Defect Correction On Shopping Websites
On shopping websites, product images of low quality negatively affect cu...
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08/22/2023
SwinV2DNet: Pyramid and Self-Supervision Compounded Feature Learning for Remote Sensing Images Change Detection
Among the current mainstream change detection networks, transformer is d...
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07/25/2023
A Novel Computationally Efficient Group Signature for Anonymous and Secure V2X Communications
The use of vehicle-to-everything (V2X) communication is expected to sign...
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07/22/2023
Topology-Preserving Automatic Labeling of Coronary Arteries via Anatomy-aware Connection Classifier
Automatic labeling of coronary arteries is an essential task in the prac...
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06/19/2023
AdaSelection: Accelerating Deep Learning Training through Data Subsampling
In this paper, we introduce AdaSelection, an adaptive sub-sampling metho...
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06/07/2023
Knowing-how Knowing-that: A New Task for Machine Reading Comprehension of User Manuals
The machine reading comprehension (MRC) of user manuals has huge potenti...
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06/05/2023
Inflated 3D Convolution-Transformer for Weakly-supervised Carotid Stenosis Grading with Ultrasound Videos
Localization of the narrowest position of the vessel and corresponding v...
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03/31/2023
Unsupervised Anomaly Detection and Localization of Machine Audio: A GAN-based Approach
Automatic detection of machine anomaly remains challenging for machine l...
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03/21/2023
Learning Optical Flow and Scene Flow with Bidirectional Camera-LiDAR Fusion
In this paper, we study the problem of jointly estimating the optical fl...
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03/13/2023
The Realizations of Steganography in Encrypted Domain
With the popularization and application of privacy protection technologi...
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03/05/2023
PRECISION: Decentralized Constrained Min-Max Learning with Low Communication and Sample Complexities
Recently, min-max optimization problems have received increasing attenti...
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02/21/2023
NLPLego: Assembling Test Generation for Natural Language Processing Applications
The development of modern NLP applications often relies on various bench...
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12/13/2022
FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data
Today, recommender systems have played an increasingly important role in...
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12/13/2022
AFLGuard: Byzantine-robust Asynchronous Federated Learning
Federated learning (FL) is an emerging machine learning paradigm, in whi...
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12/05/2022
DIAMOND: Taming Sample and Communication Complexities in Decentralized Bilevel Optimization
Decentralized bilevel optimization has received increasing attention rec...
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10/03/2022
Taming Fat-Tailed ("Heavier-Tailed” with Potentially Infinite Variance) Noise in Federated Learning
A key assumption in most existing works on FL algorithms' convergence an...
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10/02/2022
SAGDA: Achieving 𝒪(ε^-2) Communication Complexity in Federated Min-Max Learning
To lower the communication complexity of federated min-max learning, a n...
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09/23/2022
Robust Domain Adaptation for Machine Reading Comprehension
Most domain adaptation methods for machine reading comprehension (MRC) u...
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08/20/2022
Reversible Data hiding in Encrypted Domain with Public Key Embedding Mechanism
Considering the prospects of public key embedding (PKE) mechanism in act...
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08/17/2022
NET-FLEET: Achieving Linear Convergence Speedup for Fully Decentralized Federated Learning with Heterogeneous Data
Federated learning (FL) has received a surge of interest in recent years...
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08/17/2022
SYNTHESIS: A Semi-Asynchronous Path-Integrated Stochastic Gradient Method for Distributed Learning in Computing Clusters
To increase the training speed of distributed learning, recent years hav...
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07/27/2022
INTERACT: Achieving Low Sample and Communication Complexities in Decentralized Bilevel Learning over Networks
In recent years, decentralized bilevel optimization problems have receiv...
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07/16/2022
On Scheduling Ring-All-Reduce Learning Jobs in Multi-Tenant GPU Clusters with Communication Contention
Powered by advances in deep learning (DL) techniques, machine learning a...
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07/12/2022
Bi-fidelity Evolutionary Multiobjective Search for Adversarially Robust Deep Neural Architectures
Deep neural networks have been found vulnerable to adversarial attacks, ...
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06/02/2022
A Dual-fusion Semantic Segmentation Framework With GAN For SAR Images
Deep learning based semantic segmentation is one of the popular methods ...
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05/19/2022
CHARLES: Channel-Quality-Adaptive Over-the-Air Federated Learning over Wireless Networks
Over-the-air federated learning (OTA-FL) has emerged as an efficient mec...
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05/12/2022
Over-the-Air Federated Learning with Joint Adaptive Computation and Power Control
This paper considers over-the-air federated learning (OTA-FL). OTA-FL ex...
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04/01/2022
An End-to-end Supervised Domain Adaptation Framework for Cross-Domain Change Detection
Existing deep learning-based change detection methods try to elaborately...
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02/02/2022
GADGET: Online Resource Optimization for Scheduling Ring-All-Reduce Learning Jobs
Fueled by advances in distributed deep learning (DDL), recent years have...
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01/14/2022
Probabilistic Mass Mapping with Neural Score Estimation
Weak lensing mass-mapping is a useful tool to access the full distributi...
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11/24/2021
SoK: Untangling File-based Encryption on Mobile Devices
File-based encryption (FBE) schemes have been developed by software vend...
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11/20/2021
CamLiFlow: Bidirectional Camera-LiDAR Fusion for Joint Optical Flow and Scene Flow Estimation
In this paper, we study the problem of jointly estimating the optical fl...
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10/11/2021
A global convergence theory for deep ReLU implicit networks via over-parameterization
Implicit deep learning has received increasing attention recently due to...
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09/17/2021
CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research
Interest in applying Artificial Intelligence (AI) techniques to compiler...
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08/23/2021
Anarchic Federated Learning
Present-day federated learning (FL) systems deployed over edge networks ...
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08/06/2021
Toward Efficient Online Scheduling for Distributed Machine Learning Systems
Recent years have witnessed a rapid growth of distributed machine learni...
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07/25/2021
Federated Learning with Fair Worker Selection: A Multi-Round Submodular Maximization Approach
In this paper, we study the problem of fair worker selection in Federate...
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07/04/2021
The Role of "Live" in Livestreaming Markets: Evidence Using Orthogonal Random Forest
The common belief about the growing medium of livestreaming is that its ...
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06/19/2021
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning
Federated Learning (FL) refers to the paradigm where multiple worker nod...
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06/14/2021
CFedAvg: Achieving Efficient Communication and Fast Convergence in Non-IID Federated Learning
Federated learning (FL) is a prevailing distributed learning paradigm, w...
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05/28/2021
A Sum-of-Ratios Multi-Dimensional-Knapsack Decomposition for DNN Resource Scheduling
In recent years, to sustain the resource-intensive computational needs f...
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05/19/2021
Incentivized Bandit Learning with Self-Reinforcing User Preferences
In this paper, we investigate a new multi-armed bandit (MAB) online lear...
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05/12/2021
Silicon Photonics in Optical Access Networks for 5G Communications
Only radio access networks can provide connectivity across multiple ante...
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05/04/2021
GT-STORM: Taming Sample, Communication, and Memory Complexities in Decentralized Non-Convex Learning
Decentralized nonconvex optimization has received increasing attention i...
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02/18/2021
Data Poisoning Attacks and Defenses to Crowdsourcing Systems
A key challenge of big data analytics is how to collect a large volume o...
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01/27/2021
Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning
Federated learning (FL) is a distributed machine learning architecture t...
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01/16/2021
Multi-objective Search of Robust Neural Architectures against Multiple Types of Adversarial Attacks
Many existing deep learning models are vulnerable to adversarial example...
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12/27/2020