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09/15/2023
Cartoondiff: Training-free Cartoon Image Generation with Diffusion Transformer Models
Image cartoonization has attracted significant interest in the field of ...
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07/12/2023
Early Autism Diagnosis based on Path Signature and Siamese Unsupervised Feature Compressor
Autism Spectrum Disorder (ASD) has been emerging as a growing public hea...
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07/12/2023
Study on Virtual Gear Hobbing Simulation and Gear Tooth Surface Accuracy
This paper presents a digital simulation method for the hobbing process ...
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06/30/2023
Improving Federated Aggregation with Deep Unfolding Networks
The performance of Federated learning (FL) is negatively affected by dev...
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06/27/2023
Quantum Federated Learning: Analysis, Design and Implementation Challenges
Quantum Federated Learning (QFL) has gained significant attention due to...
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06/26/2023
Performance Analysis and Evaluation of Post Quantum Secure Blockchained Federated Learning
Post-quantum security is critical in the quantum era. Quantum computers,...
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06/20/2023
Decentralized Quantum Federated Learning for Metaverse: Analysis, Design and Implementation
With the emerging developments of the Metaverse, a virtual world where p...
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06/05/2023
LibAUC: A Deep Learning Library for X-Risk Optimization
This paper introduces the award-winning deep learning (DL) library calle...
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05/23/2023
Learning a Single Convolutional Layer Model for Low Light Image Enhancement
Low-light image enhancement (LLIE) aims to improve the illuminance of im...
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04/26/2023
Secure Communication Model For Quantum Federated Learning: A Post Quantum Cryptography (PQC) Framework
We design a model of Post Quantum Cryptography (PQC) Quantum Federated L...
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04/04/2023
IterativePFN: True Iterative Point Cloud Filtering
The quality of point clouds is often limited by noise introduced during ...
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03/30/2023
NN-Copula-CD: A Copula-Guided Interpretable Neural Network for Change Detection in Heterogeneous Remote Sensing Images
Change detection (CD) in heterogeneous remote sensing images is a practi...
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03/13/2023
Ins-ATP: Deep Estimation of ATP for Organoid Based on High Throughput Microscopic Images
Adenosine triphosphate (ATP) is a high-energy phosphate compound and the...
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02/26/2023
Post Quantum Secure Blockchain-based Federated Learning for Mobile Edge Computing
Mobile Edge Computing (MEC) has been a promising paradigm for communicat...
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02/18/2023
Digital Privacy Under Attack: Challenges and Enablers
Users have renewed interest in protecting their private data in the digi...
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02/01/2023
A^2Q: Aggregation-Aware Quantization for Graph Neural Networks
As graph data size increases, the vast latency and memory consumption du...
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01/16/2023
A joint model of the individual mean and within-subject variability of a longitudinal outcome with a competing risks time-to-event outcome
Motivated by recent findings that within-subject (WS) variability of lon...
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12/30/2022
Detecting Change Intervals with Isolation Distributional Kernel
Detecting abrupt changes in data distribution is one of the most signifi...
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11/25/2022
3DDesigner: Towards Photorealistic 3D Object Generation and Editing with Text-guided Diffusion Models
Text-guided diffusion models have shown superior performance in image/vi...
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10/14/2022
MCTNet: A Multi-Scale CNN-Transformer Network for Change Detection in Optical Remote Sensing Images
For the task of change detection (CD) in remote sensing images, deep con...
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08/22/2022
A Survey of Distributed Ledger Technology for IoT Verticals
The Internet of Things (IoT) and Distributed ledger technology (DLT) hav...
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08/14/2022
Contrastive Learning for Joint Normal Estimation and Point Cloud Filtering
Point cloud filtering and normal estimation are two fundamental research...
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08/09/2022
Longitudinal Prediction of Postnatal Brain Magnetic Resonance Images via a Metamorphic Generative Adversarial Network
Missing scans are inevitable in longitudinal studies due to either subje...
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08/03/2022
PalQuant: Accelerating High-precision Networks on Low-precision Accelerators
Recently low-precision deep learning accelerators (DLAs) have become pop...
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07/18/2022
Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization
Variance reduction techniques such as SPIDER/SARAH/STORM have been exten...
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06/26/2022
FAIR-BFL: Flexible and Incentive Redesign for Blockchain-based Federated Learning
Vanilla Federated learning (FL) relies on the centralized global aggrega...
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06/21/2022
SemMAE: Semantic-Guided Masking for Learning Masked Autoencoders
Recently, significant progress has been made in masked image modeling to...
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04/28/2022
An Efficient Methodology to Identify Missing Tags in Large-Scale RFID Systems
Radio frequency identification (RFID) has been widely has broad applicat...
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03/29/2022
A Multi-size Kernel based Adaptive Convolutional Neural Network for Bearing Fault Diagnosis
Bearing fault identification and analysis is an important research area ...
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03/01/2022
When AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guarantee
In this paper, we propose systematic and efficient gradient-based method...
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01/28/2022
Adversarial Examples for Good: Adversarial Examples Guided Imbalanced Learning
Adversarial examples are inputs for machine learning models that have be...
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12/24/2021
SimViT: Exploring a Simple Vision Transformer with sliding windows
Although vision Transformers have achieved excellent performance as back...
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10/30/2021
Finding citations for PubMed: A large-scale comparison between five freely available bibliographic data sources
As an important biomedical database, PubMed provides users with free acc...
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10/28/2021
Efficient Algorithms and Implementation of a Semiparametric Joint Model for Longitudinal and Competing Risks Data: With Applications to Massive Biobank Data
Semiparametric joint models of longitudinal and competing risks data are...
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10/06/2021
A Few-shot Learning Graph Multi-Trajectory Evolution Network for Forecasting Multimodal Baby Connectivity Development from a Baseline Timepoint
Charting the baby connectome evolution trajectory during the first year ...
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06/30/2021
A Flexible Joint Model for Multiple Longitudinal Biomarkers and A Time-to-Event Outcome: With Applications to Dynamic Prediction Using Highly Correlated Biomarkers
In biomedical studies it is common to collect data on multiple biomarker...
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05/19/2021
Block Convolution: Towards Memory-Efficient Inference of Large-Scale CNNs on FPGA
Deep convolutional neural networks have achieved remarkable progress in ...
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03/04/2021
Hardware Acceleration of Fully Quantized BERT for Efficient Natural Language Processing
BERT is the most recent Transformer-based model that achieves state-of-t...
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12/24/2020
Decentralized Federated Learning via Mutual Knowledge Transfer
In this paper, we investigate the problem of decentralized federated lea...
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11/27/2020
Broken Adaptive Ridge Regression for Right-Censored Survival Data
Broken adaptive ridge (BAR) is a computationally scalable surrogate to L...
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10/12/2020
The Impact of Isolation Kernel on Agglomerative Hierarchical Clustering Algorithms
Agglomerative hierarchical clustering (AHC) is one of the popular cluste...
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09/06/2020
Deep Modeling of Growth Trajectories for Longitudinal Prediction of Missing Infant Cortical Surfaces
Charting cortical growth trajectories is of paramount importance for und...
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07/27/2020
The Adaptability and Challenges of Autonomous Vehicles to Pedestrians in Urban China
China is the world's largest automotive market and is ambitious for auto...
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07/08/2020
Deep Fiducial Inference
Since the mid-2000s, there has been a resurrection of interest in modern...
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07/04/2020
Multi-Site Infant Brain Segmentation Algorithms: The iSeg-2019 Challenge
To better understand early brain growth patterns in health and disorder,...
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04/08/2020
Change Detection in Heterogeneous Optical and SAR Remote Sensing Images via Deep Homogeneous Feature Fusion
Change detection in heterogeneous remote sensing images is crucial for d...
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03/12/2020
The Medical Scribe: Corpus Development and Model Performance Analyses
There is a growing interest in creating tools to assist in clinical note...
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12/17/2019
Performance of regression models as a function of experiment noise
A challenge in developing machine learning regression models is that it ...
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11/07/2019
Scalable Algorithms for Large Competing Risks Data
This paper develops two orthogonal contributions to scalable sparse regr...
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10/31/2019