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Representing Alzheimer's Disease Progression via Deep Prototype Tree
For decades, a variety of predictive approaches have been proposed and e...
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Data-driven peakon and periodic peakon travelling wave solutions of some nonlinear dispersive equations via deep learning
In the field of mathematical physics, there exist many physically intere...
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Trace Ratio Optimization with an Application to Multi-view Learning
A trace ratio optimization problem over the Stiefel manifold is investig...
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Data-driven rogue waves and parameter discovery in the defocusing NLS equation with a potential using the PINN deep learning
The physics-informed neural networks (PINNs) can be used to deep learn t...
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Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design
Deep Neural Networks (DNNs) have achieved remarkable progress in various...
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Complex Relation Extraction: Challenges and Opportunities
Relation extraction aims to identify the target relations of entities in...
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Computer Stereo Vision for Autonomous Driving
For a long time, autonomous cars were found only in science fiction movi...
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A relaxation accelerated two-sweep modulus-based matrix splitting iteration method for solving linear complementarity problems
For a linear complementarity problem, we present a relaxaiton accelerate...
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Improving Federated Relational Data Modeling via Basis Alignment and Weight Penalty
Federated learning (FL) has attracted increasing attention in recent yea...
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Uncorrelated Semi-paired Subspace Learning
Multi-view datasets are increasingly collected in many real-world applic...
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Survey and Open Problems in Privacy Preserving Knowledge Graph: Merging, Query, Representation, Completion and Applications
Knowledge Graph (KG) has attracted more and more companies' attention fo...
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A Theoretical Perspective on Differentially Private Federated Multi-task Learning
In the era of big data, the need to expand the amount of data through da...
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Exploiting Reconfigurable Intelligent Surfaces in Edge Caching: Joint Hybrid Beamforming and Content Placement Optimization
Edge caching can effectively reduce backhaul burden at core network and ...
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ASFGNN: Automated Separated-Federated Graph Neural Network
Graph Neural Networks (GNNs) have achieved remarkable performance by tak...
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Domain Adaptation Using Class Similarity for Robust Speech Recognition
When only limited target domain data is available, domain adaptation cou...
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Multi-Accent Adaptation based on Gate Mechanism
When only a limited amount of accented speech data is available, to prom...
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Orthogonal Multi-view Analysis by Successive Approximations via Eigenvectors
We propose a unified framework for multi-view subspace learning to learn...
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Privacy-preserving Transfer Learning via Secure Maximum Mean Discrepancy
The success of machine learning algorithms often relies on a large amoun...
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A Comprehensive Analysis of Information Leakage in Deep Transfer Learning
Transfer learning is widely used for transferring knowledge from a sourc...
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Deep Historical Borrowing Framework to Prospectively and Simultaneously Synthesize Control Information in Confirmatory Clinical Trials with Multiple Endpoints
In current clinical trial development, historical information is receivi...
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Multi-view Orthonormalized Partial Least Squares: Regularizations and Deep Extensions
We establish a family of subspace-based learning method for multi-view l...
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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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Variational Asymptotic Preserving Scheme for the Vlasov-Poisson-Fokker-Planck System
We design a variational asymptotic preserving scheme for the Vlasov-Pois...
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A Proximal-Gradient Algorithm for Crystal Surface Evolution
As a counterpoint to recent numerical methods for crystal surface evolut...
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Comparing and Integrating US COVID-19 Daily Data from Multiple Sources: A County-Level Dataset with Local Characteristics
Over the past several months, the outbreak of COVID-19 has been expandin...
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Deep Tensor CCA for Multi-view Learning
We present Deep Tensor Canonical Correlation Analysis (DTCCA), a method ...
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Privacy-Preserving Graph Neural Network for Node Classification
Recently, Graph Neural Network (GNN) has achieved remarkable progresses ...
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Drosophila-Inspired 3D Moving Object Detection Based on Point Clouds
3D moving object detection is one of the most critical tasks in dynamic ...
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Spatiotemporal Dynamics, Nowcasting and Forecasting of COVID-19 in the United States
In response to the ongoing public health emergency of COVID-19, we inves...
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Practical Privacy Preserving POI Recommendation
Point-of-Interest (POI) recommendation has been extensively studied and ...
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InfDetect: a Large Scale Graph-based Fraud Detection System for E-Commerce Insurance
The insurance industry has been creating innovative products around the ...
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Adapted tree boosting for Transfer Learning
Secure online transaction is an essential task for e-commerce platforms....
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Privacy Preserving PCA for Multiparty Modeling
In this paper, we present a general multiparty model-ing paradigm with P...
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Secure Social Recommendation based on Secret Sharing
Nowadays, privacy preserving machine learning has been drawing much atte...
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Show, Recall, and Tell: Image Captioning with Recall Mechanism
Generating natural and accurate descriptions in image cap-tioning has al...
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Large-Scale Semi-Supervised Learning via Graph Structure Learning over High-Dense Points
We focus on developing a novel scalable graph-based semi-supervised lear...
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There is Limited Correlation between Coverage and Robustness for Deep Neural Networks
Deep neural networks (DNN) are increasingly applied in safety-critical s...
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Insights from BB-MAS – A Large Dataset for Typing, Gait and Swipes of the Same Person on Desktop, Tablet and Phone
Behavioral biometrics are key components in the landscape of research in...
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BB-MAS: A Very Large Dataset for Typing, Gait and Swipe of the Same Person on Desktop, Tablet and Phone
Behavioral biometrics are key components in the landscape of research in...
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Towards understanding the boundary propagation speeds in tumor growth models
At the continuous level, we consider two types of tumor growth models: t...
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Hetero-Center Loss for Cross-Modality Person Re-Identification
Cross-modality person re-identification is a challenging problem which r...
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Unsupervised Multi-stream Highlight detection for the Game "Honor of Kings"
With the increasing popularity of E-sport live, Highlight Flashback has ...
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A particle method for the homogeneous Landau equation
We propose a novel deterministic particle method to numerically approxim...
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Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics
Bayesian deep learning is recently regarded as an intrinsic way to chara...
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A Self-consistent-field Iteration for Orthogonal Canonical Correlation Analysis
We propose an efficient algorithm for solving orthogonal canonical corre...
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Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection
In this paper, we aim to understand the generalization properties of gen...
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Fisher information regularization schemes for Wasserstein gradient flows
We propose a variational scheme for computing Wasserstein gradient flows...
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Probabilistic Structure Learning for EEG/MEG Source Imaging with Hierarchical Graph Prior
Brain source imaging is an important method for noninvasively characteri...
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Disentangling Dynamics and Returns: Value Function Decomposition with Future Prediction
Value functions are crucial for model-free Reinforcement Learning (RL) t...
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Glioma Grade Predictions using Scattering Wavelet Transform-Based Radiomics
Glioma grading before the surgery is very critical for the prognosis pre...
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