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Towards Visually Explaining Variational Autoencoders
Recent advances in Convolutional Neural Network (CNN) model interpretabi...
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Self-supervised Training of Graph Convolutional Networks
Graph Convolutional Networks (GCNs) have been successfully applied to an...
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Hybrid Federated Learning: Algorithms and Implementation
Federated learning (FL) is a recently proposed distributed machine learn...
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Chart Auto-Encoders for Manifold Structured Data
Auto-encoding and generative models have made tremendous successes in im...
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Multi-organ Segmentation over Partially Labeled Datasets with Multi-scale Feature Abstraction
This paper presents a unified training strategy that enables a novel mul...
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Image-driven discriminative and generative machine learning algorithms for establishing microstructure-processing relationships
We investigate methods of microstructure representation for the purpose ...
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Deep Encoder-decoder Adversarial Reconstruction (DEAR) Network for 3D CT from Few-view Data
X-ray computed tomography (CT) is widely used in clinical practice. The ...
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A Dynamical Systems Approach for Convergence of the Bayesian EM Algorithm
Out of the recent advances in systems and control (S&C)-based analysis o...
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Deep Efficient End-to-end Reconstruction (DEER) Network for Low-dose Few-view Breast CT from Projection Data
Breast CT provides image volumes with isotropic resolution in high contr...
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Duality of Width and Depth of Neural Networks
Here, we report that the depth and the width of a neural network are dua...
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Unsupervised Geometric Disentanglement for Surfaces via CFAN-VAE
For non-Euclidean data such as meshes of humans, a prominent task for ge...
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Adaptive Temporal Difference Learning with Linear Function Approximation
This paper revisits the celebrated temporal difference (TD) learning alg...
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Truth Discovery via Proxy Voting
Truth discovery is a general name for a broad range of statistical metho...
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Reinforcement Learning with Quantum Variational Circuits
The development of quantum computational techniques has advanced greatly...
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Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases
When the training data are maliciously tampered, the predictions of the ...
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Can Deep Learning Outperform Modern Commercial CT Image Reconstruction Methods?
Commercial iterative reconstruction techniques on modern CT scanners tar...
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Boundary-weighted Domain Adaptive Neural Network for Prostate MR Image Segmentation
Accurate segmentation of the prostate from magnetic resonance (MR) image...
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An image-driven machine learning approach to kinetic modeling of a discontinuous precipitation reaction
Micrograph quantification is an essential component of several materials...
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Multi-person Spatial Interaction in a Large Immersive Display Using Smartphones as Touchpads
In this paper, we present a multi-user interaction interface for a large...
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Sensorless Freehand 3D Ultrasound Reconstruction via Deep Contextual Learning
Transrectal ultrasound (US) is the most commonly used imaging modality t...
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Universal Approximation with Quadratic Deep Networks
Recently, deep learning has been playing a central role in machine learn...
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Rational Neural Networks for Approximating Jump Discontinuities of Graph Convolution Operator
For node level graph encoding, a recent important state-of-art method is...
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Nonisometric Surface Registration via Conformal Laplace-Beltrami Basis Pursuit
Surface registration is one of the most fundamental problems in geometry...
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Knowledge-based Analysis for Mortality Prediction from CT Images
Recent studies have highlighted the high correlation between cardiovascu...
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A Grounded Unsupervised Universal Part-of-Speech Tagger for Low-Resource Languages
Unsupervised part of speech (POS) tagging is often framed as a clusterin...
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GATCluster: Self-Supervised Gaussian-Attention Network for Image Clustering
Deep clustering has achieved state-of-the-art results via joint represen...
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Dual Network Architecture for Few-view CT --Trained on ImageNet Data and Transferred for Medical Imaging
X-ray computed tomography (CT) reconstructs cross-sectional images from ...
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Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients
The present paper develops a novel aggregated gradient approach for dist...
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A Dependency-Based Neural Network for Relation Classification
Previous research on relation classification has verified the effectiven...
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Influence of Personal Preferences on Link Dynamics in Social Networks
We study a unique network dataset including periodic surveys and electro...
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Application of a Shallow Neural Network to Short-Term Stock Trading
Machine learning is increasingly prevalent in stock market trading. Thou...
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Towards Cognitive-and-Immersive Systems: Experiments in a Shared (or common) Blockworld Framework
As computational power has continued to increase, and sensors have becom...
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A Generative Restricted Boltzmann Machine Based Method for High-Dimensional Motion Data Modeling
Many computer vision applications involve modeling complex spatio-tempor...
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From Data to City Indicators: A Knowledge Graph for Supporting Automatic Generation of Dashboards
In the context of Smart Cities, indicator definitions have been used to ...
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Deep Learning for Passive Synthetic Aperture Radar
We introduce a deep learning (DL) framework for inverse problems in imag...
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Scalable Kernel K-Means Clustering with Nystrom Approximation: Relative-Error Bounds
Kernel k-means clustering can correctly identify and extract a far more ...
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Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Loss
In this paper, we introduce a new CT image denoising method based on the...
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KATE: K-Competitive Autoencoder for Text
Autoencoders have been successful in learning meaningful representations...
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Truthful Mechanisms for Matching and Clustering in an Ordinal World
We study truthful mechanisms for matching and related problems in a part...
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Census Signal Temporal Logic Inference for Multi-Agent Group Behavior Analysis
In this paper, we define a novel census signal temporal logic (CensusSTL...
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Rank Persistence: Assessing the Temporal Performance of Real-World Person Re-Identification
Designing useful person re-identification systems for real-world applica...
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Accelerated Primal-Dual Proximal Block Coordinate Updating Methods for Constrained Convex Optimization
Block Coordinate Update (BCU) methods enjoy low per-update computational...
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Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging
We address the statistical and optimization impacts of using classical s...
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CrossNets : A New Approach to Complex Learning
We propose a novel neural network structure called CrossNets, which cons...
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Building a Fine-Grained Entity Typing System Overnight for a New X (X = Language, Domain, Genre)
Recent research has shown great progress on fine-grained entity typing. ...
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Randomized Social Choice Functions Under Metric Preferences
We determine the quality of randomized social choice mechanisms in a set...
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Hybrid Jacobian and Gauss-Seidel proximal block coordinate update methods for linearly constrained convex programming
Recent years have witnessed the rapid development of block coordinate up...
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Manifold Based Low-rank Regularization for Image Restoration and Semi-supervised Learning
Low-rank structures play important role in recent advances of many probl...
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Allocating Indivisible Items in Categorized Domains
We formulate a general class of allocation problems called categorized d...
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Optimal Sparse Linear Auto-Encoders and Sparse PCA
Principal components analysis (PCA) is the optimal linear auto-encoder o...
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