
DEAL: Difficultyaware Active Learning for Semantic Segmentation
Active learning aims to address the paucity of labeled data by finding t...
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Towards Theoretically Understanding Why SGD Generalizes Better Than ADAM in Deep Learning
It is not clear yet why ADAMalike adaptive gradient algorithms suffer f...
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DistDGL: Distributed Graph Neural Network Training for BillionScale Graphs
Graph neural networks (GNN) have shown great success in learning from gr...
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Infrared target tracking based on proximal robust principal component analysis method
Infrared target tracking plays an important role in both civil and milit...
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Interpretable Neural Computation for RealWorld Compositional Visual Question Answering
There are two main lines of research on visual question answering (VQA):...
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Towards a Mathematical Understanding of Neural NetworkBased Machine Learning: what we know and what we don't
The purpose of this article is to review the achievements made in the la...
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Complexity Measures for Neural Networks with General Activation Functions Using Pathbased Norms
A simple approach is proposed to obtain complexity controls for neural n...
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A Qualitative Study of the Dynamic Behavior of Adaptive Gradient Algorithms
The dynamic behavior of RMSprop and Adam algorithms is studied through a...
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The Slow Deterioration of the Generalization Error of the Random Feature Model
The random feature model exhibits a kind of resonance behavior when the ...
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Rethinking Image Deraining via Rain Streaks and Vapors
Single image deraining regards an input image as a fusion of a backgroun...
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Unsupervised Deep Representation Learning for RealTime Tracking
The advancement of visual tracking has continuously been brought by deep...
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Robust Tracking against Adversarial Attacks
While deep convolutional neural networks (CNNs) are vulnerable to advers...
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Semantic Equivalent Adversarial Data Augmentation for Visual Question Answering
Visual Question Answering (VQA) has achieved great success thanks to the...
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The QuenchingActivation Behavior of the Gradient Descent Dynamics for Twolayer Neural Network Models
A numerical and phenomenological study of the gradient descent (GD) algo...
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Accelerating MRI Reconstruction on TPUs
The advanced magnetic resonance (MR) image reconstructions such as the c...
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VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data
Deep generative models often perform poorly in realworld applications d...
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DGLKE: Training Knowledge Graph Embeddings at Scale
Knowledge graphs have emerged as a key abstraction for organizing inform...
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Twostage model and optimal SISNR for monaural multispeaker speech separation in noisy environment
In daily listening environments, speech is always distorted by backgroun...
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A Meanfield Analysis of Deep ResNet and Beyond: Towards Provable Optimization Via Overparameterization From Depth
Training deep neural networks with stochastic gradient descent (SGD) can...
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See More, Know More: Unsupervised Video Object Segmentation with CoAttention Siamese Networks
We introduce a novel network, called COattention Siamese Network (COSNe...
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Machine Learning from a Continuous Viewpoint
We present a continuous formulation of machine learning, as a problem in...
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On the Generalization Properties of Minimumnorm Solutions for Overparameterized Neural Network Models
We study the generalization properties of minimumnorm solutions for thr...
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Deep Image Deraining Via Intrinsic Rainy Image Priors and Multiscale Auxiliary Decoding
Different rain models and novel network structures have been proposed to...
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Global Convergence of Gradient Descent for Deep Linear Residual Networks
We analyze the global convergence of gradient descent for deep linear re...
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RealTime Correlation Tracking via Joint Model Compression and Transfer
Correlation filters (CF) have received considerable attention in visual ...
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Deep Single Image Deraining Via Estimating Transmission and Atmospheric Light in rainy Scenes
Rain removal in images/videos is still an important task in computer vis...
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Barron Spaces and the Compositional Function Spaces for Neural Network Models
One of the key issues in the analysis of machine learning models is to i...
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Analysis of the Gradient Descent Algorithm for a Deep Neural Network Model with Skipconnections
The behavior of the gradient descent (GD) algorithm is analyzed for a de...
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A Comparative Analysis of the Optimization and Generalization Property of Twolayer Neural Network and Random Feature Models Under Gradient Descent Dynamics
A fairly comprehensive analysis is presented for the gradient descent dy...
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Unsupervised Deep Tracking
We propose an unsupervised visual tracking method in this paper. Differe...
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TargetAware Deep Tracking
Existing deep trackers mainly use convolutional neural networks pretrai...
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DepthAware Video Frame Interpolation
Video frame interpolation aims to synthesize nonexistent frames inbetwe...
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A Priori Estimates of the Population Risk for Residual Networks
Optimal a priori estimates are derived for the population risk of a regu...
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A Priori Estimates of the Generalization Error for Twolayer Neural Networks
New estimates for the generalization error are established for the twol...
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Deep Attentive Tracking via Reciprocative Learning
Visual attention, derived from cognitive neuroscience, facilitates human...
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PersonJob Fit: Adapting the Right Talent for the Right Job with Joint Representation Learning
PersonJob Fit is the process of matching the right talent for the right...
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EDDI: Efficient Dynamic Discovery of HighValue Information with Partial VAE
Making decisions requires information relevant to the task at hand. Many...
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Model Reduction with Memory and the Machine Learning of Dynamical Systems
The wellknown MoriZwanzig theory tells us that model reduction leads t...
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Joint Neural Entity Disambiguation with Output Space Search
In this paper, we present a novel model for entity disambiguation that c...
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Variational Implicit Processes
This paper introduces the variational implicit processes (VIPs), a Bayes...
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VITAL: VIsual Tracking via Adversarial Learning
The trackingbydetection framework consists of two stages, i.e., drawin...
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CREST: Convolutional Residual Learning for Visual Tracking
Discriminative correlation filters (DCFs) have been shown to perform sup...
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Visual Question Answering with MemoryAugmented Networks
This paper exploits a memoryaugmented neural network to predict accurat...
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Robust Visual Tracking via Hierarchical Convolutional Features
Visual tracking is challenging as target objects often undergo significa...
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Adaptive Correlation Filters with LongTerm and ShortTerm Memory for Object Tracking
Object tracking is challenging as target objects often undergo drastic a...
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Person ReIdentification via Recurrent Feature Aggregation
We address the person reidentification problem by effectively exploitin...
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Learning a NoReference Quality Metric for SingleImage SuperResolution
Numerous singleimage superresolution algorithms have been proposed in ...
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Deep Extreme Feature Extraction: New MVA Method for Searching Particles in High Energy Physics
In this paper, we present Deep Extreme Feature Extraction (DEFE), a new ...
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Chao Ma
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