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Modern strategies for time series regression
This paper discusses several modern approaches to regression analysis in...
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Transform-Invariant Convolutional Neural Networks for Image Classification and Search
Convolutional neural networks (CNNs) have achieved state-of-the-art resu...
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Interpretable Time-series Classification on Few-shot Samples
Recent few-shot learning works focus on training a model with prior meta...
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Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation Approach
Weakly supervised semantic segmentation is a challenging task as it only...
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Potential Passenger Flow Prediction: A Novel Study for Urban Transportation Development
Recently, practical applications for passenger flow prediction have brou...
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Heterogeneous Multi-task Metric Learning across Multiple Domains
Distance metric learning (DML) plays a crucial role in diverse machine l...
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Large Margin Multi-modal Multi-task Feature Extraction for Image Classification
The features used in many image analysis-based applications are frequent...
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Shakeout: A New Approach to Regularized Deep Neural Network Training
Recent years have witnessed the success of deep neural networks in deali...
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Correlated Logistic Model With Elastic Net Regularization for Multilabel Image Classification
In this paper, we present correlated logistic (CorrLog) model for multil...
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Searching for A Robust Neural Architecture in Four GPU Hours
Conventional neural architecture search (NAS) approaches are based on re...
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Bridging the Theoretical Bound and Deep Algorithms for Open Set Domain Adaptation
In the unsupervised open set domain adaptation (UOSDA), the target domai...
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Continuous Dropout
Dropout has been proven to be an effective algorithm for training robust...
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More Than Privacy: Applying Differential Privacy in Key Areas of Artificial Intelligence
Artificial Intelligence (AI) has attracted a great deal of attention in ...
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See More Than Once -- Kernel-Sharing Atrous Convolution for Semantic Segmentation
The state-of-the-art semantic segmentation solutions usually leverage di...
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Cubic LSTMs for Video Prediction
Predicting future frames in videos has become a promising direction of r...
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PDANet: Pyramid Density-aware Attention Net for Accurate Crowd Counting
Crowd counting, i.e., estimating the number of people in a crowded area,...
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On the Neural Tangent Kernel of Deep Networks with Orthogonal Initialization
In recent years, a critical initialization scheme with orthogonal initia...
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Binarized Graph Neural Network
Recently, there have been some breakthroughs in graph analysis by applyi...
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Unsupervised Scene Adaptation with Memory Regularization in vivo
We consider the unsupervised scene adaptation problem of learning from b...
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RDP-GAN: A Rényi-Differential Privacy based Generative Adversarial Network
Generative adversarial network (GAN) has attracted increasing attention ...
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Decoupled and Memory-Reinforced Networks: Towards Effective Feature Learning for One-Step Person Search
The goal of person search is to localize and match query persons from sc...
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Instance-Invariant Adaptive Object Detection via Progressive Disentanglement
Most state-of-the-art methods of object detection suffer from poor gener...
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Gaussian Process Latent Variable Model Factorization for Context-aware Recommender Systems
Context-aware recommender systems (CARS) have gained increasing attentio...
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Supervised Discriminative Sparse PCA with Adaptive Neighbors for Dimensionality Reduction
Dimensionality reduction is an important operation in information visual...
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Multi-View Intact Space Learning
It is practical to assume that an individual view is unlikely to be suff...
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Learning to Transfer Learn
We propose a novel framework, learning to transfer learn (L2TL), to impr...
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Rectifying Pseudo Label Learning via Uncertainty Estimation for Domain Adaptive Semantic Segmentation
This paper focuses on the unsupervised domain adaptation of transferring...
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Memory Aggregation Networks for Efficient Interactive Video Object Segmentation
Interactive video object segmentation (iVOS) aims at efficiently harvest...
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Multi-Center Federated Learning
Federated learning has received great attention for its capability to tr...
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Path Integral Based Convolution and Pooling for Graph Neural Networks
Graph neural networks (GNNs) extends the functionality of traditional ne...
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Motor-Imagery-Based Brain Computer Interface using Signal Derivation and Aggregation Functions
Brain Computer Interface technologies are popular methods of communicati...
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Understanding Human Context in 3D Scenes by Learning Spatial Affordances with Virtual Skeleton Models
Robots are often required to operate in environments where humans are no...
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TOAN: Target-Oriented Alignment Network for Fine-Grained Image Categorization with Few Labeled Samples
The challenges of high intra-class variance yet low inter-class fluctuat...
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Pumpout: A Meta Approach for Robustly Training Deep Neural Networks with Noisy Labels
It is challenging to train deep neural networks robustly on the industri...
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BIT: Biologically Inspired Tracker
Visual tracking is challenging due to image variations caused by various...
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Face Hallucination with Finishing Touches
Obtaining a high-quality frontal face image from a low-resolution (LR) n...
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Robust Tensor Decomposition for Image Representation Based on Generalized Correntropy
Traditional tensor decomposition methods, e.g., two dimensional principa...
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How does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches?
Unsupervised domain adaptation (UDA) aims to train a target classifier w...
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Structured Discriminative Tensor Dictionary Learning for Unsupervised Domain Adaptation
Unsupervised Domain Adaptation (UDA) addresses the problem of performanc...
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A Distributed Approach towards Discriminative Distance Metric Learning
Distance metric learning is successful in discovering intrinsic relation...
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Domain-adversarial Network Alignment
Network alignment is a critical task to a wide variety of fields. Many e...
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SBSGAN: Suppression of Inter-Domain Background Shift for Person Re-Identification
Cross-domain person re-identification (re-ID) is challenging due to the ...
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Knowledge-guided Deep Reinforcement Learning for Interactive Recommendation
Interactive recommendation aims to learn from dynamic interactions betwe...
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Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting
Modeling complex spatial and temporal correlations in the correlated tim...
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Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot Learning on Category Graph
A variety of machine learning applications expect to achieve rapid learn...
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Very Long Natural Scenery Image Prediction by Outpainting
Comparing to image inpainting, image outpainting receives less attention...
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Meta3D: Single-View 3D Object Reconstruction from Shape Priors in Memory
3D shape reconstruction from a single-view RGB image is an ill-posed pro...
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GID-Net: Detecting Human-Object Interaction with Global and Instance Dependency
Since detecting and recognizing individual human or object are not adequ...
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Probabilistic CCA with Implicit Distributions
Canonical Correlation Analysis (CCA) is a classic technique for multi-vi...
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Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection
Facial landmark detection aims to localize the anatomically defined poin...
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