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11/08/2019
Learning Connectivity and Higher-order Interactions in Radial Distribution Grids
To perform any meaningful optimization task, distribution grid operators...
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11/03/2019
Finite-Sample Analysis of Decentralized Temporal-Difference Learning with Linear Function Approximation
Motivated by the emerging use of multi-agent reinforcement learning (MAR...
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10/25/2019
A Statistical Learning Approach to Reactive Power Control in Distribution Systems
Pronounced variability due to the growth of renewable energy sources, fl...
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10/02/2019
MAC Protocols for Wireless Mesh Networks with Multi-beam Antennas: A Survey
Multi-beam antenna technologies have provided lots of promising solution...
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10/02/2019
ChainSplitter: Towards Blockchain-based Industrial IoT Architecture for Supporting Hierarchical Storage
The fast developing Industrial Internet of Things (IIoT) technologies pr...
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09/10/2019
A Multistep Lyapunov Approach for Finite-Time Analysis of Biased Stochastic Approximation
Motivated by the widespread use of temporal-difference (TD-) and Q-learn...
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09/05/2019
Semantic Correlation Promoted Shape-Variant Context for Segmentation
Context is essential for semantic segmentation. Due to the diverse shape...
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08/31/2019
Boundary-Aware Feature Propagation for Scene Segmentation
In this work, we address the challenging issue of scene segmentation. To...
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05/12/2019
NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding
Research on depth-based human activity analysis achieved outstanding per...
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03/26/2019
Unpaired Image Captioning via Scene Graph Alignments
Deep neural networks have achieved great success on the image captioning...
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02/27/2019
Adaptive Caching via Deep Reinforcement Learning
Caching is envisioned to play a critical role in next-generation content...
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02/19/2019
2D LiDAR Map Prediction via Estimating Motion Flow with GRU
It is a significant problem to predict the 2D LiDAR map at next moment f...
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02/08/2019
Skeleton-Based Online Action Prediction Using Scale Selection Network
Action prediction is to recognize the class label of an ongoing activity...
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01/15/2019
Feature Boosting Network For 3D Pose Estimation
In this paper, a feature boosting network is proposed for estimating 3D ...
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11/29/2018
Graph Multiview Canonical Correlation Analysis
Multiview canonical correlation analysis (MCCA) seeks latent low-dimensi...
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11/15/2018
Real-time Power System State Estimation and Forecasting via Deep Neural Networks
Contemporary smart power grids are being challenged by rapid voltage flu...
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11/13/2018
Modeling Local Dependence in Natural Language with Multi-channel Recurrent Neural Networks
Recurrent Neural Networks (RNNs) have been widely used in processing nat...
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10/06/2018
Context-Aware Deep Spatio-Temporal Network for Hand Pose Estimation from Depth Images
As a fundamental and challenging problem in computer vision, hand pose e...
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08/14/2018
Learning ReLU Networks on Linearly Separable Data: Algorithm, Optimality, and Generalization
Neural networks with ReLU activations have achieved great empirical succ...
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05/15/2018
Nonlinear Dimensionality Reduction for Discriminative Analytics of Multiple Datasets
Principal component analysis (PCA) is widely used for feature extraction...
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04/18/2018
Effect of Spatial and Temporal Traffic Statistics on the Performance of Wireless Networks
The traffic in wireless networks has become diverse and fluctuating both...
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03/27/2018
Canonical Correlation Analysis of Datasets with a Common Source Graph
Canonical correlation analysis (CCA) is a powerful technique for discove...
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03/27/2018
Dual Attention Matching Network for Context-Aware Feature Sequence based Person Re-Identification
Typical person re-identification (ReID) methods usually describe each pe...
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03/14/2018
Unpaired Image Captioning by Language Pivoting
Image captioning is a multimodal task involving computer vision and natu...
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03/13/2018
Multimodal Recurrent Neural Networks with Information Transfer Layers for Indoor Scene Labeling
This paper proposes a new method called Multimodal RNNs for RGB-D scene ...
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01/29/2018
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks
It is desirable to train convolutional networks (CNNs) to run more effic...
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01/06/2018
Learning Hierarchical Features for Visual Object Tracking with Recursive Neural Networks
Recently, deep learning has achieved very promising results in visual ob...
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01/02/2018
Revisiting Email Spoofing Attacks
The email system is the central battleground against phishing and social...
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12/06/2017
Compressive Phase Retrieval via Reweighted Amplitude Flow
The problem of reconstructing a sparse signal vector from magnitude-only...
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11/17/2017
Towards the Adoption of Anti-spoofing Protocols for Email Systems
Email spoofing is a critical step of phishing, where the attacker impers...
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11/17/2017
Look, Imagine and Match: Improving Textual-Visual Cross-Modal Retrieval with Generative Models
Textual-visual cross-modal retrieval has been a hot research topic in bo...
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10/25/2017
DPCA: Dimensionality Reduction for Discriminative Analytics of Multiple Large-Scale Datasets
Principal component analysis (PCA) has well-documented merits for data e...
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09/11/2017
Stack-Captioning: Coarse-to-Fine Learning for Image Captioning
The existing image captioning approaches typically train a one-stage sen...
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08/02/2017
A Novel Neural Network Model Specified for Representing Logical Relations
With computers to handle more and more complicated things in variable en...
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07/18/2017
Skeleton Based Human Action Recognition with Global Context-Aware Attention LSTM Networks
Human action recognition in 3D skeleton sequences has attracted a lot of...
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07/18/2017
Beyond Forward Shortcuts: Fully Convolutional Master-Slave Networks (MSNets) with Backward Skip Connections for Semantic Segmentation
Recent deep CNNs contain forward shortcut connections; i.e. skip connect...
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06/26/2017
Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates
Skeleton-based human action recognition has attracted a lot of research ...
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05/29/2017
Solving Almost all Systems of Random Quadratic Equations
This paper deals with finding an n-dimensional solution x to a system of...
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12/21/2016
An Empirical Study of Language CNN for Image Captioning
Language Models based on recurrent neural networks have dominated recent...
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11/28/2016
Improving Fully Convolution Network for Semantic Segmentation
Fully Convolution Networks (FCN) have achieved great success in dense pr...
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11/17/2016
DelugeNets: Deep Networks with Efficient and Flexible Cross-layer Information Inflows
Deluge Networks (DelugeNets) are deep neural networks which efficiently ...
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10/29/2016
Solving Large-scale Systems of Random Quadratic Equations via Stochastic Truncated Amplitude Flow
A novel approach termed stochastic truncated amplitude flow (STAF) is de...
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09/27/2016
Decision Making Based on Cohort Scores for Speaker Verification
Decision making is an important component in a speaker verification syst...
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08/03/2016
Learning Common and Specific Features for RGB-D Semantic Segmentation with Deconvolutional Networks
In this paper, we tackle the problem of RGB-D semantic segmentation of i...
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07/28/2016
A Siamese Long Short-Term Memory Architecture for Human Re-Identification
Matching pedestrians across multiple camera views known as human re-iden...
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07/28/2016
Gated Siamese Convolutional Neural Network Architecture for Human Re-Identification
Matching pedestrians across multiple camera views, known as human re-ide...
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07/24/2016
Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition
3D action recognition - analysis of human actions based on 3D skeleton d...
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05/26/2016
Solving Systems of Random Quadratic Equations via Truncated Amplitude Flow
This paper presents a new algorithm, termed truncated amplitude flow (TA...
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04/20/2016
Scene Parsing with Integration of Parametric and Non-parametric Models
We adopt Convolutional Neural Networks (CNNs) to be our parametric model...
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04/12/2016