
An Upper Limit of Decaying Rate with Respect to Frequency in Deep Neural Network
Deep neural network (DNN) usually learns the target function from low to...
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Fourierdomain Variational Formulation and Its Wellposedness for Supervised Learning
A supervised learning problem is to find a function in a hypothesis func...
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Defocus Blur Detection via Salient Region Detection Prior
Defocus blur always occurred in photos when people take photos by Digita...
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MultiScale OneClass Recurrent Neural Networks for Discrete Event Sequence Anomaly Detection
Discrete event sequences are ubiquitous, such as an ordered event series...
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Chat as Expected: Learning to Manipulate Blackbox Neural Dialogue Models
Recently, neural network based dialogue systems have become ubiquitous i...
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Siamese Neural Networks for Class Activity Detection
Classroom activity detection (CAD) aims at accurately recognizing speake...
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Graph Computing based Distributed State Estimation with PMUs
Power system state estimation plays a fundamental and critical role in t...
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Learning Multilevel Dependencies for Robust Word Recognition
Robust language processing systems are becoming increasingly important g...
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Twostage WECC Composite Load Modeling: A Double Deep QLearning Networks Approach
With the increasing complexity of modern power systems, conventional dyn...
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Automatic Short Answer Grading via Multiway Attention Networks
Automatic short answer grading (ASAG), which autonomously score student ...
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Deep Knowledge Tracing with Side Information
Monitoring student knowledge states or skill acquisition levels known as...
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Recommender Systems with Heterogeneous Side Information
In modern recommender systems, both users and items are associated with ...
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RTransformer: Recurrent Neural Network Enhanced Transformer
Recurrent Neural Networks have long been the dominating choice for seque...
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Autonomous Voltage Control for Grid Operation Using Deep Reinforcement Learning
Modern power grids are experiencing grand challenges caused by the stoch...
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A HighPerformance Energy Management System based on Evolving Graph
As the fast growth and large integration of distributed generation, rene...
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Graph Computing based Fast Screening in Contingency Analysis
During last decades, contingency analysis has been facing challenges fro...
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Probabilistic Load Forecasting via Point Forecast Feature Integration
Shortterm load forecasting is a critical element of power systems energ...
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Shortterm Load Forecasting at Different Aggregation Levels with Predictability Analysis
Shortterm load forecasting (STLF) is essential for the reliable and eco...
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Submodular Load Clustering with Robust Principal Component Analysis
Traditional load analysis is facing challenges with the new electricity ...
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Graph Computing based Distributed Fast Decoupled Power Flow Analysis
Power flow analysis plays a fundamental and critical role in the energy ...
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Semisupervised mpMRI Data Synthesis with StitchLayer and Auxiliary Distance Maximization
In this paper, we address the problem of synthesizing multiparameter ma...
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A RpropNeuralNetworkBased PV Maximum Power Point Tracking Algorithm with ShortCircuit Current Limitation
This paper proposes a resilientbackpropagationneuralnetwork(RpropNN...
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A NeuronNetworkBased Optimal Control of UltraCapacitors with System Uncertainties
In this paper, a neuralnetwork (NN)based online optimal control method...
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Graph Based Power Flow Calculation for Energy Management System
Power flow calculation in EMS is required to accommodate a large and com...
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Power Market Price Forecasting via Deep Learning
A study on power market price forecasting by deep learning is presented....
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Exploration of BiLevel PageRank Algorithm for Power Flow Analysis Using Graph Database
Compared with traditional relational database, graph database, GDB, is a...
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Power Flow Analysis Using Graph based Combination of Iterative Methods and Vertex Contraction Approach
Compared with relational database (RDB), graph database (GDB) is a more ...
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Linked Recurrent Neural Networks
Recurrent Neural Networks (RNNs) have been proven to be effective in mod...
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CIM/E Oriented Graph Database Model Architecture and Parallel Network Topology Processing
CIM/E is an easy and efficient electric power model exchange standard be...
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Exploration of Graph Computing in Power System State Estimation
With the increased complexity of power systems due to the integration of...
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Recover the lost Phasor Measurement Unit Data Using Alternating Direction Multipliers Method
This paper presents a novel algorithm for recovering missing data of pha...
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Zhiwei Wang
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