
SiENet: Siamese Expansion Network for Image Extrapolation
Different from image inpainting, image outpainting has relative less con...
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Generating AdjacencyConstrained Subgoals in Hierarchical Reinforcement Learning
Goalconditioned hierarchical reinforcement learning (HRL) is a promisin...
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Braininspired globallocal hybrid learning towards humanlike intelligence
The combination of neuroscienceoriented and computerscienceoriented a...
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Bridging the Gap between Spatial and Spectral Domains: A Survey on Graph Neural Networks
The success of deep learning has been widely recognized in many machine ...
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TLFW: A Threelayer Framework in Wireless Rechargeable Sensor Network with a Mobile Base Station
Wireless sensor networks as the base support for the Internet of things ...
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FewFeatures Attack to Fool Machine Learning Models through MaskBased GAN
GAN is a deeplearning based generative approach to generate contents su...
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Quantifying Classification Uncertainty using Regularized Evidential Neural Networks
Traditional deep neural nets (NNs) have shown the stateoftheart perfo...
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Deep Learning for Predicting Dynamic Uncertain Opinions in Network Data
Subjective Logic (SL) is one of wellknown belief models that can explic...
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Subjectivity Learning Theory towards Artificial General Intelligence
The construction of artificial general intelligence (AGI) was a longter...
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Dual Averaging Method for Online Graphstructured Sparsity
Online learning algorithms update models via one sample per iteration, t...
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Stochastic Iterative Hard Thresholding for Graphstructured Sparsity Optimization
Stochastic optimization algorithms update models with cheap periteratio...
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Convolution with evensized kernels and symmetric padding
Compact convolutional neural networks gain efficiency mainly through dep...
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NeuroTreeNet: A New Method to Explore Horizontal Expansion Network
It is widely recognized that the deeper networks or networks with more f...
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Revealing Fine Structures of the Retinal Receptive Field by Deep Learning Networks
Deep convolutional neural networks (CNNs) have demonstrated impressive p...
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Abstraction Learning
There has been a gap between artificial intelligence and human intellige...
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Rational Neural Networks for Approximating Jump Discontinuities of Graph Convolution Operator
For node level graph encoding, a recent important stateofart method is...
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Water Disaggregation via Shape Features based Bayesian Discriminative Sparse Coding
As the issue of freshwater shortage is increasing daily, it is critical ...
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Marked SelfExciting Point Process Modelling of Information Diffusion on Twitter
Information diffusion occurs on microblogging platforms like Twitter as ...
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A Deep Learning Approach for Privacy Preservation in Assisted Living
In the era of Internet of Things (IoT) technologies the potential for pr...
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Training and Inference with Integers in Deep Neural Networks
Researches on deep neural networks with discrete parameters and their de...
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Revealing structure components of the retina by deep learning networks
Deep convolutional neural networks (CNNs) have demonstrated impressive p...
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A Generic Framework for Interesting Subspace Cluster Detection in Multiattributed Networks
Detection of interesting (e.g., coherent or anomalous) clusters has been...
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Experimental comparison of singlepixel imaging algorithms
Singlepixel imaging (SPI) is a novel technique capturing 2D images usin...
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Performance Evaluation and Modeling of HPC I/O on NonVolatile Memory
HPC applications pose high demands on I/O performance and storage capabi...
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Technical Report: A Generalized Matching Pursuit Approach for GraphStructured Sparsity
Sparsityconstrained optimization is an important and challenging proble...
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Technical Report: GraphStructured Sparse Optimization for Connected Subgraph Detection
Structured sparse optimization is an important and challenging problem f...
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CaMKII activation supports rewardbased neural network optimization through Hamiltonian sampling
Synaptic plasticity is implemented and controlled through over thousand ...
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Fourier ptychographic reconstruction using Poisson maximum likelihood and truncated Wirtinger gradient
Fourier ptychographic microscopy (FPM) is a novel computational coherent...
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Samplingbased Causal Inference in Cue Combination and its Neural Implementation
Causal inference in cue combination is to decide whether the cues have a...
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Multiframe denoising of high speed optical coherence tomography data using interframe and intraframe priors
Optical coherence tomography (OCT) is an important interferometric diagn...
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