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Personalized Bundle Recommendation in Online Games
In business domains, bundling is one of the most important marketing str...
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Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation
In recent years, there are great interests as well as challenges in appl...
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Neural Architecture Search based on Cartesian Genetic Programming Coding Method
Neural architecture search (NAS) is a hot topic in the field of AutoML, ...
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A High-dimensional Sparse Fourier Transform in the Continuous Setting
In this paper, we theoretically propose a new hashing scheme to establis...
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GraphGallery: A Platform for Fast Benchmarking and Easy Development of Graph Neural Networks Based Intelligent Software
Graph Neural Networks (GNNs) have recently shown to be powerful tools fo...
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Material absorption-based carrier generation model for modeling optoelectronic devices
The generation rate of photocarriers in optoelectronic materials is comm...
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Deep Reinforcement Learning with Spatio-temporal Traffic Forecasting for Data-Driven Base Station Sleep Control
To meet the ever increasing mobile traffic demand in 5G era, base statio...
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Learning to Sample the Most Useful Training Patches from Images
Some image restoration tasks like demosaicing require difficult training...
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Ensembled CTR Prediction via Knowledge Distillation
Recently, deep learning-based models have been widely studied for click-...
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GAIN: Graph Attention Interaction Network for Inductive Semi-Supervised Learning over Large-scale Graphs
Graph Neural Networks (GNNs) have led to state-of-the-art performance on...
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Self-supervised Graph Learning for Recommendation
Representation learning on user-item graph for recommendation has evolve...
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Topology Optimization through Differentiable Finite Element Solver
In this paper, a topology optimization framework utilizing automatic dif...
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AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results
This paper reviews the AIM 2020 challenge on efficient single image supe...
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Adversarial Attack on Large Scale Graph
Recent studies have shown that graph neural networks are vulnerable agai...
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Variance-reduced Language Pretraining via a Mask Proposal Network
Self-supervised learning, a.k.a., pretraining, is important in natural l...
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Interactive Path Reasoning on Graph for Conversational Recommendation
Traditional recommendation systems estimate user preference on items fro...
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A Memory-efficient Implementation of Perfectly Matched Layer with Smoothly-varying Coefficients in Discontinuous Galerkin Time-Domain Method
Wrapping a computation domain with a perfectly matched layer (PML) is on...
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Crossed-Time Delay Neural Network for Speaker Recognition
Time Delay Neural Network (TDNN) is a well-performing structure for DNN-...
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An Efficient Discontinuous Galerkin Scheme for Simulating Terahertz Photoconductive Devices with Periodic Nanostructures
Photoconductive devices (PCDs) enhanced with nanostructures have shown a...
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A hybridizable discontinuous Galerkin method for simulation of electrostatic problems with floating potential conductors
In an electrostatic simulation, an equipotential condition with an undef...
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Modelling High-Order Social Relations for Item Recommendation
The prevalence of online social network makes it compulsory to study how...
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A Survey of Adversarial Learning on Graphs
Deep learning models on graphs have achieved remarkable performance in v...
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DeepCP: Deep Learning Driven Cascade Prediction Based Autonomous Content Placement in Closed Social Network
Online social networks (OSNs) are emerging as the most popular mainstrea...
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A re-formulization of the transfer matrix method for calculating wave-functions in higher dimensional disordered open systems
We present a numerically stable re-formulization of the transfer matrix ...
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Multiphysics Simulation of Plasmonic Photoconductive Antennas using Discontinuous Galerkin Methods
Plasmonic nanostructures significantly improve the performance of photoc...
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Multiphysics Modeling of Plasmonic Photoconductive Devices using Discontinuous Galerkin Methods
Plasmonic nanostructures can significantly improve the performance of ph...
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Data Poisoning Attacks on Neighborhood-based Recommender Systems
Nowadays, collaborative filtering recommender systems have been widely d...
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The Intrinsic Properties of Brain Based on the Network Structure
Objective: Brain is a fantastic organ that helps creature adapting to th...
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Selecting Reliable Blockchain Peers via Hybrid Blockchain Reliability Prediction
Blockchain and blockchain-based decentralized applications are attractin...
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Steady-state Simulation of Semiconductor Devices using Discontinuous Galerkin Methods
Design of modern nanostructured semiconductor devices often calls for si...
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Intelligent image synthesis to attack a segmentation CNN using adversarial learning
Deep learning approaches based on convolutional neural networks (CNNs) h...
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A New CGAN Technique for Constrained Topology Design Optimization
This paper presents a new conditional GAN (named convex relaxing CGAN or...
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GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks
One of the biggest issues facing the use of machine learning in medical ...
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Attention-Gated Networks for Improving Ultrasound Scan Plane Detection
In this work, we apply an attention-gated network to real-time automated...
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A Broad Learning Approach for Context-Aware Mobile Application Recommendation
With the rapid development of mobile apps, the availability of a large n...
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Object Recognition Based on Amounts of Unlabeled Data
This paper proposes a novel semi-supervised method on object recognition...
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Feature-Area Optimization: A Novel SAR Image Registration Method
This letter proposes a synthetic aperture radar (SAR) image registration...
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Boost Picking: A Universal Method on Converting Supervised Classification to Semi-supervised Classification
This paper proposes a universal method, Boost Picking, to train supervis...
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Robustness of Regional Matching Scheme over Global Matching Scheme
The paper has established and verified the theory prevailing widely amon...
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