
Learning Graphon Autoencoders for Generative Graph Modeling
Graphon is a nonparametric model that generates graphs with arbitrary si...
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Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation
Recent studies imply that deep neural networks are vulnerable to adversa...
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Sparse online relative similarity learning
For many data mining and machine learning tasks, the quality of a simila...
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FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks
Graph Neural Network (GNN) research is rapidly growing thanks to the cap...
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ParetoFrontieraware Neural Architecture Generation for Diverse Budgets
Designing feasible and effective architectures under diverse computation...
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Towards Accurate and Compact Architectures via Neural Architecture Transformer
Designing effective architectures is one of the key factors behind the s...
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Hierarchical Graph Capsule Network
Graph Neural Networks (GNNs) draw their strength from explicitly modelin...
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Supervised Learning Achieves HumanLevel Performance in MOBA Games: A Case Study of Honor of Kings
We present JueWuSL, the first supervisedlearningbased artificial inte...
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RetroXpert: Decompose Retrosynthesis Prediction like a Chemist
Retrosynthesis is the process of recursively decomposing target molecule...
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Inverse Graph Identification: Can We Identify Node Labels Given Graph Labels?
Graph Identification (GI) has long been researched in graph learning and...
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COVIDDA: Deep Domain Adaptation from Typical Pneumonia to COVID19
The outbreak of novel coronavirus disease 2019 (COVID19) has already in...
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Disturbanceimmune Weight Sharing for Neural Architecture Search
Neural architecture search (NAS) has gained increasing attention in the ...
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Privacy Preserving Pointofinterest Recommendation Using Decentralized Matrix Factorization
Points of interest (POI) recommendation has been drawn much attention re...
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ContextAware Domain Adaptation in Semantic Segmentation
In this paper, we consider the problem of unsupervised domain adaptation...
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CostSensitive Portfolio Selection via Deep Reinforcement Learning
Portfolio Selection is an important realworld financial task and has at...
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Joint Wasserstein Distribution Matching
Joint distribution matching (JDM) problem, which aims to learn bidirecti...
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Rumor Detection on Social Media with BiDirectional Graph Convolutional Networks
Social media has been developing rapidly in public due to its nature of ...
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Online Adaptive Asymmetric Active Learning with Limited Budgets
Online Active Learning (OAL) aims to manage unlabeled datastream by sele...
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Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis
Deep learning based medical image diagnosis has shown great potential in...
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NAT: Neural Architecture Transformer for Accurate and Compact Architectures
Designing effective architectures is one of the key factors behind the s...
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Aggregated Gradient Langevin Dynamics
In this paper, we explore a general Aggregated Gradient Langevin Dynamic...
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Graph Convolutional Networks for Temporal Action Localization
Most stateoftheart action localization systems process each action pr...
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Transferable Neural Processes for Hyperparameter Optimization
Automated machine learning aims to automate the whole process of machine...
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Decentralized Online Learning: Take Benefits from Others' Data without Sharing Your Own to Track Global Trend
Decentralized Online Learning (online learning in decentralized networks...
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Hyperparameter Learning via Distributional Transfer
Bayesian optimisation is a popular technique for hyperparameter learning...
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Dual Reconstruction Nets for Image SuperResolution with Gradient Sensitive Loss
Deep neural networks have exhibited promising performance in image super...
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Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication
Recently, the decentralized optimization problem is attracting growing a...
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A Boosting Framework of Factorization Machine
Recently, Factorization Machines (FM) has become more and more popular f...
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Distributed Collaborative Hashing and Its Applications in Ant Financial
Collaborative filtering, especially latent factor model, has been popula...
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Adaptive Costsensitive Online Classification
CostSensitive Online Classification has drawn extensive attention in re...
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Online Learning: A Comprehensive Survey
Online learning represents an important family of machine learning algor...
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Online Compact Convexified Factorization Machine
Factorization Machine (FM) is a supervised learning approach with a powe...
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Robust CostSensitive Learning for Recommendation with Implicit Feedback
Recommendation is the task of improving customer experience through pers...
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Robust Online MultiTask Learning with Correlative and Personalized Structures
MultiTask Learning (MTL) can enhance a classifier's generalization perf...
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Accelerating Minibatch Stochastic Gradient Descent using Stratified Sampling
Stochastic Gradient Descent (SGD) is a popular optimization method which...
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Stochastic Optimization with Importance Sampling
Uniform sampling of training data has been commonly used in traditional ...
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Adaptive Stochastic Alternating Direction Method of Multipliers
The Alternating Direction Method of Multipliers (ADMM) has been studied ...
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Active Learning with Expert Advice
Conventional learning with expert advice methods assumes a learner is al...
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Peilin Zhao
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