
Performance Portable Backprojection Algorithms on CPUs: Agnostic Data Locality and Vectorization Optimizations
Computed Tomography (CT) is a key 3D imaging technology that fundamental...
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Contrastive Learning with Stronger Augmentations
Representation learning has significantly been developed with the advanc...
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Lorentzian Graph Convolutional Networks
Graph convolutional networks (GCNs) have received considerable research ...
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TextFlint: Unified Multilingual Robustness Evaluation Toolkit for Natural Language Processing
Various robustness evaluation methodologies from different perspectives ...
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CaPC Learning: Confidential and Private Collaborative Learning
Machine learning benefits from large training datasets, which may not al...
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Interpreting and Unifying Graph Neural Networks with An Optimization Framework
Graph Neural Networks (GNNs) have received considerable attention on gra...
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Beyond Lowfrequency Information in Graph Convolutional Networks
Graph neural networks (GNNs) have been proven to be effective in various...
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HighDimensional Spatial Quantile FunctiononScalar Regression
This paper develops a novel spatial quantile functiononscalar regressi...
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yNet: a multiinput convolutional network for ultrafast simulation of field evolvement
The capability of multiinput fieldtofield regression, i.e. mapping th...
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A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources
Heterogeneous graphs (HGs) also known as heterogeneous information netwo...
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CrossLingual Document Retrieval with Smooth Learning
Crosslingual document search is an information retrieval task in which ...
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Fast Convergence of Langevin Dynamics on Manifold: Geodesics meet LogSobolev
Sampling is a fundamental and arguably very important task with numerous...
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Dynamic Fusion based Federated Learning for COVID19 Detection
Medical diagnostic image analysis (e.g., CT scan or XRay) using machine...
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Domain Priori Knowledge based Integrated Solution Design for Internet of Services
Various types of services, such as web APIs, IoT services, O2O services,...
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Heterogeneous Graph Neural Network for Recommendation
The prosperous development of ecommerce has spawned diverse recommendat...
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Decisionmaking at Unsignalized Intersection for Autonomous Vehicles: Leftturn Maneuver with Deep Reinforcement Learning
Decisionmaking module enables autonomous vehicles to reach appropriate ...
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Towards Class Imbalance in Federated Learning
Federated learning (FL) is a promising approach for training decentraliz...
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Deep Reinforced Query Reformulation for Information Retrieval
Query reformulations have long been a key mechanism to alleviate the voc...
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SaADB: A Selfattention Guided ADB Network for Person Reidentification
Recently, Batch DropBlock network (BDB) has demonstrated its effectivene...
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AMGCN: Adaptive Multichannel Graph Convolutional Networks
Graph Convolutional Networks (GCNs) have gained great popularity in tack...
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FalsificationBased Robust Adversarial Reinforcement Learning
Reinforcement learning (RL) has achieved tremendous progress in solving ...
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Decorrelated Clustering with Data Selection Bias
Most of existing clustering algorithms are proposed without considering ...
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FMT:Fusing Multitask Convolutional Neural Network for Person Search
Person search is to detect all persons and identify the query persons fr...
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Convergence to SecondOrder Stationarity for Nonnegative Matrix Factorization: Provably and Concurrently
Nonnegative matrix factorization (NMF) is a fundamental nonconvex opti...
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AdvMS: A Multisource Multicost Defense Against Adversarial Attacks
Designing effective defense against adversarial attacks is a crucial top...
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Block Switching: A Stochastic Approach for Deep Learning Security
Recent study of adversarial attacks has revealed the vulnerability of mo...
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Last iterate convergence in noregret learning: constrained minmax optimization for convexconcave landscapes
In a recent series of papers it has been established that variants of Gr...
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Stochastic Approximate Gradient Descent via the Langevin Algorithm
We introduce a novel and efficient algorithm called the stochastic appro...
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Structural Deep Clustering Network
Clustering is a fundamental task in data analysis. Recently, deep cluste...
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cmSalGAN: RGBD Salient Object Detection with CrossView Generative Adversarial Networks
Image salient object detection (SOD) is an active research topic in comp...
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Measuring Compositional Generalization: A Comprehensive Method on Realistic Data
Stateoftheart machine learning methods exhibit limited compositional ...
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DepthWidth Tradeoffs for ReLU Networks via Sharkovsky's Theorem
Understanding the representational power of Deep Neural Networks (DNNs) ...
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Hyperbolic Graph Attention Network
Graph neural network (GNN) has shown superior performance in dealing wit...
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Independence Promoted Graph Disentangled Networks
We address the problem of disentangled representation learning with inde...
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MultiComponent Graph Convolutional Collaborative Filtering
The interactions of users and items in recommender system could be natur...
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EnAET: SelfTrained Ensemble AutoEncoding Transformations for SemiSupervised Learning
Deep neural networks have been successfully applied to many realworld a...
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Eavesdrop the Composition Proportion of Training Labels in Federated Learning
Federated learning (FL) has recently emerged as a new form of collaborat...
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ISTHMUS: Secure, Scalable, Realtime and Robust Machine Learning Platform for Healthcare
In recent times, machine learning (ML) and artificial intelligence (AI) ...
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Deep Collaborative Filtering with MultiAspect Information in Heterogeneous Networks
Recently, recommender systems play a pivotal role in alleviating the pro...
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Temporal Network Embedding with Micro and Macrodynamics
Network embedding aims to embed nodes into a lowdimensional space, whil...
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Protecting Neural Networks with Hierarchical Random Switching: Towards Better RobustnessAccuracy Tradeoff for Stochastic Defenses
Despite achieving remarkable success in various domains, recent studies ...
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Learning Targetoriented Dual Attention for Robust RGBT Tracking
RGBThermal object tracking attempt to locate target object using comple...
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Deep Learning Models to Predict Pediatric Asthma Emergency Department Visits
Pediatric asthma is the most prevalent chronic childhood illness, afflic...
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Dense Feature Aggregation and Pruning for RGBT Tracking
How to perform effective information fusion of different modalities is a...
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Improved Hard Example Mining by Discovering Attributebased Hard Person Identity
In this paper, we propose Hard Person Identity Mining (HPIM) that attemp...
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A RightofWay Based Strategy to Implement Safe and Efficient Driving at NonSignalized Intersections for Automated Vehicles
Nonsignalized intersection is a typical and common scenario for connect...
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Optimal Penalized FunctiononFunction Regression under a Reproducing Kernel Hilbert Space Framework
Many scientific studies collect data where the response and predictor va...
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Pedestrian Attribute Recognition: A Survey
Recognizing pedestrian attributes is an important task in computer visio...
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QualityAware Multimodal Saliency Detection via Deep Reinforcement Learning
Incorporating various modes of information into the machine learning pro...
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Describe and Attend to Track: Learning Natural Language guided Structural Representation and Visual Attention for Object Tracking
The trackingbydetection framework requires a set of positive and negat...
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