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A relic sketch extraction framework based on detail-aware hierarchical deep network
As the first step of the restoration process of painted relics, sketch e...
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Learning the Implicit Semantic Representation on Graph-Structured Data
Existing representation learning methods in graph convolutional networks...
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Efficient Semi-Implicit Variational Inference
In this paper, we propose CI-VI an efficient and scalable solver for sem...
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FaceX-Zoo: A PyTorch Toolbox for Face Recognition
Deep learning based face recognition has achieved significant progress i...
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Causal World Models by Unsupervised Deconfounding of Physical Dynamics
The capability of imagining internally with a mental model of the world ...
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Generalized Relation Learning with Semantic Correlation Awareness for Link Prediction
Developing link prediction models to automatically complete knowledge gr...
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Learn molecular representations from large-scale unlabeled molecules for drug discovery
How to produce expressive molecular representations is a fundamental cha...
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Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training
Most recently, there has been significant interest in learning contextua...
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Are we Forgetting about Compositional Optimisers in Bayesian Optimisation?
Bayesian optimisation presents a sample-efficient methodology for global...
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Automatic Test Suite Generation for Key-points Detection DNNs Using Many-Objective Search
Automatically detecting the positions of key-points (e.g., facial key-po...
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Semi-supervised Active Learning for Instance Segmentation via Scoring Predictions
Active learning generally involves querying the most representative samp...
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HEBO: Heteroscedastic Evolutionary Bayesian Optimisation
We introduce HEBO: Heteroscedastic Evolutionary Bayesian Optimisation th...
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Automated Prostate Cancer Diagnosis Based on Gleason Grading Using Convolutional Neural Network
The Gleason grading system using histological images is the most powerfu...
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Reinforcement Learning Control of Constrained Dynamic Systems with Uniformly Ultimate Boundedness Stability Guarantee
Reinforcement learning (RL) is promising for complicated stochastic nonl...
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Targeted Poisoning Attacks on Black-Box Neural Machine Translation
As modern neural machine translation (NMT) systems have been widely depl...
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An Overview of Multi-Agent Reinforcement Learning from Game Theoretical Perspective
Following the remarkable success of the AlphaGO series, 2019 was a boomi...
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U-rank: Utility-oriented Learning to Rank with Implicit Feedback
Learning to rank with implicit feedback is one of the most important tas...
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Empirical or Invariant Risk Minimization? A Sample Complexity Perspective
Recently, invariant risk minimization (IRM) was proposed as a promising ...
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GMH: A General Multi-hop Reasoning Model for KG Completion
Knowledge graphs are essential for numerous downstream natural language ...
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Boosted EfficientNet: Detection of Lymph Node Metastases in Breast Cancer Using Convolutional Neural Network
In recent years, advances in the development of whole-slide images have ...
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Style Attuned Pre-training and Parameter Efficient Fine-tuning for Spoken Language Understanding
Neural models have yielded state-of-the-art results in deciphering spoke...
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Multi-typed Objects Multi-view Multi-instance Multi-label Learning
Multi-typed objects Multi-view Multi-instance Multi-label Learning (M4L)...
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Deep Incomplete Multi-View Multiple Clusterings
Multi-view clustering aims at exploiting information from multiple heter...
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Towards Target-Driven Visual Navigation in Indoor Scenes via Generative Imitation Learning
We present a target-driven navigation system to improve mapless visual n...
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Multi-modal Summarization for Video-containing Documents
Summarization of multimedia data becomes increasingly significant as it ...
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3DPVNet: Patch-level 3D Hough Voting Network for 6D Pose Estimation
In this paper, we focus on estimating the 6D pose of objects in point cl...
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A Real-time Contribution Measurement Method for Participants in Federated Learning
In recent years, individuals, business organizations or the country have...
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Learning to Infer User Hidden States for Online Sequential Advertising
To drive purchase in online advertising, it is of the advertiser's great...
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Computational prediction of RNA tertiary structures using machine learning methods
RNAs play crucial and versatile roles in biological processes. Computati...
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Deep Architectures for Modulation Recognition with Multiple Receive Antennas
Modulation recognition using deep neural networks has shown promising ad...
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Bilevel Learning Model Towards Industrial Scheduling
Automatic industrial scheduling, aiming at optimizing the sequence of jo...
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NPCFace: A Negative-Positive Cooperation Supervision for Training Large-scale Face Recognition
Deep face recognition has made remarkable advances in the last few years...
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Off-Policy Reinforcement Learning for Efficient and Effective GAN Architecture Search
In this paper, we introduce a new reinforcement learning (RL) based neur...
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InfoFocus: 3D Object Detection for Autonomous Driving with Dynamic Information Modeling
Real-time 3D object detection is crucial for autonomous cars. Achieving ...
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Semi-Siamese Training for Shallow Face Learning
Most existing public face datasets, such as MS-Celeb-1M and VGGFace2, pr...
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Bidirectional Loss Function for Label Enhancement and Distribution Learning
Label distribution learning (LDL) is an interpretable and general learni...
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Structural Landmarking and Interaction Modelling: on Resolution Dilemmas in Graph Classification
Graph neural networks are promising architecture for learning and infere...
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Automated Radiological Report Generation For Chest X-Rays With Weakly-Supervised End-to-End Deep Learning
The chest X-Ray (CXR) is the one of the most common clinical exam used t...
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SAMBA: Safe Model-Based Active Reinforcement Learning
In this paper, we propose SAMBA, a novel framework for safe reinforcemen...
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Learning to Model Opponent Learning
Multi-Agent Reinforcement Learning (MARL) considers settings in which a ...
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Explore Training of Deep Convolutional Neural Networks on Battery-powered Mobile Devices: Design and Application
The fast-growing smart applications on mobile devices leverage pre-train...
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Learning from a Lightweight Teacher for Efficient Knowledge Distillation
Knowledge Distillation (KD) is an effective framework for compressing de...
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Resisting the Distracting-factors in Pedestrian Detection
Pedestrian detection has been heavily studied in the last decade due to ...
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ViTAA: Visual-Textual Attributes Alignment in Person Search by Natural Language
Person search by natural language aims at retrieving a specific person i...
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Actor-Critic Reinforcement Learning for Control with Stability Guarantee
Deep Reinforcement Learning (DRL) has achieved impressive performance in...
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Deep Feature-preserving Normal Estimation for Point Cloud Filtering
Point cloud filtering, the main bottleneck of which is removing noise (o...
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Uncertainty Quantification for Hyperspectral Image Denoising Frameworks based on Low-rank Matrix Approximation
Low-rank matrix approximation (LRMA) is a technique widely applied in hy...
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Toward Terabits-per-second Communications: Low-Complexity Parallel Decoding of G_N-Coset Codes
Recently, a parallel decoding framework of G_N-coset codes was proposed....
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Toward Terabits-per-second Communications: A High-Throughput Hardware Implementation of G_N-Coset Codes
Recently, a parallel decoding algorithm of G_N-coset codes was proposed....
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CausalVAE: Structured Causal Disentanglement in Variational Autoencoder
Learning disentanglement aims at finding a low dimensional representatio...
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