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08/22/2023
Learning from Semantic Alignment between Unpaired Multiviews for Egocentric Video Recognition
We are concerned with a challenging scenario in unpaired multiview video...
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08/22/2023
Decoupled Contrastive Multi-view Clustering with High-order Random Walks
In recent, some robust contrastive multi-view clustering (MvC) methods h...
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08/19/2023
Noisy-Correspondence Learning for Text-to-Image Person Re-identification
Text-to-image person re-identification (TIReID) is a compelling topic in...
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07/26/2023
Topology-aware Robust Optimization for Out-of-distribution Generalization
Out-of-distribution (OOD) generalization is a challenging machine learni...
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07/12/2023
Deep learning-based estimation of whole-body kinematics from multi-view images
It is necessary to analyze the whole-body kinematics (including joint lo...
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06/14/2023
High-Dimensional MR Reconstruction Integrating Subspace and Adaptive Generative Models
We present a novel method that integrates subspace modeling with an adap...
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06/03/2023
Provable Dynamic Fusion for Low-Quality Multimodal Data
The inherent challenge of multimodal fusion is to precisely capture the ...
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06/02/2023
dugMatting: Decomposed-Uncertainty-Guided Matting
Cutting out an object and estimating its opacity mask, known as image ma...
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05/22/2023
Semantic Invariant Multi-view Clustering with Fully Incomplete Information
Robust multi-view learning with incomplete information has received sign...
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04/21/2023
Deep Multiview Clustering by Contrasting Cluster Assignments
Multiview clustering (MVC) aims to reveal the underlying structure of mu...
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01/26/2023
Incomplete Multi-view Clustering via Prototype-based Imputation
In this paper, we study how to achieve two characteristics highly-expect...
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12/08/2022
Relationship Quantification of Image Degradations
In this paper, we study two challenging but less-touched problems in ima...
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12/08/2022
Graph Matching with Bi-level Noisy Correspondence
In this paper, we study a novel and widely existing problem in graph mat...
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10/21/2022
Twin Contrastive Learning for Online Clustering
This paper proposes to perform online clustering by conducting twin cont...
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09/26/2022
Deep Fair Clustering via Maximizing and Minimizing Mutual Information
Fair clustering aims to divide data into distinct clusters, while preven...
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09/23/2022
Robust Domain Adaptation for Machine Reading Comprehension
Most domain adaptation methods for machine reading comprehension (MRC) u...
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08/16/2022
FALCON: Sound and Complete Neural Semantic Entailment over ALC Ontologies
Many ontologies, i.e., Description Logic (DL) knowledge bases, have been...
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05/29/2022
TAR: Neural Logical Reasoning across TBox and ABox
Many ontologies, i.e., Description Logic (DL) knowledge bases, have been...
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05/23/2022
OPQ: Compressing Deep Neural Networks with One-shot Pruning-Quantization
As Deep Neural Networks (DNNs) usually are overparameterized and have mi...
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05/04/2022
Symmetry and Uncertainty-Aware Object SLAM for 6DoF Object Pose Estimation
We propose a keypoint-based object-level SLAM framework that can provide...
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04/12/2022
Are Multimodal Transformers Robust to Missing Modality?
Multimodal data collected from the real world are often imperfect due to...
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03/08/2022
Multi-Scale Adaptive Network for Single Image Denoising
Multi-scale architectures have shown effectiveness in a variety of tasks...
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02/28/2022
Description Logic EL++ Embeddings with Intersectional Closure
Many ontologies, in particular in the biomedical domain, are based on th...
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12/17/2021
Deep Learning for Spatiotemporal Modeling of Urbanization
Urbanization has a strong impact on the health and wellbeing of populati...
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08/16/2021
Understanding the factors driving the opioid epidemic using machine learning
In recent years, the US has experienced an opioid epidemic with an unpre...
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08/05/2021
Out-of-domain Generalization from a Single Source: A Uncertainty Quantification Approach
We study a worst-case scenario in generalization: Out-of-domain generali...
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07/14/2021
Unsupervised Neural Rendering for Image Hazing
Image hazing aims to render a hazy image from a given clean one, which c...
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06/28/2021
Dizygotic Conditional Variational AutoEncoder for Multi-Modal and Partial Modality Absent Few-Shot Learning
Data augmentation is a powerful technique for improving the performance ...
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04/30/2021
A Good Image Generator Is What You Need for High-Resolution Video Synthesis
Image and video synthesis are closely related areas aiming at generating...
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03/12/2021
Uncertainty-guided Model Generalization to Unseen Domains
We study a worst-case scenario in generalization: Out-of-domain generali...
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03/09/2021
SMIL: Multimodal Learning with Severely Missing Modality
A common assumption in multimodal learning is the completeness of traini...
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12/02/2020
Learning View-Disentangled Human Pose Representation by Contrastive Cross-View Mutual Information Maximization
We introduce a novel representation learning method to disentangle pose-...
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10/15/2020
Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness
Adversarial data augmentation has shown promise for training robust deep...
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09/21/2020
Contrastive Clustering
In this paper, we propose a one-stage online clustering method called Co...
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08/31/2020
Structured Graph Learning for Clustering and Semi-supervised Classification
Graphs have become increasingly popular in modeling structures and inter...
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06/30/2020
You Only Look Yourself: Unsupervised and Untrained Single Image Dehazing Neural Network
In this paper, we study two challenging and less-touched problems in sin...
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04/28/2020
Heterogeneous Representation Learning: A Review
The real-world data usually exhibits heterogeneous properties such as mo...
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04/01/2020
Knowledge as Priors: Cross-Modal Knowledge Generalization for Datasets without Superior Knowledge
Cross-modal knowledge distillation deals with transferring knowledge fro...
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03/30/2020
Learning to Learn Single Domain Generalization
We are concerned with a worst-case scenario in model generalization, in ...
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03/13/2020
Learning Graph Embedding with Limited Labeled Data: An Efficient Sampling Approach
Semi-supervised graph embedding methods represented by graph convolution...
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12/05/2019
Deep Anomaly Detection in Packet Payload
With the widespread adoption of cloud services, especially the extensive...
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11/25/2019
Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding
Graph kernels are widely used for measuring the similarity between graph...
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11/15/2019
DNNRE: A Dynamic Neural Network for Distant Supervised Relation Extraction
Distant Supervised Relation Extraction (DSRE) is usually formulated as a...
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10/06/2019
Rethinking Kernel Methods for Node Representation Learning on Graphs
Graph kernels are kernel methods measuring graph similarity and serve as...
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07/20/2019
Construct Dynamic Graphs for Hand Gesture Recognition via Spatial-Temporal Attention
We propose a Dynamic Graph-Based Spatial-Temporal Attention (DG-STA) met...
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06/04/2019
Automatic Health Problem Detection from Gait Videos Using Deep Neural Networks
The aim of this study is developing an automatic system for detection of...
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04/06/2019
Semantic Graph Convolutional Networks for 3D Human Pose Regression
In this paper, we study the problem of learning Graph Convolutional Netw...
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03/01/2019
Learning where to look: Semantic-Guided Multi-Attention Localization for Zero-Shot Learning
Zero-shot learning extends the conventional object classification to the...
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08/22/2018
k-meansNet: When k-means Meets Differentiable Programming
In this paper, we study how to make clustering benefiting from different...
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08/20/2018
