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09/20/2023
Long-tail Augmented Graph Contrastive Learning for Recommendation
Graph Convolutional Networks (GCNs) has demonstrated promising results f...
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09/14/2023
Leveraging Contextual Information for Effective Entity Salience Detection
In text documents such as news articles, the content and key events usua...
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08/02/2023
Beta-trees: Multivariate histograms with confidence statements
Multivariate histograms are difficult to construct due to the curse of d...
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06/15/2023
Winsorized Robust Credibility Models
The Bühlmann model, a branch of classical credibility theory, has been s...
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05/08/2023
MultiModal-GPT: A Vision and Language Model for Dialogue with Humans
We present a vision and language model named MultiModal-GPT to conduct m...
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02/28/2023
Interactive Segmentation as Gaussian Process Classification
Click-based interactive segmentation (IS) aims to extract the target obj...
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09/21/2022
KXNet: A Model-Driven Deep Neural Network for Blind Super-Resolution
Although current deep learning-based methods have gained promising perfo...
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08/18/2022
An Adaptively Resized Parametric Bootstrap for Inference in High-dimensional Generalized Linear Models
Accurate statistical inference in logistic regression models remains a c...
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04/05/2022
Method of Winsorized Moments for Robust Fitting of Truncated and Censored Lognormal Distributions
When constructing parametric models to predict the cost of future claims...
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03/01/2022
An Effective Graph Learning based Approach for Temporal Link Prediction: The First Place of WSDM Cup 2022
Temporal link prediction, as one of the most crucial work in temporal gr...
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02/16/2022
Diagnosing Batch Normalization in Class Incremental Learning
Extensive researches have applied deep neural networks (DNNs) in class i...
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02/12/2022
Low-light Image Enhancement by Retinex Based Algorithm Unrolling and Adjustment
Motivated by their recent advances, deep learning techniques have been w...
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07/30/2021
Fourier Series Expansion Based Filter Parametrization for Equivariant Convolutions
It has been shown that equivariant convolution is very helpful for many ...
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07/14/2021
RCDNet: An Interpretable Rain Convolutional Dictionary Network for Single Image Deraining
As a common weather, rain streaks adversely degrade the image quality. H...
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07/02/2021
Unsupervised Single Image Super-resolution Under Complex Noise
While the researches on single image super-resolution (SISR), especially...
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06/05/2021
A Deep Variational Bayesian Framework for Blind Image Deblurring
Blind image deblurring is an important yet very challenging problem in l...
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03/14/2021
Semi-Supervised Video Deraining with Dynamic Rain Generator
While deep learning (DL)-based video deraining methods have achieved sig...
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10/13/2020
Cross-Supervised Joint-Event-Extraction with Heterogeneous Information Networks
Joint-event-extraction, which extracts structural information (i.e., ent...
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08/25/2020
Variational Image Restoration Network
Deep neural networks (DNNs) have achieved significant success in image r...
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08/08/2020
From Rain Removal to Rain Generation
Single image deraining is an important yet challenging issue due to the ...
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08/08/2020
Meta Feature Modulator for Long-tailed Recognition
Deep neural networks often degrade significantly when training data suff...
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08/03/2020
Learning to Purify Noisy Labels via Meta Soft Label Corrector
Recent deep neural networks (DNNs) can easily overfit to biased training...
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07/29/2020
Meta-LR-Schedule-Net: Learned LR Schedules that Scale and Generalize
The learning rate (LR) is one of the most important hyper-parameters in ...
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07/28/2020
ECNU-SenseMaker at SemEval-2020 Task 4: Leveraging Heterogeneous Knowledge Resources for Commonsense Validation and Explanation
This paper describes our system for SemEval-2020 Task 4: Commonsense Val...
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07/12/2020
Dual Adversarial Network: Toward Real-world Noise Removal and Noise Generation
Real-world image noise removal is a long-standing yet very challenging t...
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06/10/2020
Meta Transition Adaptation for Robust Deep Learning with Noisy Labels
To discover intrinsic inter-class transition probabilities underlying da...
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05/19/2020
Structural Residual Learning for Single Image Rain Removal
To alleviate the adverse effect of rain streaks in image processing task...
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05/04/2020
A Model-driven Deep Neural Network for Single Image Rain Removal
Deep learning (DL) methods have achieved state-of-the-art performance in...
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02/16/2020
Learning Adaptive Loss for Robust Learning with Noisy Labels
Robust loss minimization is an important strategy for handling robust le...
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01/25/2020
The Asymptotic Distribution of the MLE in High-dimensional Logistic Models: Arbitrary Covariance
We study the distribution of the maximum likelihood estimate (MLE) in hi...
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12/18/2019
Neural Networks Weights Quantization: Target None-retraining Ternary (TNT)
Quantization of weights of deep neural networks (DNN) has proven to be a...
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11/28/2019
Understand Dynamic Regret with Switching Cost for Online Decision Making
As a metric to measure the performance of an online method, dynamic regr...
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09/18/2019
A Survey on Rain Removal from Video and Single Image
Rain streaks might severely degenerate the performance of video/image pr...
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09/13/2019
Video Rain/Snow Removal by Transformed Online Multiscale Convolutional Sparse Coding
Video rain/snow removal from surveillance videos is an important task in...
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08/29/2019
Variational Denoising Network: Toward Blind Noise Modeling and Removal
Blind image denoising is an important yet very challenging problem in co...
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07/08/2019
Variational Bayes' method for functions with applications to some inverse problems
Bayesian approach as a useful tool for quantifying uncertainties has bee...
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02/20/2019
Push the Student to Learn Right: Progressive Gradient Correcting by Meta-learner on Corrupted Labels
While deep networks have strong fitting capability to complex input patt...
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02/20/2019
Tug the Student to Learn Right: Progressive Gradient Correcting by Meta-learner on Corrupted Labels
While deep networks have strong fitting capability to complex input patt...
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01/10/2019
Multispectral and Hyperspectral Image Fusion by MS/HS Fusion Net
Hyperspectral imaging can help better understand the characteristics of ...
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09/18/2018
Enhanced 3DTV Regularization and Its Applications on Hyper-spectral Image Denoising and Compressed Sensing
The 3-D total variation (3DTV) is a powerful regularization term, which ...
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09/06/2018
Discovering Influential Factors in Variational Autoencoder
In the field of machine learning, it is still a critical issue to identi...
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08/08/2018
Unsupervised/Semi-supervised Deep Learning for Low-dose CT Enhancement
Recently, deep learning(DL) methods have been proposed for the low-dose ...
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07/29/2018
Semi-supervised CNN for Single Image Rain Removal
Single image rain removal is a typical inverse problem in computer visio...
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07/08/2017
Hyperspectral Image Restoration via Total Variation Regularized Low-rank Tensor Decomposition
Hyperspectral images (HSIs) are often corrupted by a mixture of several ...
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06/20/2017
SPLBoost: An Improved Robust Boosting Algorithm Based on Self-paced Learning
It is known that Boosting can be interpreted as a gradient descent techn...
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05/18/2017
A General Model for Robust Tensor Factorization with Unknown Noise
Because of the limitations of matrix factorization, such as losing spati...
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02/01/2017
Denoising Hyperspectral Image with Non-i.i.d. Noise Structure
Hyperspectral image (HSI) denoising has been attracting much research at...
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01/06/2016
Low-rank Matrix Factorization under General Mixture Noise Distributions
Many computer vision problems can be posed as learning a low-dimensional...
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11/30/2012