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07/12/2023
SwiFT: Swin 4D fMRI Transformer
The modeling of spatiotemporal brain dynamics from high-dimensional data...
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06/08/2023
Sy-CON: Symmetric Contrastive Loss for Continual Self-Supervised Representation Learning
We introduce a novel and general loss function, called Symmetric Contras...
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03/21/2023
Continual Learning in the Presence of Spurious Correlation
Most continual learning (CL) algorithms have focused on tackling the sta...
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03/01/2023
Re-weighting Based Group Fairness Regularization via Classwise Robust Optimization
Many existing group fairness-aware training methods aim to achieve the g...
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01/27/2023
Learning to Unlearn: Instance-wise Unlearning for Pre-trained Classifiers
Since the recent advent of regulations for data protection (e.g., the Ge...
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11/29/2022
Towards More Robust Interpretation via Local Gradient Alignment
Neural network interpretation methods, particularly feature attribution ...
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08/08/2022
GRIT-VLP: Grouped Mini-batch Sampling for Efficient Vision and Language Pre-training
Most of the currently existing vision and language pre-training (VLP) me...
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06/22/2022
Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks
Heterogeneous graph neural networks (GNNs) achieve strong performance on...
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06/16/2022
Is Continual Learning Truly Learning Representations Continually?
Continual learning (CL) aims to learn from sequentially arriving tasks w...
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01/29/2022
Task-Balanced Batch Normalization for Exemplar-based Class-Incremental Learning
Batch Normalization (BN) is an essential layer for training neural netwo...
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11/29/2021
Learning Fair Classifiers with Partially Annotated Group Labels
Recently, fairness-aware learning have become increasingly crucial, but ...
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11/24/2021
Supervised Neural Discrete Universal Denoiser for Adaptive Denoising
We improve the recently developed Neural DUDE, a neural network-based ad...
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10/08/2021
Observations on K-image Expansion of Image-Mixing Augmentation for Classification
Image-mixing augmentations (e.g., Mixup or CutMix), which typically mix ...
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06/22/2021
Self-Supervised Iterative Contextual Smoothing for Efficient Adversarial Defense against Gray- and Black-Box Attack
We propose a novel and effective input transformation based adversarial ...
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06/22/2021
SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning
We consider a class-incremental semantic segmentation (CISS) problem. Wh...
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05/23/2021
FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian Noise
We consider the challenging blind denoising problem for Poisson-Gaussian...
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06/12/2020
CPR: Classifier-Projection Regularization for Continual Learning
We propose a general, yet simple patch that can be applied to existing r...
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03/31/2020
A Simple Class Decision Balancing for Incremental Learning
Class incremental learning (CIL) problem, in which a learning agent cont...
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03/30/2020
Adaptive Group Sparse Regularization for Continual Learning
We propose a novel regularization-based continual learning method, dubbe...
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03/05/2020
Unsupervised Neural Universal Denoiser for Finite-Input General-Output Noisy Channel
We devise a novel neural network-based universal denoiser for the finite...
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05/28/2019
Uncertainty-based Continual Learning with Adaptive Regularization
We introduce a new regularization-based continual learning algorithm, du...
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05/25/2019
GAN2GAN: Generative Noise Learning for Blind Image Denoising with Single Noisy Images
We tackle a challenging blind image denoising problem, in which only sin...
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02/24/2019
Iterative Channel Estimation for Discrete Denoising under Channel Uncertainty
We propose a novel iterative channel estimation (ICE) algorithm that ess...
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02/07/2019
DoPAMINE: Double-sided Masked CNN for Pixel Adaptive Multiplicative Noise Despeckling
We propose DoPAMINE, a new neural network based multiplicative noise des...
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02/06/2019
Fooling Neural Network Interpretations via Adversarial Model Manipulation
We ask whether the neural network interpretation methods can be fooled v...
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11/16/2018
Subtask Gated Networks for Non-Intrusive Load Monitoring
Non-intrusive load monitoring (NILM), also known as energy disaggregatio...
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07/19/2018
Fully Convolutional Pixel Adaptive Image Denoiser
We propose a new denoising algorithm, dubbed as Fully Convolutional Adap...
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09/17/2017
Neural Affine Grayscale Image Denoising
We propose a new grayscale image denoiser, dubbed as Neural Affine Image...
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09/11/2017
3D Densely Convolutional Networks for Volumetric Segmentation
In the isointense stage, the accurate volumetric image segmentation is a...
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02/21/2015
Regularization and Kernelization of the Maximin Correlation Approach
Robust classification becomes challenging when each class consists of mu...
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03/19/2011
