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08/31/2023
Improving Lens Flare Removal with General Purpose Pipeline and Multiple Light Sources Recovery
When taking images against strong light sources, the resulting images of...
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08/12/2023
Multi-Label Knowledge Distillation
Existing knowledge distillation methods typically work by imparting the ...
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05/04/2023
Class-Distribution-Aware Pseudo Labeling for Semi-Supervised Multi-Label Learning
Pseudo labeling is a popular and effective method to leverage the inform...
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04/28/2023
ALL-E: Aesthetics-guided Low-light Image Enhancement
Evaluating the performance of low-light image enhancement (LLE) is highl...
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03/03/2023
Implicit Stochastic Gradient Descent for Training Physics-informed Neural Networks
Physics-informed neural networks (PINNs) have effectively been demonstra...
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09/03/2022
Noise-Robust Bidirectional Learning with Dynamic Sample Reweighting
Deep neural networks trained with standard cross-entropy loss are more p...
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08/26/2022
Meta Objective Guided Disambiguation for Partial Label Learning
Partial label learning (PLL) is a typical weakly supervised learning fra...
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07/06/2022
A Deep Model for Partial Multi-Label Image Classification with Curriculum Based Disambiguation
In this paper, we study the partial multi-label (PML) image classificati...
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01/31/2022
Can Adversarial Training Be Manipulated By Non-Robust Features?
Adversarial training, originally designed to resist test-time adversaria...
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01/18/2022
Active Learning for Open-set Annotation
Existing active learning studies typically work in the closed-set settin...
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07/11/2021
Learning from Crowds with Sparse and Imbalanced Annotations
Traditional supervised learning requires ground truth labels for the tra...
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05/16/2021
CCMN: A General Framework for Learning with Class-Conditional Multi-Label Noise
Class-conditional noise commonly exists in machine learning tasks, where...
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03/27/2021
Improving Model Robustness by Adaptively Correcting Perturbation Levels with Active Queries
In addition to high accuracy, robustness is becoming increasingly import...
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03/27/2021
Co-Imitation Learning without Expert Demonstration
Imitation learning is a primary approach to improve the efficiency of re...
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02/09/2021
Provable Defense Against Delusive Poisoning
Delusive poisoning is a special kind of attack to obstruct learning, whe...
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06/14/2020
Reinforcement Learning with Supervision from Noisy Demonstrations
Reinforcement learning has achieved great success in various application...
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01/12/2019
ALiPy: Active Learning in Python
Supervised machine learning methods usually require a large set of label...
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11/21/2018
Recent Advances in Open Set Recognition: A Survey
In real-world recognition/classification tasks, limited by various objec...
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02/15/2018
Cost-Effective Training of Deep CNNs with Active Model Adaptation
Deep convolutional neural networks have achieved great success in variou...
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02/15/2018
Active Feature Acquisition with Supervised Matrix Completion
Feature missing is a serious problem in many applications, which may lea...
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12/20/2016
