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08/29/2023
From SMOTE to Mixup for Deep Imbalanced Classification
Given imbalanced data, it is hard to train a good classifier using deep ...
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07/09/2023
Score-based Conditional Generation with Fewer Labeled Data by Self-calibrating Classifier Guidance
Score-based Generative Models (SGMs) are a popular family of deep genera...
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06/15/2023
Re-Benchmarking Pool-Based Active Learning for Binary Classification
Active learning is a paradigm that significantly enhances the performanc...
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05/15/2023
Enhancing Label Sharing Efficiency in Complementary-Label Learning with Label Augmentation
Complementary-label Learning (CLL) is a form of weakly supervised learni...
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05/15/2023
CLCIFAR: CIFAR-Derived Benchmark Datasets with Human Annotated Complementary Labels
As a weakly-supervised learning paradigm, complementary label learning (...
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03/01/2023
SUNY: A Visual Interpretation Framework for Convolutional Neural Networks from a Necessary and Sufficient Perspective
Researchers have proposed various methods for visually interpreting the ...
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02/05/2023
Semi-Supervised Domain Adaptation with Source Label Adaptation
Semi-Supervised Domain Adaptation (SSDA) involves learning to classify u...
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10/21/2022
Reducing Training Sample Memorization in GANs by Training with Memorization Rejection
Generative adversarial network (GAN) continues to be a popular research ...
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09/20/2022
Reduction from Complementary-Label Learning to Probability Estimates
Complementary-Label Learning (CLL) is a weakly-supervised learning probl...
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11/03/2021
Improving Model Compatibility of Generative Adversarial Networks by Boundary Calibration
Generative Adversarial Networks (GANs) is a powerful family of models th...
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11/01/2021
A Unified View of cGANs with and without Classifiers
Conditional Generative Adversarial Networks (cGANs) are implicit generat...
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09/29/2021
Active Refinement for Multi-Label Learning: A Pseudo-Label Approach
The goal of multi-label learning (MLL) is to associate a given instance ...
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06/06/2021
On Training Sample Memorization: Lessons from Benchmarking Generative Modeling with a Large-scale Competition
Many recent developments on generative models for natural images have re...
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02/16/2021
Accurate and Clear Precipitation Nowcasting with Consecutive Attention and Rain-map Discrimination
Precipitation nowcasting is an important task for weather forecasting. M...
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10/19/2020
Cold-start Active Learning through Self-supervised Language Modeling
Active learning strives to reduce annotation costs by choosing the most ...
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09/15/2020
360-Degree Gaze Estimation in the Wild Using Multiple Zoom Scales
Gaze estimation involves predicting where the person is looking at, give...
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07/05/2020
Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels
In weakly supervised learning, unbiased risk estimator(URE) is a powerfu...
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05/24/2020
SERIL: Noise Adaptive Speech Enhancement using Regularization-based Incremental Learning
Numerous noise adaptation techniques have been proposed to address the m...
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10/29/2019
Learning from Label Proportions with Consistency Regularization
The problem of learning from label proportions (LLP) involves training c...
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09/25/2019
Attention-based Deep Tropical Cyclone Rapid Intensification Prediction
Rapid intensification (RI) is when a sudden and considerable increase in...
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12/06/2018
Active Deep Q-learning with Demonstration
Recent research has shown that although Reinforcement Learning (RL) can ...
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02/05/2018
Deep Learning with a Rethinking Structure for Multi-label Classification
Multi-label classification (MLC) is an important learning problem that e...
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12/02/2017
Compatibility Family Learning for Item Recommendation and Generation
Compatibility between items, such as clothes and shoes, is a major facto...
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08/24/2017
Active Sampling of Pairs and Points for Large-scale Linear Bipartite Ranking
Bipartite ranking is a fundamental ranking problem that learns to order ...
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11/16/2016
Cost-Sensitive Deep Learning with Layer-Wise Cost Estimation
While deep neural networks have succeeded in several visual applications...
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08/02/2016
Can Active Learning Experience Be Transferred?
Active learning is an important machine learning problem in reducing the...
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07/12/2016
Automatic Bridge Bidding Using Deep Reinforcement Learning
Bridge is among the zero-sum games for which artificial intelligence has...
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03/30/2016
Cost-Sensitive Label Embedding for Multi-Label Classification
Label embedding (LE) is an important family of multi-label classificatio...
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11/30/2015
Cost-aware Pre-training for Multiclass Cost-sensitive Deep Learning
Deep learning has been one of the most prominent machine learning techni...
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06/04/2015
Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA
We study the problem of recovering the subspace spanned by the first k p...
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06/27/2012