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03/08/2023
Loss-Curvature Matching for Dataset Selection and Condensation
Training neural networks on a large dataset requires substantial computa...
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05/02/2022
From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model
Noisy labels are inevitable yet problematic in machine learning society....
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10/20/2021
ABC: Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learning
Existing semi-supervised learning (SSL) algorithms typically assume clas...
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06/10/2021
Score Matching Model for Unbounded Data Score
Recent advance in score-based models incorporates the stochastic differe...
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03/15/2021
Refine Myself by Teaching Myself: Feature Refinement via Self-Knowledge Distillation
Knowledge distillation is a method of transferring the knowledge from a ...
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02/15/2021
Posterior-Aided Regularization for Likelihood-Free Inference
The recent development of likelihood-free inference aims training a flex...
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11/24/2020
Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder
The problem of fair classification can be mollified if we develop a meth...
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04/13/2020
Adversarial Likelihood-Free Inference on Black-Box Generator
Generative Adversarial Network (GAN) can be viewed as an implicit estima...
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04/07/2020
Neutralizing Gender Bias in Word Embedding with Latent Disentanglement and Counterfactual Generation
Recent researches demonstrate that word embeddings, trained on the human...
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03/04/2020
