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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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11/28/2022
Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models
While the success of diffusion models has been witnessed in various doma...
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06/15/2022
Unknown-Aware Domain Adversarial Learning for Open-Set Domain Adaptation
Open-Set Domain Adaptation (OSDA) assumes that a target domain contains ...
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05/27/2022
Maximum Likelihood Training of Implicit Nonlinear Diffusion Models
Whereas diverse variations of diffusion models exist, expanding the line...
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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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03/07/2022
Automatic Calibration Framework of Agent-Based Models for Dynamic and Heterogeneous Parameters
Agent-based models (ABMs) highlight the importance of simulation validat...
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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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11/09/2020
LADA: Look-Ahead Data Acquisition via Augmentation for Active Learning
Active learning effectively collects data instances for training deep le...
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10/15/2020
Sequential Likelihood-Free Inference with Implicit Surrogate Proposal
Bayesian inference without the access of likelihood, called likelihood-f...
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06/11/2020
Implicit Kernel Attention
Attention compute the dependency between representations, and it encoura...
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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
Generalized Gumbel-Softmax Gradient Estimator for Various Discrete Random Variables
Estimating the gradients of stochastic nodes is one of the crucial resea...
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11/15/2019
Sequential Recommendation with Relation-Aware Kernelized Self-Attention
Recent studies identified that sequential Recommendation is improved by ...
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08/09/2019
Automatic Calibration of Dynamic and Heterogeneous Parameters in Agent-based Model
While simulations have been utilized in diverse domains, such as urban g...
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05/25/2019
Bivariate Beta LSTM
Long Short-Term Memory (LSTM) infers the long term dependency through a ...
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04/26/2019
Neural Ideal Point Estimation Network
Understanding politics is challenging because the politics take the infl...
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04/26/2019
Hierarchical Context enabled Recurrent Neural Network for Recommendation
A long user history inevitably reflects the transitions of personal inte...
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04/22/2019
Adversarial Dropout for Recurrent Neural Networks
Successful application processing sequential data, such as text and spee...
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01/28/2019
Hierarchically Clustered Representation Learning
The joint optimization of representation learning and clustering in the ...
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01/09/2019
Dirichlet Variational Autoencoder
This paper proposes Dirichlet Variational Autoencoder (DirVAE) using a D...
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07/12/2017