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06/12/2023
Leveraging Skill-to-Skill Supervision for Knowledge Tracing
Knowledge tracing plays a pivotal role in intelligent tutoring systems. ...
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04/21/2023
RPLKG: Robust Prompt Learning with Knowledge Graph
Large-scale pre-trained models have been known that they are transferabl...
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03/26/2023
BlackVIP: Black-Box Visual Prompting for Robust Transfer Learning
With the surge of large-scale pre-trained models (PTMs), fine-tuning the...
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02/23/2023
Causally Disentangled Generative Variational AutoEncoder
We propose a new supervised learning method for Variational AutoEncoder ...
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10/24/2022
Sharpness-aware Minimization for Worst Case Optimization
Improvement of worst group performance and generalization performance ar...
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09/14/2022
Graph Perceiver IO: A General Architecture for Graph Structured Data
Multimodal machine learning has been widely studied for the development ...
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06/17/2022
Learning Fair Representation via Distributional Contrastive Disentanglement
Learning fair representation is crucial for achieving fairness or debias...
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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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05/02/2022
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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03/08/2022
Multi-Modal Mixup for Robust Fine-tuning
Pre-trained large-scale models provide a transferable embedding, and the...
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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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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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06/12/2020
Approximate Inference for Spectral Mixture Kernel
A spectral mixture (SM) kernel is a flexible kernel used to model any st...
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06/11/2020
Implicit Kernel Attention
Attention compute the dependency between representations, and it encoura...
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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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11/15/2019
Sequential Recommendation with Relation-Aware Kernelized Self-Attention
Recent studies identified that sequential Recommendation is improved by ...
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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