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06/05/2023
Nonparametric Iterative Machine Teaching
In this paper, we consider the problem of Iterative Machine Teaching (IM...
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01/04/2022
DigNet: Digging Clues from Local-Global Interactive Graph for Aspect-level Sentiment Classification
In aspect-level sentiment classification (ASC), state-of-the-art models ...
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06/23/2021
Imitation Learning: Progress, Taxonomies and Opportunities
Imitation learning aims to extract knowledge from human experts' demonst...
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06/11/2021
Neural Optimization Kernel: Towards Robust Deep Learning
Recent studies show a close connection between neural networks (NN) and ...
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03/09/2021
Generative Transition Mechanism to Image-to-Image Translation via Encoded Transformation
In this paper, we revisit the Image-to-Image (I2I) translation problem w...
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09/15/2020
Towards Equivalent Transformation of User Preferences in Cross Domain Recommendation
Cross domain recommendation (CDR) has been proposed to tackle the data s...
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08/26/2020
Learning Robust Node Representation on Graphs
Graph neural networks (GNN), as a popular methodology for node represent...
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02/25/2020
Copy and Paste GAN: Face Hallucination from Shaded Thumbnails
Existing face hallucination methods based on convolutional neural networ...
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08/15/2019
Domain-adversarial Network Alignment
Network alignment is a critical task to a wide variety of fields. Many e...
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07/04/2019
Probabilistic CCA with Implicit Distributions
Canonical Correlation Analysis (CCA) is a classic technique for multi-vi...
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09/28/2018
Pumpout: A Meta Approach for Robustly Training Deep Neural Networks with Noisy Labels
It is challenging to train deep neural networks robustly on the industri...
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05/21/2018
Masking: A New Perspective of Noisy Supervision
It is important to learn classifiers under noisy labels due to their ubi...
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04/18/2018
Co-sampling: Training Robust Networks for Extremely Noisy Supervision
Training robust deep networks is challenging under noisy labels. Current...
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04/12/2018
Variational Composite Autoencoders
Learning in the latent variable model is challenging in the presence of ...
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11/02/2017
Deep Learning from Noisy Image Labels with Quality Embedding
There is an emerging trend to leverage noisy image datasets in many visu...
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06/27/2012
Discovering Support and Affiliated Features from Very High Dimensions
In this paper, a novel learning paradigm is presented to automatically i...
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06/27/2012