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04/28/2023
Earning Extra Performance from Restrictive Feedbacks
Many machine learning applications encounter a situation where model pro...
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12/13/2022
Coarse-to-Fine Contrastive Learning on Graphs
Inspired by the impressive success of contrastive learning (CL), a varie...
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12/15/2021
Taming Overconfident Prediction on Unlabeled Data from Hindsight
Minimizing prediction uncertainty on unlabeled data is a key factor to a...
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11/26/2021
TRIP: Refining Image-to-Image Translation via Rival Preferences
Relative attribute (RA), referring to the preference over two images on ...
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07/14/2021
Differential-Critic GAN: Generating What You Want by a Cue of Preferences
This paper proposes Differential-Critic Generative Adversarial Network (...
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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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05/24/2020
Multi-view Alignment and Generation in CCA via Consistent Latent Encoding
Multi-view alignment, achieving one-to-one correspondence of multi-view ...
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03/30/2020
Secure Metric Learning via Differential Pairwise Privacy
Distance Metric Learning (DML) has drawn much attention over the last tw...
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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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05/29/2019
Fast and Robust Rank Aggregation against Model Misspecification
In rank aggregation, preferences from different users are summarized int...
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05/03/2018
Multi-Context Label Embedding
Label embedding plays an important role in zero-shot learning. Side info...
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02/26/2018
