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07/15/2022
Subgroup Discovery in Unstructured Data
Subgroup discovery is a descriptive and exploratory data mining techniqu...
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06/15/2022
A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions
Clustering is a fundamental machine learning task which has been widely ...
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05/19/2022
Causal Inference from Small High-dimensional Datasets
Many methods have been proposed to estimate treatment effects with obser...
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12/14/2021
M3E2: Multi-gate Mixture-of-experts for Multi-treatment Effect Estimation
This work proposes the M3E2, a multi-task learning neural network model ...
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11/09/2021
An Interactive Visualization Tool for Understanding Active Learning
Despite recent progress in artificial intelligence and machine learning,...
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11/16/2020
CoSam: An Efficient Collaborative Adaptive Sampler for Recommendation
Sampling strategies have been widely applied in many recommendation syst...
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10/31/2020
Combining Domain-Specific Meta-Learners in the Parameter Space for Cross-Domain Few-Shot Classification
The goal of few-shot classification is to learn a model that can classif...
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09/26/2020
Domain Generalization via Semi-supervised Meta Learning
The goal of domain generalization is to learn from multiple source domai...
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03/17/2020
ParKCa: Causal Inference with Partially Known Causes
Causal Inference methods based on observational data are an alternative ...
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11/14/2019
Hierarchical Graph Pooling with Structure Learning
Graph Neural Networks (GNNs), which generalize deep neural networks to g...
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10/27/2019
An Active Approach for Model Interpretation
Model interpretation, or explanation of a machine learning classifier, a...
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07/25/2018
PADME: A Deep Learning-based Framework for Drug-Target Interaction Prediction
In silico Drug-target Interaction (DTI) prediction is an important and c...
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09/09/2016
Detecting Singleton Review Spammers Using Semantic Similarity
Online reviews have increasingly become a very important resource for co...
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04/13/2009