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10/25/2020
Towards Interaction Detection Using Topological Analysis on Neural Networks
Detecting statistical interactions between input features is a crucial a...
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06/29/2020
Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction
Click-Through Rate (CTR) prediction is one of the most important machine...
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06/26/2020
AutoRec: An Automated Recommender System
Realistic recommender systems are often required to adapt to ever-changi...
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12/17/2019
Multi-Channel Graph Convolutional Networks
Graph neural networks (GNN) has been demonstrated to be effective in cla...
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10/01/2019
Sub-Architecture Ensemble Pruning in Neural Architecture Search
Neural architecture search (NAS) is gaining more and more attention in r...
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09/07/2019
Auto-GNN: Neural Architecture Search of Graph Neural Networks
Graph neural networks (GNN) has been successfully applied to operate on ...
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07/21/2019
Techniques for Automated Machine Learning
Automated machine learning (AutoML) aims to find optimal machine learnin...
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06/11/2019
Coupled Variational Recurrent Collaborative Filtering
We focus on the problem of streaming recommender system and explore nove...
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01/02/2019
Multi-Label Adversarial Perturbations
Adversarial examples are delicately perturbed inputs, which aim to misle...
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06/27/2018
Efficient Neural Architecture Search with Network Morphism
While neural architecture search (NAS) has drawn increasing attention fo...
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03/19/2018
Towards Explanation of DNN-based Prediction with Guided Feature Inversion
While deep neural networks (DNN) have become an effective computational ...
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11/28/2017
