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Neural Collaborative Filtering
In recent years, deep neural networks have yielded immense success on speech recognition, computer vision and natural language processing. However, the exploration of deep neural networks onExpand
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Neural Factorization Machines for Sparse Predictive Analytics
Many predictive tasks of web applications need to model categorical variables, such as user IDs and demographics like genders and occupations. To apply standard machine learning techniques, theseExpand
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Fast Matrix Factorization for Online Recommendation with Implicit Feedback
This paper contributes improvements on both the effectiveness and efficiency of Matrix Factorization (MF) methods for implicit feedback. We highlight two critical issues of existing works. First, dueExpand
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TriRank: Review-aware Explainable Recommendation by Modeling Aspects
Most existing collaborative filtering techniques have focused on modeling the binary relation of users to items by extracting from user ratings. Aside from users' ratings, their affiliated reviewsExpand
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Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks
Factorization Machines (FMs) are a supervised learning approach that enhances the linear regression model by incorporating the second-order feature interactions. Despite effectiveness, FM can beExpand
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Neural Graph Collaborative Filtering
Learning vector representations (aka. embeddings) of users and items lies at the core of modern recommender systems. Ranging from early matrix factorization to recently emerged deep learning basedExpand
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Sequicity: Simplifying Task-oriented Dialogue Systems with Single Sequence-to-Sequence Architectures
Existing solutions to task-oriented dialogue systems follow pipeline designs which introduce architectural complexity and fragility. We propose a novel, holistic, extendable framework based on aExpand
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Attentive Moment Retrieval in Videos
In the past few years, language-based video retrieval has attracted a lot of attention. However, as a natural extension, localizing the specific video moments within a video given a description queryExpand
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Adversarial Personalized Ranking for Recommendation
Item recommendation is a personalized ranking task. To this end, many recommender systems optimize models with pairwise ranking objectives, such as the Bayesian Personalized Ranking (BPR). UsingExpand
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Outer Product-based Neural Collaborative Filtering
In this work, we contribute a new multi-layer neural network architecture named ONCF to perform collaborative filtering. The idea is to use an outer product to explicitly model the pairwiseExpand
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