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06/15/2022
Rethinking Reinforcement Learning for Recommendation: A Prompt Perspective
Modern recommender systems aim to improve user experience. As reinforcem...
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11/05/2021
Supervised Advantage Actor-Critic for Recommender Systems
Casting session-based or sequential recommendation as reinforcement lear...
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10/31/2021
Enhancing Top-N Item Recommendations by Peer Collaboration
Deep neural networks (DNN) have achieved great success in the recommende...
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10/28/2021
Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning
Since the inception of Recommender Systems (RS), the accuracy of the rec...
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05/19/2021
On Interpretation and Measurement of Soft Attributes for Recommendation
We address how to robustly interpret natural language refinements (or cr...
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03/05/2021
Graph Convolutional Embeddings for Recommender Systems
Modern recommender systems (RS) work by processing a number of signals t...
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09/29/2020
One Person, One Model, One World: Learning Continual User Representation without Forgetting
Learning generic user representations which can then be applied to other...
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06/10/2020
Self-Supervised Reinforcement Learning forRecommender Systems
In session-based or sequential recommendation, it is important to consid...
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06/10/2020
Self-Supervised Reinforcement Learning for Recommender Systems
In session-based or sequential recommendation, it is important to consid...
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04/09/2020
Graph Highway Networks
Graph Convolution Networks (GCN) are widely used in learning graph repre...
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01/13/2020
Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation
Inductive transfer learning has had a big impact on computer vision and ...
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01/13/2020
Parameter-Efficient Transfer from Sequential Behaviors for User Profiling and Recommendation
Inductive transfer learning has greatly impacted the computer vision and...
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08/15/2018
A Simple but Hard-to-Beat Baseline for Session-based Recommendations
Convolutional Neural Networks (CNNs) models have been recently introduce...
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08/02/2018
RecoGym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising
Recommender Systems are becoming ubiquitous in many settings and take ma...
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05/10/2018
Towards a universal neural network encoder for time series
We study the use of a time series encoder to learn representations that ...
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01/04/2018
Overcoming catastrophic forgetting with hard attention to the task
Catastrophic forgetting occurs when a neural network loses the informati...
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06/13/2017
Getting deep recommenders fit: Bloom embeddings for sparse binary input/output networks
Recommendation algorithms that incorporate techniques from deep learning...
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08/06/2016
On Context-Dependent Clustering of Bandits
We investigate a novel cluster-of-bandit algorithm CAB for collaborative...
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05/02/2016
Graph Clustering Bandits for Recommendation
We investigate an efficient context-dependent clustering technique for r...
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11/21/2015
Session-based Recommendations with Recurrent Neural Networks
We apply recurrent neural networks (RNN) on a new domain, namely recomme...
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11/16/2015
A genetic algorithm to discover flexible motifs with support
Finding repeated patterns or motifs in a time series is an important uns...
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02/11/2015
