Deep Learning and Recommenders

papers / frameworks / libraries

Main Papers

• A Multi-View Deep Learning Approach for Cross Domain User Modeling in Recommendation Systems (Link 2 ) - WWW2015

• Collaborative Deep Learning for Recommender Systems Link 2 - KDD2015

• Deep Collaborative Filtering via Marginalized Denoising Auto-encoder Link 2 - CIKM2015

• Session-base Recommendations with Recurrent Neural Networks - ICLR2016

• Meta-Prod2Vec - Product Embeddings Using Side-Information for Recommendation - RecSys2016

• Convolutional Matrix Factorization for Document Context-Aware Recommendation - RecSys2016

• Parallel Recurrent Neural Network Architectures for Feature-rich Session-based Recommendations - RecSys2016

• Conversational Recommendation System with Unsupervised Learning - RecSys2016

• Ask the GRU: Multi-task Learning for Deep Text Recommendations ( Link 2 ) - RecSys2016

• Deep Auto-Encoding for Context-Aware Inference of Preferred Items' Categories RecSys 2016 Poster

• Improved Recurrent Neural Networks for Session-based Recommendations - DLRS2016

• Neural Autoregressive Collaborative Filtering for Implicit Feedback - DLRS2016

• Wide & Deep Learning for Recommender Systems Link 2 - DLRS2016

• Hybrid Recommender System based on Autoencoders Link 2 - DLRS2016

• Infusing Collaborative Recommenders with Distributed Representations Link 2 - DLRS2016

• Recurrent Coevolutionary Latent Feature Processes for Continuous-Time Recommendation Link 2 - DLRS2016

• Collaborative Denoising Auto-Encoders for Top-N Recommender Systems Link 2 - WSDM2016

• Collaborative Knowledge Base Embedding for Recommender Systems Link 2 - KDD2016

• Multi-Rate Deep Learning for Temporal Recommendation Link 2 - SIGIR2016

• Collaborative Deep Ranking: A Hybrid Pair-Wise Recommendation Algorithm with Implicit Feedback Link 2 - PAKDD2016

• Recurrent Latent Variable Networks for Session-Based Recommendation - DLRS2017

• Contextual Sequence Modeling for Recommendation with Recurrent Neural Networks - DLRS2017

• Inter-Session Modeling for Session-Based Recommendation - DLRS2017

• Specializing Joint Representations for the task of Product Recommendation - DLRS2017

• AutoSVD++: An E�icient Hybrid Collaborative Filtering Model via Contractive Auto-encoders Link 2 - SIGIR2017

• Neural Collaborative Filtering - WWW2017

• Localy Connected Deep Learning Framework for Industrial-scale Recommender Systems - WWW2017 Companion

• Recurrent Recommender Networks - WSDM2017

• Neural Survival Recommender - WSDM2017

• Joint Deep Modeling of Users and Items Using Reviews for Recommendation - WSDM2017

• Deep Coevolutionary Network: Embedding User and Item Features for Recommendation KDD2017

• Dynamic Attention Deep Model for Article Recommendation by Learning Human Editors' Demonstration Link 2 - KDD2017

• Bridging Collaborative Filtering and Semi-Supervised Learning: A Neural Approach for POI Recommendation Link 2 - KDD2017

• TransNets: Learning to Transform for Recommendation - RecSys2017

• Sequential User-based Recurrent Neural Network Recommendations - RecSys2017

• Collaborative filtering and deep learning based recommendation system for cold start items Link 2 - Exp.Sys.App, 2017

• Deep hybrid recommender systems via exploiting document context and statistics of items - Inf.Sci, 2017

• Representation Learning of Users and Items for Review Rating Prediction Using Attention-based Convolutional Neural Network - MLRec2017 (In conjunction with SDM2017)

• Understanding Consumer Behavior with Recurrent Neural Networks - MLRec2017 (In conjunction with SDM2017)

• Relational Deep Learning: A Deep Latent Variable Model for Link Prediction - AAAI2017

• A Deep Architecture for Content-based Recommendations Exploiting Recurrent Neural Networks - UMAP2017

• Trust-aware Collaborative Denoising Auto-Encoder for Top-N Recommendation - Arxiv 2017

• Deep Learning based Recommender System: A Survey and New Perspectives - Arxiv 2017

Relevant Papers (but somewhat not necessarily focused on recommendation task)

• Natural-Parameter Networks: A Class of Probabilistic Neural Networks - NIPS2016
• Towards Bayesian Deep Learning: A Framework and Some Existing Methods Link 2 - IEEE TKDE, 2016
• On Sampling Strategies for Neural Network-based Collaborative Filtering - KDD2017
• Generative Temporal Models with Memory - Arxiv, 2017 (Deepmind)