Recommendation

• Articles

  • Building a Recommender System Using Embeddings
  • Embedding Everything for Anything2Anything Recommendations
  • Deep Learning with Emojis Not Math
  • Building a Recommender System Using Embeddings
  • Building a Recommender System Using Embeddings
  • Embedding Everything for Anything2Anything Recommendations
  • Deep Learning with Emojis Not Math
  • Embedding Everything for Anything2Anything Recommendations
  • Deep Learning with Emojis Not Math
  • Building a Recommender System Using Embeddings
  • Embedding Everything for Anything2Anything Recommendations
  • Deep Learning with Emojis Not Math
  • Building a Recommender System Using Embeddings
  • Towards Large Scale Training Of Autoencoders For Collaborative Filtering
  • Building a Recommender System Using Embeddings
  • Embedding Everything for Anything2Anything Recommendations
  • Deep Learning with Emojis Not Math
  • Embedding Everything for Anything2Anything Recommendations
  • Building a Recommender System Using Embeddings
  • Deep Learning with Emojis Not Math
  • Revisiting the Performance of iALS on Item Recommendation Benchmarks
  • Neural Collaborative Filtering
  • BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
  • Self-Attentive Hawkes Process
  • Behavior Sequence Transformer for E-commerce Recommendation in Alibaba
  • Variational Autoencoders for Collaborative Filtering
  • Embarrassingly Shallow Autoencoders for Sparse Data
  • Hybrid Recommender System based on Autoencoders
  • Deep Interest Network for Click-Through Rate Prediction
  • Using Word2vec for Music Recommendations
  • Embedding Everything for Anything2Anything Recommendations
  • Deep Learning with Emojis Not Math
  • Building a Recommender System Using Embeddings
  • Using Word2vec for Music Recommendations
  • Embedding Everything for Anything2Anything Recommendations
  • Deep Learning with Emojis Not Math
  • Building a Recommender System Using Embeddings
  • Embedding Everything for Anything2Anything Recommendations
  • Deep Learning with Emojis Not Math
  • Building a Recommender System Using Embeddings
  • Using Word2vec for Music Recommendations
  • Embedding Everything for Anything2Anything Recommendations
  • Deep Learning with Emojis Not Math
  • On the Difficulty of Evaluating Baselines: A Study on Recommender Systems
  • Hybrid Recommender System based on Autoencoders
  • AutoRec: Autoencoders Meet Collaborative Filtering
  • Self-Attentive Sequential Recommendation
  • Scaling Factorization Machines to Relational Data
  • Bayesian Factorization Machines
  • Challenging the Long Tail Recommendation
  • Factorization Meets the Neighborhood: a Multifaceted Collaborative Filtering Model
  • Applying Deep Learning to Related Pins
  • Applying word2vec to Recommenders and Advertising
  • Instagram’s Explore recommender system
  • Home Embeddings for Similar Home Recommendations
  • Building a Recommender System Using Embeddings
  • Deep neural networks for YouTube recommendations
  • The Illustrated Word2vec
  • Real-time Personalization using Embeddings for Search Ranking at Airbnb
  • Listing Embeddings in Search Ranking
  • Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba
  • Machine learning @ Spotify
  • Using Word2vec for Music Recommendations
  • Embedding Everything for Anything2Anything Recommendations
  • Learning Embeddings for Music Recommendation with MXNet’s Sparse API
  • How GOAT Taught a Machine to Love Sneakers
  • Wide & Deep Learning for Recommender Systems
  • Deep Learning with Emojis Not Math
  • Collaborative Filtering for Implicit Feedback Datasets
  • Applications of the conjugate gradient method for implicit feedback collaborative filtering
  • BPR: Bayesian Personalized Ranking from Implicit Feedback
  • WSABIE: Scaling Up To Large Vocabulary Image Annotation
  • Logistic Matrix Factorization for Implicit Feedback Data
  • Revisiting the Performance of iALS on Item Recommendation Benchmarks
  • Neural Collaborative Filtering
  • BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
  • Self-Attentive Hawkes Process
  • Behavior Sequence Transformer for E-commerce Recommendation in Alibaba
  • Variational Autoencoders for Collaborative Filtering
  • Towards Large Scale Training Of Autoencoders For Collaborative Filtering
  • Degenerate Feedback Loops in Recommender Systems
  • Deconvolving Feedback Loops in Recommender Systems
  • Collaborative Filtering with Temporal Dynamics
  • Enhancing VAEs for Collaborative Filtering: Flexible Priors & Gating Mechanisms
  • Embarrassingly Shallow Autoencoders for Sparse Data
  • Deep Variational Autoencoder with Shallow Parallel Path for Top-N Recommendation (VASP)
  • RecVAE: a New Variational Autoencoder for Top-N Recommendations with Implicit Feedback
  • Building a Recommender System Using Embeddings
  • Embedding Everything for Anything2Anything Recommendations
  • Deep Learning with Emojis Not Math
  • Embedding Everything for Anything2Anything Recommendations
  • Deep Learning with Emojis Not Math
  • Building a Recommender System Using Embeddings
  • Building a Recommender System Using Embeddings
  • Embedding Everything for Anything2Anything Recommendations
  • Deep Learning with Emojis Not Math
  • Building a Recommender System Using Embeddings
  • Embedding Everything for Anything2Anything Recommendations
  • Deep Learning with Emojis Not Math

• Lists

  • Papers with Code - Recsys

• Datasets

  • Criteo 1TB Click Logs
  • Kaggle Version

• Videos

  • How NVIDIA Supports Recommender Systems
  • RecSys 2020 Tutorial: Feature Engineering for Recommender Systems
  • Grandmaster Series – How to Build a Winning Deep Learning Recommender System