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[Airbnb Embedding] Real-time Personalization using Embeddings for Search Ranking at Airbnb (Airbnb 2018).pdf
[Airbnb Embedding] Real-time Personalization using Embeddings for Search Ranking at Airbnb (Airbnb 2018).pdf
[Alibaba Embedding] Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba (Alibaba 2018).pdf
[Alibaba Embedding] Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba (Alibaba 2018).pdf
[Graph Embedding] DeepWalk- Online Learning of Social Representations (SBU 2014).pdf
[Graph Embedding] DeepWalk- Online Learning of Social Representations (SBU 2014).pdf
[Item2Vec] Item2Vec-Neural Item Embedding for Collaborative Filtering (Microsoft 2016).pdf
[Item2Vec] Item2Vec-Neural Item Embedding for Collaborative Filtering (Microsoft 2016).pdf
[LINE] LINE - Large-scale Information Network Embedding (MSRA 2015).pdf
[LINE] LINE - Large-scale Information Network Embedding (MSRA 2015).pdf
[LSH] Locality-Sensitive Hashing for Finding Nearest Neighbors (IEEE 2008).pdf
[LSH] Locality-Sensitive Hashing for Finding Nearest Neighbors (IEEE 2008).pdf
[Negative Sampling] Word2vec Explained Negative-Sampling Word-Embedding Method (2014).pdf
[Negative Sampling] Word2vec Explained Negative-Sampling Word-Embedding Method (2014).pdf
[Node2vec] Node2vec - Scalable Feature Learning for Networks (Stanford 2016).pdf
[Node2vec] Node2vec - Scalable Feature Learning for Networks (Stanford 2016).pdf
[SDNE] Structural Deep Network Embedding (THU 2016).pdf
[SDNE] Structural Deep Network Embedding (THU 2016).pdf
[Word2Vec] Distributed Representations of Words and Phrases and their Compositionality (Google 2013).pdf
[Word2Vec] Distributed Representations of Words and Phrases and their Compositionality (Google 2013).pdf
[Word2Vec] Efficient Estimation of Word Representations in Vector Space (Google 2013).pdf
[Word2Vec] Efficient Estimation of Word Representations in Vector Space (Google 2013).pdf
[Word2Vec] Word2vec Parameter Learning Explained (UMich 2016).pdf
[Word2Vec] Word2vec Parameter Learning Explained (UMich 2016).pdf
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