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Recurrent Neural Networks for Session-based Recommendations - Alexandros Karatzoglou

1.88K subscribers

6.9K views 7 years ago

Our research in the area started with our work on RNN’s for session-based based recommendations that was published in 2015 at ICLR. Since then we have extended the session-based RNN model with features, improved loss functions, personalization with hierarchical RNN’s, and compressed representations with bloom embeddings. I will give an overview of our work in the area over the past two years.

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These chapters are auto-generated

Intro

Session Data

Recurrent Neural Networks

Pairwise Loss Function

Sampling

Results

Training

Residual Training

Text Features

Datasets

Sampling Issues

Bloom Filters

Bering Strait

Recurrent Neural Networks for Session-based Recommendations - Alexandros Karatzoglou

105Likes

6,934Views

2018Jan 30

Our research in the area started with our work on RNN’s for session-based based recommendations that was published in 2015 at ICLR. Since then we have extended the session-based RNN model with features, improved loss functions, personalization with hierarchical RNN’s, and compressed representations with bloom embeddings. I will give an overview of our work in the area over the past two years.

Intro

Session Data

Recurrent Neural Networks

Pairwise Loss Function

Transcript

Follow along using the transcript.

Criteo Eng

1.88K subscribers