learning_to_recommend
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| + | {{keywords>learning to recommend}} | ||
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| + | <title classes #id> | ||
| + | Learning to Recommend | ||
| + | </title> | ||
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| + | ===== Recommended Reading ===== | ||
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| + | * [[http://irntez.ir/wp-content/uploads/2016/12/sciencedirec.pdf|Recommender systems survey]] by Bobadilla et al. (2013) | ||
| + | * [[https://link.springer.com/content/pdf/10.1007/s11257-011-9112-x.pdf|Recommender systems: from algorithms to user experience]] by Joseph Konstan and John Riedl (2012) | ||
| + | * [[https://arxiv.org/pdf/1202.1112.pdf|Recommender Systems]] by Le et al. (2012) | ||
| + | * [[https://www.comp.nus.edu.sg/~xiangnan/papers/ncf.pdf|Neural Collaborative Filtering]] by He et al. (2017) | ||
| + | * [[https://www.csie.ntu.edu.tw/~b97053/paper/Rendle2010FM.pdf|Factorization Machines]] by Steffen Rendle (2010) | ||
| + | * [[https://securityintelligence.com/factorization-machines-a-new-way-of-looking-at-machine-learning/|Factorization Machines: A New Way of Looking at Machine Learning]] by Brad Harris (2015) | ||
| + | * [[http://alicezheng.org/papers/wsdm16-cdae.pdf|Collaborative Denoising Auto-Encoders for Top-N Recommender Systems]] by Wu et al. (2016) | ||
| + | * [[https://arxiv.org/pdf/1409.2944.pdf|Collaborative Deep Learning for Recommender Systems]] by Wang et al. (2015) | ||
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