Difference between revisions of "User:Zeno Gantner"

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Primary developer of the [[MyMediaLite]] recommender system library.
 
Primary developer of the [[MyMediaLite]] recommender system library.
 
Co-organizer of the [[Recommender Stammtisch]] in Berlin.
 
Co-organizer of the [[Recommender Stammtisch]] in Berlin.
 
 
[[Open positions at Zalando 2020]]
 
 
  
 
[http://www.ismll.uni-hildesheim.de/personen/gantner_en.html homepage], [https://scholar.google.com/citations?user=AhVYsaoAAAAJ Google Scholar], [https://github.com/zenogantner/ GitHub], [http://stackoverflow.com/users/404824/zenog StackOverflow], [http://www.kaggle.com/users/15462/zenog Kaggle], [http://www.slideshare.net/zenogantner SlideShare]
 
[http://www.ismll.uni-hildesheim.de/personen/gantner_en.html homepage], [https://scholar.google.com/citations?user=AhVYsaoAAAAJ Google Scholar], [https://github.com/zenogantner/ GitHub], [http://stackoverflow.com/users/404824/zenog StackOverflow], [http://www.kaggle.com/users/15462/zenog Kaggle], [http://www.slideshare.net/zenogantner SlideShare]
 
  
 
== TODO ==
 
== TODO ==
  
* article about Zalando
+
* page about Fashion RecSys workshop
* article about Fashion RecSys
+
* add link to Google tutorial
* extend Person template
+
* add pages about PyTorch and TF recommendations
* extend/create dataset template
+
* marker templates for sequential recommendations, embeddings, e-commerce, CTR prediction, reinforcement learning, cold-start
 +
* extend Person template: Google Scholar, LinkedIn, SlideShare, and GitHub
 +
* extend/create dataset template (link to downloads, Google scholar search, Papers with Code)
 +
* event/conference template (individual events and conference series)
 +
* create company template (similar to persons), with github link, tech blog, Wikipedia link, corporate page, etc.
 +
* page about [[Recsperts podcast]]
  
 
== Article wishlist ==
 
== Article wishlist ==
 
* [[A/B testing]]
 
* [[A/B testing]]
 
* <s>[[active learning]]</s>
 
* <s>[[active learning]]</s>
 +
* [[approximate nearest neighbor search]]
 
* [[attribute-aware recommendation]]
 
* [[attribute-aware recommendation]]
 
* [[attribute-based recommendation]] [http://www.theatlantic.com/technology/archive/2014/01/how-netflix-reverse-engineered-hollywood/282679/]
 
* [[attribute-based recommendation]] [http://www.theatlantic.com/technology/archive/2014/01/how-netflix-reverse-engineered-hollywood/282679/]
 +
* [[autoencoder]]
 +
* [[bag-of-items]]
 
* [[bagging]]
 
* [[bagging]]
 
* [[bandit]] (-> [[multi-arm bandit]])
 
* [[bandit]] (-> [[multi-arm bandit]])
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* [[click stream]]
 
* [[click stream]]
 
* [[client-side recommendation]] (ask Chris)
 
* [[client-side recommendation]] (ask Chris)
* [[coclustering]]
 
 
* [[code recommendation]] [http://t.co/QakdUh02]
 
* [[code recommendation]] [http://t.co/QakdUh02]
 
* [[CofiRank]] (ask Markus)
 
* [[CofiRank]] (ask Markus)
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* [[data analytics]]
 
* [[data analytics]]
 
* [[data mining]]
 
* [[data mining]]
* [[decision theory]] (ask Martijn or Bart)
+
* [[decision theory]]
 +
* [[deep learning]]
 
* [[distance]]
 
* [[distance]]
 
* [[distributed computing]] (ask Sebastian)
 
* [[distributed computing]] (ask Sebastian)
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* [[FAQ for recommender system developers]]
 
* [[FAQ for recommender system developers]]
 
* [[FAQ for recommender system users]]
 
* [[FAQ for recommender system users]]
 +
* [[Fashion recommendation]], [[Fashion recommendations]]
 
* [[Filter bubble]] (ask Alan and Neal)
 
* [[Filter bubble]] (ask Alan and Neal)
 
* [[Flixster dataset]]
 
* [[Flixster dataset]]
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* [[Matchbox]] [http://research.microsoft.com/en-us/um/cambridge/projects/infernet/docs/Recommender%20System.aspx] (ask Noam)
 
* [[Matchbox]] [http://research.microsoft.com/en-us/um/cambridge/projects/infernet/docs/Recommender%20System.aspx] (ask Noam)
 
* <s>[[matrix factorization]]</s>
 
* <s>[[matrix factorization]]</s>
* [[maximum a-priori estimation]] ([[MAP]]) (ask Christoph)
+
* [[maximum a-priori estimation]] ([[MAP]])
 +
* [[maximum inner product search]]
 
* [[mean average precision]] ([[MAP]]) - link to [http://en.wikipedia.org/wiki/Information_retrieval#Mean_average_precision]
 
* [[mean average precision]] ([[MAP]]) - link to [http://en.wikipedia.org/wiki/Information_retrieval#Mean_average_precision]
 
* [[mean reciprocal rank]]
 
* [[mean reciprocal rank]]
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* <s>[[Million Song Dataset Challenge]]</s> (<s>ask Brian McFee</s>)
 
* <s>[[Million Song Dataset Challenge]]</s> (<s>ask Brian McFee</s>)
 
* [[MinHash]]
 
* [[MinHash]]
 +
* [[MLOps]
 
* [[model]]
 
* [[model]]
 
* [[monetization]]
 
* [[monetization]]
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* <s>[[MyMedia]]</s> (thank you Alan!)
 
* <s>[[MyMedia]]</s> (thank you Alan!)
 
* <s>[[NDCG]]</s>
 
* <s>[[NDCG]]</s>
 +
* [[neural networks]]
 
* [[news recommendation]]
 
* [[news recommendation]]
 
* [[offline experiment]]
 
* [[offline experiment]]
 
* [[one-class feedback]]
 
* [[one-class feedback]]
 
* [[overfitting]]
 
* [[overfitting]]
 +
* [[page composition]]
 
* [[pairwise interaction tensor factorization]] ([[PITF]], ask Steffen)
 
* [[pairwise interaction tensor factorization]] ([[PITF]], ask Steffen)
 +
* [[Papers with Code]]
 
* [[parallel factor analysis]] ([[PARAFAC]]), [[canonical decomposition]] (ask Steffen)
 
* [[parallel factor analysis]] ([[PARAFAC]]), [[canonical decomposition]] (ask Steffen)
 
* [[parallel matrix factorization]]
 
* [[parallel matrix factorization]]
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* [[scalability]] (ask Sebastian)
 
* [[scalability]] (ask Sebastian)
 
* [[semi-supervised learning]]
 
* [[semi-supervised learning]]
 +
* [[sequential recommendation]]
 
* [[serendipity]] (ask Alan, ask Ben)
 
* [[serendipity]] (ask Alan, ask Ben)
 +
* [[session-based recommendation]]
 
* [[similarity]]
 
* [[similarity]]
 
* [[SmartTypes]] [http://www.smarttypes.org/blog/graphlab_datasets]
 
* [[SmartTypes]] [http://www.smarttypes.org/blog/graphlab_datasets]
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* [[TaFeng]]
 
* [[TaFeng]]
 
* <s>[[tag]]</s> (thanks Alan)
 
* <s>[[tag]]</s> (thanks Alan)
* [[tag-aware recommendation]] (ask Karen or Leandro)
 
 
* [[Tanimoto coefficient]] --> [[Jaccard index]]
 
* [[Tanimoto coefficient]] --> [[Jaccard index]]
 
* [[Tapestry]]
 
* [[Tapestry]]
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* [[Tucker decomposition]] (ask Steffen)
 
* [[Tucker decomposition]] (ask Steffen)
 
* [[TV program recommendation]] (ask Chris)
 
* [[TV program recommendation]] (ask Chris)
* [[UMAP]]: [[UMAP 2010]], <s>[[UMAP 2011]]</s>, [[UMAP 2012]]
+
* [[UMAP]]
 
* [[user]]
 
* [[user]]
 
* [[user-item matrix]]
 
* [[user-item matrix]]
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* [[user satisfaction]]
 
* [[user satisfaction]]
 
* [[video recommendation]]
 
* [[video recommendation]]
* [[web service]]
+
* [[WSDM]]
* [[1st Workshop on Context-Aware Recommender Systems]] (ask Alan)
+
* [[Yahoo Movie Dataset]]
* [[2nd Workshop on Context-Aware Recommender Systems]] (ask Alan)
 
* [[3rd Workshop on Context-Aware Recommender Systems]] (ask Alan)
 
* [[Workshop on Context-Aware Recommender Systems]] ([[CARS]], ask Alan)
 
* [[WSDM]]: [[WSDM 2010]], [[WSDM 2011]], [[WSDM 2012]], [[WSDM 2013]]
 
* [[Yahoo Movie Dataset]] (ask Noam and Markus)
 
  
 
=== RecSys people ===
 
=== RecSys people ===
 +
 
* [[Joseph Konstan]]
 
* [[Joseph Konstan]]
 
* [[John Riedl]]
 
* [[John Riedl]]
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* [[Greg Linden]]
 
* [[Greg Linden]]
 
* [[Paul Lamere]]
 
* [[Paul Lamere]]
* <s>[[Oscar Celma]]</s>
+
* [[Ted Dunning]]
 +
* [[Sebastian Schelter]] -- https://scholar.google.de/citations?user=zCpQUukAAAAJ&hl=en -- https://github.com/sscdotopen -- https://github.com/schelterlabs
 +
* [[Ralf Herbrich]]
  
 
=== Companies ===
 
=== Companies ===
* [[aklamio]] [http://www.aklamio.com/] (ask Robert)
 
 
* [[Alleyoop]] -- [http://gigaom.com/2012/06/06/with-new-recommendation-engine-alleyoop-wants-to-be-a-tutor-for-teens]
 
* [[Alleyoop]] -- [http://gigaom.com/2012/06/06/with-new-recommendation-engine-alleyoop-wants-to-be-a-tutor-for-teens]
* [[Amazon]]
+
* [[Baidu]] -- [http://www.yichang-cs.com/jlu/WSDM21_unbiased.pdf]  
* [[Apple]] -- [http://www.edibleapple.com/2010/06/03/the-algorithms-behind-apples-itunes-genius/]
 
 
* [[BBC]] -- [http://www.bbc.co.uk/blogs/researchanddevelopment/2012/05/client-side-recommendations.shtml]
 
* [[BBC]] -- [http://www.bbc.co.uk/blogs/researchanddevelopment/2012/05/client-side-recommendations.shtml]
* [[BMAT]] (ask Oscar)
+
* [[BMAT]]
* [[Commendo]] (ask Michael)
+
* [[Bol.com]]
 +
* [[Booking.com]] [https://dl.acm.org/doi/pdf/10.1145/3383313.3412215] [https://www.researchgate.net/profile/Dmitri-Goldenberg/publication/349762238_Personalization_in_Practice_Methods_and_Applications/links/60409bf04585154e8c75323d/Personalization-in-Practice-Methods-and-Applications.pdf] [https://dl.acm.org/doi/pdf/10.1145/3383313.3412215] [https://dl.acm.org/doi/abs/10.1145/3460231.3474611] [https://dl.acm.org/doi/abs/10.1145/3511808.3557100] [https://dl.acm.org/doi/abs/10.1145/3292500.3330744] [http://www.toinebogers.com/workshops/complexrec2020/Mavridis.pdf] [https://arxiv.org/abs/2109.06723] [https://dl.acm.org/doi/abs/10.1145/3460231.3474611]
 +
* '''[[ByteDance]]''' and [[TikTok]]/[[Douyin]] (redirect), [https://newsroom.tiktok.com/en-us/how-tiktok-recommends-videos-for-you], [https://github.com/bytedance/Hammer], [https://github.com/bytedance/byteps], [https://github.com/bytedance/LargeBatchCTR], [https://dl.acm.org/doi/pdf/10.1145/3308558.3313447] [https://arxiv.org/pdf/2204.06240.pdf]
 +
* [[Commendo]]
 
* [[Directed Edge]] -- http://www.directededge.com
 
* [[Directed Edge]] -- http://www.directededge.com
 
* [[EBay]]
 
* [[EBay]]
* [[The Echo Nest]] [http://blog.echonest.com/post/33229165293/taste-profiles-go-public] [http://notes.variogr.am/post/37675885491/how-music-recommendation-works-and-doesnt-work] (ask Paul Lamere)
+
* [[The Echo Nest]] [http://blog.echonest.com/post/33229165293/taste-profiles-go-public] [http://notes.variogr.am/post/37675885491/how-music-recommendation-works-and-doesnt-work] => [[Spotify]]
* [[Facebook]] [http://mypersonality.org/wiki/doku.php?id=download_databases]
+
* [[Etsy]]
* [[Filmaster]]
+
* [[foursquare]] -- [http://engineering.foursquare.com/2011/03/22/building-a-recommendation-engine-foursquare-style/] [http://engineering.foursquare.com/2012/03/23/machine-learning-with-large-networks-of-people-and-places/]
* <s>[[Filmtipset]]</s> (thanks Alan)
+
* [[Froomle]]
* <s>[[Flixster]]</s> (thanks srbecker)
 
* [[foursquare]] -- [http://engineering.foursquare.com/2011/03/22/building-a-recommendation-engine-foursquare-style/] [http://engineering.foursquare.com/2012/03/23/machine-learning-with-large-networks-of-people-and-places/] (ask Max)
 
* [[Fredhopper]] (ask David)
 
* [[Google]]
 
* [[Gracenote]] (ask Oscar)
 
* <s>[[Gravity]]</s>
 
* <s>[[Hulu]]</s>
 
 
* [[Hunch]]
 
* [[Hunch]]
 +
* [[Ikea]]
 
* [[Kaggle]]
 
* [[Kaggle]]
* <s>[[Knewton]]</s>
+
* [[Kuaishou]] [https://en.wikipedia.org/wiki/Kuaishou], [https://arxiv.org/abs/2302.01724], [https://arxiv.org/pdf/2212.02779.pdf]
 
* [[last.fm]] -- [http://www.slideshare.net/MarkLevy/algorithms-on-hadoop-at-lastfm] [http://www.quora.com/How-does-Last-fm-compute-lists-of-similar-artists]
 
* [[last.fm]] -- [http://www.slideshare.net/MarkLevy/algorithms-on-hadoop-at-lastfm] [http://www.quora.com/How-does-Last-fm-compute-lists-of-similar-artists]
* <s>[[LinkedIn]]</s>
 
 
* [[Lumi]]
 
* [[Lumi]]
* [[Microsoft]] (ask Noam and Markus)
+
* [[Microsoft]]
* <s>[[Moviepilot]]</s> (thanks Alan)
+
* [[Myrrix]]
* [[Myrrix]] (ask Sean)
+
* [[Nokia]] -- add 2011 Buzzwords presentation
* [[Netflix]] (ask Xavier)
+
* [[Otto]]
* [[Nokia]]
 
 
* [[outbrain]] -- [http://www.conversationagent.com/2012/05/content-recommendation-engine-outbrain.html]
 
* [[outbrain]] -- [http://www.conversationagent.com/2012/05/content-recommendation-engine-outbrain.html]
 
* [[Pandora]] [http://www.fastcompany.com/1808123/tom-conrad-pandora-music-genome-project] [http://blog.pandora.com/pandora/archives/2012/10/pandora-and-art.html] (ask Tao)
 
* [[Pandora]] [http://www.fastcompany.com/1808123/tom-conrad-pandora-music-genome-project] [http://blog.pandora.com/pandora/archives/2012/10/pandora-and-art.html] (ask Tao)
* [[Plista]] (ask Andreas+Torben)
+
* [[Pinterest]] -- [https://arxiv.org/pdf/1702.07969.pdf]
 
* [[Prudsys]]
 
* [[Prudsys]]
 
* [[Recommind]] [http://www.recommind.com/]
 
* [[Recommind]] [http://www.recommind.com/]
 
* [[RichRelevance]] (ask Darren)
 
* [[RichRelevance]] (ask Darren)
 
* [[Samsung]]
 
* [[Samsung]]
* [[Scarab Research]]
 
 
* [[sematext]]
 
* [[sematext]]
 +
* [[ShareChat]] -- [https://dl.acm.org/doi/abs/10.1145/3543873.3587679]
 +
* [[Shopify]] -- ACM RecSys
 
* [[Sidebar]]
 
* [[Sidebar]]
* [[SoundCloud]] (ask Amelie and Michael)
+
* [[SoundCloud]]
* [[Spotify]] -- [http://paidcontent.org/2012/12/06/spotify-solves-discovery-by-discovering-music-aint-so-social-after-all/] [http://vimeo.com/57900625]
+
* [[Spotify]] -- [http://paidcontent.org/2012/12/06/spotify-solves-discovery-by-discovering-music-aint-so-social-after-all/] [http://vimeo.com/57900625] [https://urldefense.com/v3/__https://www.wsj.com/video/series/wsj-explains/how-spotify-knows-what-you-want-to-hear-next/E91EB935-C3EE-42FF-B41A-246614F8F1A1?mod=tech_lead_pos5__;!!Bt8RZUm9aw!9jWj6_eMhtjp9bJ_vhQae7R843i0wMfn2_BVASWQvcyzT13IedsQDJaJiyNBokkz4L2UKM0H4C8I8s4T$]
 
* [[Strands]]
 
* [[Strands]]
 
* [[TiVo]]
 
* [[TiVo]]
* [[Twitter]] [http://engineering.twitter.com/2012/03/generating-recommendations-with.html]
+
* [[Twitter]] [http://engineering.twitter.com/2012/03/generating-recommendations-with.html] [https://blog.twitter.com/engineering/en_us/topics/open-source/2023/twitter-recommendation-algorithm] [https://github.com/twitter/the-algorithm] [https://github.com/twitter/sbf]
* [[Yahoo]]
+
* '''[[Yahoo]]''' [https://people.csail.mit.edu/romer/papers/TISTRespPredAds.pdf]
* [[YooChoose]] (ask David)
+
* [[Yandex]] [https://openreview.net/pdf?id=MXfTQp8bZF]
* [[Zalando]] (ask Peter/Lina/Tobias/Ulf)
+
* [[YooChoose]]
 
* [[Zite]]
 
* [[Zite]]
  

Latest revision as of 06:39, 28 September 2023

Zeno Gantner, formerly at University of Hildesheim, Germany. Now working at Zalando in Berlin. Primary developer of the MyMediaLite recommender system library. Co-organizer of the Recommender Stammtisch in Berlin.

homepage, Google Scholar, GitHub, StackOverflow, Kaggle, SlideShare

TODO

  • page about Fashion RecSys workshop
  • add link to Google tutorial
  • add pages about PyTorch and TF recommendations
  • marker templates for sequential recommendations, embeddings, e-commerce, CTR prediction, reinforcement learning, cold-start
  • extend Person template: Google Scholar, LinkedIn, SlideShare, and GitHub
  • extend/create dataset template (link to downloads, Google scholar search, Papers with Code)
  • event/conference template (individual events and conference series)
  • create company template (similar to persons), with github link, tech blog, Wikipedia link, corporate page, etc.
  • page about Recsperts podcast

Article wishlist

RecSys people

Companies

RecSys slides, classes, etc.