https://recsyswiki.com/index.php?action=history&feed=atom&title=Criteo 2026-04-18T10:08:18Z Revision history for this page on the wiki MediaWiki 1.34.2 https://recsyswiki.com/index.php?title=Criteo&diff=2655&oldid=prev 2023-04-27T14:35:12Z

<p>add paper Field-aware Factorization Machines in a Real-world Online Advertising System</p> <table class="diff diff-contentalign-left" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en"> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 14:35, 27 April 2023</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l9" >Line 9:</td> <td colspan="2" class="diff-lineno">Line 9:</td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># {{bandits}} [https://www.kdd.org/kdd2020/accepted-papers/view/blob-a-probabilistic-model-for-recommendation-that-combines-organic-and-ban BLOB: A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals], [[KDD 2020]]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># {{bandits}} [https://www.kdd.org/kdd2020/accepted-papers/view/blob-a-probabilistic-model-for-recommendation-that-combines-organic-and-ban BLOB: A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals], [[KDD 2020]]</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># [https://dl.acm.org/doi/10.1145/3240323.3240360 Causal embeddings for recommendation], [[RecSys 2018]] (best long paper award)</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># [https://dl.acm.org/doi/10.1145/3240323.3240360 Causal embeddings for recommendation], [[RecSys 2018]] (best long paper award)</div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># {{ads}} [https://arxiv.org/pdf/1701.04099.pdf Field-aware Factorization Machines in a Real-world Online Advertising System], [[WWW 2017]]</ins></div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># {{ads}} Olivier Chapelle: [http://wnzhang.net/share/rtb-papers/ctr-bid.pdf Offline Evaluation of Response Prediction in Online Advertising Auctions], [[WWW 2015]]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># {{ads}} Olivier Chapelle: [http://wnzhang.net/share/rtb-papers/ctr-bid.pdf Offline Evaluation of Response Prediction in Online Advertising Auctions], [[WWW 2015]]</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># {{experimentation}} [https://arxiv.org/pdf/1801.07030.pdf Offline A/B testing for Recommender Systems]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># {{experimentation}} [https://arxiv.org/pdf/1801.07030.pdf Offline A/B testing for Recommender Systems]</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[Category:Company]]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[Category:Company]]</div></td></tr> <!-- diff cache key recsys_mw-mw_:diff::1.12:old-2623:rev-2655 --> </table>

Zeno Gantner https://recsyswiki.com/index.php?title=Criteo&diff=2623&oldid=prev 2022-12-02T23:42:04Z

<p>Created page with &quot;&#039;&#039;&#039;Criteo&#039;&#039;&#039; is a French online advertisement company. == Software == # [https://github.com/criteo-research/reco-gym reco-gym] == Papers == # {{bandits}} [https://www.kdd....&quot;</p> <p><b>New page</b></p><div>'''Criteo''' is a French online advertisement company.<br /> <br /> == Software ==<br /> <br /> # [https://github.com/criteo-research/reco-gym reco-gym]<br /> <br /> == Papers ==<br /> <br /> # {{bandits}} [https://www.kdd.org/kdd2020/accepted-papers/view/blob-a-probabilistic-model-for-recommendation-that-combines-organic-and-ban BLOB: A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals], [[KDD 2020]]<br /> # [https://dl.acm.org/doi/10.1145/3240323.3240360 Causal embeddings for recommendation], [[RecSys 2018]] (best long paper award)<br /> # {{ads}} Olivier Chapelle: [http://wnzhang.net/share/rtb-papers/ctr-bid.pdf Offline Evaluation of Response Prediction in Online Advertising Auctions], [[WWW 2015]]<br /> # {{experimentation}} [https://arxiv.org/pdf/1801.07030.pdf Offline A/B testing for Recommender Systems]<br /> <br /> [[Category:Company]]</div>

Zeno Gantner