All times are given in EDT (Eastern Daylight Time, UTC -4) .<\/p>\n
9:00am:<\/strong> Introduction (chair: Luis Gal\u00e1rraga) 10:35am:<\/strong> Break 2:00pm:<\/strong> Virtual Posters Session (chair: Adrien Bibal) 3:50pm:<\/strong> Closing discussion (chair: Luis Gal\u00e1rraga)<\/p>\n","protected":false},"excerpt":{"rendered":" All times are given in EDT (Eastern Daylight Time, UTC -4) . 9:00am: Introduction (chair: Luis Gal\u00e1rraga) 9:10am: Invited Talk, Overcoming real-world challenges in AI decision support by Niels van Berkel 9:55am: First round of presentations (chair: Jos\u00e9 Oramas) 9:55am: Shortcomings of Interpretability Taxonomies for Deep Neural Networks by Anders\u2026<\/p>\n
\n9:10am:<\/strong> Invited Talk, Overcoming real-world challenges in AI decision support<\/em> by Niels van Berkel
\n9:55am:<\/strong> First round of presentations (chair: Jos\u00e9 Oramas)<\/p>\n\n
9:55am:<\/strong> Shortcomings of Interpretability Taxonomies for Deep Neural Networks<\/em> by Anders S\u00f8gaard
\n<\/s> [paper<\/a>]<\/li>\n10:10am:<\/strong><\/s>9:55am:<\/strong> Interpretability in Activation Space Analysis of Transformers<\/em>: A Focused Survey by Soniya Vijayakumar [slides<\/a>][paper<\/a>]<\/li>\n10:20am:<\/strong><\/s>10:15am:<\/strong> Explainer Divergence Score (EDS): Some Post-Hoc Explanations May be Effective for Detecting Unknown Spurious Correlations<\/em> by Shea Cardozo and Gabriel Islas Montero [paper<\/a>][slides<\/a>][poster<\/a>]<\/li>\n<\/ul>\n
\n11:00am:<\/strong> Invited Talk, White Coat, Black Box: Mitigating Shortcuts in ML for Health<\/em> by Jenna Wiens (chair: Jos\u00e9 Oramas)
\n11:30am:<\/strong> Invited Talk,\u00a0Explainability in Graph Neural Networks<\/em> by Alexandre Duval [slides<\/a>] (chair: Luis Gal\u00e1rraga)
\n12:00pm:<\/strong> Lunch Break
\n1:30pm:<\/strong> Poster Spotlights (chair: Julien Delaunay)<\/p>\n\n
\n2:50pm:<\/strong> Second round of presentations (chair: Julien Delaunay)<\/p>\n\n
![poster<\/a>]<\/li>\n<\/ul>\n10:35am:<\/strong> Break\n11:00am:<\/strong> Invited Talk, White Coat, Black Box: Mitigating Shortcuts in ML for Health<\/em> by Jenna Wiens (chair: Jos\u00e9 Oramas)\n11:30am:<\/strong> Invited Talk,\u00a0Explainability in Graph Neural Networks<\/em> by Alexandre Duval [slides<\/a>] (chair: Luis Gal\u00e1rraga)\n12:00pm:<\/strong> Lunch Break\n1:30pm:<\/strong> Poster Spotlights (chair: Julien Delaunay)<\/p>\n\n1:30pm:<\/strong> Explaining Convolutional Neural Networks by Tagging Filters<\/em> by Michael F\u00e4rber<\/li>\n1:35pm:<\/strong> Offensive Text Detection Across Languages and Datasets Using Rule-based and Hybrid Methods<\/em> by Kinga Andrea G\u00e9mes<\/li>\n1:40pm:<\/strong> Explainability for Misinformation in Financial Statements<\/em> by Sushodhan Vaishampayan<\/li>\n1:45pm:<\/strong> Finding Components of a Good Accuracy with XAI!<\/em> by Benjamin Chamand and Olivier Risser-Maroix [paper<\/a>]<\/li>\n1:50pm:<\/strong> Want robust explanations? Get smoother predictions first<\/em> by Deddy Jobson [paper<\/a>][poster<\/a>]<\/li>\n<\/ul>\n2:00pm:<\/strong> Virtual Posters Session (chair: Adrien Bibal)\n2:50pm:<\/strong> Second round of presentations (chair: Julien Delaunay)<\/p>\n\n2:50pm:<\/strong> Privacy and Transparency in Graph Machine Learning: A Unified Perspective<\/em> (Position Paper) by Megha Khosla [slides<\/a>] [paper<\/a>]<\/li>\n3:10pm:<\/strong> Globally Local and Fast Explanations of t-SNE-like Non-linear Embeddings<\/em> by Pierre Lambert<\/li>\n3:30pm:<\/strong> Fast Optimization of Weighted Sparse Decision Trees for use in Optimal Treatment Regimes and Optimal Policy Design<\/em> by Ali Behrouz [slides<\/a>][paper<\/a>]<\/li>\n<\/ul>\n3:50pm:<\/strong> Closing discussion (chair: Luis Gal\u00e1rraga)<\/p>\n","protected":false},"excerpt":{"rendered":"All times are given in EDT (Eastern Daylight Time, UTC -4) . 9:00am: Introduction (chair: Luis Gal\u00e1rraga) 9:10am: Invited Talk, Overcoming real-world challenges in AI decision support by Niels van Berkel 9:55am: First round of presentations (chair: Jos\u00e9 Oramas) 9:55am: Shortcomings of Interpretability Taxonomies for Deep Neural Networks by Anders\u2026<\/p>\n Continue reading<\/span><\/i><\/a> <\/p>\n","protected":false},"author":1481,"featured_media":0,"parent":359,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-282","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/project.inria.fr\/aimlai\/wp-json\/wp\/v2\/pages\/282","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/project.inria.fr\/aimlai\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/project.inria.fr\/aimlai\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/aimlai\/wp-json\/wp\/v2\/users\/1481"}],"replies":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/aimlai\/wp-json\/wp\/v2\/comments?post=282"}],"version-history":[{"count":37,"href":"https:\/\/project.inria.fr\/aimlai\/wp-json\/wp\/v2\/pages\/282\/revisions"}],"predecessor-version":[{"id":353,"href":"https:\/\/project.inria.fr\/aimlai\/wp-json\/wp\/v2\/pages\/282\/revisions\/353"}],"up":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/aimlai\/wp-json\/wp\/v2\/pages\/359"}],"wp:attachment":[{"href":"https:\/\/project.inria.fr\/aimlai\/wp-json\/wp\/v2\/media?parent=282"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}](\"https:\/\/project.inria.fr\/aimlai\/files\/2022\/10\/poster_paper9_aimlai_cikm22.png\"){kind=link}
![poster<\/a>]<\/li>\n<\/ul>\n2:00pm:<\/strong> Virtual Posters Session (chair: Adrien Bibal)\n2:50pm:<\/strong> Second round of presentations (chair: Julien Delaunay)<\/p>\n\n2:50pm:<\/strong> Privacy and Transparency in Graph Machine Learning: A Unified Perspective<\/em> (Position Paper) by Megha Khosla [slides<\/a>] [paper<\/a>]<\/li>\n3:10pm:<\/strong> Globally Local and Fast Explanations of t-SNE-like Non-linear Embeddings<\/em> by Pierre Lambert<\/li>\n3:30pm:<\/strong> Fast Optimization of Weighted Sparse Decision Trees for use in Optimal Treatment Regimes and Optimal Policy Design<\/em> by Ali Behrouz [slides<\/a>][paper<\/a>]<\/li>\n<\/ul>\n3:50pm:<\/strong> Closing discussion (chair: Luis Gal\u00e1rraga)<\/p>\n","protected":false},"excerpt":{"rendered":"All times are given in EDT (Eastern Daylight Time, UTC -4) . 9:00am: Introduction (chair: Luis Gal\u00e1rraga) 9:10am: Invited Talk, Overcoming real-world challenges in AI decision support by Niels van Berkel 9:55am: First round of presentations (chair: Jos\u00e9 Oramas) 9:55am: Shortcomings of Interpretability Taxonomies for Deep Neural Networks by Anders\u2026<\/p>\n Continue reading<\/span><\/i><\/a> <\/p>\n","protected":false},"author":1481,"featured_media":0,"parent":359,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-282","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/project.inria.fr\/aimlai\/wp-json\/wp\/v2\/pages\/282","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/project.inria.fr\/aimlai\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/project.inria.fr\/aimlai\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/aimlai\/wp-json\/wp\/v2\/users\/1481"}],"replies":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/aimlai\/wp-json\/wp\/v2\/comments?post=282"}],"version-history":[{"count":37,"href":"https:\/\/project.inria.fr\/aimlai\/wp-json\/wp\/v2\/pages\/282\/revisions"}],"predecessor-version":[{"id":353,"href":"https:\/\/project.inria.fr\/aimlai\/wp-json\/wp\/v2\/pages\/282\/revisions\/353"}],"up":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/aimlai\/wp-json\/wp\/v2\/pages\/359"}],"wp:attachment":[{"href":"https:\/\/project.inria.fr\/aimlai\/wp-json\/wp\/v2\/media?parent=282"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}](\"https:\/\/project.inria.fr\/aimlai\/files\/2022\/10\/poster_paper3_aimlai_cikm22.png\"){kind=link}