際際滷shows by User: ntoutsi / http://www.slideshare.net/images/logo.gif 際際滷shows by User: ntoutsi / Tue, 06 Apr 2021 06:05:59 GMT 際際滷Share feed for 際際滷shows by User: ntoutsi AAISI AI Colloquium 30/3/2021: Bias in AI systems /slideshow/aaisi-ai-colloquium-3032021-bias-in-ai-systems/245762020 aaisi-210406060600
An overview of bias in AI systems and the many steps in the data-driven learning pipeline contributing to/aggravating the bias problem.]]>
An overview of bias in AI systems and the many steps in the data-driven learning pipeline contributing to/aggravating the bias problem.]]> Tue, 06 Apr 2021 06:05:59 GMT /slideshow/aaisi-ai-colloquium-3032021-bias-in-ai-systems/245762020 ntoutsi@slideshare.net(ntoutsi) AAISI AI Colloquium 30/3/2021: Bias in AI systems ntoutsi An overview of bias in AI systems and the many steps in the data-driven learning pipeline contributing to/aggravating the bias problem. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/aaisi-210406060600-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> An overview of bias in AI systems and the many steps in the data-driven learning pipeline contributing to/aggravating the bias problem.
AAISI AI Colloquium 30/3/2021: Bias in AI systems from Eirini Ntoutsi
]]> 195 0 https://cdn.slidesharecdn.com/ss_thumbnails/aaisi-210406060600-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Fairness-aware learning: From single models to sequential ensemble learning and learning over data streams /ntoutsi/fairnessaware-learning-from-single-models-to-sequential-ensemble-learning-and-learning-over-data-streams recsgrouptampere-210220154820
An overview of fairness-aware learning: from batch-learning with single models to batch-learning with sequential ensembles and to fairness-aware learning over non-stationary data streams ]]>
An overview of fairness-aware learning: from batch-learning with single models to batch-learning with sequential ensembles and to fairness-aware learning over non-stationary data streams ]]> Sat, 20 Feb 2021 15:48:19 GMT /ntoutsi/fairnessaware-learning-from-single-models-to-sequential-ensemble-learning-and-learning-over-data-streams ntoutsi@slideshare.net(ntoutsi) Fairness-aware learning: From single models to sequential ensemble learning and learning over data streams ntoutsi An overview of fairness-aware learning: from batch-learning with single models to batch-learning with sequential ensembles and to fairness-aware learning over non-stationary data streams <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/recsgrouptampere-210220154820-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> An overview of fairness-aware learning: from batch-learning with single models to batch-learning with sequential ensembles and to fairness-aware learning over non-stationary data streams
Fairness-aware learning: From single models to sequential ensemble learning and learning over data streams from Eirini Ntoutsi
]]> 55 0 https://cdn.slidesharecdn.com/ss_thumbnails/recsgrouptampere-210220154820-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Bias in AI-systems: A multi-step approach /slideshow/bias-in-aisystems-a-multistep-approach/241221191 nl4xai-210112061031
Invited talk on fairness in AI systems at the 2nd Workshop on Interactive Natural Language Technology for Explainable AI co-located with the International Conference on Natural Language Generation, 18/12/2020.]]>
Invited talk on fairness in AI systems at the 2nd Workshop on Interactive Natural Language Technology for Explainable AI co-located with the International Conference on Natural Language Generation, 18/12/2020.]]> Tue, 12 Jan 2021 06:10:30 GMT /slideshow/bias-in-aisystems-a-multistep-approach/241221191 ntoutsi@slideshare.net(ntoutsi) Bias in AI-systems: A multi-step approach ntoutsi Invited talk on fairness in AI systems at the 2nd Workshop on Interactive Natural Language Technology for Explainable AI co-located with the International Conference on Natural Language Generation, 18/12/2020. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/nl4xai-210112061031-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Invited talk on fairness in AI systems at the 2nd Workshop on Interactive Natural Language Technology for Explainable AI co-located with the International Conference on Natural Language Generation, 18/12/2020.
Bias in AI-systems: A multi-step approach from Eirini Ntoutsi
]]> 510 0 https://cdn.slidesharecdn.com/ss_thumbnails/nl4xai-210112061031-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Sentiment Analysis of Social Media Content: A multi-tool for listening to your audience and developing sentimental content strategies. /slideshow/sentiment-analysis-of-social-media-content-a-multitool-for-listening-to-your-audience-and-developing-sentimental-content-strategies-126983354/126983354 presentationeirinieumade4all-181230143217
Presentation at the EU Made 4all meeting in Hannover, 29/9/2017]]>
Presentation at the EU Made 4all meeting in Hannover, 29/9/2017]]> Sun, 30 Dec 2018 14:32:16 GMT /slideshow/sentiment-analysis-of-social-media-content-a-multitool-for-listening-to-your-audience-and-developing-sentimental-content-strategies-126983354/126983354 ntoutsi@slideshare.net(ntoutsi) Sentiment Analysis of Social Media Content: A multi-tool for listening to your audience and developing sentimental content strategies. ntoutsi Presentation at the EU Made 4all meeting in Hannover, 29/9/2017 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/presentationeirinieumade4all-181230143217-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Presentation at the EU Made 4all meeting in Hannover, 29/9/2017
Sentiment Analysis of Social Media Content: A multi-tool for listening to your audience and developing sentimental content strategies. from Eirini Ntoutsi
]]> 358 2 https://cdn.slidesharecdn.com/ss_thumbnails/presentationeirinieumade4all-181230143217-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 A Machine Learning Primer, /slideshow/a-machine-learning-primer/126982305 presentationeirinintoutsiama-181230141230
Presentation at AMA (Applied Machine Learning) industrial event on 13/4/2018]]>
Presentation at AMA (Applied Machine Learning) industrial event on 13/4/2018]]> Sun, 30 Dec 2018 14:12:30 GMT /slideshow/a-machine-learning-primer/126982305 ntoutsi@slideshare.net(ntoutsi) A Machine Learning Primer, ntoutsi Presentation at AMA (Applied Machine Learning) industrial event on 13/4/2018 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/presentationeirinintoutsiama-181230141230-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Presentation at AMA (Applied Machine Learning) industrial event on 13/4/2018
A Machine Learning Primer, from Eirini Ntoutsi
]]> 231 3 https://cdn.slidesharecdn.com/ss_thumbnails/presentationeirinintoutsiama-181230141230-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 (Machine)Learning with limited labels(Machine)Learning with limited labels(Machine)Learning with limited labels( /slideshow/machinelearning-with-limited-labelsmachinelearning-with-limited-labelsmachinelearning-with-limited-labels/126056011 17-181216233405
(Machine)Learning with limited labels(Machine)Learning with limited labels(Machine)Learning with limited labels, Alexandria Workshop 2017]]>
(Machine)Learning with limited labels(Machine)Learning with limited labels(Machine)Learning with limited labels, Alexandria Workshop 2017]]> Sun, 16 Dec 2018 23:34:04 GMT /slideshow/machinelearning-with-limited-labelsmachinelearning-with-limited-labelsmachinelearning-with-limited-labels/126056011 ntoutsi@slideshare.net(ntoutsi) (Machine)Learning with limited labels(Machine)Learning with limited labels(Machine)Learning with limited labels( ntoutsi (Machine)Learning with limited labels(Machine)Learning with limited labels(Machine)Learning with limited labels, Alexandria Workshop 2017 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/17-181216233405-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> (Machine)Learning with limited labels(Machine)Learning with limited labels(Machine)Learning with limited labels, Alexandria Workshop 2017
(Machine)Learning with limited labels(Machine)Learning with limited labels(Machine)Learning with limited labels( from Eirini Ntoutsi
]]> 399 1 https://cdn.slidesharecdn.com/ss_thumbnails/17-181216233405-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Redundancies in Data and their E鐃ect on the Evaluation of Recommendation Systems: A Case Study on the Amazon Reviews Datasets /slideshow/redundancies-in-data-and-their-eect-on-the-evaluation-of-recommendation-systems-a-case-study-on-the-amazon-reviews-datasets/126055948 17-181216233233
Redundancies in Data and their Eect on the Evaluation of Recommendation Systems: A Case Study on the Amazon Reviews Datasets, SDM 2017]]>
Redundancies in Data and their Eect on the Evaluation of Recommendation Systems: A Case Study on the Amazon Reviews Datasets, SDM 2017]]> Sun, 16 Dec 2018 23:32:33 GMT /slideshow/redundancies-in-data-and-their-eect-on-the-evaluation-of-recommendation-systems-a-case-study-on-the-amazon-reviews-datasets/126055948 ntoutsi@slideshare.net(ntoutsi) Redundancies in Data and their E鐃ect on the Evaluation of Recommendation Systems: A Case Study on the Amazon Reviews Datasets ntoutsi Redundancies in Data and their E鐃ect on the Evaluation of Recommendation Systems: A Case Study on the Amazon Reviews Datasets, SDM 2017 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/17-181216233233-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Redundancies in Data and their E鐃ect on the Evaluation of Recommendation Systems: A Case Study on the Amazon Reviews Datasets, SDM 2017
Redundancies in Data and their E ect on the Evaluation of Recommendation Systems: A Case Study on the Amazon Reviews Datasets from Eirini Ntoutsi
]]> 69 1 https://cdn.slidesharecdn.com/ss_thumbnails/17-181216233233-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Density-based Projected Clustering over High Dimensional Data Streams /slideshow/densitybased-projected-clustering-over-high-dimensional-data-streams/126055418 12-181216232114
Density-based Projected Clustering over High Dimensional Data Streams, SDM 2012]]>
Density-based Projected Clustering over High Dimensional Data Streams, SDM 2012]]> Sun, 16 Dec 2018 23:21:14 GMT /slideshow/densitybased-projected-clustering-over-high-dimensional-data-streams/126055418 ntoutsi@slideshare.net(ntoutsi) Density-based Projected Clustering over High Dimensional Data Streams ntoutsi Density-based Projected Clustering over High Dimensional Data Streams, SDM 2012 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/12-181216232114-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Density-based Projected Clustering over High Dimensional Data Streams, SDM 2012
Density-based Projected Clustering over High Dimensional Data Streams from Eirini Ntoutsi
]]> 73 1 https://cdn.slidesharecdn.com/ss_thumbnails/12-181216232114-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Density Based Subspace Clustering Over Dynamic Data /slideshow/density-based-subspace-clustering-over-dynamic-data/126055322 11-181216231951
Density Based Subspace Clustering Over Dynamic Data, SSDBM 2011]]>
Density Based Subspace Clustering Over Dynamic Data, SSDBM 2011]]> Sun, 16 Dec 2018 23:19:51 GMT /slideshow/density-based-subspace-clustering-over-dynamic-data/126055322 ntoutsi@slideshare.net(ntoutsi) Density Based Subspace Clustering Over Dynamic Data ntoutsi Density Based Subspace Clustering Over Dynamic Data, SSDBM 2011 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/11-181216231951-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Density Based Subspace Clustering Over Dynamic Data, SSDBM 2011
Density Based Subspace Clustering Over Dynamic Data from Eirini Ntoutsi
]]> 115 1 https://cdn.slidesharecdn.com/ss_thumbnails/11-181216231951-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Summarizing Cluster Evolution in Dynamic Environments /slideshow/summarizing-cluster-evolution-in-dynamic-environments/126055266 11-181216231856
Summarizing Cluster Evolution in Dynamic Environments, ICSSA 2011]]>
Summarizing Cluster Evolution in Dynamic Environments, ICSSA 2011]]> Sun, 16 Dec 2018 23:18:56 GMT /slideshow/summarizing-cluster-evolution-in-dynamic-environments/126055266 ntoutsi@slideshare.net(ntoutsi) Summarizing Cluster Evolution in Dynamic Environments ntoutsi Summarizing Cluster Evolution in Dynamic Environments, ICSSA 2011 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/11-181216231856-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Summarizing Cluster Evolution in Dynamic Environments, ICSSA 2011
Summarizing Cluster Evolution in Dynamic Environments from Eirini Ntoutsi
]]> 78 1 https://cdn.slidesharecdn.com/ss_thumbnails/11-181216231856-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Cluster formation over huge volatile robotic data /ntoutsi/cluster-formation-over-huge-volatile-robotic-data 11-181216231535
Revealing cluster formation over huge volatile robotic data, DDDM workshop co-located with ICDM 2011.]]>
Revealing cluster formation over huge volatile robotic data, DDDM workshop co-located with ICDM 2011.]]> Sun, 16 Dec 2018 23:15:35 GMT /ntoutsi/cluster-formation-over-huge-volatile-robotic-data ntoutsi@slideshare.net(ntoutsi) Cluster formation over huge volatile robotic data ntoutsi Revealing cluster formation over huge volatile robotic data, DDDM workshop co-located with ICDM 2011. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/11-181216231535-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Revealing cluster formation over huge volatile robotic data, DDDM workshop co-located with ICDM 2011.
Cluster formation over huge volatile robotic data from Eirini Ntoutsi
]]> 92 1 https://cdn.slidesharecdn.com/ss_thumbnails/11-181216231535-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Discovering and Monitoring Product Features and the Opinions on them with OPINSTREAM /slideshow/enopinionated-streamshdms2014presented-engl/41151944 en-141105062130-conversion-gate02
Opinion stream mining encompasses methods for monitoring and understanding how peoples attitude towards products changes. Understanding which product features influence a buyers choice positively or negatively allows decision makers to make well-informed decisions on improving their products or marketing them properly. We propose OPINSTREAM, a framework for the discovery and polarity monitoring of implicit product features deemed important in the peoples reviews on different products.]]>
Opinion stream mining encompasses methods for monitoring and understanding how peoples attitude towards products changes. Understanding which product features influence a buyers choice positively or negatively allows decision makers to make well-informed decisions on improving their products or marketing them properly. We propose OPINSTREAM, a framework for the discovery and polarity monitoring of implicit product features deemed important in the peoples reviews on different products.]]> Wed, 05 Nov 2014 06:21:30 GMT /slideshow/enopinionated-streamshdms2014presented-engl/41151944 ntoutsi@slideshare.net(ntoutsi) Discovering and Monitoring Product Features and the Opinions on them with OPINSTREAM ntoutsi Opinion stream mining encompasses methods for monitoring and understanding how peoples attitude towards products changes. Understanding which product features influence a buyers choice positively or negatively allows decision makers to make well-informed decisions on improving their products or marketing them properly. We propose OPINSTREAM, a framework for the discovery and polarity monitoring of implicit product features deemed important in the peoples reviews on diff鐃erent products. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/en-141105062130-conversion-gate02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Opinion stream mining encompasses methods for monitoring and understanding how peoples attitude towards products changes. Understanding which product features influence a buyers choice positively or negatively allows decision makers to make well-informed decisions on improving their products or marketing them properly. We propose OPINSTREAM, a framework for the discovery and polarity monitoring of implicit product features deemed important in the peoples reviews on diff鐃erent products.
Discovering and Monitoring Product Features and the Opinions on them with OPINSTREAM from Eirini Ntoutsi
]]> 410 2 https://cdn.slidesharecdn.com/ss_thumbnails/en-141105062130-conversion-gate02-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 NeeMo@OpenCoffeeXX /slideshow/neemoopencoffeexx/1128527 opencoffee-neemo-090310170813-phpapp02
里凌 NeeMo 竜溜僚留旅 劉僚留 竜粒留了竜溜凌 粒旅留 侶僚 留亮留侶 僚凌侶 侶 了了侶僚旅虜流 blogo-留旅留. 僚略 留虜略 凌僚旅虜略 隆旅留流亮留留, 凌 NeeMo 了了劉粒竜旅 posts 留 了留 留 blogs, 留 凌亮留隆凌凌旅竜溜 竜 慮劉亮留留 虜留旅 留 留凌旅略龍竜旅 亮竜 硫略侶 凌 凌 竜僚隆旅留劉凌僚 侶僚 虜凌旅僚流 粒僚ﾎ捨.]]>
里凌 NeeMo 竜溜僚留旅 劉僚留 竜粒留了竜溜凌 粒旅留 侶僚 留亮留侶 僚凌侶 侶 了了侶僚旅虜流 blogo-留旅留. 僚略 留虜略 凌僚旅虜略 隆旅留流亮留留, 凌 NeeMo 了了劉粒竜旅 posts 留 了留 留 blogs, 留 凌亮留隆凌凌旅竜溜 竜 慮劉亮留留 虜留旅 留 留凌旅略龍竜旅 亮竜 硫略侶 凌 凌 竜僚隆旅留劉凌僚 侶僚 虜凌旅僚流 粒僚ﾎ捨.]]> Tue, 10 Mar 2009 17:07:41 GMT /slideshow/neemoopencoffeexx/1128527 ntoutsi@slideshare.net(ntoutsi) NeeMo@OpenCoffeeXX ntoutsi 里凌 NeeMo 竜溜僚留旅 劉僚留 竜粒留了竜溜凌 粒旅留 侶僚 留亮留侶 僚凌侶 侶 了了侶僚旅虜流 blogo-留旅留. 僚略 留虜略 凌僚旅虜略 隆旅留流亮留留, 凌 NeeMo 了了劉粒竜旅 posts 留 了留 留 blogs, 留 凌亮留隆凌凌旅竜溜 竜 慮劉亮留留 虜留旅 留 留凌旅略龍竜旅 亮竜 硫略侶 凌 凌 竜僚隆旅留劉凌僚 侶僚 虜凌旅僚流 粒僚ﾎ捨. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/opencoffee-neemo-090310170813-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 里凌 NeeMo 竜溜僚留旅 劉僚留 竜粒留了竜溜凌 粒旅留 侶僚 留亮留侶 僚凌侶 侶 了了侶僚旅虜流 blogo-留旅留. 僚略 留虜略 凌僚旅虜略 隆旅留流亮留留, 凌 NeeMo 了了劉粒竜旅 posts 留 了留 留 blogs, 留 凌亮留隆凌凌旅竜溜 竜 慮劉亮留留 虜留旅 留 留凌旅略龍竜旅 亮竜 硫略侶 凌 凌 竜僚隆旅留劉凌僚 侶僚 虜凌旅僚流 粒僚ﾎ捨.
NeeMo@OpenCoffeeXX from Eirini Ntoutsi
]]> 516 3 https://cdn.slidesharecdn.com/ss_thumbnails/opencoffee-neemo-090310170813-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-ntoutsi-48x48.jpg?cb=1643021853 AI expert, combining data mining and machine learning towards positive goals and real-world problems. www.mi.fu-berlin.de/en/inf/groups/ag-KIML/index.html https://cdn.slidesharecdn.com/ss_thumbnails/aaisi-210406060600-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/aaisi-ai-colloquium-3032021-bias-in-ai-systems/245762020 AAISI AI Colloquium 30... https://cdn.slidesharecdn.com/ss_thumbnails/recsgrouptampere-210220154820-thumbnail.jpg?width=320&height=320&fit=bounds ntoutsi/fairnessaware-learning-from-single-models-to-sequential-ensemble-learning-and-learning-over-data-streams Fairness-aware learnin... https://cdn.slidesharecdn.com/ss_thumbnails/nl4xai-210112061031-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/bias-in-aisystems-a-multistep-approach/241221191 Bias in AI-systems: A ...