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Program

Accepted Contributions

Conference Schedule

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14:00 – 16:00	Doctoral Symposium
	Break
17:00 – 19:00	Doctoral Symposium

13:30 – 14:00	Welcome
14:00 – 15:00	Keynote by Filippo Menczer supported by Globo.com
	Break
16:00 – 17:30	Session P1A Real-World Applications I	3:00 – 4:30	Session P1B Real-World Applications I
17:30 – 18:30	Social 2A RecSys newbies meet RecSys oldies		Break
18:30 – 20:00	Session P2A Evaluating and Explaining Recommendations	5:30 – 7:00	Session P2B Evaluating and Explaining Recommendations
	Break	7:00 – 8:00	Social 3A Women in RecSys
21:00 – 23:00	Session O1A Posters: Short Papers supported by iFood	8:00 – 10:00	Session O1B Posters: Short Papers supported by iFood
23:00 – 0:00	Social 2B RecSys newbies meet RecSys oldies	10:00 – 11:00	Social 4 Sharing is Caring
00:00 – 1:30	Session P3A Novel Machine Learning Approaches I	11:00 – 12:30	Session P3B Novel Machine Learning Approaches I
	Program continues in right column.	12:30 – 14:00	Reception supported by Netflix Research

14:00 – 15:00	Keynote by Ricardo Baeza-Yates supported by Spotify
15:00 – 16:00	Social 6 RecSysIndia		Break
16:00 – 17:30	Session P4A Fairness, Filter Bubbles, and Ethical Concerns	3:00 – 4:30	Session P4B Fairness, Filter Bubbles, and Ethical Concerns
17:30 – 18:30	Social 7 A Wolf in “A Cidade Maravilhosa”		Break
18:30 – 20:00	Session P5A Real-World Applications II	5:30 – 7:00	Session P5B Real-World Applications II
20:00 – 21:00	Social 3B Women in RecSys		Break
21:00 – 23:00	Session O2A Posters: Demos & Doctoral Symposium supported by Pandora SXM	8:00 – 10:00	Session O2B Posters: Demos & Doctoral Symposium supported by Pandora SXM
23:00 – 0:00	Social 8 Towards Shared RecSys Experiment Infrastructure: Personalized News		Break
00:00 – 1:30	Session P6A Unbiased Recommendation and Evaluation	11:00 – 12:30	Session P6B Unbiased Recommendation and Evaluation
	Program continues in right column.	12:30 – 14:00	Banquet

14:00 – 15:00	Keynote by Michelle Zhou supported by Zalando SE
	Break
16:00 – 17:30	Session P7A Understanding and Modeling Preferences	3:00 – 4:30	Session P7B Understanding and Modeling Preferences
17:30 – 18:30	Social 11 Ask a RecSys Expert		Break
18:30 – 20:00	Session P8A Novel Machine Learning Approaches II	5:30 – 7:00	Session P8B Novel Machine Learning Approaches II
	Break
21:00 – 23:00	Session O3A Posters: Late-breaking Results supported by The Home Depot	8:00 – 10:00	Session O3B Posters: Late-breaking Results supported by The Home Depot
23:00 – 0:00	Social 12 Deep Learning RecSys: Conversations over Cocktails or Coffee		Break
00:00 – 1:30	Session P9A Real-World Applications III	11:00 – 12:30	Session P9B Real-World Applications III
	Program continues in right column.		Break
		13:30 – 14:00	Farewell
		15:30 – 16:30	Social 14 News Recommender Systems

14:00 – 15:00	Tutorial 1A Conversational Recommender Systems	1:00 – 2:00	Tutorial 1B Conversational Recommender Systems
	Break
15:30 – 16:30	Tutorial 2A Feature Engineering	2:30 – 3:30	Tutorial 2B Feature Engineering
	Break
17:00 – 18:00	Tutorial 3A Counteracting Bias and Increasing Fairness	4:00 – 5:00	Tutorial 3B Counteracting Bias and Increasing Fairness
	Break
18:30 – 19:30	Tutorial 4A Introduction to Bandits	5:30 – 6:30	Tutorial 4B Introduction to Bandits
	Break
20:00 – 21:00	Tutorial 5A Bayesian Value Based Recommendation	7:00 – 8:00	Tutorial 5B Bayesian Value Based Recommendation
	Break
21:30 – 22:30	Tutorial 6A Adversarial Learning	8:30 – 9:30	Tutorial 6B Adversarial Learning

14:00 – 14:30	CARS ComplexRec ImpactRS OHARS ORSUM PodRecs	14:00 – 15:30	Challenge FAccTRec fashionXrecsys IntRS REVEAL HealthRecSys (starts 13:00)
Break
16:30 – 18:00	CARS ComplexRec ImpactRS OHARS ORSUM PodRecs	16:30 – 18:00	Challenge FAccTRec fashionXrecsys IntRS REVEAL HealthRecSys (starts 15:30)
Break
		19:00 – 20:30	Challenge FAccTRec fashionXrecsys IntRS REVEAL HealthRecSys (starts 18:00)