recsys 2020 tutorial: counteracting bias and increasing fairness in search and recommender systems
Published 4 years ago • 2.7K plays • Length 1:08:01Download video MP4
Download video MP3
Similar videos
-
1:03:04
recsys 2020 keynote: bias on search and recommender systems
-
2:14:10
recsys 2020 tutorial: adversarial learning for recommendation
-
3:32:27
bias issues and solutions in recommender system
-
2:01:52
recsys 2020 tutorial: bayesian value based recommendation
-
1:25:59
recsys 2020 session p2b: evaluating and explaining recommendations
-
1:01:36
bias, fairness, and more in recommender systems
-
35:17
navigating the reskilling imperative amid genai disruption
-
13:01
machine learning system design (youtube recommendation system)
-
38:43
user intents and journeys in recommender systems by minmin chen | videorecsys workshop | recsys 2023
-
1:33:19
recsys 2020 session p7a: understanding and modeling preferences
-
1:32:51
recsys 2020 session p7b: understanding and modeling preferences
-
13:27
debiased explainable pairwise ranking from implicit feedback
-
14:32
user-oriented fairness in recommendation
-
30:57
session 4: countering popularity bias by regularizing score differences
-
1:34:15
recsys 2020 session p4b: fairness, filter bubbles, and ethical concerns
-
1:31:56
recsys 2020 session p6b: unbiased recommendation and evaluation
-
15:21
session 4: imbalanced data sparsity as source of unfair bias in collaborative filtering
-
15:01
debiasing career recommendations with neural fair collaborative filtering
-
1:30:52
recsys 2020 session p2a: evaluating and explaining recommendations
-
13:38
debiased off-policy evaluation for recommender systems