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Approximating Interactive Human Evaluation with Self-Play for Open-Domain Dialog Systems.

, , , , , , and . NeurIPS, page 13658-13669. (2019)

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Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning, , , , , , , and . (2018)cite arxiv:1810.08647.Tackling Climate Change with Machine Learning, , , , , , , , , and 12 other author(s). ACM Comput. Surv., (February 2022)Predicting Tomorrow's Mood, Health, and Stress Level using Personalized Multitask Learning and Domain Adaptation., , , , and . AffComp@IJCAI, volume 66 of Proceedings of Machine Learning Research, page 17-33. PMLR, (2017)Reinforcement learning from Affective Cues in Dialogue.. AffCon@AAAI, volume 2614 of CEUR Workshop Proceedings, CEUR-WS.org, (2020)Automatic identification of artifacts in electrodermal activity data., , , , , and . EMBC, page 1934-1937. IEEE, (2015)Predicting students' happiness from physiology, phone, mobility, and behavioral data., , , , , and . ACII, page 222-228. IEEE Computer Society, (2015)Predicting Affect from Gaze Data during Interaction with an Intelligent Tutoring System., , , and . Intelligent Tutoring Systems, volume 8474 of Lecture Notes in Computer Science, page 29-38. Springer, (2014)Understanding and Predicting Bonding in Conversations Using Thin Slices of Facial Expressions and Body Language., , , and . IVA, volume 10011 of Lecture Notes in Computer Science, page 64-74. (2016)Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control., , , , , and . ICML, volume 70 of Proceedings of Machine Learning Research, page 1645-1654. PMLR, (2017)Personality, Attitudes, and Bonding in Conversations., , and . IVA, volume 10011 of Lecture Notes in Computer Science, page 378-382. (2016)