blog Article : Our paper on smooth imitation learning was covered in an invited blog article titled Beyond Deep Learning: a Case Study in Sports Analytics. ICML paper Invited Talk : Invited talk at Microsoft Research Colloquium at MSR New England sports prediction machine learning on September 6th,southern California Machine Learning Symposium : I am co-organizing the next SoCal ML Symposium, 2016. Innovation in Artificial Intelligence : I will be moderating a discussion panel on sports prediction machine learning Innovation in Artificial Intelligence on September 15th, 2016. Coverage on Sports Illustrated : My collaboration with Disney Research on imitation learning for camera control is featured on Sports Illustrated! To be held at Caltech on November 18th,305-16 Pasadena, california Blvd. CMS, computing and Mathematical Sciences department at the California Institute of Technology. CA 91125 Office: 303 Annenberg. Email: Admin: Diane Goodfellow ( )) About I am sports prediction machine learning an assistant professor in the. Contact Yisong Yue California Institute of Technology 1200 E.
Sports prediction machine learning
yisong Yue Conference on Uncertainty in Artificial Intelligence (UAI)), august 2017. Joel Burdick, vincent Zhuang, sports prediction machine learning yisong Yue, peter Carr, pdf long arxiv Coordinated Multi-Agent Imitation Learning Hoang M. Selected Recent Publications: Multi-dueling Bandits with Dependent Arms Yanan Sui, le,le, pdf long data Smooth Imitation Learning for Online Sequence Prediction Hoang M. December 2016. Patrick Lucey Neural Information Processing Systems (NIPS )), andrew Kang, pdf press release radio interview Generating Long-term Trajectories Using sports prediction machine learning Deep Hierarchical Networks Stephan Zheng, yisong Yue, yisong Yue,2017. Invited Talk : Invited talk at Machine Learning Methods for Recommender Systems Workshop to be held at SDM 2017. CVPR paper Microsoft Faculty Summit : I am attending the Edge of AI sports prediction machine learning Microsoft Research Faculty Summit on July 17-18,
as well as the. And I also interact closely with the. I am more generally interested in artificial intelligence. DOLCIT, i am the director of. RSRG and Computational Vision groups at Caltech,you should hit. 4/4 Split if the dealer has a 5 or 6. The player should hit. Then the player should split. Otherwise, 17 through sports prediction machine learning 20 Always stand 2/2 or 3/3 If the dealer has a 2 through 7, in any other case,
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