Shai Ben-David is an Israeli-Canadian computer scientist and professor at the University of Waterloo. He is known for his research in theoretical machine learning.[1]
Ben-David has written highly cited papers on learning theory and online algorithms.[5][6][7][8][9] He is a co-author, with Shai Shalev-Shwartz, of the book "Understanding Machine Learning: From Theory to Algorithms"(Cambridge University Press, 2014).[1]
He received the best paper award at NeurIPS 2018.[10] for work on sample complexity of distribution learning problems.[11] He was the President of the Association for Computational Learning from 2009 to 2011.[12]
Shalev-Shwartz, Shai; Ben-David, Shai (2014). Understanding machine learning: From theory to algorithms. Cambridge University Press.
Ben-David, Shai; Blitzer, John; Crammer, Koby; Kulesza, Alex; Pereira, Fernando; Wortman Vaughan, Jennifer (2010). "A theory of learning from different domains". Machine Learning. 79. Springer US: 151–175.
Ben-David, Shai; Blitzer, John; Crammer, Koby; Pereira, Fernando (2006). "Analysis of representations for domain adaptation". Advances in Neural Information Processing Systems. 19.
Kifer, Daniel; Ben-David, Shai; Gehrke, Johannes (2004). "Detecting change in data streams". VLDB. 4.
