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Exponentiated Gradient Versus Gradient Descent for Linear Predictors.

, and . Inf. Comput., 132 (1): 1-63 (1997)

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Sample Compression, Learnability, and the Vapnik-Chervonenkis Dimension.. EuroCOLT, volume 1208 of Lecture Notes in Computer Science, page 1-2. Springer, (1997)Matrix Exponentiated Gradient Updates for On-line Learning and Bregman Projection., , and . J. Mach. Learn. Res., (2005)Open Problem: Shifting Experts on Easy Data., and . COLT, volume 35 of JMLR Workshop and Conference Proceedings, page 1295-1298. JMLR.org, (2014)Online Non-Additive Path Learning under Full and Partial Information., , , , and . ALT, volume 98 of Proceedings of Machine Learning Research, page 274-299. PMLR, (2019)Combining Initial Segments of Lists., , and . ALT, volume 6925 of Lecture Notes in Computer Science, page 219-233. Springer, (2011)Unlabeled Compression Schemes for Maximum Classes, ., and . COLT, volume 3559 of Lecture Notes in Computer Science, page 591-605. Springer, (2005)Tracking a Small Set of Experts by Mixing Past Posteriors., and . COLT/EuroCOLT, volume 2111 of Lecture Notes in Computer Science, page 31-47. Springer, (2001)Leaving the Span., and . COLT, volume 3559 of Lecture Notes in Computer Science, page 366-381. Springer, (2005)Computing on an anonymous ring., , and . J. ACM, 35 (4): 845-875 (1988)Exponentiated Gradient Versus Gradient Descent for Linear Predictors., and . Inf. Comput., 132 (1): 1-63 (1997)