Near-Optimal Algorithms for Online Matrix Prediction
暂无分享,去创建一个
[1] S. Golden. LOWER BOUNDS FOR THE HELMHOLTZ FUNCTION , 1965 .
[2] C. Thompson. Inequality with Applications in Statistical Mechanics , 1965 .
[3] Gunnar Rätsch,et al. Matrix Exponentiated Gradient Updates for On-line Learning and Bregman Projection , 2004, J. Mach. Learn. Res..
[4] Sanjeev Arora,et al. A combinatorial, primal-dual approach to semidefinite programs , 2007, STOC '07.
[5] Jacob Abernethy,et al. Can we learn to gamble efficiently , 2010, COLT 2010.
[6] Ruslan Salakhutdinov,et al. Practical Large-Scale Optimization for Max-norm Regularization , 2010, NIPS.
[7] Robert D. Kleinberg,et al. Regret bounds for sleeping experts and bandits , 2010, Machine Learning.
[8] Ohad Shamir,et al. Efficient Online Learning via Randomized Rounding , 2011, NIPS.
[9] Ohad Shamir,et al. Collaborative Filtering with the Trace Norm: Learning, Bounding, and Transducing , 2011, COLT.
[10] Rina Foygel. Commentary on "Near-Optimal Algorithms for Online Matrix Prediction" , 2012, COLT.
[11] Ambuj Tewari,et al. Regularization Techniques for Learning with Matrices , 2009, J. Mach. Learn. Res..
[12] Thomas Steinke,et al. Learning hurdles for sleeping experts , 2012, ITCS '12.