Understanding Machine Learning: From Theory to Algorithms

References 441 Hinton, G. E., Osindero, S. & Teh, Y.-W. (2006), ‘A fast learning algorithm for deep belief nets’,Neural Comp ...

442 References Le, Q. V., Ranzato, M.-A., Monga, R., Devin, M., Corrado, G., Chen, K., Dean, J. & Ng, A. Y. (2012), Building ...

References 443 Nesterov, Y. & Nesterov, I. (2004),Introductory lectures on convex optimization: A basic course, Vol. 87, Spr ...

444 References Sankaran, J. K. (1993), ‘A note on resolving infeasibility in linear programs by con- straint relaxation’,Operati ...

References 445 Shelah, S. (1972), ‘A combinatorial problem; stability and order for models and theories in infinitary languages’ ...

446 References Weston, J., Chapelle, O., Vapnik, V., Elisseeff, A. & Sch ̈olkopf, B. (2002), Kernel depen- dency estimation, ...

Index 3-term DNF, 107 F 1 -score, 244 ` 1 norm, 183, 332, 363, 386 accuracy, 38, 43 activation function, 269 AdaBoost, 130, 134 ...

448 Index forward greedy selection, 360 frequentist, 353 gain, 253 GD,seegradient descent generalization error, 35 generative mo ...

Index 449 Normalized Discounted Cumulative Gain, seeNDCG Occam’s razor, 91 OMP, 360 one-vs-all, 227 one-vs-rest,seeone-vs-all on ...