暂无分享,去创建一个
[1] Guanghui Lan,et al. Complexity of Training ReLU Neural Network , 2018, Discret. Optim..
[2] Roi Livni,et al. On the Computational Efficiency of Training Neural Networks , 2014, NIPS.
[3] Ambuj Tewari,et al. On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization , 2008, NIPS.
[4] David Haussler,et al. Decision Theoretic Generalizations of the PAC Model for Neural Net and Other Learning Applications , 1992, Inf. Comput..
[5] Russell Impagliazzo,et al. Complexity of k-SAT , 1999, Proceedings. Fourteenth Annual IEEE Conference on Computational Complexity (Formerly: Structure in Complexity Theory Conference) (Cat.No.99CB36317).
[6] Guanghui Lan,et al. Complexity of Training ReLU Neural Networks , 2018 .
[7] Russell Impagliazzo,et al. Which problems have strongly exponential complexity? , 1998, Proceedings 39th Annual Symposium on Foundations of Computer Science (Cat. No.98CB36280).
[8] Adam Tauman Kalai,et al. Reliable Agnostic Learning , 2009, COLT.
[9] Irit Dinur,et al. On the hardness of approximating label-cover , 2004, Inf. Process. Lett..
[10] Guy Kindler,et al. Polynomially Low Error PCPs with polyloglog n Queries via Modular Composition , 2015, STOC.
[11] Francis R. Bach,et al. Breaking the Curse of Dimensionality with Convex Neural Networks , 2014, J. Mach. Learn. Res..
[12] R. Schapire,et al. Toward efficient agnostic learning , 1992, COLT '92.
[13] Sébastien Bubeck,et al. Convex Optimization: Algorithms and Complexity , 2014, Found. Trends Mach. Learn..
[14] Andrew L. Maas. Rectifier Nonlinearities Improve Neural Network Acoustic Models , 2013 .
[15] Michael Alekhnovich,et al. Minimum propositional proof length is NP-hard to linearly approximate , 1998, Journal of Symbolic Logic.
[16] Ronald L. Rivest,et al. Training a 3-node neural network is NP-complete , 1988, COLT '88.
[17] Amir Globerson,et al. Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs , 2017, ICML.
[18] Raman Arora,et al. Understanding Deep Neural Networks with Rectified Linear Units , 2016, Electron. Colloquium Comput. Complex..
[19] Varun Kanade,et al. Reliably Learning the ReLU in Polynomial Time , 2016, COLT.
[20] Peter L. Bartlett,et al. Rademacher and Gaussian Complexities: Risk Bounds and Structural Results , 2003, J. Mach. Learn. Res..
[21] Leslie G. Valiant,et al. A theory of the learnable , 1984, STOC '84.
[22] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.