Boolean autoencoders and hypercube clustering complexity
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[1] David S. Johnson,et al. Computers and In stractability: A Guide to the Theory of NP-Completeness. W. H Freeman, San Fran , 1979 .
[2] Geoffrey E. Hinton,et al. Deep, Narrow Sigmoid Belief Networks Are Universal Approximators , 2008, Neural Computation.
[3] Robert McEliece,et al. The Theory of Information and Coding: Information theory , 2002 .
[4] David G. Stork,et al. Pattern Classification , 1973 .
[5] Bernhard Schölkopf,et al. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond , 2005, IEEE Transactions on Neural Networks.
[6] James R. Slagle,et al. A Clustering and Data-Reorganizing Algorithm , 1975, IEEE Transactions on Systems, Man, and Cybernetics.
[7] F. Harary. Cubical graphs and cubical dimensions , 1988 .
[8] Yoshua Bengio,et al. Scaling learning algorithms towards AI , 2007 .
[9] Pierre Baldi,et al. Complex-Valued Autoencoders , 2011, Neural Networks.
[10] Peter Glöckner,et al. Why Does Unsupervised Pre-training Help Deep Learning? , 2013 .
[11] Peter Winkler,et al. Proof of the squashed cube conjecture , 1983, Comb..
[12] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[13] David G. Stork,et al. Pattern Classification (2nd ed.) , 1999 .
[14] Geoffrey E. Hinton,et al. Learning internal representations by error propagation , 1986 .
[15] Alexander Vardy,et al. The intractability of computing the minimum distance of a code , 1997, IEEE Trans. Inf. Theory.
[16] Meena Mahajan,et al. The Planar k-means Problem is NP-hard I , 2009 .
[17] Nimrod Megiddo,et al. On the Complexity of Some Common Geometric Location Problems , 1984, SIAM J. Comput..
[18] I. Havel,et al. $B$-valuations of graphs , 1972 .
[19] S. Louis Hakimi,et al. On the complexity of some coding problems , 1981, IEEE Trans. Inf. Theory.
[20] Jehuda Hartman. The homeomorphic embedding of Kn in the m-cube , 1976, Discret. Math..
[21] Ronald L. Rivest,et al. Training a 3-node neural network is NP-complete , 1988, COLT '88.
[22] Andrea Vattani. The hardness of k-means clustering in the plane , 2010 .
[23] Geoffrey E. Hinton,et al. Reducing the Dimensionality of Data with Neural Networks , 2006, Science.
[24] George Papageorgiou,et al. The Complexity of Cubical Graphs , 1985, Inf. Control..
[25] Jehuda Hartman. The homeomorphic embedding of K n in the m-cube. , 1976 .
[26] Elwyn R. Berlekamp,et al. On the inherent intractability of certain coding problems (Corresp.) , 1978, IEEE Trans. Inf. Theory.
[27] Kurt Hornik,et al. Neural networks and principal component analysis: Learning from examples without local minima , 1989, Neural Networks.
[28] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[29] Delbert Dueck,et al. Clustering by Passing Messages Between Data Points , 2007, Science.
[30] Jason Weston,et al. Large-scale kernel machines , 2007 .
[31] M. Livingston,et al. Embeddings in hypercubes , 1988 .
[32] Pierre Baldi,et al. Autoencoders, Unsupervised Learning, and Deep Architectures , 2011, ICML Unsupervised and Transfer Learning.