Detecting Patterns Can Be Hard : Circuit Lower Bounds for the Pattern Matching Problem
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[1] D. Hubel,et al. Receptive fields and functional architecture of monkey striate cortex , 1968, The Journal of physiology.
[2] Marvin Minsky,et al. Perceptrons: An Introduction to Computational Geometry , 1969 .
[3] Saburo Muroga,et al. Threshold logic and its applications , 1971 .
[4] Robert S. Boyer,et al. A fast string searching algorithm , 1977, CACM.
[5] Donald E. Knuth,et al. Fast Pattern Matching in Strings , 1977, SIAM J. Comput..
[6] Zvi Galil. Optimal Parallel Algorithms for String Matching , 1985, Inf. Control..
[7] Georg Schnitger,et al. Parallel Computation with Threshold Functions , 1986, J. Comput. Syst. Sci..
[8] Pavel Pudlák,et al. Threshold circuits of bounded depth , 1987, 28th Annual Symposium on Foundations of Computer Science (sfcs 1987).
[9] N. Nisan. The communication complexity of threshold gates , 1993 .
[10] Jehoshua Bruck,et al. Depth efficient neural networks for division and related problems , 1993, IEEE Trans. Inf. Theory.
[11] D. V. van Essen,et al. A neurobiological model of visual attention and invariant pattern recognition based on dynamic routing of information , 1993, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[12] György Turán,et al. A Liniear lower bound for the size of threshold circuits , 1993, Bull. EATCS.
[13] Ian Parberry,et al. Circuit complexity and neural networks , 1994 .
[14] Alon Orlitsky,et al. Lower bounds on threshold and related circuits via communication complexity , 1994, IEEE Trans. Inf. Theory.
[15] Alon Orlitsky,et al. Neural Models and Spectral Methods , 1994 .
[16] Terrence J. Sejnowski,et al. The Computational Brain , 1996, Artif. Intell..
[17] D. A. Wolfram. Solving generalized Fibonacci recurrences , 1998 .
[18] Yoshua Bengio,et al. Convolutional networks for images, speech, and time series , 1998 .
[19] Robert A. Legenstein,et al. Foundations for a Circuit Complexity Theory of Sensory Processing , 2000, NIPS.
[20] Satyanarayana V. Lokam,et al. Relations Between Communication Complexity, Linear Arrangements, and Computational Complexity , 2001, FSTTCS.
[21] Gonzalo Navarro,et al. Flexible Pattern Matching in Strings: Practical On-Line Search Algorithms for Texts and Biological Sequences , 2002 .
[22] Robert A. Legenstein,et al. Neural circuits for pattern recognition with small total wire length , 2002, Theor. Comput. Sci..
[23] Kunihiko Fukushima,et al. Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position , 1980, Biological Cybernetics.
[24] Mark Daniel Ward,et al. On Correlation Polynomials and Subword Complexity , 2007 .
[25] Yann LeCun,et al. Convolutional networks and applications in vision , 2010, Proceedings of 2010 IEEE International Symposium on Circuits and Systems.
[26] Amit Chakrabarti,et al. An Optimal Lower Bound on the Communication Complexity of Gap-Hamming-Distance , 2012, SIAM J. Comput..
[27] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[28] R. Zemel,et al. On the Representational Efficiency of Restricted Boltzmann Machines , 2013, NIPS 2013.
[29] Stasys Jukna,et al. Boolean Function Complexity Advances and Frontiers , 2012, Bull. EATCS.
[30] Surya Ganguli,et al. Exact solutions to the nonlinear dynamics of learning in deep linear neural networks , 2013, ICLR.
[31] Xiao Zhou,et al. Threshold Circuits for Global Patterns in 2-Dimensional Maps , 2015, WALCOM.
[32] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[33] Ohad Shamir,et al. The Power of Depth for Feedforward Neural Networks , 2015, COLT.
[34] Daniel M. Kane,et al. Super-linear gate and super-quadratic wire lower bounds for depth-two and depth-three threshold circuits , 2015, STOC.
[35] Surya Ganguli,et al. On the Expressive Power of Deep Neural Networks , 2016, ICML.