Hava Siegelmann
Hava Siegelmann
Professor of Computer Science, and Brain Sciences, UMass Amherst
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Support vector clustering
A Ben-Hur, D Horn, HT Siegelmann, V Vapnik
Journal of machine learning research 2 (Dec), 125-137, 2001
On the computational power of neural nets
HT Siegelmann, ED Sontag
Proceedings of the fifth annual workshop on Computational learning theory …, 1992
Neural networks and analog computation: beyond the Turing limit
HT Siegelmann
Springer Science & Business Media, 2012
Computational capabilities of recurrent NARX neural networks
HT Siegelmann, BG Horne, CL Giles
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 27 …, 1997
Turing computability with neural nets
HT Siegelmann, ED Sontag
Applied Mathematics Letters 4 (6), 77-80, 1991
Analog computation via neural networks
HT Siegelmann, ED Sontag
Theoretical Computer Science 131 (2), 331-360, 1994
Computation beyond the Turing limit
HT Siegelmann
Science 268 (5210), 545-548, 1995
Brain-inspired replay for continual learning with artificial neural networks
GM Van de Ven, HT Siegelmann, AS Tolias
Nature communications 11 (1), 4069, 2020
Posttranscriptional regulation of BK channel splice variant stability by miR-9 underlies neuroadaptation to alcohol
AZ Pietrzykowski, RM Friesen, GE Martin, SI Puig, CL Nowak, PM Wynne, ...
Neuron 59 (2), 274-287, 2008
Bindsnet: A machine learning-oriented spiking neural networks library in python
H Hazan, DJ Saunders, H Khan, D Patel, DT Sanghavi, HT Siegelmann, ...
Frontiers in neuroinformatics 12, 89, 2018
A support vector clustering method
A Ben-Hur, D Horn, HT Siegelmann, V Vapnik
Proceedings 15th International Conference on Pattern Recognition. ICPR-2000 …, 2000
Biological underpinnings for lifelong learning machines
D Kudithipudi, M Aguilar-Simon, J Babb, M Bazhenov, D Blackiston, ...
Nature Machine Intelligence 4 (3), 196-210, 2022
The dynamic universality of sigmoidal neural networks
J Kilian, HT Siegelmann
Information and computation 128 (1), 48-56, 1996
The global landscape of cognition: hierarchical aggregation as an organizational principle of human cortical networks and functions
P Taylor, JN Hobbs, J Burroni, HT Siegelmann
Scientific reports 5 (1), 18112, 2015
Symbolic dynamics and computation in model gene networks
R Edwards, HT Siegelmann, K Aziza, L Glass
Chaos: An Interdisciplinary Journal of Nonlinear Science 11 (1), 160-169, 2001
Replay in deep learning: Current approaches and missing biological elements
TL Hayes, GP Krishnan, M Bazhenov, HT Siegelmann, TJ Sejnowski, ...
Neural computation 33 (11), 2908-2950, 2021
Analog computation with dynamical systems
HT Siegelmann, S Fishman
Physica D: Nonlinear Phenomena 120 (1-2), 214-235, 1998
Neural and super-Turing computing
HT Siegelmann
Minds and Machines 13, 103-114, 2003
A support vector method for clustering
A Ben-Hur, D Horn, HT Siegelmann, V Vapnik
Advances in Neural Information Processing Systems, 367-373, 2001
Computational power of neural networks: A characterization in terms of Kolmogorov complexity
JL Balcázar, R Gavalda, HT Siegelmann
IEEE Transactions on Information Theory 43 (4), 1175-1183, 1997
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