Isaac Meilijson

Yael Perlman

Ann. Oper. Res., March, 2024

2023

Queueing with Negative Network Effects.

[BibT_eX]

[DOI]

Refael Hassin

Yael Perlman

Manuf. Serv. Oper. Manag., September, 2023

2016

Splitting matters: how monotone transformation of predictor variables may improve the predictions of decision tree models.

[BibT_eX]

[DOI]

Tal Galili

CoRR, 2016

Filtering With the Crowd: CrowdScreen Revisited.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Database Theory, 2016

2011

Genome-Scale Analysis of Translation Elongation with a Ribosome Flow Model.

[BibT_eX]

[DOI]

PLoS Comput. Biol., 2011

The signal model: A model for competing risks of opportunistic maintenance.

[BibT_eX]

[DOI]

Eur. J. Oper. Res., 2011

A Ribosome Flow Model for Analyzing Translation Elongation - (Extended Abstract).

[BibT_eX]

[DOI]

Proceedings of the Research in Computational Molecular Biology, 2011

2008

Can single knockouts accurately single out gene functions?

[BibT_eX]

[DOI]

BMC Syst. Biol., 2008

2006

Gene Expression of <i>Caenorhabditis elegans</i> Neurons Carries Information on Their Synaptic Connectivity.

[BibT_eX]

[DOI]

PLoS Comput. Biol., 2006

Axiomatic Scalable Neurocontroller Analysis via the Shapley Value.

[BibT_eX]

[DOI]

Artif. Life, 2006

2005

Quantitative Analysis of Genetic and Neuronal Multi-Perturbation Experiments.

[BibT_eX]

[DOI]

PLoS Comput. Biol., 2005

2004

Fair Attribution of Functional Contribution in Artificial and Biological Networks.

[BibT_eX]

[DOI]

Neural Comput., 2004

Causal localization of neural function: the Shapley value method.

[BibT_eX]

[DOI]

Neurocomputing, 2004

2003

Linearization of local probabilistic sensitivity via sample re-weighting.

[BibT_eX]

[DOI]

Roger M. Cooke

Dorota Kurowicka

Reliab. Eng. Syst. Saf., 2003

Localization of Function via Lesion Analysis.

[BibT_eX]

[DOI]

Neural Comput., 2003

High-Dimensional Analysis of Evolutionary Autonomous Agents.

[BibT_eX]

[DOI]

Artif. Life, 2003

2002

Evolution of reinforcement learning in foraging bees: a simple explanation for risk averse behavior.

[BibT_eX]

[DOI]

Neurocomputing, 2002

Evolution of Reinforcement Learning in Uncertain Environments: A Simple Explanation for Complex Foraging Behaviors.

[BibT_eX]

[DOI]

Adapt. Behav., 2002

2001

Distributed synchrony in a cell assembly of spiking neurons.

[BibT_eX]

[DOI]

Neural Networks, 2001

Effective Neuronal Learning with Ineffective Hebbian Learning Rules.

[BibT_eX]

[DOI]

Neural Comput., 2001

Evolution of Reinforcement Learning in Uncertain Environments: Emergence of Risk-Aversion and Matching.

[BibT_eX]

[DOI]

Proceedings of the Advances in Artificial Life, 6th European Conference, 2001

Understanding the Agent's Brain: A Quantitative Approach.

[BibT_eX]

[DOI]

Ranit Aharonov-Barki

Proceedings of the Advances in Artificial Life, 6th European Conference, 2001

2000

Neuronal normalization provides effective learning through ineffective synaptic learning rules.

[BibT_eX]

[DOI]

Neurocomputing, 2000

Who Does What? A Novel Algorithm to Determine Function Localization.

[BibT_eX]

[DOI]

Ranit Aharonov-Barki

Proceedings of the Advances in Neural Information Processing Systems 13, 2000

1999

Neuronal Regulation: A Mechanism for Synaptic Pruning During Brain Maturation.

[BibT_eX]

[DOI]

Neural Comput., 1999

Neuronal regulation: A biologically plausible mechanism for efficient synaptic pruning in development.

[BibT_eX]

[DOI]

Neurocomputing, 1999

Distributed Synchrony of Spiking Neurons in a Hebbian Cell Assembly.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Effective Learning Requires Neuronal Remodeling of Hebbian Synapses.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

1998

Synaptic Pruning In Development: A Computational Account.

[BibT_eX]

[DOI]

Neural Comput., 1998

Neuronal Regulation Implements Efficient Synaptic Pruning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Fast computation in hamming and hopfield networks.

[BibT_eX]

[DOI]

Moshe Sipper

Proceedings of the Algorithms and Architectures., 1998

1996

Optimal firing in sparsely-connected low-activity attractor networks.

[BibT_eX]

[DOI]

Biol. Cybern., 1996

1995

A single-iteration threshold Hamming network.

[BibT_eX]

[DOI]

Moshe Sipper

IEEE Trans. Neural Networks, 1995

1994

Co-monotone allocations, Bickel-Lehmann dispersion and the Arrow-Pratt measure of risk aversion.

[BibT_eX]

[DOI]

Michael Landsberger

Ann. Oper. Res., 1994

1993

Optimal Signalling in Attractor Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 6, 1993

1992

Single-Iteration Threshold Hamming Networks.

[BibT_eX]

[DOI]

Moshe Sipper

Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

History-Dependent Attractor Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

1984

The Organ Pipe Permutation.

[BibT_eX]

[DOI]

M. Keane

Alan G. Konheim

SIAM J. Comput., 1984

Minimizing Flow Time on Parallel Identical Processors with Variable Unit Processing Time.

[BibT_eX]

[DOI]