Isaac Meilijson

Orcid: 0000-0001-7825-9053

Affiliations:
  • Tel Aviv University, School of Mathematical Sciences, Israel


According to our database1, Isaac Meilijson authored at least 37 papers between 1992 and 2024.

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Bibliography

2024
Dynamic history-dependent tax and environmental compliance monitoring of risk-averse firms.
Ann. Oper. Res., March, 2024

2023
Queueing with Negative Network Effects.
Manuf. Serv. Oper. Manag., September, 2023

2016
Splitting matters: how monotone transformation of predictor variables may improve the predictions of decision tree models.
CoRR, 2016

Filtering With the Crowd: CrowdScreen Revisited.
Proceedings of the 19th International Conference on Database Theory, 2016

2011
Genome-Scale Analysis of Translation Elongation with a Ribosome Flow Model.
PLoS Comput. Biol., 2011

The signal model: A model for competing risks of opportunistic maintenance.
Eur. J. Oper. Res., 2011

A Ribosome Flow Model for Analyzing Translation Elongation - (Extended Abstract).
Proceedings of the Research in Computational Molecular Biology, 2011

2008
Can single knockouts accurately single out gene functions?
BMC Syst. Biol., 2008

2006
Gene Expression of <i>Caenorhabditis elegans</i> Neurons Carries Information on Their Synaptic Connectivity.
PLoS Comput. Biol., 2006

Axiomatic Scalable Neurocontroller Analysis via the Shapley Value.
Artif. Life, 2006

2005
Quantitative Analysis of Genetic and Neuronal Multi-Perturbation Experiments.
PLoS Comput. Biol., 2005

2004
Fair Attribution of Functional Contribution in Artificial and Biological Networks.
Neural Comput., 2004

Causal localization of neural function: the Shapley value method.
Neurocomputing, 2004

2003
Linearization of local probabilistic sensitivity via sample re-weighting.
Reliab. Eng. Syst. Saf., 2003

Localization of Function via Lesion Analysis.
Neural Comput., 2003

High-Dimensional Analysis of Evolutionary Autonomous Agents.
Artif. Life, 2003

2002
Evolution of reinforcement learning in foraging bees: a simple explanation for risk averse behavior.
Neurocomputing, 2002

Evolution of Reinforcement Learning in Uncertain Environments: A Simple Explanation for Complex Foraging Behaviors.
Adapt. Behav., 2002

2001
Distributed synchrony in a cell assembly of spiking neurons.
Neural Networks, 2001

Effective Neuronal Learning with Ineffective Hebbian Learning Rules.
Neural Comput., 2001

Evolution of Reinforcement Learning in Uncertain Environments: Emergence of Risk-Aversion and Matching.
Proceedings of the Advances in Artificial Life, 6th European Conference, 2001

Understanding the Agent's Brain: A Quantitative Approach.
Proceedings of the Advances in Artificial Life, 6th European Conference, 2001

2000
Neuronal normalization provides effective learning through ineffective synaptic learning rules.
Neurocomputing, 2000

Who Does What? A Novel Algorithm to Determine Function Localization.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

1999
Neuronal Regulation: A Mechanism for Synaptic Pruning During Brain Maturation.
Neural Comput., 1999

Neuronal regulation: A biologically plausible mechanism for efficient synaptic pruning in development.
Neurocomputing, 1999

Distributed Synchrony of Spiking Neurons in a Hebbian Cell Assembly.
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.
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.
Neural Comput., 1998

Neuronal Regulation Implements Efficient Synaptic Pruning.
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.
Proceedings of the Algorithms and Architectures., 1998

1996
Optimal firing in sparsely-connected low-activity attractor networks.
Biol. Cybern., 1996

1995
A single-iteration threshold Hamming network.
IEEE Trans. Neural Networks, 1995

1994
Co-monotone allocations, Bickel-Lehmann dispersion and the Arrow-Pratt measure of risk aversion.
Ann. Oper. Res., 1994

1993
Optimal Signalling in Attractor Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 6, 1993

1992
Single-Iteration Threshold Hamming Networks.
Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

History-Dependent Attractor Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992


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