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 39 papers between 1984 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

1984
The Organ Pipe Permutation.
SIAM J. Comput., 1984

Minimizing Flow Time on Parallel Identical Processors with Variable Unit Processing Time.
Oper. Res., 1984


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