Ron Meir

According to our database, Ron Meir authored at least 106 papers between 1988 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Analysis of the Identifying Regulation With Adversarial Surrogates Algorithm.

Ron Teichner, Ron Meir, Michael Margaliot

IEEE Control. Syst. Lett., 2024

Data-dependent and Oracle Bounds on Forgetting in Continual Learning.

Lior Friedman, Ron Meir

CoRR, 2024

Characterization of the Distortion-Perception Tradeoff for Finite Channels with Arbitrary Metrics.

Dror Freirich, Nir Weinberger, Ron Meir

Proceedings of the IEEE International Symposium on Information Theory, 2024

Statistical curriculum learning: An elimination algorithm achieving an oracle risk.

Omer Cohen, Ron Meir, Nir Weinberger

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Concept-Best-Matching: Evaluating Compositionality In Emergent Communication.

Boaz Carmeli, Yonatan Belinkov, Ron Meir

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Identifying Dynamic Regulation with Adversarial Surrogates.

Ron Teichner, Naama Brenner, Ron Meir

CoRR, 2023

Meta-Learning Adversarial Bandit Algorithms.

Mikhail Khodak, Ilya Osadchiy, Keegan Harris, Maria-Florina Balcan, Kfir Y. Levy, Ron Meir, Zhiwei Steven Wu

CoRR, 2023

Meta-Learning Adversarial Bandit Algorithms.

Misha Khodak, Ilya Osadchiy, Keegan Harris, Maria-Florina Balcan, Kfir Y. Levy, Ron Meir, Zhiwei Steven Wu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Perceptual Kalman Filters: Online State Estimation under a Perfect Perceptual-Quality Constraint.

Dror Freirich, Tomer Michaeli, Ron Meir

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Discrete-Time Kalman Filter Error Bounds in the Presence of Misspecified Measurements.

Ron Teichner, Ron Meir

Proceedings of the European Control Conference, 2023

Adaptive Meta-Learning via data-dependent PAC-Bayes bounds.

Lior Friedman, Ron Meir

Proceedings of the Conference on Lifelong Learning Agents, 2023

Emergent Quantized Communication.

Boaz Carmeli, Ron Meir, Yonatan Belinkov

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Online Meta-Learning in Adversarial Multi-Armed Bandits.

Ilya Osadchiy, Kfir Y. Levy, Ron Meir

CoRR, 2022

Integral Probability Metrics PAC-Bayes Bounds.

Ron Amit, Baruch Epstein, Shay Moran, Ron Meir

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Enhancing Causal Estimation through Unlabeled Offline Data.

Ron Teichner, Danny Eytan, Ron Meir

Proceedings of the 7th International Conference on Frontiers of Signal Processing, 2022

Metalearning Linear Bandits by Prior Update.

Amit Peleg, Naama Pearl, Ron Meir

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

A Theory of the Distortion-Perception Tradeoff in Wasserstein Space.

Dror Freirich, Tomer Michaeli, Ron Meir

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Ensemble Bootstrapping for Q-Learning.

Oren Peer, Chen Tessler, Nadav Merlis, Ron Meir

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Optimal Multivariate Tuning with Neuron-Level and Population-Level Energy Constraints.

Yuval Harel, Ron Meir

Neural Comput., 2020

Option Discovery in the Absence of Rewards with Manifold Analysis.

Amitay Bar, Ronen Talmon, Ron Meir

Proceedings of the 37th International Conference on Machine Learning, 2020

Discount Factor as a Regularizer in Reinforcement Learning.

Ron Amit, Ron Meir, Kamil Ciosek

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

PAC Guarantees for Concurrent Reinforcement Learning with Restricted Communication.

Or Raveh, Ron Meir

CoRR, 2019

Generalization Bounds For Unsupervised and Semi-Supervised Learning With Autoencoders.

Baruch Epstein, Ron Meir

CoRR, 2019

Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN.

Dror Freirich, Tzahi Shimkin, Ron Meir, Aviv Tamar

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Optimal Decoding of Dynamic Stimuli by Heterogeneous Populations of Spiking Neurons: A Closed-Form Approximation.

Yuval Harel, Ron Meir, Manfred Opper

Neural Comput., 2018

Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN.

Dror Freirich, Ron Meir, Aviv Tamar

CoRR, 2018

Joint Autoencoders: A Flexible Meta-learning Framework.

Baruch Epstein, Ron Meir, Tomer Michaeli

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory.

Ron Amit, Ron Meir

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Lifelong Learning by Adjusting Priors.

Ron Amit, Ron Meir

CoRR, 2017

Integer Forcing: Effective SNR Distribution and Practical Block-Based Schemes.

Ron Meir, Omer Gurewitz, Asaf Cohen

CoRR, 2017

Joint auto-encoders: a flexible multi-task learning framework.

Baruch Epstein, Ron Meir, Tomer Michaeli

CoRR, 2017

Learning an attention model in an artificial visual system.

Alon Hazan, Yuval Harel, Ron Meir

CoRR, 2017

2016

Hierarchical Coupled-Geometry Analysis for Neuronal Structure and Activity Pattern Discovery.

Gal Mishne, Ronen Talmon, Ron Meir, Jackie Schiller, Maria Lavzin, Uri Dubin, Ronald R. Coifman

IEEE J. Sel. Top. Signal Process., 2016

2015

A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding.

Yuval Harel, Ron Meir, Manfred Opper

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

The neuronal response at extended timescales: a linearized spiking input-output relation.

Daniel Soudry, Ron Meir

Frontiers Comput. Neurosci., 2014

The neuronal response at extended timescales: long-term correlations without long-term memory.

Daniel Soudry, Ron Meir

Frontiers Comput. Neurosci., 2014

Optimal Population Codes for Control and Estimation.

Alex K. Susemihl, Ron Meir, Manfred Opper

CoRR, 2014

Optimal Neural Codes for Control and Estimation.

Alex K. Susemihl, Ron Meir, Manfred Opper

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights.

Daniel Soudry, Itay Hubara, Ron Meir

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2012

Integrating a Partial Model into Model Free Reinforcement Learning.

Aviv Tamar, Dotan Di Castro, Ron Meir

J. Mach. Learn. Res., 2012

Conductance-Based Neuron Models and the Slow Dynamics of Excitability.

Daniel Soudry, Ron Meir

Frontiers Comput. Neurosci., 2012

2011

Delayed feedback control requires an internal forward model.

Dmitry Volkinshtein, Ron Meir

Biol. Cybern., 2011

Analytical Results for the Error in Filtering of Gaussian Processes.

Alex K. Susemihl, Ron Meir, Manfred Opper

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Integrating Partial Model Knowledge in Model Free RL Algorithms.

Aviv Tamar, Dotan Di Castro, Ron Meir

Proceedings of the 28th International Conference on Machine Learning, 2011

2010

A Convergent Online Single Time Scale Actor Critic Algorithm.

Dotan Di Castro, Ron Meir

J. Mach. Learn. Res., 2010

Error-Based Analysis of Optimal Tuning Functions Explains Phenomena Observed in Sensory Neurons.

Steve Yaeli, Ron Meir

Frontiers Comput. Neurosci., 2010

History-Dependent Dynamics in a Generic Model of Ion Channels - An Analytic Study.

Daniel Soudry, Ron Meir

Frontiers Comput. Neurosci., 2010

2009

A sparsity driven kernel machine based on minimizing a generalization error bound.

Dori Peleg, Ron Meir

Pattern Recognit., 2009

Delays and Oscillations in Networks of Spiking Neurons: A Two-Timescale Analysis.

Dotan Di Castro, Ron Meir, Irad Yavneh

Neural Comput., 2009

Bayesian Filtering in Spiking Neural Networks: Noise, Adaptation, and Multisensory Integration.

Omer Bobrowski, Ron Meir, Yonina C. Eldar

Neural Comput., 2009

On the precarious path of reverse neuro-engineering.

Shimon Marom, Ron Meir, Erez Braun, Asaf Gal, Einat Kermany, Danny Eytan

Frontiers Comput. Neurosci., 2009

2008

A bilinear formulation for vector sparsity optimization.

Dori Peleg, Ron Meir

Signal Process., 2008

Selective Adaptation in Networks of Heterogeneous Populations: Model, Simulation, and Experiment.

Avner Wallach, Danny Eytan, Shimon Marom, Ron Meir

PLoS Comput. Biol., 2008

Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation.

Dotan Di Castro, Dmitry Volkinshtein, Ron Meir

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007

Size-density spectra and their application to image classification.

Igor Zingman, Ron Meir, Ran El-Yaniv

Pattern Recognit., 2007

Reinforcement Learning, Spike-Time-Dependent Plasticity, and the BCM Rule.

Dorit Baras, Ron Meir

Neural Comput., 2007

A neural network implementing optimal state estimation based on dynamic spike train decoding.

Omer Bobrowski, Ron Meir, Shy Shoham, Yonina C. Eldar

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2005

Semantic-oriented 3d shape retrieval using relevance feedback.

George Leifman, Ron Meir, Ayellet Tal

Vis. Comput., 2005

Reinforcement learning with Gaussian processes.

Yaakov Engel, Shie Mannor, Ron Meir

Proceedings of the Machine Learning, 2005

2004

The kernel recursive least-squares algorithm.

Yaakov Engel, Shie Mannor, Ron Meir

IEEE Trans. Signal Process., 2004

Explicit Learning Curves for Transduction and Application to Clustering and Compression Algorithms.

Philip Derbeko, Ran El-Yaniv, Ron Meir

J. Artif. Intell. Res., 2004

A Feature Selection Algorithm Based on the Global Minimization of a Generalization Error Bound.

Dori Peleg, Ron Meir

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Data Dependent Risk Bounds for Hierarchical Mixture of Experts Classifiers.

Arik Azran, Ron Meir

Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004

2003

Generalization Error Bounds for Bayesian Mixture Algorithms.

Ron Meir, Tong Zhang

J. Mach. Learn. Res., 2003

Greedy Algorithms for Classification -- Consistency, Convergence Rates, and Adaptivity.

Shie Mannor, Ron Meir, Tong Zhang

J. Mach. Learn. Res., 2003

Towards Behaviometric Security Systems: Learning to Identify a Typist.

Mordechai Nisenson, Ido Yariv, Ran El-Yaniv, Ron Meir

Proceedings of the Knowledge Discovery in Databases: PKDD 2003, 2003

Error Bounds for Transductive Learning via Compression and Clustering.

Philip Derbeko, Ran El-Yaniv, Ron Meir

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Bayes Meets Bellman: The Gaussian Process Approach to Temporal Difference Learning.

Yaakov Engel, Shie Mannor, Ron Meir

Proceedings of the Machine Learning, 2003

Data-Dependent Bounds for Multi-category Classification Based on Convex Losses.

Ilya Desyatnikov, Ron Meir

Proceedings of the Computational Learning Theory and Kernel Machines, 2003

2002

On the Existence of Linear Weak Learners and Applications to Boosting.

Shie Mannor, Ron Meir

Mach. Learn., 2002

Data-Dependent Bounds for Bayesian Mixture Methods.

Ron Meir, Tong Zhang

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

An Introduction to Boosting and Leveraging.

Ron Meir, Gunnar Rätsch

Proceedings of the Advanced Lectures on Machine Learning, 2002

Sparse Online Greedy Support Vector Regression.

Yaakov Engel, Shie Mannor, Ron Meir

Proceedings of the Machine Learning: ECML 2002, 2002

Variance Optimized Bagging.

Philip Derbeko, Ran El-Yaniv, Ron Meir

Proceedings of the Machine Learning: ECML 2002, 2002

The Consistency of Greedy Algorithms for Classification.

Shie Mannor, Ron Meir, Tong Zhang

Proceedings of the Computational Learning Theory, 2002

2001

Lower bounds for multivariate approximation by affine-invariant dictionaries.

Vitaly Maiorov, Ron Meir

IEEE Trans. Inf. Theory, 2001

Best estimated inverse versus inverse of the best estimator.

Amir Karniel, Ron Meir, Gideon F. Inbar

Neural Networks, 2001

Polyhedral mixture of linear experts for many-to-one mapping inversion and multiple controllers.

Amir Karniel, Ron Meir, Gideon F. Inbar

Neurocomputing, 2001

Geometric Bounds for Generalization in Boosting.

Shie Mannor, Ron Meir

Proceedings of the Computational Learning Theory, 2001

2000

On the optimality of neural-network approximation using incremental algorithms.

Ron Meir, V. E. Maiorov

IEEE Trans. Neural Networks Learn. Syst., 2000

Nonparametric Time Series Prediction Through Adaptive Model Selection.

Ron Meir

Mach. Learn., 2000

On the near optimality of the stochastic approximation of smooth functions by neural networks.

Vitaly Maiorov, Ron Meir

Adv. Comput. Math., 2000

Weak Learners and Improved Rates of Convergence in Boosting.

Shie Mannor, Ron Meir

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

Localized Boosting.

Ron Meir, Ran El-Yaniv, Shai Ben-David

Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 2000

1999

Distortion bounds for vector quantizers with finite codebook size.

Ron Meir, Vitaly Maiorov

IEEE Trans. Inf. Theory, 1999

Exploiting the virtue of redundancy.

Amir Karniel, Ron Meir, Gideon F. Inbar

Proceedings of the International Joint Conference Neural Networks, 1999

1998

Approximation bounds for smooth functions in C(R^d) by neural and mixture networks.

V. E. Maiorov, R. S. Meir

IEEE Trans. Neural Networks, 1998

Error Bounds for Functional Approximation and Estimation Using Mixtures of Experts.

Assaf J. Zeevi, Ron Meir, Vitaly Maiorov

IEEE Trans. Inf. Theory, 1998

Almost Linear VC-Dimension Bounds for Piecewise Polynomial Networks.

Peter L. Bartlett, Vitaly Maiorov, Ron Meir

Neural Comput., 1998

On the Optimality of Incremental Neural Network Algorithms.

Ron Meir, Vitaly Maiorov

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

Polyhedral mixture of linear experts for many-to-one mapping inversion.

Amir Karniel, Ron Meir, Gideon F. Inbar

Proceedings of the 6th European Symposium on Artificial Neural Networks, 1998

1997

Density Estimation Through Convex Combinations of Densities: Approximation and Estimation Bounds.

Assaf J. Zeevi, Ronny Meir

Neural Networks, 1997

Structural Risk Minimization for Nonparametric Time Series Prediction.

Ron Meir

Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Performance Bounds for Nonlinear Time Series Prediction.

Ron Meir

Proceedings of the Tenth Annual Conference on Computational Learning Theory, 1997

1996

Time Series Prediction using Mixtures of Experts.

Assaf J. Zeevi, Ron Meir, Robert J. Adler

Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Towards Robust Model Selection Using Estimation and Approximation Error Bounds.

Joel Ratsaby, Ron Meir, Vitaly Maiorov

Proceedings of the Ninth Annual Conference on Computational Learning Theory, 1996

1995

Empirical Risk Minimization versus Maximum-Likelihood Estimation: A Case Study.

Ronny Meir

Neural Comput., 1995

On the Stochastic Complexity of Learning Realizable and Unrealizable Rules.

Ronny Meir, Neri Merhav

Mach. Learn., 1995

1994

Bias, Variance and the Combination of Least Squares Estimators.

Ronny Meir

Proceedings of the Advances in Neural Information Processing Systems 7, 1994

1992

A Parallel Gradient Descent Method for Learning in Analog VLSI Neural Networks.

Joshua Alspector, Ronny Meir, Ben P. Yuhas, Anthony Jayakumar, D. Lippe

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

On Learning Noisy Threshold Functions with Finite Precision Weights.

Ronny Meir, José F. Fontanari

Proceedings of the Fifth Annual ACM Conference on Computational Learning Theory, 1992

1991

On Deriving Deterministic Learning Rules from Stochastic Systems.

Ronny Meir

Int. J. Neural Syst., 1991

1990

Computing with Arrays of Coupled Oscillators: An Application to Preattentive Texture Discrimination.

Pierre Baldi, Ronny Meir

Neural Comput., 1990

The Effect of Learning on the Evolution of Asexual Populations.

José F. Fontanari, Ron Meir

Complex Syst., 1990

Relaxation Networks for Large Supervised Learning Problems.

Joshua Alspector, Robert B. Allen, Anthony Jayakumar, Torsten Zeppenfeld, Ronny Meir

Proceedings of the Advances in Neural Information Processing Systems 3, 1990

1988

Learning by Choice of Internal Representations.

Tal Grossman, Ronny Meir, Eytan Domany

Complex Syst., 1988