Ron Meir

ORCID

Publication Activity (10 Years)

Years Active: 1990-2024
Publications (10 Years): 44

Top Venues

Publications

Ron Teichner, Ron Meir, Michael Margaliot
Analysis of the Identifying Regulation With Adversarial Surrogates Algorithm. IEEE Control. Syst. Lett. 8 (2024)
Dror Freirich, Nir Weinberger, Ron Meir
Characterization of the Distortion-Perception Tradeoff for Finite Channels with Arbitrary Metrics. CoRR (2024)
Lior Friedman, Ron Meir
Data-dependent and Oracle Bounds on Forgetting in Continual Learning. CoRR (2024)
Omer Cohen, Ron Meir, Nir Weinberger
Statistical curriculum learning: An elimination algorithm achieving an oracle risk. CoRR (2024)
Ron Teichner, Ron Meir, Michael Margaliot
Analysis of the Identifying Regulation with Adversarial Surrogates Algorithm. CoRR (2024)
Omer Cohen, Ron Meir, Nir Weinberger
Statistical curriculum learning: An elimination algorithm achieving an oracle risk. COLT (2024)
Boaz Carmeli, Yonatan Belinkov, Ron Meir
Concept-Best-Matching: Evaluating Compositionality in Emergent Communication. CoRR (2024)
Boaz Carmeli, Yonatan Belinkov, Ron Meir
Concept-Best-Matching: Evaluating Compositionality In Emergent Communication. ACL (Findings) (2024)
Boaz Carmeli, Ron Meir, Yonatan Belinkov
Emergent Quantized Communication. AAAI (2023)
Ron Teichner, Ron Meir
Discrete-Time Kalman Filter Error Bounds in the Presence of Misspecified Measurements. ECC (2023)
Misha Khodak, Ilya Osadchiy, Keegan Harris, Maria-Florina Balcan, Kfir Y. Levy, Ron Meir, Steven Z. Wu
Meta-Learning Adversarial Bandit Algorithms. NeurIPS (2023)
Mikhail Khodak, Ilya Osadchiy, Keegan Harris, Maria-Florina Balcan, Kfir Y. Levy, Ron Meir, Zhiwei Steven Wu
Meta-Learning Adversarial Bandit Algorithms. CoRR (2023)
Lior Friedman, Ron Meir
Adaptive Meta-Learning via data-dependent PAC-Bayes bounds. CoLLAs (2023)
Dror Freirich, Tomer Michaeli, Ron Meir
Perceptual Kalman Filters: Online State Estimation under a Perfect Perceptual-Quality Constraint. CoRR (2023)
Dror Freirich, Tomer Michaeli, Ron Meir
Perceptual Kalman Filters: Online State Estimation under a Perfect Perceptual-Quality Constraint. NeurIPS (2023)
Ron Teichner, Naama Brenner, Ron Meir
Identifying Dynamic Regulation with Adversarial Surrogates. CoRR (2023)
Ilya Osadchiy, Kfir Y. Levy, Ron Meir
Online Meta-Learning in Adversarial Multi-Armed Bandits. CoRR (2022)
Ron Teichner, Danny Eytan, Ron Meir
Enhancing Causal Estimation through Unlabeled Offline Data. ICFSP (2022)
Amit Peleg, Naama Pearl, Ron Meir
Metalearning Linear Bandits by Prior Update. AISTATS (2022)
Ron Amit, Baruch Epstein, Shay Moran, Ron Meir
Integral Probability Metrics PAC-Bayes Bounds. CoRR (2022)
Ron Amit, Baruch Epstein, Shay Moran, Ron Meir
Integral Probability Metrics PAC-Bayes Bounds. NeurIPS (2022)
Boaz Carmeli, Ron Meir, Yonatan Belinkov
Emergent Quantized Communication. CoRR (2022)
Amit Peleg, Naama Pearl, Ron Meir
Metalearning Linear Bandits by Prior Update. CoRR (2021)
Oren Peer, Chen Tessler, Nadav Merlis, Ron Meir
Ensemble Bootstrapping for Q-Learning. ICML (2021)
Oren Peer, Chen Tessler, Nadav Merlis, Ron Meir
Ensemble Bootstrapping for Q-Learning. CoRR (2021)
Dror Freirich, Tomer Michaeli, Ron Meir
A Theory of the Distortion-Perception Tradeoff in Wasserstein Space. NeurIPS (2021)
Dror Freirich, Tomer Michaeli, Ron Meir
A Theory of the Distortion-Perception Tradeoff in Wasserstein Space. CoRR (2021)
Yuval Harel, Ron Meir
Optimal Multivariate Tuning with Neuron-Level and Population-Level Energy Constraints. Neural Comput. 32 (4) (2020)
Ron Amit, Ron Meir, Kamil Ciosek
Discount Factor as a Regularizer in Reinforcement Learning. ICML (2020)
Amitay Bar, Ronen Talmon, Ron Meir
Option Discovery in the Absence of Rewards with Manifold Analysis. CoRR (2020)
Ron Amit, Ron Meir, Kamil Ciosek
Discount Factor as a Regularizer in Reinforcement Learning. CoRR (2020)
Amitay Bar, Ronen Talmon, Ron Meir
Option Discovery in the Absence of Rewards with Manifold Analysis. ICML (2020)
Or Raveh, Ron Meir
PAC Guarantees for Concurrent Reinforcement Learning with Restricted Communication. CoRR (2019)
Dror Freirich, Tzahi Shimkin, Ron Meir, Aviv Tamar
Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN. ICML (2019)
Baruch Epstein, Ron Meir
Generalization Bounds For Unsupervised and Semi-Supervised Learning With Autoencoders. CoRR (2019)
Dror Freirich, Ron Meir, Aviv Tamar
Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN. CoRR (2018)
Yuval Harel, Ron Meir, Manfred Opper
Optimal Decoding of Dynamic Stimuli by Heterogeneous Populations of Spiking Neurons: A Closed-Form Approximation. Neural Comput. 30 (8) (2018)
Baruch Epstein, Ron Meir, Tomer Michaeli
Joint Autoencoders: A Flexible Meta-learning Framework. ECML/PKDD (1) (2018)
Ron Amit, Ron Meir
Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory. ICML (2018)
Ron Amit, Ron Meir
Lifelong Learning by Adjusting Priors. CoRR (2017)
Alon Hazan, Yuval Harel, Ron Meir
Learning an attention model in an artificial visual system. CoRR (2017)
Baruch Epstein, Ron Meir, Tomer Michaeli
Joint auto-encoders: a flexible multi-task learning framework. CoRR (2017)
Ron Meir, Omer Gurewitz, Asaf Cohen
Integer Forcing: Effective SNR Distribution and Practical Block-Based Schemes. CoRR (2017)
Gal Mishne, Ronen Talmon, Ron Meir, Jackie Schiller, Maria Lavzin, Uri Dubin, Ronald R. Coifman
Hierarchical Coupled-Geometry Analysis for Neuronal Structure and Activity Pattern Discovery. IEEE J. Sel. Top. Signal Process. 10 (7) (2016)
Yuval Harel, Ron Meir, Manfred Opper
A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding. NIPS (2015)
Daniel Soudry, Itay Hubara, Ron Meir
Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights. NIPS (2014)
Alex K. Susemihl, Ron Meir, Manfred Opper
Optimal Neural Codes for Control and Estimation. NIPS (2014)
Daniel Soudry, Ron Meir
The neuronal response at extended timescales: a linearized spiking input-output relation. Frontiers Comput. Neurosci. 8 (2014)
Alex K. Susemihl, Ron Meir, Manfred Opper
Optimal Population Codes for Control and Estimation. CoRR (2014)
Daniel Soudry, Ron Meir
The neuronal response at extended timescales: long-term correlations without long-term memory. Frontiers Comput. Neurosci. 8 (2014)
Daniel Soudry, Ron Meir
Conductance-Based Neuron Models and the Slow Dynamics of Excitability. Frontiers Comput. Neurosci. 6 (2012)
Aviv Tamar, Dotan Di Castro, Ron Meir
Integrating a Partial Model into Model Free Reinforcement Learning. J. Mach. Learn. Res. 13 (2012)
Dmitry Volkinshtein, Ron Meir
Delayed feedback control requires an internal forward model. Biol. Cybern. 105 (1) (2011)
Aviv Tamar, Dotan Di Castro, Ron Meir
Integrating Partial Model Knowledge in Model Free RL Algorithms. ICML (2011)
Philip Derbeko, Ran El-Yaniv, Ron Meir
Explicit Learning Curves for Transduction and Application to Clustering and Compression Algorithms CoRR (2011)
Alex K. Susemihl, Ron Meir, Manfred Opper
Analytical Results for the Error in Filtering of Gaussian Processes. NIPS (2011)
Dotan Di Castro, Ron Meir
A Convergent Online Single Time Scale Actor Critic Algorithm. J. Mach. Learn. Res. 11 (2010)
Steve Yaeli, Ron Meir
Error-Based Analysis of Optimal Tuning Functions Explains Phenomena Observed in Sensory Neurons. Frontiers Comput. Neurosci. 4 (2010)
Daniel Soudry, Ron Meir
History-Dependent Dynamics in a Generic Model of Ion Channels - An Analytic Study. Frontiers Comput. Neurosci. 4 (2010)
Shimon Marom, Ron Meir, Erez Braun, Asaf Gal, Einat Kermany, Danny Eytan
On the precarious path of reverse neuro-engineering. Frontiers Comput. Neurosci. 3 (2009)
Dori Peleg, Ron Meir
A sparsity driven kernel machine based on minimizing a generalization error bound. Pattern Recognit. 42 (11) (2009)
Omer Bobrowski, Ron Meir, Yonina C. Eldar
Bayesian Filtering in Spiking Neural Networks: Noise, Adaptation, and Multisensory Integration. Neural Comput. 21 (5) (2009)
Dotan Di Castro, Ron Meir, Irad Yavneh
Delays and Oscillations in Networks of Spiking Neurons: A Two-Timescale Analysis. Neural Comput. 21 (4) (2009)
Avner Wallach, Danny Eytan, Shimon Marom, Ron Meir
Selective Adaptation in Networks of Heterogeneous Populations: Model, Simulation, and Experiment. PLoS Comput. Biol. 4 (2) (2008)
Dori Peleg, Ron Meir
A bilinear formulation for vector sparsity optimization. Signal Process. 88 (2) (2008)
Dotan Di Castro, Dmitry Volkinshtein, Ron Meir
Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation. NIPS (2008)
Igor Zingman, Ron Meir, Ran El-Yaniv
Size-density spectra and their application to image classification. Pattern Recognit. 40 (12) (2007)
Dorit Baras, Ron Meir
Reinforcement Learning, Spike-Time-Dependent Plasticity, and the BCM Rule. Neural Comput. 19 (8) (2007)
Omer Bobrowski, Ron Meir, Shy Shoham, Yonina C. Eldar
A neural network implementing optimal state estimation based on dynamic spike train decoding. NIPS (2007)
Yaakov Engel, Shie Mannor, Ron Meir
Reinforcement learning with Gaussian processes. ICML (2005)
George Leifman, Ron Meir, Ayellet Tal
Semantic-oriented 3d shape retrieval using relevance feedback. Vis. Comput. 21 (8-10) (2005)
Dori Peleg, Ron Meir
A Feature Selection Algorithm Based on the Global Minimization of a Generalization Error Bound. NIPS (2004)
Yaakov Engel, Shie Mannor, Ron Meir
The kernel recursive least-squares algorithm. IEEE Trans. Signal Process. 52 (8) (2004)
Philip Derbeko, Ran El-Yaniv, Ron Meir
Explicit Learning Curves for Transduction and Application to Clustering and Compression Algorithms. J. Artif. Intell. Res. 22 (2004)
Arik Azran, Ron Meir
Data Dependent Risk Bounds for Hierarchical Mixture of Experts Classifiers. COLT (2004)
Ilya Desyatnikov, Ron Meir
Data-Dependent Bounds for Multi-category Classification Based on Convex Losses. COLT (2003)
Mordechai Nisenson, Ido Yariv, Ran El-Yaniv, Ron Meir
Towards Behaviometric Security Systems: Learning to Identify a Typist. PKDD (2003)
Yaakov Engel, Shie Mannor, Ron Meir
Bayes Meets Bellman: The Gaussian Process Approach to Temporal Difference Learning. ICML (2003)
Ron Meir, Tong Zhang
Generalization Error Bounds for Bayesian Mixture Algorithms. J. Mach. Learn. Res. 4 (2003)
Philip Derbeko, Ran El-Yaniv, Ron Meir
Error Bounds for Transductive Learning via Compression and Clustering. NIPS (2003)
Shie Mannor, Ron Meir, Tong Zhang
Greedy Algorithms for Classification -- Consistency, Convergence Rates, and Adaptivity. J. Mach. Learn. Res. 4 (2003)
Shie Mannor, Ron Meir
On the Existence of Linear Weak Learners and Applications to Boosting. Mach. Learn. 48 (1-3) (2002)
Ron Meir, Gunnar Rätsch
An Introduction to Boosting and Leveraging. Machine Learning Summer School (2002)
Shie Mannor, Ron Meir, Tong Zhang
The Consistency of Greedy Algorithms for Classification. COLT (2002)
Yaakov Engel, Shie Mannor, Ron Meir
Sparse Online Greedy Support Vector Regression. ECML (2002)
Ron Meir, Tong Zhang
Data-Dependent Bounds for Bayesian Mixture Methods. NIPS (2002)
Philip Derbeko, Ran El-Yaniv, Ron Meir
Variance Optimized Bagging. ECML (2002)
Vitaly Maiorov, Ron Meir
Lower bounds for multivariate approximation by affine-invariant dictionaries. IEEE Trans. Inf. Theory 47 (4) (2001)
Amir Karniel, Ron Meir, Gideon F. Inbar
Polyhedral mixture of linear experts for many-to-one mapping inversion and multiple controllers. Neurocomputing 37 (1-4) (2001)
Amir Karniel, Ron Meir, Gideon F. Inbar
Best estimated inverse versus inverse of the best estimator. Neural Networks 14 (9) (2001)
Shie Mannor, Ron Meir
Geometric Bounds for Generalization in Boosting. COLT/EuroCOLT (2001)
Ron Meir, Ran El-Yaniv, Shai Ben-David
Localized Boosting. COLT (2000)
Shie Mannor, Ron Meir
Weak Learners and Improved Rates of Convergence in Boosting. NIPS (2000)
Vitaly Maiorov, Ron Meir
On the near optimality of the stochastic approximation of smooth functions by neural networks. Adv. Comput. Math. 13 (1) (2000)
Ron Meir, V. E. Maiorov
On the optimality of neural-network approximation using incremental algorithms. IEEE Trans. Neural Networks Learn. Syst. 11 (2) (2000)
Ron Meir
Nonparametric Time Series Prediction Through Adaptive Model Selection. Mach. Learn. 39 (1) (2000)
Amir Karniel, Ron Meir, Gideon F. Inbar
Exploiting the virtue of redundancy. IJCNN (1999)
Ron Meir, Vitaly Maiorov
Distortion bounds for vector quantizers with finite codebook size. IEEE Trans. Inf. Theory 45 (5) (1999)
Amir Karniel, Ron Meir, Gideon F. Inbar
Polyhedral mixture of linear experts for many-to-one mapping inversion. ESANN (1998)
Assaf J. Zeevi, Ron Meir, Vitaly Maiorov
Error Bounds for Functional Approximation and Estimation Using Mixtures of Experts. IEEE Trans. Inf. Theory 44 (3) (1998)

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Publication Activity (10 Years)

Top Topics

Top Venues

Ron Meir