Ron Meir

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Optimal Population Codes for Control and Estimation pdf

Alex K. Susemihl, Ron Meir, Manfred Opper, 2014, ArXiv.

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

Shie Mannor, Ron Meir, Tong Zhang, 2003, J. Mach. Learn. Res..

The neuron's response at extended timescales

Ron Meir, Daniel Soudry, 2013 .

Performance bounds for nonlinear time series prediction

Ron Meir, 1997, COLT '97.

Towards robust model selection using estimation and approximation error bounds

Ron Meir, Joel Ratsaby, Vitaly Maiorov, 1996, COLT '96.

Extracting grid cell characteristics from place cell inputs using non-negative principal component analysis

Ron Meir, Daniel Soudry, Yedidyah Dordek, 2016, eLife.

Best estimated inverse versus inverse of the best estimator

Ron Meir, Gideon F. Inbar, Amir Karniel, 2001, Neural Networks.

Finite sample bounds for time series prediction

Ron Meir, 1998 .

Weak Learners and Improved Rates of Convergence in Boosting

Shie Mannor, Ron Meir, 2000, NIPS.

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

Ron Meir, Baruch Epstein, R. Meir, 2019, ArXiv.

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

Ron Meir, Ilya Desyatnikov, R. Meir, 2003, COLT.

On the Optimality of Incremental Neural Network Algorithms

Ron Meir, Vitaly Maiorov, R. Meir, 1998, NIPS.

A generic model for selective adaptation in networks of heterogeneous populations

Ron Meir, Avner Wallach, Danny Eytan, 2007, BMC Neuroscience.

Evolving a learning algorithm for the binary perceptron

Ron Meir, José F. Fontanari, 1991 .

Exploiting the virtue of redundancy

Ron Meir, Gideon F. Inbar, Amir Karniel, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

A Convergent Online Single Time Scale Actor Critic Algorithm pdf

Ron Meir, Dotan Di Castro, R. Meir, 2009, J. Mach. Learn. Res..

Computing with Arrays of Coupled Oscillators

Joachim M. Buhmann, Pierre Baldi, Ron Meir, 1990 .

Analytical Results for the Error in Filtering of Gaussian Processes

Alex K. Susemihl, Ron Meir, Manfred Opper, 2011, NIPS.

Localized Boosting

Ran El-Yaniv, Shai Ben-David, Ron Meir, 2000, COLT.

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

Ron Meir, Dori Peleg, 2004, NIPS.

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

Ron Meir, 1995, Neural Computation.

Extracting grid characteristics from spatially distributed place cell inputs using non-negative PCA

Ron Meir, Yedidyah Dordek, Dori Derdikman, 2015, 1505.03711.

Learning from examples in weight-constrained neural networks

Ron Meir, José F. Fontanari, R. Meir, 1992 .

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

Ron Meir, Manfred Opper, Yuval Harel, 2015, NIPS.

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

Ron Meir, Omer Gurewitz, Asaf Cohen, 2017, ArXiv.

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

Pierre Baldi, Ron Meir, P. Baldi, 1990, Neural Computation.

Spiking input-output relation for general biophysical neuron models

Ron Meir, Daniel Soudry, R. Meir, 2012, 1207.6251.

Almost Linear VC-Dimension Bounds for Piecewise Polynomial Networks

Peter L. Bartlett, Ron Meir, Vitaly Maiorov, 1998, Neural Computation.

The Effect of Learning on the Evolution of Asexual Populations

Ron Meir, José F. Fontanari, R. Meir, 1990, Complex Syst..

An Introduction to Boosting and Leveraging

Gunnar Rätsch, Ron Meir, R. Meir, 2002, Machine Learning Summer School.

On Deriving Deterministic Learning Rules from Stochastic Systems

Ron Meir, 1991, Int. J. Neural Syst..

Size-density spectra and their application to image classification

Ran El-Yaniv, Ron Meir, Igor Zingman, 2007, Pattern Recognit..

Delayed feedback control requires an internal forward model

Ron Meir, Dmitry Volkinshtein, 2011, Biological Cybernetics.

Distortion bounds for vector quantizers with finite codebook size

Ron Meir, Vitaly Maiorov, R. Meir, 1999, IEEE Trans. Inf. Theory.

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

Ron Meir, Assaf J. Zeevi, R. Meir, 1997, Neural Networks.

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

Ron Meir, Dori Peleg, R. Meir, 2009, Pattern Recognit..

Towards Behaviometric Security Systems: Learning to Identify a Typist

Ran El-Yaniv, Ron Meir, Mordechai Nisenson, 2003, PKDD.

Conductance-Based Neuron Models and the Slow Dynamics of Excitability

Ron Meir, Daniel Soudry, R. Meir, 2012, Front. Comput. Neurosci..

Learning an attention model in an artificial visual system

Ron Meir, Yuval Harel, Alon Hazan, 2016, 2016 IEEE International Conference on the Science of Electrical Engineering (ICSEE).

Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation

Ron Meir, Dotan Di Castro, Dmitry Volkinshtein, 2008, NIPS.

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

Ron Meir, Tomer Michaeli, Baruch Epstein, 2017, ArXiv.

Tradeoffs and Constraints on Neural Representation in Networks of Cortical Neurons

Ron Meir, Danny Eytan, Asaf Gal, 2010, The Journal of Neuroscience.

Layered neural networks

Eytan Domany, Ron Meir, 1991 .

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

Ron Meir, Joshua Alspector, Ben P. Yuhas, 1992, NIPS.

Signatures of 3D Models for Retrieval

Ron Meir, Ayellet Tal, George Leifman, 2002 .

The kernel recursive least-squares algorithm

Shie Mannor, Ron Meir, Yaakov Engel, 2004, IEEE Transactions on Signal Processing.

Variance Optimized Bagging

Ran El-Yaniv, Ron Meir, Philip Derbeko, 2002, ECML.

Frontiers in Computational Neuroscience Computational Neuroscience Perspective Article on the Precarious Path of Reverse Neuro-engineering

Ron Meir, Danny Eytan, Asaf Gal, 2022 .

9. Layered Neural Networks

Eytan Domany, Ron Meir, 1991 .

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

Ron Meir, Manfred Opper, Yuval Harel, 2018, Neural Computation.

Data Dependent Risk Bounds for Hierarchical Mixture of Experts Classifiers

Ron Meir, Arik Azran, R. Meir, 2004, COLT.

Storing and Retrieving Information in a Layered Spin System

Ron Meir, Wolfgang Kinzel, Eytan Domany, 1986 .

Optimal Neural Codes for Control and Estimation

Alex K. Susemihl, Ron Meir, Manfred Opper, 2014, NIPS.

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

Ron Meir, Ron Amit, R. Meir, 2017, ICML.

Proceedings of the 18th annual conference on Learning Theory

Peter Auer, Ron Meir, P. Auer, 2005 .

Breast Cancer Diagnosis From Biopsy Images Using Generic Features and SVMs

Ron Kimmel, Ron Meir, Alexander Brook, 2006 .

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

Yonina C. Eldar, Ron Meir, Omer Bobrowski, 2009, Neural Computation.

Nonparametric Time Series Prediction Through Adaptive Model Selection

Ron Meir, R. Meir, 2000, Machine Learning.

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

Ronald R. Coifman, Ron Meir, Ronen Talmon, 2015, IEEE Journal of Selected Topics in Signal Processing.

Approximation bounds for smooth functions in C(Rd) by neural and mixture networks

Ron Meir, Vitaly Maiorov, R. Meir, 1998, IEEE Trans. Neural Networks.

Error Bounds for Transductive Learning via Compression and Clustering

Ran El-Yaniv, Ron Meir, Philip Derbeko, 2003, NIPS.

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

Ron Meir, Vitaly Maiorov, R. Meir, 2000, Adv. Comput. Math..

Mean Field Bayes Backpropagation: scalable training of multilayer neural networks with binary weights

Ron Meir, Daniel Soudry, 2013 .

Relaxation Networks for Large Supervised Learning Problems

Robert B. Allen, Ron Meir, Joshua Alspector, 1990, NIPS.

Semantic-oriented 3d shape retrieval using relevance feedback

Ron Meir, Ayellet Tal, George Leifman, 2005, The Visual Computer.

Data-Dependent Bounds for Bayesian Mixture Methods

Ron Meir, Tong Zhang, 2002, NIPS.

Learning by Choice of Internal Representations

Eytan Domany, Ron Meir, Tal Grossman, 1988, Complex Syst..

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

Ron Meir, Steve Yaeli, R. Meir, 2010, Front. Comput. Neurosci..

Integrating Partial Model Knowledge in Model Free RL Algorithms

Ron Meir, Dotan Di Castro, Aviv Tamar, 2011, ICML.

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

Ron Meir, Gideon F. Inbar, Amir Karniel, 2001, ESANN.

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

Ron Meir, Daniel Soudry, R. Meir, 2009, Front. Comput. Neurosci..

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

Irad Yavneh, Ron Meir, Dotan Di Castro, 2009, Neural Computation.

On learning noisy threshold functions with finite precision weights

Ron Meir, José F. Fontanari, 1992, COLT '92.

Reinforcement learning with Gaussian processes

Shie Mannor, Ron Meir, Yaakov Engel, 2005, ICML.

Joint Autoencoders: A Flexible Meta-learning Framework

Ron Meir, Tomer Michaeli, Baruch Epstein, 2018, ECML/PKDD.

Stochastic dynamics of a layered neural network. Exact solution

Eytan Domany, Ron Meir, 1987 .

On the optimality of neural-network approximation using incremental algorithms

Ron Meir, Vitaly Maiorov, R. Meir, 2000, IEEE Trans. Neural Networks Learn. Syst..

Lifelong Learning by Adjusting Priors pdf

Ron Meir, Ron Amit, R. Meir, 2018, ArXiv.

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

Yonina C. Eldar, Ron Meir, Shy Shoham, 2007, NIPS.

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

Ron Meir, Dorit Baras, R. Meir, 2007, Neural Computation.

A bilinear formulation for vector sparsity optimization

Ron Meir, Dori Peleg, R. Meir, 2008, Signal Process..

On the Existence of Linear Weak Learners and Applications to Boosting

Shie Mannor, Ron Meir, Shie Mannor, 2002, Machine Learning.

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

Ron Meir, Daniel Soudry, Itay Hubara, 2014, NIPS.

Direct reinforcement learning, spike time dependent plasticity and the BCM rule

Ron Meir, Dorit Barash, R. Meir, 2007, BMC Neuroscience.

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

Ron Meir, Daniel Soudry, R. Meir, 2014, Front. Comput. Neurosci..

Optimal encoding and decoding for point process observations: An approximate closed-form filter

Ron Meir, Manfred Opper, Yuval Harel, 2016, 2016 IEEE International Conference on the Science of Electrical Engineering (ICSEE).

Sparse Online Greedy Support Vector Regression

Shie Mannor, Ron Meir, Yaakov Engel, 2002, ECML.

Lifelong learning and inductive bias

Ron Meir, Ron Amit, 2019, Current Opinion in Behavioral Sciences.

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

Ran El-Yaniv, Ron Meir, Philip Derbeko, 2004, J. Artif. Intell. Res..

WEAK MODEL BASED APPROACH FOR FAULT DETECTION AND ISOLATION OF SENSORS IN FLIGHT CONTROL SYSTEMS

Moshe Idan, Ron Meir, Oded M. Golan, 2000 .

Generalization Error Bounds for Bayesian Mixture Algorithms

Ron Meir, Tong Zhang, Tong Zhang, 2003, J. Mach. Learn. Res..

Learning Theory, 18th Annual Conference on Learning Theory, COLT 2005, Bertinoro, Italy, June 27-30, 2005, Proceedings

Peter Auer, Ron Meir, 2005, COLT.

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

Ron Meir, Avner Wallach, Danny Eytan, 2008, PLoS Comput. Biol..

Lower bounds for multivariate approximation by affine-invariant dictionaries

Ron Meir, Vitaly Maiorov, R. Meir, 2001, IEEE Trans. Inf. Theory.

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

Shie Mannor, Ron Meir, Yaakov Engel, 2003, ICML.

Extensions of a solvable feed forward neural network

Ron Meir, 1988 .

The Consistency of Greedy Algorithms for Classification

Shie Mannor, Ron Meir, Tong Zhang, 2002, COLT.

Bias, Variance and the Combination of Least Squares Estimators

Ron Meir, R. Meir, 1994, NIPS.

Time Series Prediction using Mixtures of Experts

Ron Meir, Assaf J. Zeevi, Robert J. Adler, 1996, NIPS.

Error Bounds for Functional Approximation and Estimation Using Mixtures of Experts

Ron Meir, Vitaly Maiorov, Assaf J. Zeevi, 1998, IEEE Trans. Inf. Theory.

PAC Guarantees for Concurrent Reinforcement Learning with Restricted Communication pdf

Ron Meir, Or Raveh, 2019, ArXiv.

Geometric Bounds for Generalization in Boosting

Shie Mannor, Ron Meir, 2001, COLT/EuroCOLT.

Structural Risk Minimization for Nonparametric Time Series Prediction

Ron Meir, 1997, NIPS.

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

Ron Meir, Daniel Soudry, R. Meir, 2014, Front. Comput. Neurosci..

A two-way model for motor control of redundant systems

Ron Meir, Gideon F. Inbar, Amir Karniel, 2000, Proceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (Cat. No.00CH37143).

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

Ron Meir, Tomer Michaeli, Dror Freirich, 2021, NeurIPS.

Ensemble Bootstrapping for Q-Learning

Ron Meir, Chen Tessler, Nadav Merlis, 2021, ICML.

Metalearning Linear Bandits by Prior Update pdf

Ron Meir, Amit Peleg, Naama Pearl, 2021, ArXiv.

Finite Sample Size Results for Robust Model Selection; Application to Neural Networks

Ron Meir, Joel Ratsaby, 1995 .

An exact reduction of the master equation to a strictly stable system with an explicit expression for the stationary distribution

Ron Meir, Daniel Soudry, R. Meir, 2012, 1207.4436.

Dynamic state estimation based on Poisson spike trains—towards a theory of optimal encoding

Alex K. Susemihl, Ron Meir, Manfred Opper, 2012, 1209.5559.

Data compression and prediction in neural networks

Ron Meir, José F. Fontanari, 1993 .

Relevance Feedback for 3 D Shape Retrieval ∗

Ron Meir, Ayellet Tal, George Leifman, .

Signatures of 3 D Models for Retrieval 1

Ron Meir, Ayellet Tal, George Leifman, 2002 .