← Authors

Ron Meir

26 papers · 2003–2026 · 8 conferences · across top CS/AI conferences

Achievements

πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (15) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (8) πŸƒ Academic Marathon (22) 🐝 Cross-Pollinator (8) 🌈 Renaissance Researcher (8) 🌟 Keyword Trendsetter Combo (7) πŸ† Keyword Champion πŸ† Grand Slam πŸ’Ž Century Club (25) πŸ—ƒοΈ Keyword Collector (134) πŸ”₯ Unstoppable (8) πŸ“ˆ Trend Setter

Conferences

NIPS (10) ICML (5) JMLR (4) AAAI (3) ACL (1) AISTATS (1) COLT (1) ICLR (1)

Top co-authors

Boaz Carmeli (4) Yonatan Belinkov (4) Manfred Opper (3) Ron Amit (3) Dror Freirich (3) Tong Zhang (2) Tomer Michaeli (2) Dotan Di Castro (2) Alex K. Susemihl (2) Aviv Tamar (2)

Keywords

state estimation (5) reinforcement learning (4) point process (3) emergent communication (3) bayesian inference (2) representation learning (2) wasserstein distance (2) perceptual quality (2) neural network (2) multi-armed bandit (2) online learning (2) regret bound (2) temporal difference (2) policy gradient (2) optimal filtering (2) neural coding (1) temporal difference learning (1) image restoration (1) unsupervised learning (1) graph laplacian (1)

Papers

Unsupervised Feature Selection Through Group Discovery AAAI 2026
Unsupervised Translation of Emergent Communication AAAI 2025
CtD: Composition through Decomposition in Emergent Communication ICLR 2025
Concept-Best-Matching: Evaluating Compositionality In Emergent Communication ACL 2024
Statistical curriculum learning: An elimination algorithm achieving an oracle risk COLT 2024
Meta-Learning Adversarial Bandit Algorithms NIPS 2023
Emergent Quantized Communication AAAI 2023
Perceptual Kalman Filters: Online State Estimation under a Perfect Perceptual-Quality Constraint NIPS 2023
Metalearning Linear Bandits by Prior Update AISTATS 2022
Integral Probability Metrics PAC-Bayes Bounds NIPS 2022
A Theory of the Distortion-Perception Tradeoff in Wasserstein Space NIPS 2021
Ensemble Bootstrapping for Q-Learning ICML 2021
Discount Factor as a Regularizer in Reinforcement Learning ICML 2020
Option Discovery in the Absence of Rewards with Manifold Analysis ICML 2020
Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN ICML 2019
Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory ICML 2018
A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding NIPS 2015
Optimal Neural Codes for Control and Estimation NIPS 2014
Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights NIPS 2014
Integrating a Partial Model into Model Free Reinforcement Learning JMLR 2012
Analytical Results for the Error in Filtering of Gaussian Processes NIPS 2011
A Convergent Online Single Time Scale Actor Critic Algorithm JMLR 2010
Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation NIPS 2008
A neural network implementing optimal state estimation based on dynamic spike train decoding NIPS 2007
Generalization Error Bounds for Bayesian Mixture Algorithms JMLR 2003
Greedy Algorithms for Classification -- Consistency, Convergence Rates, and Adaptivity JMLR 2003