Ron Amit

I am a PhD Graduate from the Technion - Israel Institute of Technology, where I was advised by Prof. Ron Meir,  in the Reinforcement Learning Research Labs.  

• ‪Ron Amit‬ - ‪Google Scholar‬

• Linkedin

• https://github.com/ron-amit

PhD thesis : Knowledge Transfer in Machine Learning: Theory and Algorithms, 2023

Publications:

• R. Amit,  B. Epstein, S. Moran, R. Meir, "Integral Probability Metrics PAC-Bayes Bounds",  NeurIPS 2022 [OpenReview] [Code] [Slides] [video]

• R. Amit, R. Meir, K. Ciosek, “Discount Factor as a Regularizer in Reinforcement Learning”,  ICML 2020  [Paper]  [Code]  [Slides]  [Video] [bib]

• R. Amit, R. Meir, “Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory”,  ICML 2018   [Paper]    [Code]  [Slides-Short] [Slides-long]   [Video]  [bib] [reviews]

• R. Amit, G. Mishne, R. Talmon, “Improving resolution in supervised patch-based target detection",  ICASSP 2016. [Paper]

• T. Chernyakova, Y. C. Eldar, R. Amit , "Fourier Domain Beamforming for Medical Ultrasound", ICASSP 2013.  [Paper]

Patents:

• Y. C. Eldar, T. Chernyakova,  R. Amit. "Frequency-domain beamforming." U.S. Patent Application No. 14/097,281.

Presentations:

• State Space Models & Mamba 2024 

• PhD graduation Seminar:  PAC-Bayes - Extensions to Integral Probability Metrics and to Meta-Learning  2022 [PDF] [PPTX]

• Discount Factor as a Regularizer in Reinforcement Learning   2020

• Meta-Learning by Adjusting Priors based on Extended PAC-Bayes Theory   2018

• Distributional Reinforcement Learning 2018

• PAC-Bayes bounds and application in deep learning 2017

• Variational Inference  and Deep Generative Models  2016 

• Dimensionality Reduction 2014   (PCA, Laplacian Eigenmaps, Diffusion Maps)

• Optimization and Non-Linear Least Squares 2013   

Useful stuff:

• Python environment setup and workflow  

• macOS tips  

Personal Projects:

• Bayesian Neural network implementation in Matlab 2016

• Multi-model Tracking (Kalman , IMM  and LMMSE filters) 2014   Report    Code