Yehuda Dar

According to our database, Yehuda Dar authored at least 22 papers between 2014 and 2023.

Collaborative distances:

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

2023

Recovery of Training Data from Overparameterized Autoencoders: An Inverse Problem Perspective.

Koren Abitbul, Yehuda Dar

CoRR, 2023

2022

Double Double Descent: On Generalization Errors in Transfer Learning between Linear Regression Tasks.

Yehuda Dar, Richard G. Baraniuk

SIAM J. Math. Data Sci., December, 2022

Overfreezing Meets Overparameterization: A Double Descent Perspective on Transfer Learning of Deep Neural Networks.

Yehuda Dar, Lorenzo Luzi, Richard G. Baraniuk

CoRR, 2022

Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective.

Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Benefiting from Duplicates of Compressed Data: Shift-Based Holographic Compression of Images.

Yehuda Dar, Alfred M. Bruckstein

J. Math. Imaging Vis., 2021

A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning.

Yehuda Dar, Vidya Muthukumar, Richard G. Baraniuk

CoRR, 2021

Double Descent and Other Interpolation Phenomena in GANs.

Lorenzo Luzi, Yehuda Dar, Richard G. Baraniuk

CoRR, 2021

Transfer Learning Can Outperform the True Prior in Double Descent Regularization.

Yehuda Dar, Richard G. Baraniuk

CoRR, 2021

2020

Regularized Compression of MRI Data: Modular Optimization of Joint Reconstruction and Coding.

Veronica Corona, Yehuda Dar, Carola-Bibiane Schönlieb

CoRR, 2020

Subspace Fitting Meets Regression: The Effects of Supervision and Orthonormality Constraints on Double Descent of Generalization Errors.

Yehuda Dar, Paul M. Mayer, Lorenzo Luzi, Richard G. Baraniuk

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

2019

On High-Resolution Adaptive Sampling of Deterministic Signals.

Yehuda Dar, Alfred M. Bruckstein

J. Math. Imaging Vis., 2019

Algorithms for Piecewise Constant Signal Approximations.

Leif Bergerhoff, Joachim Weickert, Yehuda Dar

Proceedings of the 27th European Signal Processing Conference, 2019

2018

New Methods for Signal Compression and Their Relations to Restoration Problems.

Yehuda Dar

PhD thesis, 2018

Restoration by Compression.

Yehuda Dar, Michael Elad, Alfred M. Bruckstein

IEEE Trans. Signal Process., 2018

Optimized Pre-Compensating Compression.

Yehuda Dar, Michael Elad, Alfred M. Bruckstein

IEEE Trans. Image Process., 2018

System-Aware Compression.

Yehuda Dar, Michael Elad, Alfred M. Bruckstein

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Compression for Multiple Reconstructions.

Yehuda Dar, Michael Elad, Alfred M. Bruckstein

Proceedings of the 2018 IEEE International Conference on Image Processing, 2018

2016

Postprocessing of Compressed Images via Sequential Denoising.

Yehuda Dar, Alfred M. Bruckstein, Michael Elad, Raja Giryes

IEEE Trans. Image Process., 2016

Optimal High-Resolution Adaptive Sampling of Deterministic Signals.

Yehuda Dar, Alfred M. Bruckstein

CoRR, 2016

Image restoration via successive compression.

Yehuda Dar, Alfred M. Bruckstein, Michael Elad

Proceedings of the 2016 Picture Coding Symposium, 2016

2014

Improving Low Bit-Rate Video Coding using Spatio-Temporal Down-Scaling.

Yehuda Dar, Alfred M. Bruckstein

CoRR, 2014

Motion-Compensated Coding and Frame-Rate Up-Conversion: Models and Analysis.

Yehuda Dar, Alfred M. Bruckstein

CoRR, 2014