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ORCIDYehuda Dar
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2020 – today
- 2024
[j7]Yehuda Dar, Daniel LeJeune, Richard G. Baraniuk:
The Common Intuition to Transfer Learning Can Win or Lose: Case Studies for Linear Regression. SIAM J. Math. Data Sci. 6(2): 454-480 (2024)- [c7]Koren Abitbul, Yehuda Dar:
How Much Training Data Is Memorized in Overparameterized Autoencoders? An Inverse Problem Perspective on Memorization Evaluation. ECML/PKDD (2) 2024: 321-339 - [i21]Yuval Sharon, Yehuda Dar:
How Does Perfect Fitting Affect Representation Learning? On the Training Dynamics of Representations in Deep Neural Networks. CoRR abs/2405.17377 (2024) - [i20]Sharon Hendy, Yehuda Dar:
TL-PCA: Transfer Learning of Principal Component Analysis. CoRR abs/2410.10805 (2024) - 2023
- [i19]Koren Abitbul, Yehuda Dar:
Recovery of Training Data from Overparameterized Autoencoders: An Inverse Problem Perspective. CoRR abs/2310.02897 (2023) - 2022
- [j6]Yehuda Dar, Richard G. Baraniuk:
Double Double Descent: On Generalization Errors in Transfer Learning between Linear Regression Tasks. SIAM J. Math. Data Sci. 4(4): 1447-1472 (2022) - [c6]Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein:
Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective. CVPR 2022: 13689-13698 - [i18]Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein:
Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective. CoRR abs/2203.08124 (2022) - [i17]Yehuda Dar, Lorenzo Luzi, Richard G. Baraniuk:
Overfreezing Meets Overparameterization: A Double Descent Perspective on Transfer Learning of Deep Neural Networks. CoRR abs/2211.11074 (2022) - 2021
- [j5]Yehuda Dar
, Alfred M. Bruckstein:
Benefiting from Duplicates of Compressed Data: Shift-Based Holographic Compression of Images. J. Math. Imaging Vis. 63(3): 380-393 (2021) - [i16]Yehuda Dar, Richard G. Baraniuk:
Transfer Learning Can Outperform the True Prior in Double Descent Regularization. CoRR abs/2103.05621 (2021) - [i15]Lorenzo Luzi, Yehuda Dar, Richard G. Baraniuk:
Double Descent and Other Interpolation Phenomena in GANs. CoRR abs/2106.04003 (2021) - [i14]Yehuda Dar, Vidya Muthukumar, Richard G. Baraniuk:
A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning. CoRR abs/2109.02355 (2021) - 2020
- [c5]Yehuda Dar, Paul M. Mayer, Lorenzo Luzi, Richard G. Baraniuk:
Subspace Fitting Meets Regression: The Effects of Supervision and Orthonormality Constraints on Double Descent of Generalization Errors. ICML 2020: 2366-2375 - [i13]Yehuda Dar, Paul M. Mayer, Lorenzo Luzi, Richard G. Baraniuk:
Subspace Fitting Meets Regression: The Effects of Supervision and Orthonormality Constraints on Double Descent of Generalization Errors. CoRR abs/2002.10614 (2020) - [i12]Yehuda Dar, Richard G. Baraniuk:
Double Double Descent: On Generalization Errors in Transfer Learning between Linear Regression Tasks. CoRR abs/2006.07002 (2020) - [i11]Veronica Corona, Yehuda Dar, Carola-Bibiane Schönlieb:
Regularized Compression of MRI Data: Modular Optimization of Joint Reconstruction and Coding. CoRR abs/2010.04065 (2020)
2010 – 2019
- 2019
- [j4]Yehuda Dar, Alfred M. Bruckstein:
On High-Resolution Adaptive Sampling of Deterministic Signals. J. Math. Imaging Vis. 61(7): 944-966 (2019) - [c4]Leif Bergerhoff, Joachim Weickert, Yehuda Dar:
Algorithms for Piecewise Constant Signal Approximations. EUSIPCO 2019: 1-5 - [i10]Yehuda Dar, Alfred M. Bruckstein:
Benefiting from Duplicates of Compressed Data: Shift-Based Holographic Compression of Images. CoRR abs/1901.10812 (2019) - [i9]Leif Bergerhoff, Joachim Weickert, Yehuda Dar:
Algorithms for Piecewise Constant Signal Approximations. CoRR abs/1903.01320 (2019) - 2018
- [b1]Yehuda Dar:
New Methods for Signal Compression and Their Relations to Restoration Problems. Technion - Israel Institute of Technology, Israel, 2018 - [j3]Yehuda Dar, Michael Elad, Alfred M. Bruckstein:
Optimized Pre-Compensating Compression. IEEE Trans. Image Process. 27(10): 4798-4809 (2018) - [j2]Yehuda Dar, Michael Elad, Alfred M. Bruckstein:
Restoration by Compression. IEEE Trans. Signal Process. 66(22): 5833-5847 (2018) - [c3]Yehuda Dar, Michael Elad, Alfred M. Bruckstein:
Compression for Multiple Reconstructions. ICIP 2018: 440-444 - [c2]Yehuda Dar, Michael Elad, Alfred M. Bruckstein:
System-Aware Compression. ISIT 2018: 2226-2230 - [i8]Yehuda Dar, Michael Elad, Alfred M. Bruckstein:
System-Aware Compression. CoRR abs/1801.04853 (2018) - [i7]Yehuda Dar, Michael Elad, Alfred M. Bruckstein:
Compression for Multiple Reconstructions. CoRR abs/1802.03937 (2018) - 2017
- [i6]Yehuda Dar, Michael Elad, Alfred M. Bruckstein:
Restoration by Compression. CoRR abs/1711.05147 (2017) - [i5]Yehuda Dar, Michael Elad, Alfred M. Bruckstein:
Optimized Pre-Compensating Compression. CoRR abs/1711.07901 (2017) - 2016
- [j1]Yehuda Dar, Alfred M. Bruckstein, Michael Elad, Raja Giryes:
Postprocessing of Compressed Images via Sequential Denoising. IEEE Trans. Image Process. 25(7): 3044-3058 (2016) - [c1]Yehuda Dar, Alfred M. Bruckstein, Michael Elad:
Image restoration via successive compression. PCS 2016: 1-5 - [i4]Yehuda Dar, Alfred M. Bruckstein:
Optimal High-Resolution Adaptive Sampling of Deterministic Signals. CoRR abs/1611.01850 (2016) - 2015
- [i3]Yehuda Dar, Alfred M. Bruckstein, Michael Elad, Raja Giryes:
Postprocessing of Compressed Images via Sequential Denoising. CoRR abs/1510.09041 (2015) - 2014
- [i2]Yehuda Dar, Alfred M. Bruckstein:
Motion-Compensated Coding and Frame-Rate Up-Conversion: Models and Analysis. CoRR abs/1404.3290 (2014) - [i1]Yehuda Dar, Alfred M. Bruckstein:
Improving Low Bit-Rate Video Coding using Spatio-Temporal Down-Scaling. CoRR abs/1404.4026 (2014)
Coauthor Index
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