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2020 – today
- 2024
[j2]Aahlad Manas Puli, Nitish Joshi, Yoav Wald, He He, Rajesh Ranganath:
Nuisances via Negativa: Adjusting for Spurious Correlations via Data Augmentation. Trans. Mach. Learn. Res. 2024 (2024)- [j1]Gina Wong, Joshua Gleason, Rama Chellappa, Yoav Wald, Anqi Liu:
Weighted Risk Invariance: Domain Generalization under Invariant Feature Shift. Trans. Mach. Learn. Res. 2024 (2024) - [c12]Hsing-Huan Chung, Shravan Chaudhari, Yoav Wald, Xing Han, Joydeep Ghosh:
Novel Node Category Detection Under Subpopulation Shift. ECML/PKDD (4) 2024: 196-212 - [i9]Hsing-Huan Chung, Shravan Chaudhari, Yoav Wald, Xing Han, Joydeep Ghosh:
Novel Node Category Detection Under Subpopulation Shift. CoRR abs/2404.01216 (2024) - [i8]Gina Wong, Joshua Gleason, Rama Chellappa, Yoav Wald, Anqi Liu:
Weighted Risk Invariance: Domain Generalization under Invariant Feature Shift. CoRR abs/2407.18428 (2024) - 2023
- [c11]Yoav Wald, Gal Yona, Uri Shalit, Yair Carmon:
Malign Overfitting: Interpolation and Invariance are Fundamentally at Odds. ICLR 2023 - [c10]Amir Feder, Yoav Wald, Claudia Shi, Suchi Saria, David M. Blei:
Causal-structure Driven Augmentations for Text OOD Generalization. NeurIPS 2023 - [c9]Aahlad Manas Puli, Lily H. Zhang, Yoav Wald, Rajesh Ranganath:
Don't blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy. NeurIPS 2023 - [c8]Yoav Wald, Suchi Saria:
Birds of an odd feather: guaranteed out-of-distribution (OOD) novel category detection. UAI 2023: 2179-2191 - [i7]Aahlad Manas Puli, Lily H. Zhang, Yoav Wald, Rajesh Ranganath:
Don't blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy. CoRR abs/2308.12553 (2023) - [i6]Amir Feder, Yoav Wald, Claudia Shi, Suchi Saria, David M. Blei:
Causal-structure Driven Augmentations for Text OOD Generalization. CoRR abs/2310.12803 (2023) - 2022
- [c7]Amir Feder, Guy Horowitz, Yoav Wald, Roi Reichart, Nir Rosenfeld:
In the Eye of the Beholder: Robust Prediction with Causal User Modeling. NeurIPS 2022 - [i5]Amir Feder, Guy Horowitz, Yoav Wald, Roi Reichart, Nir Rosenfeld:
In the Eye of the Beholder: Robust Prediction with Causal User Modeling. CoRR abs/2206.00416 (2022) - [i4]Yoav Wald, Gal Yona, Uri Shalit, Yair Carmon:
Malign Overfitting: Interpolation Can Provably Preclude Invariance. CoRR abs/2211.15724 (2022) - 2021
- [b1]Yoav Wald:
Optimizations Towards Robustness in Machine Learning. (כותר נוסף בעברית: אופטימיזציות לאמינות של מערכות לומדות). Hebrew University of Jerusalem, Israel, 2021 - [c6]Oran Lang, Yossi Gandelsman, Michal Yarom, Yoav Wald, Gal Elidan, Avinatan Hassidim, William T. Freeman, Phillip Isola, Amir Globerson, Michal Irani, Inbar Mosseri:
Explaining in Style: Training a GAN to explain a classifier in StyleSpace. ICCV 2021: 673-682 - [c5]Yoav Wald, Amir Feder, Daniel Greenfeld, Uri Shalit:
On Calibration and Out-of-Domain Generalization. NeurIPS 2021: 2215-2227 - [i3]Yoav Wald, Amir Feder, Daniel Greenfeld, Uri Shalit:
On Calibration and Out-of-domain Generalization. CoRR abs/2102.10395 (2021) - [i2]Oran Lang, Yossi Gandelsman, Michal Yarom, Yoav Wald, Gal Elidan, Avinatan Hassidim, William T. Freeman, Phillip Isola, Amir Globerson, Michal Irani, Inbar Mosseri:
Explaining in Style: Training a GAN to explain a classifier in StyleSpace. CoRR abs/2104.13369 (2021)
2010 – 2019
- 2019
- [c4]Nofar Noy, Yoav Wald, Gal Elidan, Ami Wiesel:
Robust multitask Elliptical Regression (ROMER). CAMSAP 2019: 261-265 - [c3]Yoav Wald, Nofar Noy, Gal Elidan, Ami Wiesel:
Globally Optimal Learning for Structured Elliptical Losses. NeurIPS 2019: 13488-13497 - 2017
- [c2]Yoav Wald, Amir Globerson:
Robust Conditional Probabilities. NIPS 2017: 6359-6368 - [i1]Yoav Wald, Amir Globerson:
Robust Conditional Probabilities. CoRR abs/1708.02406 (2017) - 2014
- [c1]Yoav Wald, Amir Globerson:
Tightness Results for Local Consistency Relaxations in Continuous MRFs. UAI 2014: 839-848
Coauthor Index
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last updated on 2024-09-09 00:18 CEST by the dblp team
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