Deep Individual Active Learning: Safeguarding against Out-of-Distribution Challenges in Neural Networks.

Koby Bibas

Shachar Shayovitz Koby Bibas Meir Feder Deep Individual Active Learning: Safeguarding against Out-of-Distribution Challenges in Neural Networks. 129 2024 February 26 Entropy 2 https://doi.org/10.3390/e26020129 https://www.wikidata.org/entity/Q128988744 db/journals/entropy/entropy26.html#ShayovitzBF24

Koby Bibas Quantifying the Prediction Uncertainty of Machine Learning Models for Individual Data. 2024 abs/2412.07520 CoRR https://doi.org/10.48550/arXiv.2412.07520 db/journals/corr/corr2412.html#abs-2412-07520 streams/journals/corr

Koby Bibas Oren Sar Shalom Dietmar Jannach Semi-supervised Adversarial Learning for Complementary Item Recommendation. 1804-1812 2023 WWW https://doi.org/10.1145/3543507.3583462 conf/www/2023 db/conf/www/www2023.html#BibasSJ23

Koby Bibas Oren Sar Shalom Dietmar Jannach Semi-supervised Adversarial Learning for Complementary Item Recommendation. 2023 abs/2303.05812 CoRR https://doi.org/10.48550/arXiv.2303.05812 db/journals/corr/corr2303.html#abs-2303-05812

Koby Bibas Oren Sar Shalom Dietmar Jannach Collaborative Image Understanding. 77-87 2022 CIKM https://doi.org/10.1145/3511808.3557260 conf/cikm/2022 db/conf/cikm/cikm2022.html#BibasSJ22

Koby Bibas Meir Feder Beyond Ridge Regression for Distribution-Free Data. 2022 abs/2206.08757 CoRR https://doi.org/10.48550/arXiv.2206.08757 db/journals/corr/corr2206.html#abs-2206-08757

Koby Bibas Oren Sar Shalom Dietmar Jannach Collaborative Image Understanding. 2022 abs/2210.11907 CoRR https://doi.org/10.48550/arXiv.2210.11907 db/journals/corr/corr2210.html#abs-2210-11907

Koby Bibas Gili Weiss-Dicker Dana Cohen 0002 Noa Cahan Hayit Greenspan Learning Rotation Invariant Features For Cryogenic Electron Microscopy Image Reconstruction. 563-566 2021 ISBI https://doi.org/10.1109/ISBI48211.2021.9433789 conf/isbi/2021 db/conf/isbi/isbi2021.html#BibasWCCG21 Koby Bibas Meir Feder Tal Hassner Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection. 1179-1191 2021 NeurIPS https://proceedings.neurips.cc/paper/2021/hash/093b60fd0557804c8ba0cbf1453da22f-Abstract.html conf/nips/2021 db/conf/nips/neurips2021.html#BibasFH21

Koby Bibas Gili Weiss-Dicker Dana Cohen 0002 Noa Cahan Hayit Greenspan Learning Rotation Invariant Features for Cryogenic Electron Microscopy Image Reconstruction. 2021 abs/2101.03549 CoRR https://arxiv.org/abs/2101.03549 db/journals/corr/corr2101.html#abs-2101-03549

Koby Bibas Meir Feder The Predictive Normalized Maximum Likelihood for Over-parameterized Linear Regression with Norm Constraint: Regret and Double Descent. 2021 abs/2102.07181 CoRR https://arxiv.org/abs/2102.07181 db/journals/corr/corr2102.html#abs-2102-07181

Uriya Pesso Koby Bibas Meir Feder Utilizing Adversarial Targeted Attacks to Boost Adversarial Robustness. 2021 abs/2109.01945 CoRR https://arxiv.org/abs/2109.01945 db/journals/corr/corr2109.html#abs-2109-01945

Koby Bibas Meir Feder Tal Hassner Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection. 2021 abs/2110.09246 CoRR https://arxiv.org/abs/2110.09246 db/journals/corr/corr2110.html#abs-2110-09246

Dotan Kaufman Koby Bibas Eran Borenstein Michael Chertok Tal Hassner Balancing Specialization, Generalization, and Compression for Detection and Tracking. 219 2019 BMVC https://bmvc2019.org/wp-content/uploads/papers/0289-paper.pdf conf/bmvc/2019 db/conf/bmvc/bmvc2019.html#KaufmanBBCH19 Koby Bibas Yaniv Fogel Meir Feder A New Look at an Old Problem: A Universal Learning Approach to Linear Regression. 2304-2308 2019 ISIT https://doi.org/10.1109/ISIT.2019.8849398 conf/isit/2019 db/conf/isit/isit2019.html#BibasFF19

Koby Bibas Yaniv Fogel Meir Feder Deep pNML: Predictive Normalized Maximum Likelihood for Deep Neural Networks. 2019 abs/1904.12286 CoRR http://arxiv.org/abs/1904.12286 db/journals/corr/corr1904.html#abs-1904-12286

Koby Bibas Yaniv Fogel Meir Feder A New Look at an Old Problem: A Universal Learning Approach to Linear Regression. 2019 abs/1905.04708 CoRR http://arxiv.org/abs/1905.04708 db/journals/corr/corr1905.html#abs-1905-04708

Dotan Kaufman Koby Bibas Eran Borenstein Michael Chertok Tal Hassner Balancing Specialization, Generalization, and Compression for Detection and Tracking. 2019 abs/1909.11348 CoRR http://arxiv.org/abs/1909.11348 db/journals/corr/corr1909.html#abs-1909-11348

Eran Borenstein Noa Cahan Michael Chertok Meir Feder Yaniv Fogel Hayit Greenspan Tal Hassner Dana Cohen HochbergDana Cohen 0002 Dietmar Jannach Dotan Kaufman Uriya Pesso Oren Sar Shalom Shachar Shayovitz Gili Weiss-Dicker