Koby Bibas

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 17

Top Topics

Normalized Maximum Likelihood

Change Point Detection

Image Understanding

Linear Regression

Top Venues

Publications

Shachar Shayovitz, Koby Bibas, Meir Feder
Deep Individual Active Learning: Safeguarding against Out-of-Distribution Challenges in Neural Networks. Entropy 26 (2) (2024)
Koby Bibas, Oren Sar Shalom, Dietmar Jannach
Semi-supervised Adversarial Learning for Complementary Item Recommendation. WWW (2023)
Koby Bibas, Oren Sar Shalom, Dietmar Jannach
Semi-supervised Adversarial Learning for Complementary Item Recommendation. CoRR (2023)
Koby Bibas, Oren Sar Shalom, Dietmar Jannach
Collaborative Image Understanding. CIKM (2022)
Koby Bibas, Meir Feder
Beyond Ridge Regression for Distribution-Free Data. CoRR (2022)
Koby Bibas, Oren Sar Shalom, Dietmar Jannach
Collaborative Image Understanding. CoRR (2022)
Koby Bibas, Meir Feder
The Predictive Normalized Maximum Likelihood for Over-parameterized Linear Regression with Norm Constraint: Regret and Double Descent. CoRR (2021)
Uriya Pesso, Koby Bibas, Meir Feder
Utilizing Adversarial Targeted Attacks to Boost Adversarial Robustness. CoRR (2021)
Koby Bibas, Gili Weiss-Dicker, Dana Cohen, Noa Cahan, Hayit Greenspan
Learning Rotation Invariant Features For Cryogenic Electron Microscopy Image Reconstruction. ISBI (2021)
Koby Bibas, Meir Feder, Tal Hassner
Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection. NeurIPS (2021)
Koby Bibas, Meir Feder, Tal Hassner
Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection. CoRR (2021)
Koby Bibas, Gili Weiss-Dicker, Dana Cohen, Noa Cahan, Hayit Greenspan
Learning Rotation Invariant Features for Cryogenic Electron Microscopy Image Reconstruction. CoRR (2021)
Koby Bibas, Yaniv Fogel, Meir Feder
A New Look at an Old Problem: A Universal Learning Approach to Linear Regression. ISIT (2019)
Koby Bibas, Yaniv Fogel, Meir Feder
A New Look at an Old Problem: A Universal Learning Approach to Linear Regression. CoRR (2019)
Koby Bibas, Yaniv Fogel, Meir Feder
Deep pNML: Predictive Normalized Maximum Likelihood for Deep Neural Networks. CoRR (2019)
Dotan Kaufman, Koby Bibas, Eran Borenstein, Michael Chertok, Tal Hassner
Balancing Specialization, Generalization, and Compression for Detection and Tracking. CoRR (2019)
Dotan Kaufman, Koby Bibas, Eran Borenstein, Michael Chertok, Tal Hassner
Balancing Specialization, Generalization, and Compression for Detection and Tracking. BMVC (2019)