Koby Bibas

18 papers A* 2A 2B 1Journal 12Unranked 1

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