Deep Individual Active Learning: Safeguarding against Out-of-Distribution Challenges in Neural Networks von Shayovitz, Shachar, Bibas, Koby, Feder, Meir

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Semi-supervised Adversarial Learning for Complementary Item Recommendation von Koby Bibas, Oren Sar Shalom, Jannach, Dietmar

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Quantifying the Prediction Uncertainty of Machine Learning Models for Individual Data von Bibas, Koby

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A New Look at an Old Problem: A Universal Learning Approach to Linear Regression von Koby Bibas, Fogel, Yaniv, Feder, Meir

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Quantifying the Prediction Uncertainty of Machine Learning Models for Individual Data von Koby Bibas

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Beyond Ridge Regression for Distribution-Free Data von Bibas, Koby, Feder, Meir

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Distribution Free Uncertainty for the Minimum Norm Solution of Over-parameterized Linear Regression von Bibas, Koby, Feder, Meir

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Collaborative Image Understanding von Bibas, Koby, Shalom, Oren Sar, Jannach, Dietmar

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Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection von Bibas, Koby, Feder, Meir, Hassner, Tal

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Utilizing Adversarial Targeted Attacks to Boost Adversarial Robustness von Pesso, Uriya, Bibas, Koby, Feder, Meir

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Beyond Ridge Regression for Distribution-Free Data von Koby Bibas, Feder, Meir

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Distribution Free Uncertainty for the Minimum Norm Solution of Over-parameterized Linear Regression von Koby Bibas, Feder, Meir

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Deep pNML: Predictive Normalized Maximum Likelihood for Deep Neural Networks von Bibas, Koby, Fogel, Yaniv, Feder, Meir

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Collaborative Image Understanding von Koby Bibas, Oren Sar Shalom, Jannach, Dietmar

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Balancing Specialization, Generalization, and Compression for Detection and Tracking von Kaufman, Dotan, Bibas, Koby, Borenstein, Eran, Chertok, Michael, Hassner, Tal

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Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection von Koby Bibas, Feder, Meir, Hassner, Tal

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Utilizing Adversarial Targeted Attacks to Boost Adversarial Robustness von Pesso, Uriya, Koby Bibas, Feder, Meir

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Learning Rotation Invariant Features for Cryogenic Electron Microscopy Image Reconstruction von Bibas, Koby, Weiss-Dicker, Gili, Cohen, Dana, Cahan, Noa, Greenspan, Hayit

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Deep pNML: Predictive Normalized Maximum Likelihood for Deep Neural Networks von Koby Bibas, Fogel, Yaniv, Feder, Meir

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Balancing Specialization, Generalization, and Compression for Detection and Tracking von Kaufman, Dotan, Koby Bibas, Borenstein, Eran, Chertok, Michael, Hassner, Tal

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