Ran El-Yaniv

According to our database, Ran El-Yaniv authored at least 103 papers between 1991 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of two.

2024

Hierarchical Selective Classification.

Shani Goren, Ido Galil, Ran El-Yaniv

CoRR, 2024

2023

Window-Based Distribution Shift Detection for Deep Neural Networks.

Guy Bar-Shalom, Yonatan Geifman, Ran El-Yaniv

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

What Can we Learn From The Selective Prediction And Uncertainty Estimation Performance Of 523 Imagenet Classifiers?

Ido Galil, Mohammed Dabbah, Ran El-Yaniv

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A framework for benchmarking Class-out-of-distribution detection and its application to ImageNet.

Ido Galil, Mohammed Dabbah, Ran El-Yaniv

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Distribution Shift Detection for Deep Neural Networks.

Guy Bar-Shalom, Yonatan Geifman, Ran El-Yaniv

CoRR, 2022

Which models are innately best at uncertainty estimation?

Ido Galil, Mohammed Dabbah, Ran El-Yaniv

CoRR, 2022

TransBoost: Improving the Best ImageNet Performance using Deep Transduction.

Omer Belhasin, Guy Bar-Shalom, Ran El-Yaniv

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Using Fictitious Class Representations to Boost Discriminative Zero-Shot Learners.

Mohammed Dabbah, Ran El-Yaniv

CoRR, 2021

Train on Small, Play the Large: Scaling Up Board Games with AlphaZero and GNN.

Shai Ben-Assayag, Ran El-Yaniv

CoRR, 2021

TranstextNet: Transducing Text for Recognizing Unseen Visual Relationships.

Gal Sadeh Kenigsfield, Ran El-Yaniv

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Disrupting Deep Uncertainty Estimation Without Harming Accuracy.

Ido Galil, Ran El-Yaniv

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Net-DNF: Effective Deep Modeling of Tabular Data.

Liran Katzir, Gal Elidan, Ran El-Yaniv

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

HydroNets: Leveraging River Structure for Hydrologic Modeling.

Zach Moshe, Asher Metzger, Gal Elidan, Frederik Kratzert, Sella Nevo, Ran El-Yaniv

CoRR, 2020

DNF-Net: A Neural Architecture for Tabular Data.

Ami Abutbul, Gal Elidan, Liran Katzir, Ran El-Yaniv

CoRR, 2020

BebopNet: Deep Neural Models for Personalized Jazz Improvisations.

Shunit Haviv Hakimi, Nadav Bhonker, Ran El-Yaniv

Proceedings of the 21th International Society for Music Information Retrieval Conference, 2020

Long-and Short-Term Forecasting for Portfolio Selection with Transaction Costs.

Guy Uziel, Ran El-Yaniv

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

The Relationship Between Agnostic Selective Classification, Active Learning and the Disagreement Coefficient.

Roei Gelbhart, Ran El-Yaniv

J. Mach. Learn. Res., 2019

Accurate Hydrologic Modeling Using Less Information.

Guy Shalev, Ran El-Yaniv, Daniel Klotz, Frederik Kratzert, Asher Metzger, Sella Nevo

CoRR, 2019

Improved Detection of Adversarial Attacks via Penetration Distortion Maximization.

Shai Rozenberg, Gal Elidan, Ran El-Yaniv

CoRR, 2019

Leveraging Auxiliary Text for Deep Recognition of Unseen Visual Relationships.

Gal Sadeh Kenigsfield, Ran El-Yaniv

CoRR, 2019

ML for Flood Forecasting at Scale.

Sella Nevo, Vova Anisimov, Gal Elidan, Ran El-Yaniv, Pete Giencke, Yotam Gigi, Avinatan Hassidim, Zach Moshe, Mor Schlesinger, Guy Shalev, Ajai Tirumali, Ami Wiesel, Oleg Zlydenko, Yossi Matias

CoRR, 2019

Deep Active Learning with a Neural Architecture Search.

Yonatan Geifman, Ran El-Yaniv

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

SelectiveNet: A Deep Neural Network with an Integrated Reject Option.

Yonatan Geifman, Ran El-Yaniv

Proceedings of the 36th International Conference on Machine Learning, 2019

Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers.

Yonatan Geifman, Guy Uziel, Ran El-Yaniv

Proceedings of the 7th International Conference on Learning Representations, 2019

Multi-Hop Paragraph Retrieval for Open-Domain Question Answering.

Yair Feldman, Ran El-Yaniv

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

Boosting Uncertainty Estimation for Deep Neural Classifiers.

Yonatan Geifman, Guy Uziel, Ran El-Yaniv

CoRR, 2018

Deep Anomaly Detection Using Geometric Transformations.

Izhak Golan, Ran El-Yaniv

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Growth-Optimal Portfolio Selection under CVaR Constraints.

Guy Uziel, Ran El-Yaniv

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Toward Deep Reinforcement Learning Without a Simulator: An Autonomous Steering Example.

Bar Hilleli, Ran El-Yaniv

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Learn on Source, Refine on Target: A Model Transfer Learning Framework with Random Forests.

Noam Segev, Maayan Harel, Shie Mannor, Koby Crammer, Ran El-Yaniv

IEEE Trans. Pattern Anal. Mach. Intell., 2017

Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations.

Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, Yoshua Bengio

J. Mach. Learn. Res., 2017

Deep Active Learning over the Long Tail.

Yonatan Geifman, Ran El-Yaniv

CoRR, 2017

The Prediction Advantage: A Universally Meaningful Performance Measure for Classification and Regression.

Ran El-Yaniv, Yonatan Geifman, Yair Wiener

CoRR, 2017

Multi-Objective Non-parametric Sequential Prediction.

Guy Uziel, Ran El-Yaniv

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Selective Classification for Deep Neural Networks.

Yonatan Geifman, Ran El-Yaniv

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Online Learning of Commission Avoidant Portfolio Ensembles.

Guy Uziel, Ran El-Yaniv

CoRR, 2016

Online Learning of Portfolio Ensembles with Sector Exposure Regularization.

Guy Uziel, Ran El-Yaniv

CoRR, 2016

Deep Learning of Robotic Tasks using Strong and Weak Human Supervision.

Bar Hilleli, Ran El-Yaniv

CoRR, 2016

Estimating types in binaries using predictive modeling.

Omer Katz, Ran El-Yaniv, Eran Yahav

Proceedings of the 43rd Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, 2016

Binarized Neural Networks.

Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

A compression technique for analyzing disagreement-based active learning.

Yair Wiener, Steve Hanneke, Ran El-Yaniv

J. Mach. Learn. Res., 2015

Agnostic Pointwise-Competitive Selective Classification.

Yair Wiener, Ran El-Yaniv

J. Artif. Intell. Res., 2015

2014

Concept Drift Detection Through Resampling.

Maayan Harel, Shie Mannor, Ran El-Yaniv, Koby Crammer

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Semantic Sort: A Supervised Approach to Personalized Semantic Relatedness.

Ran El-Yaniv, David Yanay

CoRR, 2013

2012

Active Learning via Perfect Selective Classification.

Ran El-Yaniv, Yair Wiener

J. Mach. Learn. Res., 2012

Autoregressive short-term prediction of turning points using support vector regression

Ran El-Yaniv, Alexandra Faynburd

CoRR, 2012

Supervised Learning of Semantic Relatedness.

Ran El-Yaniv, David Yanay

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Pointwise Tracking the Optimal Regression Function.

Yair Wiener, Ran El-Yaniv

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011

Agnostic Selective Classification.

Yair Wiener, Ran El-Yaniv

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Selective Prediction of Financial Trends with Hidden Markov Models.

Dmitry Pidan, Ran El-Yaniv

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010

On the Foundations of Noise-free Selective Classification.

Ran El-Yaniv, Yair Wiener

J. Mach. Learn. Res., 2010

On the Foundations of Adversarial Single-Class Classification

Ran El-Yaniv, Mordechai Nisenson

CoRR, 2010

Hierarchical Multiclass Decompositions with Application to Authorship Determination

Ran El-Yaniv, Noam Etzion-Rosenberg

CoRR, 2010

2009

Transductive Rademacher Complexity and its Applications.

Ran El-Yaniv, Dmitry Pechyony

J. Artif. Intell. Res., 2009

2008

Better multiclass classification via a margin-optimized single binary problem.

Ran El-Yaniv, Dmitry Pechyony, Elad Yom-Tov

Pattern Recognit. Lett., 2008

Repairing self-confident active-transductive learners using systematic exploration.

Ron Begleiter, Ran El-Yaniv, Dmitry Pechyony

Pattern Recognit. Lett., 2008

Large margin vs. large volume in transductive learning.

Ran El-Yaniv, Dmitry Pechyony, Vladimir Vapnik

Mach. Learn., 2008

2007

Size-density spectra and their application to image classification.

Igor Zingman, Ron Meir, Ran El-Yaniv

Pattern Recognit., 2007

2006

Superior Guarantees for Sequential Prediction and Lossless Compression via Alphabet Decomposition.

Ron Begleiter, Ran El-Yaniv

J. Mach. Learn. Res., 2006

Optimal Single-Class Classification Strategies.

Ran El-Yaniv, Mordechai Nisenson

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Stable Transductive Learning.

Ran El-Yaniv, Dmitry Pechyony

Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006

2005

Effective transductive learning via objective model selection.

Ran El-Yaniv, Leonid Gerzon

Pattern Recognit. Lett., 2005

Correcting BLAST e-Values for Low-Complexity Segments.

Itai Sharon, Aaron Birkland, Kuan Y. Chang, Ran El-Yaniv, Golan Yona

J. Comput. Biol., 2005

Multi-way distributional clustering via pairwise interactions.

Ron Bekkerman, Ran El-Yaniv, Andrew McCallum

Proceedings of the Machine Learning, 2005

2004

How to Better Use Expert Advice.

Rani Yaroshinsky, Ran El-Yaniv, Steven S. Seiden

Mach. Learn., 2004

Online Choice of Active Learning Algorithms.

Yoram Baram, Ran El-Yaniv, Kobi Luz

J. Mach. Learn. Res., 2004

Explicit Learning Curves for Transduction and Application to Clustering and Compression Algorithms.

Philip Derbeko, Ran El-Yaniv, Ron Meir

J. Artif. Intell. Res., 2004

Can We Learn to Beat the Best Stock.

Allan Borodin, Ran El-Yaniv, Vincent Gogan

J. Artif. Intell. Res., 2004

On Prediction Using Variable Order Markov Models.

Ron Begleiter, Ran El-Yaniv, Golan Yona

J. Artif. Intell. Res., 2004

2003

Distributional Word Clusters vs. Words for Text Categorization.

Ron Bekkerman, Ran El-Yaniv, Naftali Tishby, Yoad Winter

J. Mach. Learn. Res., 2003

Resilient-optimal interactive consistency in constant time.

Michael Ben-Or, Ran El-Yaniv

Distributed Comput., 2003

Towards Behaviometric Security Systems: Learning to Identify a Typist.

Mordechai Nisenson, Ido Yariv, Ran El-Yaniv, Ron Meir

Proceedings of the Knowledge Discovery in Databases: PKDD 2003, 2003

Error Bounds for Transductive Learning via Compression and Clustering.

Philip Derbeko, Ran El-Yaniv, Ron Meir

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

2002

A New Nonparametric Pairwise Clustering Algorithm Based on Iterative Estimation of Distance Profiles.

Shlomo Dubnov, Ran El-Yaniv, Yoram Gdalyahu, Elad Schneidman, Naftali Tishby, Golan Yona

Mach. Learn., 2002

On Online Learning of Decision Lists.

Ziv Nevo, Ran El-Yaniv

J. Mach. Learn. Res., 2002

Synthesizing Sound Textures through Wavelet Tree Learning.

Shlomo Dubnov, Ziv Bar-Joseph, Ran El-Yaniv, Dani Lischinski, Michael Werman

IEEE Computer Graphics and Applications, 2002

On the Competitive Theory and Practice of Online List Accessing Algorithms.

Ran Bachrach, Ran El-Yaniv, M. Reinstadtler

Algorithmica, 2002

Variance Optimized Bagging.

Philip Derbeko, Ran El-Yaniv, Ron Meir

Proceedings of the Machine Learning: ECML 2002, 2002

2001

Texture Mixing and Texture Movie Synthesis Using Statistical Learning.

Ziv Bar-Joseph, Ran El-Yaniv, Dani Lischinski, Michael Werman

IEEE Trans. Vis. Comput. Graph., 2001

Optimal Search and One-Way Trading Online Algorithms.

Ran El-Yaniv, Amos Fiat, Richard M. Karp, G. Turpin

Algorithmica, 2001

On Feature Distributional Clustering for Text Categorization.

Ron Bekkerman, Ran El-Yaniv, Yoad Winter, Naftali Tishby

Proceedings of the SIGIR 2001: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2001

Iterative Double Clustering for Unsupervised and Semi-Supervised Learning.

Ran El-Yaniv, Oren Souroujon

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Smoothed Bootstrap and Statistical Data Cloning for Classifier Evaluation.

Gregory Shakhnarovich, Ran El-Yaniv, Yoram Baram

Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

2000

On the Competitive Theory and Practice of Portfolio Selection (Extended Abstract).

Allan Borodin, Ran El-Yaniv, Vincent Gogan

Proceedings of the LATIN 2000: Theoretical Informatics, 2000

Localized Boosting.

Ron Meir, Ran El-Yaniv, Shai Ben-David

Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 2000

1999

On Randomization in On-Line Computation.

Allan Borodin, Ran El-Yaniv

Inf. Comput., 1999

Competitive Optimal On-Line Leasing.

Ran El-Yaniv, Ron Kaniel, Nathan Linial

Algorithmica, 1999

Granular Synthesis of Sound Textures Using Statistical Learning.

Ziv Bar-Joseph, Dani Lischinski, Michael Werman, Shlomo Dubnov, Ran El-Yaniv

Proceedings of the 1999 International Computer Music Conference, 1999

1998

Competitive Solutions for Online Financial Prob.

Ran El-Yaniv

ACM Comput. Surv., 1998

Universal Classification Applied to Musical Sequences.

Shlomo Dubnov, Gérard Assayag, Ran El-Yaniv

Proceedings of the 1998 International Computer Music Conference, 1998

Online computation and competitive analysis.

Allan Borodin, Ran El-Yaniv

Cambridge University Press, ISBN: 978-0-521-56392-5, 1998

1997

Nearly Optimal Competitive Online Replacement Policies.

Ran El-Yaniv, Richard M. Karp

Math. Oper. Res., 1997

Online List Accessing Algorithms and Their Applications: Recent Empirical Evidence.

Ran Bachrach, Ran El-Yaniv

Proceedings of the Eighth Annual ACM-SIAM Symposium on Discrete Algorithms, 1997

Agnostic Classification of Markovian Sequences.

Ran El-Yaniv, Shai Fine, Naftali Tishby

Proceedings of the Advances in Neural Information Processing Systems 10, 1997

On Ranomization in Online Computation.

Allan Borodin, Ran El-Yaniv

Proceedings of the Twelfth Annual IEEE Conference on Computational Complexity, 1997

1996

Competitive Solutions for On-line Financial Problems.

Ran El-Yaniv

Proceedings of the Online Algorithms, 1996

1995

Geometric Two-Server Algorithms.

Ran El-Yaniv, Jon M. Kleinberg

Inf. Process. Lett., 1995

The Statistical Adversary Allows Optimal Money-Making Trading Strategies.

Andrew Chou, Jeremy R. Cooperstock, Ran El-Yaniv, Michael Klugerman, Frank Thomson Leighton

Proceedings of the Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, 1995

1994

On-line algorithms and financial decision making.

Ran El-Yaniv

PhD thesis, 1994

1993

The Mortgage Problem.

Ran El-Yaniv, Richard M. Karp

Proceedings of the Second Israel Symposium on Theory of Computing Systems, 1993

1992

Memory Adaptive Self-Stabilizing Protocols (Extended Abstract).

Efthymios Anagnostou, Ran El-Yaniv, Vassos Hadzilacos

Proceedings of the Distributed Algorithms, 6th International Workshop, 1992

Competitive Analysis of Financial Games

Ran El-Yaniv, Amos Fiat, Richard M. Karp, G. Turpin

Proceedings of the 33rd Annual Symposium on Foundations of Computer Science, 1992

1991

More on the Power of Random Walks: Uniform Self-Stabilizing Randomized Algorithms (Preliminary Report).

Efthymios Anagnostou, Ran El-Yaniv

Proceedings of the Distributed Algorithms, 5th International Workshop, 1991