Amichai Painsky

According to our database, Amichai Painsky authored at least 36 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

A Comparative Analysis of Discrete Entropy Estimators for Large-Alphabet Problems.

Assaf Pinchas, Irad Ben-Gal, Amichai Painsky

Entropy, May, 2024

Neural Joint Entropy Estimation.

Yuval Shalev, Amichai Painsky, Irad Ben-Gal

IEEE Trans. Neural Networks Learn. Syst., April, 2024

Cross-validated tree-based models for multi-target learning.

Yehuda Nissenbaum, Amichai Painsky

Frontiers Artif. Intell., 2024

Distribution Estimation under the Infinity Norm.

Aryeh Kontorovich, Amichai Painsky

CoRR, 2024

2023

Detecting Non-Overlapping Signals with Dynamic Programming.

Mordechai Roth, Amichai Painsky, Tamir Bendory

Entropy, February, 2023

2022

Convergence Guarantees for the Good-Turing Estimator.

Amichai Painsky

J. Mach. Learn. Res., 2022

Feature Importance in Gradient Boosting Trees with Cross-Validation Feature Selection.

Afek Ilay Adler, Amichai Painsky

Entropy, 2022

Confidence Intervals for Unobserved Events.

Amichai Painsky

CoRR, 2022

A Data-driven Missing Mass Estimation Framework.

Amichai Painsky

Proceedings of the IEEE International Symposium on Information Theory, 2022

2021

Robust Universal Inference.

Amichai Painsky, Meir Feder

Entropy, 2021

Refined Convergence Rates of the Good-Turing Estimator.

Amichai Painsky

Proceedings of the IEEE Information Theory Workshop, 2021

2020

Bregman Divergence Bounds and Universality Properties of the Logarithmic Loss.

Amichai Painsky, Gregory W. Wornell

IEEE Trans. Inf. Theory, 2020

Innovation Representation of Stochastic Processes With Application to Causal Inference.

Amichai Painsky, Saharon Rosset, Meir Feder

IEEE Trans. Inf. Theory, 2020

Nonlinear Canonical Correlation Analysis: A Compressed Representation Approach.

Amichai Painsky, Meir Feder, Naftali Tishby

Entropy, 2020

2019

Lossless Compression of Random Forests.

Amichai Painsky, Saharon Rosset

J. Comput. Sci. Technol., 2019

2018

Linear Independent Component Analysis Over Finite Fields: Algorithms and Bounds.

Amichai Painsky, Saharon Rosset, Meir Feder

IEEE Trans. Signal Process., 2018

An Information-Theoretic Framework for Non-linear Canonical Correlation Analysis.

Amichai Painsky, Meir Feder, Naftali Tishby

CoRR, 2018

Lossless (and Lossy) Compression of Random Forests.

Amichai Painsky, Saharon Rosset

CoRR, 2018

Bregman Divergence Bounds and the Universality of the Logarithmic Loss.

Amichai Painsky, Gregory W. Wornell

CoRR, 2018

MSc Dissertation: Exclusive Row Biclustering for Gene Expression Using a Combinatorial Auction Approach.

Amichai Painsky

CoRR, 2018

Generalized Independent Components Analysis Over Finite Alphabets.

Amichai Painsky

CoRR, 2018

On the Universality of the Logistic Loss Function.

Amichai Painsky, Gregory W. Wornell

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

2017

Large Alphabet Source Coding Using Independent Component Analysis.

Amichai Painsky, Saharon Rosset, Meir Feder

IEEE Trans. Inf. Theory, 2017

Cross-Validated Variable Selection in Tree-Based Methods Improves Predictive Performance.

Amichai Painsky, Saharon Rosset

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

Gaussian Lower Bound for the Information Bottleneck Limit.

Amichai Painsky, Naftali Tishby

J. Mach. Learn. Res., 2017

2016

Generalized Independent Component Analysis Over Finite Alphabets.

Amichai Painsky, Saharon Rosset, Meir Feder

IEEE Trans. Inf. Theory, 2016

Isotonic Modeling with Non-Differentiable Loss Functions with Application to Lasso Regularization.

Amichai Painsky, Saharon Rosset

IEEE Trans. Pattern Anal. Mach. Intell., 2016

Binary independent component analysis: Theory, bounds and algorithms.

Amichai Painsky, Saharon Rosset, Meir Feder

Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

Compressing Random Forests.

Amichai Painsky, Saharon Rosset

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

A Simple and Efficient Approach for Adaptive Entropy Coding over Large Alphabets.

Amichai Painsky, Saharon Rosset, Meir Feder

Proceedings of the 2016 Data Compression Conference, 2016

2015

Universal Compression of Memoryless Sources over Large Alphabets via Independent Component Analysis.

Amichai Painsky, Saharon Rosset, Meir Feder

Proceedings of the 2015 Data Compression Conference, 2015

2014

Optimal Set Cover Formulation for Exclusive Row Biclustering of Gene Expression.

Amichai Painsky, Saharon Rosset

J. Comput. Sci. Technol., 2014

Generalized binary independent component analysis.

Amichai Painsky, Saharon Rosset, Meir Feder

Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

2013

Memoryless representation of Markov processes.

Amichai Painsky, Saharon Rosset, Meir Feder

Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

2012

Exclusive Row Biclustering for Gene Expression Using a Combinatorial Auction Approach.

Amichai Painsky, Saharon Rosset

Proceedings of the 12th IEEE International Conference on Data Mining, 2012

2010

First Order Multiple Hypothesis Testing for the Global Nearest Neighbor Data Correlation Approach.

Amichai Painsky

Proceedings of the 40. Jahrestagung der Gesellschaft für Informatik, Service Science - Neue Perspektiven für die Informatik, INFORMATIK 2010, Leipzig, Germany, September 27, 2010