Michal Moshkovitz

According to our database, Michal Moshkovitz authored at least 27 papers between 2010 and 2024.

Collaborative distances:

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

2024

An Axiomatic Approach to Model-Agnostic Concept Explanations.

Zhili Feng, Michal Moshkovitz, Dotan Di Castro, J. Zico Kolter

CoRR, 2024

Principal-Agent Reward Shaping in MDPs.

Omer Ben-Porat, Yishay Mansour, Michal Moshkovitz, Boaz Taitler

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Finding Safe Zones of Markov Decision Processes Policies.

Lee Cohen, Yishay Mansour, Michal Moshkovitz

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

Online k-means Clustering on Arbitrary Data Streams.

Robi Bhattacharjee, Jacob Imola, Michal Moshkovitz, Sanjoy Dasgupta

Proceedings of the International Conference on Algorithmic Learning Theory, 2023

2022

A Learning-Theoretic Framework for Certified Auditing of Machine Learning Models.

Chhavi Yadav, Michal Moshkovitz, Kamalika Chaudhuri

CoRR, 2022

There is no Accuracy-Interpretability Tradeoff in Reinforcement Learning for Mazes.

Yishay Mansour, Michal Moshkovitz, Cynthia Rudin

CoRR, 2022

Finding Safe Zones of policies Markov Decision Processes.

Lee Cohen, Yishay Mansour, Michal Moshkovitz

CoRR, 2022

Framework for Evaluating Faithfulness of Local Explanations.

Sanjoy Dasgupta, Nave Frost, Michal Moshkovitz

Proceedings of the International Conference on Machine Learning, 2022

2021

A Constant Approximation Algorithm for Sequential No-Substitution k-Median Clustering under a Random Arrival Order.

Tom Hess, Michal Moshkovitz, Sivan Sabato

CoRR, 2021

A Constant Approximation Algorithm for Sequential Random-Order No-Substitution k-Median Clustering.

Tom Hess, Michal Moshkovitz, Sivan Sabato

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

Connecting Interpretability and Robustness in Decision Trees through Separation.

Michal Moshkovitz, Yao-Yuan Yang, Kamalika Chaudhuri

Proceedings of the 38th International Conference on Machine Learning, 2021

Bounded Memory Active Learning through Enriched Queries.

Max Hopkins, Daniel Kane, Shachar Lovett, Michal Moshkovitz

Proceedings of the Conference on Learning Theory, 2021

Unexpected Effects of Online no-Substitution k-means Clustering.

Michal Moshkovitz

Proceedings of the Algorithmic Learning Theory, 2021

No-substitution k-means Clustering with Adversarial Order.

Robi Bhattacharjee, Michal Moshkovitz

Proceedings of the Algorithmic Learning Theory, 2021

2020

ExKMC: Expanding Explainable k-Means Clustering.

Nave Frost, Michal Moshkovitz, Cyrus Rashtchian

CoRR, 2020

Towards a Combinatorial Characterization of Bounded-Memory Learning.

Alon Gonen, Shachar Lovett, Michal Moshkovitz

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Explainable k-Means and k-Medians Clustering.

Michal Moshkovitz, Sanjoy Dasgupta, Cyrus Rashtchian, Nave Frost

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Unexpected Effects of Online K-means Clustering.

Michal Moshkovitz

CoRR, 2019

Novel Uncertainty Framework for Deep Learning Ensembles.

Tal Kachman, Michal Moshkovitz, Michal Rosen-Zvi

CoRR, 2019

2018

Entropy Samplers and Strong Generic Lower Bounds For Space Bounded Learning.

Dana Moshkovitz, Michal Moshkovitz

Proceedings of the 9th Innovations in Theoretical Computer Science Conference, 2018

2017

Mixing Implies Strong Lower Bounds for Space Bounded Learning.

Michal Moshkovitz, Dana Moshkovitz

Electron. Colloquium Comput. Complex., 2017

Mixing Implies Lower Bounds for Space Bounded Learning.

Michal Moshkovitz, Dana Moshkovitz

Electron. Colloquium Comput. Complex., 2017

A General Memory-Bounded Learning Algorithm.

Michal Moshkovitz, Naftali Tishby

CoRR, 2017

Mixing Complexity and its Applications to Neural Networks.

Michal Moshkovitz, Naftali Tishby

CoRR, 2017

2016

Principled Option Learning in Markov Decision Processes.

Roy Fox, Michal Moshkovitz, Naftali Tishby

CoRR, 2016

2014

Control your information for better predictions.

Michal Moshkovitz, Naftali Tishby

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

2010

Distance Estimators with Sublogarithmic Number of Queries.

Michal Moshkovitz

Electron. Colloquium Comput. Complex., 2010