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Preprints/Workshops

The Sample Complexity of Gradient Descent in Stochastic Convex Optimization

R. Livni
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Not All Similarities Are Created Equal: Leveraging Data-Driven Biases to Inform GenAI Copyright Disputes

U. Hacohen, A. Haviv, S. Sarfaty, B. Friedman, N. Elkin, R. Livni and A. Bermano
CS&Law 2024
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Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization

I. Attias, G.K. Dziugaite, M. Haghifam, R. Livni, D.M. Roy
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An Algorithm for Training Polynomial Networks,

R. Livni, S.Shalev-Shwartz and O. Shamir,
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Publications

Can Copyright be Reduced to Privacy?

N. Elkin, U. Hacohen, R. Livni, S. Moran

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5th Symposium on the Foundations of Responsible Computing (FORC), 2024
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The Sample Complexity of ERMs in Stochastic Convex Optimization

D. Carmon, R. Livni, A. Yehudayoff

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27th International Conference on Artificial Intelligence and Statistics (AISTAT), 2024
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Making Progress Based on False Discoeveries

R. Livni

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14th Innovations in Theoretical Computer Science (ITCS), 2024
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Information Theoretic Lower Bounds for Information Theoretic Upper Bounds

R. Livni

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Advances of Neural Information and Processing Systems 36 (NeurIPS), 2023
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Benign Underfitting of Stochastic Gradient Descent

T. Koren, R. Livni, Y. Mansour and U. Sherman

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Advances of Neural Information and Processing Systems 35 (NeurIPS), 2022
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Thinking Outside the Ball: Optimal Learning with Gradient Descent for Generalized Linear Stochastic Convex Optimization

I. Amir, R. Livni and N. Srebro

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Advances of Neural Information and Processing Systems 35 (NeurIPS), 2022
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Better Best of Both Worlds Bounds for Bandits with Switching Costs

I. Amir, G. Azov, T. Koren and R. Livni

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Advances of Neural Information and Processing Systems 35 (NeurIPS), 2022
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Never Go Full Batch (in Stochastic Convex Optimization)

I. Amir, Y. Carmon, T. Koren, R. Livni

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Advances of Neural Information and Processing Systems 34 (NeurIPS), 2021
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Littlestone Classes are Privately Online Learnable

Noah Golowich, Roi Livni

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Advances of Neural Information and Processing Systems 34 (NeurIPS), 2021
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SGD Generalizes Better Than GD (And Regularization Doesn't Help),

I. Amir, T. Koren and R. Livni,

34th Conference on Learning Theory (COLT), 2021
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Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games,

S. Hanneke, R. Livni and S. Moran,

Best paper runner-up

34th Conference on Learning Theory (COLT), 2021
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A Limitation of the PAC-Bayes Framework,

R. Livni and S. Moran,

Advances of Neural Information and Processing Systems 33 (NeurIPS), 2020
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Can Implicit Bias Explain Generalization? Stochastic Convex Optimization as a Case Study,

A. Dauber, M. Feder, T. Koren and R. Livni,

Advances of Neural Information and Processing Systems 33 (NeurIPS), 2020
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Prediction with Corrupted Expert Advice,

I. Amir, I. Attias, T. Koren, R. Livni and Y. Mansour,

Advances of Neural Information and Processing Systems 33 (NeurIPS), 2020
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Synthetic Data Generators: Sequential and Private,

O. Bousquet, R. Livni and S. Moran,

Advances of Neural Information and Processing Systems 33 (NeurIPS), 2020
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An Equivalence Between Private Classification and Online Prediction,

M. Bun, R. Livni and S. Moran,

Best paper award

61st Symposium on Foundations of Computer Science (FOCS), 2020
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On the Expressive Power of Kernel Methods and the Efficiency of Kernel Learning by Association Schemes,

P.K Kothari and R. Livni,

31st Conference on Algorithmic Learning Theory (ALT), 2020
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Graph-based Discriminators: Sample Complexity and Expressiveness,

R. Livni and Y. Mansour,

Advances of Neural Information and Processing Systems 32 (NeurIPS), 2019
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On Communication Complexity of Classification Problems,

D. Kane, R. Livni, S. Moran and A. Yehudayoff,

32nd Conference on Learning Theory (COLT), 2019
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Private PAC Learning Implies Finite Littlestone Dimension,

N. Alon, R. Livni, M. Malliaris and S. Moran,

51st Symposium on the Theory of Computing (STOC), 2019
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Generalize Across Tasks: Efficient Algorithms for Linear Representation Learning,

B. Bullins, E. Hazan, A. Kalai and R. Livni,

30th Conference on Algorithmic Learning Theory (ALT), 2019
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Open Problem: Improper Learning of Mixtures of Gaussians,

E. Hazan and R. Livni,

31st Conference on Learning Theory (COLT), 2018
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Agnostic Learning by Refuting,

P. K. Kothari, R. Livni,

9th Innovations in Theoretical Computer Science (ITCS), 2018
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Affine-Invariant Online Optimization and the Low-Rank Expert Problem

T. Koren, R. Livni

Advances of Neural Information and Processing Systems 30 (NIPS), 2017
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Multi-Armed Bandits with Metric Movement Costs

T. Koren, R. Livni, Y. Mansour

Advances of Neural Information and Processing Systems 30 (NIPS), 2017
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Learning Infinite--Layer Networks: Without the Kernel Trick

R. Livni, D. Carmon, A. Globerson

34th International Conference on Machine Learning (ICML), 2017
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Effective Semisupervised Learning on Manifolds

A. Globerson, R. Livni, S. Shalev-Shwartz

30th Conference on Learning Theory (COLT), 2017
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Bandits with Movement Costs and Adaptive Pricing

T. Koren, R. Livni, Y. Mansour

30th Conference on Learning Theory (COLT), 2017
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Online Pricing With Strategic and Patient Buyers,

M. Feldman, T. Koren, R. Livni, Y. Mansour, A. Zohar.

Advances of Neural Information and Processing Systems 29 (NIPS), 2016
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Online Learning With Low Rank Experts,

E. Hazan, T. Koren, R. Livni, Y. Mansour

29th Conference on Learning Theory (COLT), 2016
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Improper Deep Kernels,

U.Heinemann, R. Livni, E. Eban, G. Elidan, A. Globerson.

19th International Conference on Artificial Intelligence and Statistics (AISTAT), 2016
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Classification with Low Rank and Missing Data,

E. Hazan, R. Livni, Y. Mansour

32nd International Conference on Machine Learning (ICML), 2015
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On the Computational Efficiency of Training Neural Networks,

R. Livni, S. Shalev-Shwartz and O. Shamir

Advances in Neural Information Processing Systems 27 (NIPS), 2014
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Honest Compressions and Their Application to Compression Schemes,

R. Livni and P. Simon

Best student paper

26th Conference on Learning Theory (COLT),2013
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Vanishing Component Analysis,

R.Livni, D. Lehavi, S. Schein, H. Nachlieli, S Shalev-Shwartz and A. Globerson

Best paper award

30th International Conference on Machine Learning (ICML), 2013
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A Simple Geometric Interpretation of SVM using Stochastic Adversaries,

R. Livni, K. Crammer and A. Globerson

15th International Conference on Artificial Intelligence and Statistics (AISTAT), 2012
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On Extreme Points of the Dual Ball of a Polyhedral Space,

R. Livni

Extracta Mathematicae.24(3): 219-241, 2009
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