Ronen Eldan

According to our database1, Ronen Eldan authored at least 14 papers between 2011 and 2019.

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Bibliography

2019
The Entropic Barrier: Exponential Families, Log-Concave Geometry, and Self-Concordance.
Math. Oper. Res., 2019

Depth Separations in Neural Networks: What is Actually Being Separated?
Proceedings of the Conference on Learning Theory, 2019

2018
Efficient algorithms for discrepancy minimization in convex sets.
Random Struct. Algorithms, 2018

Sampling from a Log-Concave Distribution with Projected Langevin Monte Carlo.
Discrete & Computational Geometry, 2018

2017
Braess's paradox for the spectral gap in random graphs and delocalization of eigenvectors.
Random Struct. Algorithms, 2017

Kernel-based methods for bandit convex optimization.
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017

2016
Testing for high-dimensional geometry in random graphs.
Random Struct. Algorithms, 2016

The Power of Depth for Feedforward Neural Networks.
Proceedings of the 29th Conference on Learning Theory, 2016

Multi-scale exploration of convex functions and bandit convex optimization.
Proceedings of the 29th Conference on Learning Theory, 2016

2015
Bandit Smooth Convex Optimization: Improving the Bias-Variance Tradeoff.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Finite-Time Analysis of Projected Langevin Monte Carlo.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Talagrand's Convolution Conjecture on Gaussian Space.
Proceedings of the IEEE 56th Annual Symposium on Foundations of Computer Science, 2015

The entropic barrier: a simple and optimal universal self-concordant barrier.
Proceedings of The 28th Conference on Learning Theory, 2015

2011
A Polynomial Number of Random Points Does Not Determine the Volume of a Convex Body.
Discrete & Computational Geometry, 2011


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