2 citations · 3 across the 7 of their papers we have counts for
10 papers
Distribution-Dependent Improvements of McDiarmid's Inequality via Rényi Divergence
Amedeo Roberto Esposito, Adrien Vandenbroucque, Michael Gastpar
We investigate whether Rényi divergence can sharpen McDiarmid's inequality and its distribution-dependent refinement induced by KL divergence. Starting from Marton's transportation…
Contraction of Rényi Divergences for Discrete Channels
Adrien Vandenbroucque, Amedeo Roberto Esposito, Michael Gastpar
We investigate Strong Data-Processing Inequality (SDPI) constants for Rényi Divergences on finite spaces. We study their dependence on the Rényi order , proving that they are no…
Single-Period Portfolio Selection via Information Projection
Bo-Yu Yang, Michael Gastpar
We study the single-period portfolio selection problem under Constant Relative Risk-Aversion (CRRA) utility through the information-theoretic lens. Assuming only that the market pa…
Contraction of Rényi Divergences for Discrete Channels: Properties and Applications
Adrien Vandenbroucque, Amedeo Roberto Esposito, Michael Gastpar
This work explores properties of Strong Data-Processing constants for Rényi Divergences. Parallels are made with the well-studied -Divergences, and it is shown that the order $α…
Model non-collapse: Minimax bounds for recursive discrete distribution estimation
Millen Kanabar, Michael Gastpar
Learning discrete distributions from i.i.d. samples is a well-understood problem. However, advances in generative machine learning prompt an interesting new, non-i.i.d. setting: af…
Shannon Bounds for Quadratic Rate-Distortion Problems
Michael Gastpar, Erixhen Sula
The Shannon lower bound has been the subject of several important contributions by Berger. This paper surveys Shannon bounds on rate-distortion problems under mean-squared error di…
Sibson -Mutual Information and Its Variational Representations
Amedeo Roberto Esposito, Michael Gastpar, Ibrahim Issa
Information measures can be constructed from Rényi divergences much like mutual information from Kullback-Leibler divergence. One such information measure is known as Sibson -mu…
Properties of the Strong Data Processing Constant for Rényi Divergence
Lifu Jin, Amedeo Roberto Esposito, Michael Gastpar
Strong data processing inequalities (SDPI) are an important object of study in Information Theory and have been well studied for -divergences. Universal upper and lower bounds h…
The Fundamental Limits of Least-Privilege Learning
Theresa Stadler, Bogdan Kulynych, Michael C. Gastpar +2
The promise of least-privilege learning -- to find feature representations that are useful for a learning task but prevent inference of any sensitive information unrelated to this…
Simultaneous Computation and Communication over MAC
Matthias Frey, Igor Bjelaković, Michael C. Gastpar +1
We study communication over a Gaussian multiple-access channel (MAC) with two types of transmitters: Digital transmitters hold a message from a discrete set that needs to be commun…