Publications related to Sharper Exponential Convergence Rates for Sinkhorn's Algorithm in Continuous Settings

Related publications (7)

Adaptive Bilevel Optimization

Volkan Cevher, Kimon Antonakopoulos, Luca Viano

We propose a new adaptive optimization algorithm based on mirror descent for a class of possibly non-convex smooth bilevel optimization problems. The bilevel optimization template is broadly applicable in machine learning as it features two coupled problem ...

Association for Computing Machinery (ACM)2025

Non-regular Inference: Universal Inference and Discrete Profiling

Timmy Rong Tian Tse

Non-regular or irregular statistical problems are those that do not satisfy a set of standard regularity conditions that allow useful theoretical properties of inferential procedures to be proven. Non-regular problems are prevalent; a classical example is ...

EPFL2025

Iterative pre-conditioning for expediting the distributed gradient-descent method: The case of linear least-squares problem

Nirupam Gupta

This paper considers the multi-agent linear least-squares problem in a server-agent network architecture. The system comprises multiple agents, each with a set of local data points. The agents are connected to a server, and there is no inter-agent communic ...

PERGAMON-ELSEVIER SCIENCE LTD2022

Stokes, Gibbs, and Volume Computation of Semi-Algebraic Sets

Matteo Raphael Tacchi

We consider the problem of computing the Lebesgue volume of compact basic semi-algebraic sets. In full generality, it can be approximated as closely as desired by a converging hierarchy of upper bounds obtained by applying the Moment-SOS (sums of squares) ...

SPRINGER2022

Eigenfunction Martingale Estimators for Interacting Particle Systems and Their Mean Field Limit

Andrea Zanoni

We study the problem of parameter estimation for large exchangeable interacting particle systems when a sample of discrete observations from a single particle is known. We propose a novel method based on martingale estimating functions constructed by emplo ...

Siam Publications2022

Secure Coding via Gaussian Random Fields

Florent Gérard Krzakala, Bruno Loureiro

Inverse probability problems whose generative models are given by strictly nonlinear Gaussian random fields show the all-or-nothing behavior: There exists a critical rate at which Bayesian inference exhibits a phase transition. Below this rate, the optimal ...

IEEE2022

Efficient learning of smooth probability functions from Bernoulli tests with guarantees

Volkan Cevher, Ali Kavis, Paul Thierry Yves Rolland

We study the fundamental problem of learning an unknown, smooth probability function via pointwise Bernoulli tests. We provide a scalable algorithm for efficiently solving this problem with rigorous guarantees. In particular, we prove the convergence rate ...

2019