Publications related to Accelerated Microstructure Imaging via Convex Optimization (AMICO) in crossing fibers

Safe Zeroth-Order Convex Optimization Using Quadratic Local Approximations

Giancarlo Ferrari Trecate, Maryam Kamgarpour, Yuning Jiang, Baiwei Guo

We address black-box convex optimization problems, where the objective and constraint functions are not explicitly known but can be sampled within the feasible set. The challenge is thus to generate a sequence of feasible points converging towards an optim ...

2023

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Mehmet Fatih Sahin

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

EPFL2023

Universal and adaptive methods for robust stochastic optimization

Ali Kavis

Within the context of contemporary machine learning problems, efficiency of optimization process depends on the properties of the model and the nature of the data available, which poses a significant problem as the complexity of either increases ad infinit ...

EPFL2023

A first-order primal-dual method with adaptivity to local smoothness

Volkan Cevher, Maria-Luiza Vladarean

We consider the problem of finding a saddle point for the convex-concave objective

\min_x \max_y f(x) + \langle Ax, y\rangle - g^*(y)

, where

f

is a convex function with locally Lipschitz gradient and

g

is convex and possibly non-smooth. We propose an ...

2021

Adaptation in Stochastic Algorithms: From Nonsmooth Optimization to Min-Max Problems and Beyond

Ahmet Alacaoglu

Stochastic gradient descent (SGD) and randomized coordinate descent (RCD) are two of the workhorses for training modern automated decision systems. Intriguingly, convergence properties of these methods are not well-established as we move away from the spec ...

EPFL2021

Resolving bundle-specific intra-axonal T2 values within a voxel using diffusion-relaxation tract-based estimation

Jean-Philippe Thiran, Erick Jorge Canales Rodriguez, Alessandro Daducci, Cristina Granziera, Muhamed Barakovic

At the typical spatial resolution of MRI in the human brain, approximately 60–90% of voxels contain multiple fiber populations. Quantifying microstructural properties of distinct fiber populations within a voxel is therefore challenging but necessary. Whil ...

2020

In vivo diffusion magnetic resonance imaging of the white matter microstructure from dictionaries generated by Monte Carlo simulations: development and validation

Gaëtan Olivier D Rensonnet

Non-invasive virtual histology of white matter tissues is the ultimate promise of diffusion-weighted MRI (DW-MRI). This hope is fueled by the exquisite sensitivity of DW-MRI to micrometer-scale displacement of diffusing water molecules, averaged over a who ...

EPFL2019

Stochastic Frank-Wolfe for Composite Convex Minimization

Volkan Cevher, Alp Yurtsever

A broad class of convex optimization problems can be formulated as a semidefinite program (SDP), minimization of a convex function over the positive-semidefinite cone subject to some affine constraints. The majority of classical SDP solvers are designed fo ...

2019

Robust control of systems with sector nonlinearities via convex optimization: A data-driven approach

Alireza Karimi, Achille Nicoletti

In this paper, a new data-driven method for designing robust controllers is proposed for systemswith sector-bounded nonlinearities and multimodel uncertainties. The results from the circle criterion are used to generate necessary and sufficient convex cons ...

WILEY2019

Towards non-parametric reconstruction of axon diameter distributions using diffusion MRI and regularized discrete linear modeling

David Paul Roger Romascano

The distribution of axon diameters (ADD) is an important white matter feature: it influences action potential speed, it has been shown to evolve during development, and also to be affected during pathological processes. Diffusion Magnetic Resonance Imaging ...

EPFL2019

Accelerated Microstructure Imaging via Convex Optimization (AMICO) in crossing fibers

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Safe Zeroth-Order Convex Optimization Using Quadratic Local Approximations

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Universal and adaptive methods for robust stochastic optimization

A first-order primal-dual method with adaptivity to local smoothness

Adaptation in Stochastic Algorithms: From Nonsmooth Optimization to Min-Max Problems and Beyond

Resolving bundle-specific intra-axonal T2 values within a voxel using diffusion-relaxation tract-based estimation

In vivo diffusion magnetic resonance imaging of the white matter microstructure from dictionaries generated by Monte Carlo simulations: development and validation

Stochastic Frank-Wolfe for Composite Convex Minimization

Robust control of systems with sector nonlinearities via convex optimization: A data-driven approach

Towards non-parametric reconstruction of axon diameter distributions using diffusion MRI and regularized discrete linear modeling

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Universal and adaptive methods for robust stochastic optimization

A first-order primal-dual method with adaptivity to local smoothness

Safe Zeroth-Order Convex Optimization Using Quadratic Local Approximations

Robust control of systems with sector nonlinearities via convex optimization: A data-driven approach

Adaptation in Stochastic Algorithms: From Nonsmooth Optimization to Min-Max Problems and Beyond

Resolving bundle-specific intra-axonal T2 values within a voxel using diffusion-relaxation tract-based estimation

In vivo diffusion magnetic resonance imaging of the white matter microstructure from dictionaries generated by Monte Carlo simulations: development and validation

Stochastic Frank-Wolfe for Composite Convex Minimization

Towards non-parametric reconstruction of axon diameter distributions using diffusion MRI and regularized discrete linear modeling