Publications associées à Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees

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Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Michaël Unser, Martin Kurt Storath

We consider

L ^{ 1 }

-TV regularization of univariate signals with values on the real line or on the unit circle. While the real data space leads to a convex optimization problem, the problem is nonconvex for circle-valued data. In this paper, we deriv ...

SIAM2016

Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees

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A Data-Driven Approach to Power Converter Control via Convex Optimization

Dynamic Facility Location via Exponential Clocks

Optical Tomography Based On A Nonlinear Model That Handles Multiple Scattering

Diffusion LMS for Multitask Problems With Local Linear Equality Constraints

Modifier adaptation with guaranteed feasibility in the presence of gradient uncertainty

Memetic Viability Evolution for Constrained Optimization

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

MATHICSE Technical Report : A fast gradient method for nonnegative sparse regression with self dictionary

Comparing genomes with rearrangements and segmental duplications

A Primal-dual Framework For Mixtures Of Regularisers

Optical Tomography Based On A Nonlinear Model That Handles Multiple Scattering

Memetic Viability Evolution for Constrained Optimization

A Data-Driven Approach to Power Converter Control via Convex Optimization

Comparing genomes with rearrangements and segmental duplications

A Primal-dual Framework For Mixtures Of Regularisers

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Diffusion LMS for Multitask Problems With Local Linear Equality Constraints

Modifier adaptation with guaranteed feasibility in the presence of gradient uncertainty

MATHICSE Technical Report : A fast gradient method for nonnegative sparse regression with self dictionary

Dynamic Facility Location via Exponential Clocks