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Deep Learning for Logic Optimization Algorithms

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The $ L ^{ 1 } $ -Potts Functional for Robust Jump-Sparse Reconstruction

Martin Kurt Storath

We investigate the nonsmooth and nonconvex

L ^{ 1 }

-Potts functional in discrete and continuous time. We show Γ-convergence of discrete

L ^{ 1 }

-Potts functionals toward their continuous counterpart and obtain a convergence statement for the corr ...

SIAM2015

Deep Learning for Logic Optimization Algorithms

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Chat with Graph Search

Signal Recovery and System Calibration from Multiple Compressive Poisson Measurements

Quantization Design for Distributed Optimization

Quantization Design for Unconstrained Distributed Optimization

The $ L ^{ 1 } $ -Potts Functional for Robust Jump-Sparse Reconstruction

Learning of Closed-Loop Motion Control

Source Localization and Tracking in Non-Convex Rooms

Bedrock topography reconstruction of glaciers from surface topography and mass-balance data

EYEDIAP: A Database for the Development and Evaluation of Gaze Estimation Algorithms from RGB and RGB-D Cameras

Probabilistic inverse reinforcement learning in unknown environments

Sufficient Conditions for Feasibility and Optimality of Real-Time Optimization Schemes - I. Theoretical Foundations

The $ L ^{ 1 } $ -Potts Functional for Robust Jump-Sparse Reconstruction

Probabilistic inverse reinforcement learning in unknown environments

Learning of Closed-Loop Motion Control

EYEDIAP: A Database for the Development and Evaluation of Gaze Estimation Algorithms from RGB and RGB-D Cameras

Signal Recovery and System Calibration from Multiple Compressive Poisson Measurements

Quantization Design for Distributed Optimization

Quantization Design for Unconstrained Distributed Optimization

Bedrock topography reconstruction of glaciers from surface topography and mass-balance data

Source Localization and Tracking in Non-Convex Rooms

Sufficient Conditions for Feasibility and Optimality of Real-Time Optimization Schemes - I. Theoretical Foundations