Publications associées à Learning Discriminative Features and Structured Models for Segmentation in Microscopy and Natural Images

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Efficient Continual Finite-Sum Minimization

Volkan Cevher, Efstratios Panteleimon Skoulakis, Leello Tadesse Dadi

Given a sequence of functions

f_1,\ldots,f_n

with

f_i:\mathcal{D}\mapsto \mathbb{R}

, finite-sum minimization seeks a point

{x}^\star \in \mathcal{D}

minimizing

\sum_{j=1}^nf_j(x)/n

. In this work, we propose a key twist into the finite-sum minimizat ...

2024

Learning Discriminative Features and Structured Models for Segmentation in Microscopy and Natural Images

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Chattez avec Graph Search

Fast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistency

CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds

Meta-learning to address diverse Earth observation problems across resolutions

Efficient Continual Finite-Sum Minimization

DeepGeo: Deep Geometric Mapping for Automated and Effective Parameterization in Aerodynamic Shape Optimization

Machine Learning Methods for Robust Uncertainty Quantification and Controller Approximation

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The statistical complexity of early-stopped mirror descent

Optimizing in-situ monitoring for laser powder bed fusion process: Deciphering acoustic emission and sensor sensitivity with explainable machine learning

CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds

Robust Outlier Rejection for 3D Registration with Variational Bayes

The statistical complexity of early-stopped mirror descent

Fast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistency

Meta-learning to address diverse Earth observation problems across resolutions

Efficient Continual Finite-Sum Minimization

DeepGeo: Deep Geometric Mapping for Automated and Effective Parameterization in Aerodynamic Shape Optimization

Optimizing in-situ monitoring for laser powder bed fusion process: Deciphering acoustic emission and sensor sensitivity with explainable machine learning

Machine Learning Methods for Robust Uncertainty Quantification and Controller Approximation