Publications related to Conditions of Optimal Classification for Piecewise Affine Regression

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Florent Gérard Krzakala, Lenka Zdeborová, Hugo Chao Cui

We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the number of samples, the input dimension and the network width ...

2023

Distributional Regression and Autoregression via Optimal Transport

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We present a framework for performing regression when both covariate and response are probability distributions on a compact and convex subset of

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EPFL2023

Composite Relationship Fields with Transformers for Scene Graph Generation

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Scene graph generation (SGG) methods extract relationships between objects. While most methods focus on improving top-down approaches, which build a scene graph based on detected objects from an off-the-shelf object detector, there is a limited amount of w ...

2023

Fast screening of covariates in population models empowered by machine learning

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One of the objectives of Pharmacometry (PMX) population modeling is the identification of significant and clinically relevant relationships between parameters and covariates. Here, we demonstrate how this complex selection task could benefit from supervise ...

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A Global-Local Approach For Detecting Hotspots In Multiple-Response Regression

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We tackle modelling and inference for variable selection in regression problems with many predictors and many responses. We focus on detecting hotspots, that is, predictors associated with several responses. Such a task is critical in statistical genetics, ...

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Visual Question Answering for Remote Sensing (RSVQA) aims at extracting information from remote sensing images through queries formulated in natural language. Since the answer to the query is also provided in natural language, the system is accessible to n ...

2020

Learning How to Walk: Warm-starting Optimal Control Solver with Memory of Motion

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In this paper, we propose a framework to build a memory of motion for warm-starting an optimal control solver for the locomotion task of a humanoid robot. We use HPP Loco3D, a versatile locomotion planner, to generate offline a set of dynamically consisten ...

2020

Property FW, differentiable structures and smoothability of singular actions

Yash Lodha, Nicolas Matte Bon

We provide a smoothening criterion for group actions on manifolds by singular diffeomorphisms. We prove that if a countable group Gamma has the fixed point property FW for walls (for example, if it has property(T)), every aperiodic action of Gamma by diffe ...

WILEY2020

Automatic L2 Regularization for Multiple Generalized Additive Models

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Multiple generalized additive models are a class of statistical regression models wherein parameters of probability distributions incorporate information through additive smooth functions of predictors. The functions are represented by basis function expan ...

EPFL2019

Machine Learning at the Atomic Scale

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Statistical learning algorithms are finding more and more applications in science and technology. Atomic-scale modeling is no exception, with machine learning becoming commonplace as a tool to predict energy, forces and properties of molecules and condense ...

SWISS CHEMICAL SOC2019

Conditions of Optimal Classification for Piecewise Affine Regression

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Bayes-optimal Learning of Deep Random Networks of Extensive-width

Distributional Regression and Autoregression via Optimal Transport

Composite Relationship Fields with Transformers for Scene Graph Generation

Fast screening of covariates in population models empowered by machine learning

A Global-Local Approach For Detecting Hotspots In Multiple-Response Regression

Better Generic Objects Counting When Asking Questions to Images: A Multitask approach for Remote Sensing Visual Question Answering

Learning How to Walk: Warm-starting Optimal Control Solver with Memory of Motion

Property FW, differentiable structures and smoothability of singular actions

Automatic L2 Regularization for Multiple Generalized Additive Models

Machine Learning at the Atomic Scale

A Global-Local Approach For Detecting Hotspots In Multiple-Response Regression

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Distributional Regression and Autoregression via Optimal Transport

Fast screening of covariates in population models empowered by machine learning

Better Generic Objects Counting When Asking Questions to Images: A Multitask approach for Remote Sensing Visual Question Answering

Learning How to Walk: Warm-starting Optimal Control Solver with Memory of Motion

Machine Learning at the Atomic Scale

Composite Relationship Fields with Transformers for Scene Graph Generation

Automatic L2 Regularization for Multiple Generalized Additive Models

Property FW, differentiable structures and smoothability of singular actions