Publications associées à Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

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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

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

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Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

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Efficient Continual Finite-Sum Minimization

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Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Reinforcement Learning for Joint Design and Control of Battery-PV Systems

Reactive collision-free motion generation in joint space via dynamical systems and sampling-based MPC

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

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

A Comparative Analysis of Tools & Task Types for Measuring Computational Problem-Solving

High-Resolution Modeling Without Computation Slowdown for PETALE in CROCUS

Data-driven IQC-Based Robust Control Design for Hybrid Micro-disturbance Isolation Platform

Efficient Continual Finite-Sum Minimization