Publications associées à Adaptive Models for Gene Networks

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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

Adaptive Models for Gene Networks

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

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

Inhalation of Microplastics—A Toxicological Complexity

FETCH: A Fast and Efficient Technique for Channel Selection in EEG Wearable Systems

Hybrid ground-state quantum algorithms based on neural Schrödinger forging

On-Chip Fully Reconfigurable Artificial Neural Network in 16 nm FinFET for Positron Emission Tomography

Efficient Continual Finite-Sum Minimization

Functional-Basis Analysis of Non-Stationary Signals in Modern Power Grids: Theory and Implementation in Embedded Systems

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

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

Inhalation of Microplastics—A Toxicological Complexity

Hybrid ground-state quantum algorithms based on neural Schrödinger forging

Efficient Continual Finite-Sum Minimization

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

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

Functional-Basis Analysis of Non-Stationary Signals in Modern Power Grids: Theory and Implementation in Embedded Systems

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

FETCH: A Fast and Efficient Technique for Channel Selection in EEG Wearable Systems

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

On-Chip Fully Reconfigurable Artificial Neural Network in 16 nm FinFET for Positron Emission Tomography