Publications associées à Quasi-Global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data

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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

Quasi-Global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data

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Validation and Application of Hysteresis Loss Model for HTS Stacks and Conductors for Fusion Applications

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Reliable data-driven decision-making through optimal transport

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Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning

Efficient Continual Finite-Sum Minimization

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Validation and Application of Hysteresis Loss Model for HTS Stacks and Conductors for Fusion Applications

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Seismic Testing of Adjacent Interacting Masonry Structures – Analysis of a Blind Prediction

Reliable data-driven decision-making through optimal transport

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning

Efficient Continual Finite-Sum Minimization

Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Fusing Pre-existing Knowledge and Machine Learning for Enhanced Building Thermal Modeling and Control