DECENTRALIZED FUSION OF EXPERTS OVER NETWORKS

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This paper studies the probability of error associated with the social machine learning framework, which involves an independent training phase followed by a cooperative decision-making phase over a graph. This framework addresses the problem of classifyin ...

Deep neural networks often fail to generalize when deployed in dynamic and unpredictable real-world environments, where data distributions at test time can differ significantly from those encountered during training. Since simulating all possible distribut ...

Epidural electrical stimulation (EES) has been employed to restore motor functions in the lower limbs of patients with spinal cord injuries (SCIs). However, non-invasive methods for controlling this stimulation have not yet been explored. This study aims t ...

This study introduces a Machine Learning (ML) approach for estimating the T2 spectrum and myelin water fraction (MWF) using multi-echo T2 (MET2) data from preclinical 7T Magnetic Resonance Imaging (MRI) scanners. ML methods have shown promise in MWF estima ...

The contextual stochastic block model (CSBM) was proposed for unsupervised community detection on attributed graphs where both the graph and the high-dimensional node information correlate with node labels. In the context of machine learning on graphs, the ...

Novice students in law courses or students who encounter legal education face the challenge of acquiring specialized and highly concept-oriented knowledge. Structured and persuasive writing combined with the necessary domain knowledge is challenging for ma ...

Motivation is a multifaceted phenomenon that we explore within the framework of decision-making. Through this cognitive process, actions are directed towards specific goals by performing a trade-off between the cost and benefit of an action. The dorsomedia ...

The growing availability of distributed data has led to the increased use of machine learning (ML) algorithms in distributed topologies, where multiple nodes collaborate to train models under the coordination of a central server. However, distributed learn ...

Multiple drug concentrations concurrent detection and quantification based on electrochemical sensors are of great importance for therapeutic drug monitoring (TDM) and the development of personalized therapy. Cyclic voltammogram (CV) results obtained by el ...

In this paper we study the problem of social learning under multiple true hypotheses and self-interested agents that exchange information over a graph. In this setup, each agent receives data that might be generated from a different hypothesis (or state) t ...

We present jax-cosmo, a library for automatically differentiable cosmological theory calculations. jax-cosmo uses the JAX library, which has created a new coding ecosystem, especially in probabilistic programming. As well as batch acceleration, just-in-tim ...

Current task-oriented dialog (TOD) systems mostly manage structured knowledge (e.g. databases and tables) to guide the goal-oriented conversations. However, they fall short of handling dialogs which also involve unstructured knowledge (e.g. reviews and doc ...

Under seismic actions, stone masonry buildings are prone to damage. To assess the severity of damaged masonry buildings and their failure modes, engineers connect these problems to surface crack features, such as the crack width and the extent of cracking. ...

Diatoms are diverse and widespread freshwater Eukaryotes that make excellent microbial subjects for addressing questions in metacommunity ecology. In the McMurdo Dry Valleys of Antarctica, the simple trophic structure of glacier-fed streams provides an ide ...

DECENTRALIZED FUSION OF EXPERTS OVER NETWORKS

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Non-asymptotic performance of social machine learning under limited data

Adaptive Test-Time Learning Under Domain Shift: From Augmentation to Prolonged Adaptation

Decoding Lower Limb Motor Attempts from EEG Signals in a Spinal Cord Injury Patient with Epidural Electrical Implant

In-Silico Trained AI for Enhanced T2Spectrum Imaging and Myelin Water Fraction Mapping in Preclinical 7T MRI

Optimal Inference in Contextual Stochastic Block Models

LegalWriter: An Intelligent Writing Support System for Structured and Persuasive Legal Case Writing for Novice Law Students

Neurobiological and metabolic basis of motivation and effort-based decision-making - A human 1H-MRS, fMRI and machine learning study

Towards Practical Homomorphic Aggregation in Byzantine-Resilient Distributed Learning

Automatic simulation of electrochemical sensors by machine learning for drugs quantification

Self-Aware Social Learning Over Graphs

JAX-COSMO: AN END-TO-END DIFFERENTIABLE AND GPU ACCELERATED COSMOLOGY LIBRARY

End-to-End Task-Oriented Dialog Modeling With Semi-Structured Knowledge Management

Machine-learning for damage assessment of rubble stone masonry piers based on crack patterns

Evaluating Alternative Metacommunity Hypotheses for Diatoms in the McMurdo Dry Valleys Using Simulations and Remote Sensing Data

Better features for image categorization and segmentation