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Publications associées (573)

Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection

Vinitra Swamy, Paola Mejia Domenzain, Julian Thomas Blackwell, Isadora Alves de Salles

Clustering in education, particularly in large-scale online environments like MOOCs, is essential for understanding and adapting to diverse student needs. However, the effectiveness of clustering depends on its interpretability, which becomes challenging w ...

2024

Planning urban proximities: An empirical analysis of how residential preferences conflict with the urban morphologies and residential practices

Vincent Kaufmann, Luca Giovanni Pattaroni, Marc-Edouard Baptiste Grégoire Schultheiss

Urban proximity planning is foreseen as a solution to foster a “sustainable” city, including economic viability, environmental soundness and social inclusivity. This paper focuses on the inclusivity aspects by questioning the adoption of urban proximities: ...

2024

Portfolio Construction with Hierarchical Momentum

Urban Ulrych

This article presents a portfolio construction approach that combines the hierarchical clustering of a large asset universe with the stock price momentum. On one hand, investing in high-momentum stocks enhances returns by capturing the momentum premium. On ...

Pageant Media Ltd2024

Beyond the average consumer: Mapping the potential of demand-side management among patterns of appliance usage

Claudia Rebeca Binder Signer, Selin Yilmaz, Matteo Barsanti

To support the decarbonisation of the power sector and offset the volatility of a system with high levels of renewables, there is growing interest in residential Demand-Side Management (DSM) solutions. Traditional DSM strategies require consumers to active ...

2024

Unsupervised Graph Representation Learning with Cluster-aware Self-training and Refining

Yichen Xu, Qiang Liu, Feng Yu

Unsupervised graph representation learning aims to learn low-dimensional node embeddings without supervision while preserving graph topological structures and node attributive features. Previous Graph Neural Networks (GNN) require a large number of labeled ...

New York2023

Fairness and Explainability in Clustering Problems

Xinrui Jia

In this thesis we present and analyze approximation algorithms for three different clustering problems. The formulations of these problems are motivated by fairness and explainability considerations, two issues that have recently received attention in the ...

EPFL2023

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Mehmet Fatih Sahin

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

EPFL2023

Neural ADMIXTURE for rapid genomic clustering

Albert Dominguez Mantes

Characterizing the genetic structure of large cohorts has become increasingly important as genetic studies extend to massive, increasingly diverse biobanks. Popular methods decompose individual genomes into fractional cluster assignments with each cluster ...

SPRINGERNATURE2023

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Knowledge of a program's input format is essential for effective input generation in fuzzing. Automated input format reverse engineering represents an attractive but challenging approach to learning the format. In this paper, we address several challenges ...

Berkeley2023

Landscapes of DNA Mechanics and Genomes

Thomas Antonin Zwahlen

The local physical properties - such as shape and flexibility - of the DNA double-helix is today widely believed to be influenced by nucleic acid sequence in a non-trivial way. Furthermore, there is strong evidence that these properties play a role in many ...

EPFL2023

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