Concept

Determining the number of clusters in a data set

Publications associées (32)

Linguistic traits as heritable units? Spatial Bayesian clustering reveals Swiss German dialect regions

In the early 2000s, the SADS, an extensive linguistic atlas project, surveyed more than three thousand individuals across German-speaking Switzerland on over two hundred linguistic variants, capturing the morphosyntactic variation in Swiss German. In this ...

2022

Applying the Principal Component Analysis for a deeper understanding of the groundwater system: case study of the Bacchiglione Basin (Veneto, Italy)

Andrea Rinaldo

In hydrogeology, it is often difficult to fully understand the hydraulic factors affecting the recharge of groundwater systems. Particularly, at a regional scale, the groundwater system can have different drivers depending on the considered area, i.e., soi ...

PAGEPRESS PUBL2022

Nearly-Tight and Oblivious Algorithms for Explainable Clustering

Ola Nils Anders Svensson, Adam Teodor Polak, Buddhima Ruwanmini Gamlath Gamlath Ralalage, Xinrui Jia

We study the problem of explainable clustering in the setting first formalized by Dasgupta, Frost, Moshkovitz, and Rashtchian (ICML 2020). A k-clustering is said to be explainable if it is given by a decision tree where each internal node splits data point ...

2021

Self-Supervised Neural Topic Modeling

Martin Jaggi

Topic models are useful tools for analyzing and interpreting the main underlying themes of large corpora of text. Most topic models rely on word co-occurrence for computing a topic, i.e., a weighted set of words that together represent a high-level semanti ...

Assoc Computational Linguistics-Acl2021

Size and duration of COVID-19 clusters go along with a high SARS-CoV-2 viral load: A spatio-temporal investigation in Vaud state, Switzerland

Stéphane Joost, Séverine Vuilleumier Varisco, Idris Guessous, Onya Opota, Anaïs Laurence Ladoy

To understand the geographical and temporal spread of SARS-CoV-2 during the first documented wave of infection in the state of Vaud, Switzerland, we analyzed clusters of positive cases using the precise residential location of 33,651 individuals tested (RT ...

2021

Shrinking FPGA Static Power via Machine Learning-Based Power Gating and Enhanced Routing

Mirjana Stojilovic, Hossein Asadi, Zeinab Seifoori

Despite FPGAs rapidly evolving to support the requirements of the most demanding emerging applications, their high static power consumption, concentrated within the routing resources, still presents a major hurdle for low-power applications. Augmenting the ...

2021

Sublinear Algorithms for Spectral Graph Clustering

Aidasadat Mousavifar

This thesis focuses on designing spectral tools for graph clustering in sublinear time. With the emergence of big data, many traditional polynomial time, and even linear time algorithms have become prohibitively expensive. Processing modern datasets requir ...

EPFL2021

Perturbative approach to tunneling and quantum interferences in spin clusters

Frédéric Mila, Ivo Aguiar Maceira

Collective tunneling is a ubiquitous phenomenon in finite-size spin clusters that shows up in systems as diverse as molecular magnets or spin clusters adsorbed at surfaces. The basic problem we explore is to understand how small flipping terms can cooperat ...

AMER PHYSICAL SOC2020

Image Clustering Algorithms to Identify Complicated Cerebral Diseases. Description and Comparison

Maria-Alexandra Paun

This article presents two algorithms developed based on two different techniques, from clusterization theory, namely k-means clustering technique and Fuzzy C-means technique, respectively. In this context, the study offers a sustained comparison of the two ...

2020

Model-Class Selection Using Clustering and Classification for Structural Identification and Prediction

Ian Smith, Sai Ganesh Sarvotham Pai, Masoud Sanayei

Structural identification using physics-based models and subsequent prediction have much potential to enhance civil infrastructure asset-management decision-making. Interpreting monitoring information in the presence of multiple uncertainty sources and sys ...

2020

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