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Data mining for materials: Computational experiments with AB compounds

Related publications (58)

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Graph-based Methods for Visualization and Clustering

Johann Paratte

The amount of data that we produce and consume is larger than it has been at any point in the history of mankind, and it keeps growing exponentially. All this information, gathered in overwhelming volumes, often comes with two problematic characteristics: ...

EPFL2017

Computational development of the nanoporous materials genome

Berend Smit, Peter George Boyd, Yongjin Lee

There is currently a push towards big data and data mining in materials research to accelerate discovery. Zeolites, metal-organic frameworks and other related crystalline porous materials are not immune to this phenomenon, as evidenced by the proliferation ...

Nature Publishing Group2017

BEAT: An Open-Science Web Platform

Sébastien Marcel, André Anjos, Laurent El Shafey

With the increased interest in computational sciences, machine learning (ML), pattern recognition (PR) and big data, governmental agencies, academia and manufacturers are overwhelmed by the constant influx of new algorithms and techniques promising improve ...

2017

Efficient Document Filtering Using Vector Space Topic Expansion and Pattern-Mining: The Case of Event Detection in Microposts

Karl Aberer, Philippe Cudré-Mauroux, Julia Proskurnia, Carlos Castillo

Automatically extracting information from social media is challenging given that social content is often noisy, ambiguous, and inconsistent. However, as many stories break on social channels first before being picked up by mainstream media, developing meth ...

2017

Toward timely, predictable and cost-effective data analytics

Renata Borovica-Gajic

Modern industrial, government, and academic organizations are collecting massive amounts of data at an unprecedented scale and pace. The ability to perform timely, predictable and cost-effective analytical processing of such large data sets in order to ext ...

EPFL2016

Human computation for data, information, and knowledge management

Thành Tâm Nguyên

The paradigm of Human Computation has grown rapidly in recent years and has thus sparked great interest in both the industry and the research community. In this survey, we give an overview of the state-of-the-art of human computation in the context of data ...

2016

Runtime Prediction for Scale-Out Data Analytics

Adrian Daniel Popescu

Many analytics applications generate mixed workloads, i.e., workloads comprised of analytical tasks with different processing characteristics including data pre-processing, SQL, and iterative machine learning algorithms. Examples of such mixed workloads ca ...

EPFL2015

A Precise Threshold For Quasi-Ramsey Numbers

János Pach

We consider the variation of Ramsey numbers introduced by Erdos and Pach [J. Graph Theory, 7 (1983), pp. 137-147], where instead of seeking complete or independent sets we only seek a t-homogeneous set, a vertex subset that induces a subgraph of minimum de ...

Siam Publications2015

Automated analysis of product related data generated from PLM ontology

Ana Milicic

In recent years, ontology for the Product Lifecycle Management domain has raised a lot of interest in research communities, both academic and industrial. It has emerged as a convenient method for supporting the concept of closed lifecycle information loop, ...

EPFL2015

WASP: Scalable Bayes via barycenters of subset posteriors

Volkan Cevher, Quoc Tran Dinh

The promise of Bayesian methods for big data sets has not fully been realized due to the lack of scalable computational algorithms. For massive data, it is necessary to store and process subsets on different machines in a distributed manner. We propose a s ...

2015