Analytical Engines With Context-Rich Processing: Towards Efficient Next-Generation Analytics

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SKILL: Structured Knowledge Infusion for Large Language Models

Large language models (LLMs) have demonstrated human-level performance on a vast spectrum of natural language tasks. However, it is largely unexplored whether they can better internalize knowledge from a structured data, such as a knowledge graph, or from ...

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The DES-CMASS sample (DMASS) is designed to optimally combine the weak lensing measurements from the Dark Energy Survey (DES) and redshift-space distortions (RSD) probed by the CMASS galaxy sample from the Baryonic Oscillation Spectroscopic Survey. In this ...

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Efficient Massively Parallel Join Optimization for Large Queries

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Modern data analytical workloads often need to run queries over a large number of tables. An optimal query plan for such queries is crucial for being able to run these queries within acceptable time bounds. However, with queries involving many tables, find ...

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Micro-architectural Analysis of Database Workloads

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Database workloads have significantly evolved in the past twenty years. Traditional database systems that are mainly used to serve Online Transactional Processing (OLTP) workloads evolved into specialized database systems that are optimized for particular ...

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Representation Learning for Multi-relational Data

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Recent years have witnessed a rise in real-world data captured with rich structural information that can be better depicted by multi-relational or heterogeneous graphs. However, research on relational representation learning has so far mostly focused on th ...

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Despite the rise in services generating learning analytics, there is a lack of standard models and guidelines for data integration and aggregation to inform the design choices of applications supporting learning analytics. We propose a bottom-up, user-driv ...

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Scalable Multi-Query Execution using Reinforcement Learning

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The growing demand for data-intensive decision support and the migration to multi-tenant infrastructures put databases under the stress of high analytical query load. The requirement for high throughput contradicts the traditional design of query-at-a-time ...

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Synthetic realistic noise-corrupted PPG database and noise generator for the evaluation of PPG denoising and delineation algorithms

David Atienza Alonso, Giulio Masinelli, Adriana Arza Valdes, Fabio Isidoro Tiberio Dell'Agnola

This database is meant to evaluate the performance of denoising and delineation algorithms for PPG signals affected by noise. The noise generator allows applying the algorithms under test to an artificially corrupted reference PPG signal and comparing its ...

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Matthew Wodrich, Anne-Clémence Corminboeuf, Michael Markus Busch, Boodsarin Sawatlon

For the past two decades, linear free energy scaling relationships and volcano plots have seen frequent use as computational tools that aid in understanding and predicting the catalytic behavior of heterogeneous and electrocatalysts. Based on Sabatier's pr ...

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An End-to-End Data Pipeline for Managing Learning Analytics

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Despite the importance of learning analytics in digital education, there is limited support for researchers in education to generate, access, and share experimental data while complying with ethical and privacy legislation. We propose a set of related tool ...

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Synthetic realistic noise-corrupted PPG database and noise generator for the evaluation of PPG denoising and delineation algorithms

David Atienza Alonso, Giulio Masinelli, Adriana Arza Valdes, Fabio Isidoro Tiberio Dell'Agnola

2021

The Genesis of Molecular Volcano Plots

Matthew Wodrich, Anne-Clémence Corminboeuf, Michael Markus Busch, Boodsarin Sawatlon

2021

An End-to-End Data Pipeline for Managing Learning Analytics

Denis Gillet, Juan Carlos Farah, Sandy Ingram, Joana Catarina Soares Machado

2021