Scalable Multi-Query Execution using Reinforcement Learning

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When enough annotated training data is available, supervised deep-learning. algorithms excel at estimating human body pose and shape using a single camera. The effects of too little such data being available can be mitigated by using other information sour ...

One of the primary causes of non-uniform snowfall deposition on the ground in mountainous regions is the preferential deposition of snow, which results from the interaction of near-surface winds with topography and snow particles. However, producing high-r ...

Analytical workloads are evolving as the number of users surges and applications that submit queries in batches become popular. However, traditional analytical databases that optimize-then-execute each query individually struggle to provide timely response ...

We present Sudokube, a novel system that supports interactive speed querying on high-dimensional data using partially materialized data cubes. Given a storage budget, it judiciously chooses what projections to precompute and materialize during cube constru ...

Cloud function (CF) services, such as AWS Lambda, have been applied as the new computing infrastructure in implementing analytical query engines. For bursty and sparse workloads, CF-based query engine is more elastic than the traditional query engines runn ...

As modern data pipelines continue to collect, produce, and store a variety of data formats, extracting and combining value from traditional and context-rich sources such as strings, text, video, audio, and logs becomes a manual process where such formats a ...

In the current era of big data, aggregation queries on high-dimensional datasets are frequently utilized to uncover hidden patterns, trends, and correlations critical for effective business decision-making. Data cubes facilitate such queries by employing p ...

Analytics on modern data analytic and data warehouse systems often need to run large complex queries on increasingly complex database schemas. A lot of progress has been made on executing such complex queries using techniques like scale out query processin ...

To benefit from the cloud’s higher elasticity and price-efficiency, most modern data-lake engines support S3-like cloud object storage (COS) services as their optional or preferred underlying storage. Meanwhile, the widespread column stores, such as Parque ...

As the data volume grows, reducing the query execution times remains an elusive goal. While approximate query processing (AQP) techniques present a principled method to trade off accuracy for faster queries in analytics, the sample creation is often consid ...

Grading student SQL queries manually is a tedious and error-prone process. Earlier work on testing correctness of student SQL queries, such as the XData system, can be used to test the correctness of a student query. However, in case a student query is fou ...

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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 ...

The constant flux of data and queries alike has been pushing the boundaries of data analysis systems. The increasing size of raw data files has made data loading an expensive operation that delays the data-to-insight time. To alleviate the loading cost, in ...

In this thesis, an original database is constituted, described and exploited in a geohistorical perspective, containing the registration of the population at the local level for the fifteen censuses conducted in Albania between 1918 and 2011. The precision ...

Modern applications accumulate data at an exponentially increasing rate and traditional database systems struggle to keep up. Decision support systems used in industry, rely heavily on data analysis, and require real-time responses irrespective of data siz ...

Advances in data acquisition technologies and supercomputing for large-scale simulations have led to an exponential growth in the volume of spatial data. This growth is accompanied by an increase in data complexity, such as spatial density, but also by mor ...

Modern server hardware is increasingly heterogeneous as hardware accelerators, such as GPUs, are used together with multicore CPUs to meet the computational demands of modern data analytics workloads. Unfortunately, query parallelization techniques used by ...

Privacy policies are the primary channel through which companies inform users about their data collection and sharing practices. These policies are often long and difficult to comprehend. Short notices based on information extracted from privacy policies h ...

Scalable Multi-Query Execution using Reinforcement Learning

Chattez avec Graph Search

Using Motion Cues to Supervise Single-Frame Body Pose and Shape Estimation in Low Data Regimes

Snowfall deposition in mountainous terrain: a statistical downscaling scheme from high-resolution model data on simulated topographies

Efficient Concurrent Analytical Query Processing using Data and Workload-conscious Sharing

Aggregation and Exploration of High-Dimensional Data Using the Sudokube Data Cube Engine

Using Cloud Functions as Accelerator for Elastic Data Analytics

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

Interactive-time Exploration, Querying, and Analysis of Large High-dimensional Datasets

Efficient GPU-accelerated Join Optimization for Complex Queries

Pixels: An Efficient Column Store for Cloud Data Lakes

Sampling-Based AQP in Modern Analytical Engines

Edit Based Grading of SQL Queries

Micro-architectural Analysis of Database Workloads

Holistic, Efficient, and Real-time Cleaning of Heterogeneous Data

Representation Learning for Multi-relational Data

Adaptive partitioning and indexing for in situ query processing

Géohistoire de l'Albanie moderne. Une lecture des recensements de 1918 à 2011

Timely and cost-efficient data exploration through adaptive tuning

Time- and Space-Efficient Spatial Data Analytics

HetExchange: Encapsulating heterogeneous CPU-GPU parallelism in JIT compiled engines

Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning