Approximation Schemes for Many-Objective Query Optimization

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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 ...

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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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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 ...

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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An instance of colorful k-center consists of points in a metric space that are colored red or blue, along with an integer k and a coverage requirement for each color. The goal is to find the smallest radius ρ such that there exist balls of radius ρ around ...

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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 ...

Approximation Schemes for Many-Objective Query Optimization

Chattez avec Graph Search

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning

Using Cloud Functions as Accelerator for Elastic Data Analytics

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

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

Results on Sparse Integer Programming and Geometric Independent Sets

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Efficient GPU-accelerated Join Optimization for Complex Queries

Efficient Massively Parallel Join Optimization for Large Queries

Optimal Matching of Random Parts

Edit Based Grading of SQL Queries

Scalable Multi-Query Execution using Reinforcement Learning

Simultaneous Perturbation Stochastic Approximation of the Quantum Fisher Information

Fair colorful k-center clustering

The electric autonomous dial-a-ride problem

On the Influence of Bias-Correction on Distributed Stochastic Optimization

Fair Colorful k-Center Clustering

Timely and cost-efficient data exploration through adaptive tuning

New Graph Algorithms via Polyhedral Techniques

Model-based predictive control methods for distributed energy resources in smart grids

Time- and Space-Efficient Spatial Data Analytics