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Distributed top-k aggregation queries at large

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Parallelizing Query Optimization on Shared-Nothing Architectures

Christoph Koch, Immanuel Trummer

Data processing systems offer an ever increasing degree of parallelism on the levels of cores, CPUs, and processing nodes. Query optimization must exploit high degrees of parallelism in order not to gradually become the bottleneck of query evaluation. We s ...

Assoc Computing Machinery2016

Online Inference in Bayesian Non-Parametric Mixture Models under Small Variance Asymptotics

Sylvain Calinon, Ajay Kumar Tanwani

Adapting statistical learning models online with large scale streaming data is a challenging problem. Bayesian non-parametric mixture models provide flexibility in model selection, however, their widespread use is limited by the computational overhead of e ...

2016

Designing Statistical Estimators That Balance Sample Size, Risk, and Computational Cost

Volkan Cevher

This paper proposes a tradeoff between computational time, sample complexity, and statistical accuracy that applies to statistical estimators based on convex optimization. When we have a large amount of data, we can exploit excess samples to decrease stati ...

Ieee-Inst Electrical Electronics Engineers Inc2015

RUBIK: Efficient Threshold Queries on Massive Time Series

Anastasia Ailamaki, Thomas Heinis, Farhan Tauheed, Eleni Tzirita Zacharatou

An increasing number of applications from finance, meteorology, science and others are producing time series as output. The analysis of the vast amount of time series is key to understand the phenomena studied, particularly in the simulation sciences, wher ...

2015

Smooth Scan: Statistics-Oblivious Access Paths

Anastasia Ailamaki, Renata Borovica-Gajic

Query optimizers depend heavily on statistics representing column distributions to create efficient query plans. In many cases, though, statistics are outdated or non-existent, and the process of refreshing statistics is very expensive, especially for ad-h ...

2015

RRB Vector: A Practical General Purpose Immutable Sequence

Martin Odersky, Tiark Rompf, Nicolas Alexander Stucki, Vlad Ureche

State-of-the-art immutable collections have wildly differing performance characteristics across their operations, often forcing programmers to choose different collection implementations for each task. Thus, changes to the program can invalidate the choice ...

ACM2015

Scaling Similarity Joins over Tree-Structured Data

Given a large collection of tree-structured objects (e.g., XML documents), the similarity join finds the pairs of objects that are similar to each other, based on a similarity threshold and a tree edit distance measure. The state-of-the-art similarity join ...

Assoc Computing Machinery2015

Adaptation, Learning, and Optimization over Networks

Ali H. Sayed

This work deals with the topic of information processing over graphs. The presentation is largely self-contained and covers results that relate to the analysis and design of multi-agent networks for the distributed solution of optimization, adaptation, and ...

NOW Publishers2014

Better Loop Fusion for LMS

Véra Salvisberg

This is my master thesis done at PPL in Stanford under the supervision of Prof. Kunle Olukotun. It improved LMS, a framework for embedding DSLs (domain-specific languages) into Scala which features many general optimizations that can be used by any DSLs fo ...

2014

Distributed Rate Allocation in Inter-Session Network Coding

Pascal Frossard, Nikolaos Thomos, Eirina Bourtsoulatze

In this work, we propose a distributed rate allocation algorithm that minimizes the average decoding delay for multimedia clients in inter-session network coding systems. We consider a scenario where the users are organized in a mesh network and each user ...

Institute of Electrical and Electronics Engineers2014