Publications associées à Scaling Similarity Joins over Tree-Structured Data

Automated Verification of Network Function Binaries

George Candea, Solal Vincenzo Pirelli, Aikaterini Argyraki

Formally verifying the correctness of software network functions (NFs) is necessary for network reliability, yet existing techniques require full source code and mandate the use of specific data structures. We describe an automated technique to verify NF b ...

USENIX Association2022

Tree in Tree: from Decision trees to Decision Graphs

Mahsa Shoaran, Bingzhao Zhu

Decision trees have been widely used as classifiers in many machine learning applications thanks to their lightweight and interpretable decision process. This paper introduces Tree in Tree decision graph (TnT), a framework that extends the conventional dec ...

Curran Associates, Inc, (NIPS '21: Proceedings of the 35th International Conference on Neural Information Processing Systems)2021

The Jazz Harmony Treebank

Martin Alois Rohrmeier, Daniel Harasim, Christoph Finkensiep, Petter Harald Ericson

Grammatical models which represent the hierarchical structure of chord sequences have proven very useful in recent analyses of Jazz harmony. A critical resource for building and evaluating such models is a ground-truth database of syntax trees that encode ...

ISMIR2020

Time- and Space-Efficient Spatial Data Analytics

Mirjana Pavlovic

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 ...

EPFL2019

Sequential Proximity: Towards Provably Scalable Concurrent Search Algorithms

Rachid Guerraoui, Vasileios Trigonakis, Karolos Antoniadis, Julien Michel Stainer

Establishing the scalability of a concurrent algorithm a priori, before implementing and evaluating it on a concrete multi-core platform, seems difficult, if not impossible. In the context of search data structures however, according to all practical work ...

Springer International Publishing2017

Automated Reconstruction of Evolving Curvilinear Tree Structures

Przemyslaw Rafal Glowacki

Curvilinear networks are prevalent in nature and span many different scales, ranging from micron-scale neural structures in the brain to petameter-scale dark-matter arbors binding massive galaxy clusters. Reliably reconstructing them in an automated fashio ...

EPFL2016

Concurrent Search Data Structures Can Be Blocking and Practically Wait-Free

Rachid Guerraoui, Tudor Alexandru David

We argue that there is virtually no practical situation in which one should seek a "theoretically wait-free" algorithm at the expense of a state-of-the-art blocking algorithm in the case of search data structures: blocking algorithms are simple, fast, and ...

ACM2016

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

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

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