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teaching:projh402 [2018/10/02 08:13]
svsummer
teaching:projh402 [2022/09/06 10:39] (current)
ezimanyi
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-====== ​MA Computer Science Projects (PROJ-H-402)  ​======+====== PROJ-H-402 ​: Computing Projects ​======
  
- +This is the list of Computing Projects topics ​proposed for the current academic year by the CoDE departmentÉcole polytechnique de BruxellesULB.
-===== Course objective ===== +
-The course PROJ-H-402 ​is managed by Dr. Mauro Birattari. Please refer to the course description page http://​iridia.ulb.ac.be/​proj-h-402/​index.php/​Main_Page for the rules concerning the project. ​ What follows is a list of project proposals supervised by academic members of CoDE. +
- +
-===== Project proposals ===== +
- +
-=== Engineering of a Rule-Based Information Extraction Engine === +
- +
-Information extraction, the activity of extracting structured +
-information from unstructured text, is a core data preparation +
-step. Systems for information extraction fall into two main +
-categories. The first category contains machine-learning based +
-systems, where a significant amount of training is required to train +
-good models for specific extraction tasks. The second category +
-consists of rule-based systems in which the data to be extracted from +
-the text is specified by (human-written) rules in some (often +
-declarative) extraction language. Despite advances in machine +
-learning, rule-based systems are widely used in practice. +
- +
-In recent years, novel theoretical algorithms have been proposed ​to +
-more efficiently execute rule-based information extraction +
-workloads. The objective in this project is to implement one such +
-Algorithm, by Florenzano et al (2018), experimentally analyze its +
-performance,​ and propose extensions of the algorithm to overcome +
-performance bottlenecks.  +
- +
- +
-References:  +
- +
-- Fernando Florenzano, Cristian Riveros, Martín Ugarte, +
-Stijn Vansummeren,​ Domagoj Vrgoc: Constant Delay Algorithms ​for +
-Regular Document Spanners. PODS 2018: 165-177 +
- +
- +
-**Interested?​** Contact Stijn Vansummeren (stijn.vansummeren@ulb.ac.be) +
- +
-**Status**: available +
- +
- +
-=== Query processing for mixed database-machine learning based workloads === +
- +
-Because of the growing importance and wide deployment of large-scale +
-Machine Learning (ML), there is wide interest in the design and +
-implementation of processing engines that can efficiently evaluate ML +
-workloads. One class of sytems, embodied ​by systems such as Tensorflow +
-and SystemML takes linear algebra as the key primitive for expressing +
-ML workflowsand obtain efficient processing engines by porting known +
-database-style optimization techniques to the linear algebra +
-setting. Another class of systemsembodied by FAQ queries take +
-relational algebra as the key primitive, but modify it to allow +
-expression of certain ML workloads. To some extent, the classical +
-optimization techniques as well as recent results for exploiting +
-modern hardware transfer to this extended relational algebra. As an +
-added bonus, traditional database workloads (OLTP/OLAP style) can be +
-trivially supported +
- +
-The focus in this project is in the latter style of systems. The +
-overall goal is to experimentally identify classes of FAQ queries for +
-which it would be beneficial to exploit techniques developped in the +
-former class of systems. Concretely, this can be approached by +
-experimentally studying queries in the FAQ framework (featuring joins) +
-for which known results in evaluating linear algebra operations (in +
-concretum: matrix multiplication algorithms that run in less than +
-O(n^3) time) can be exploited. +
- +
-**Contact** : Stijn Vansummeren (stijn.vansummeren@ulb.ac.be) +
- +
-**Status**: available+
  
  
 +  * [[teaching:​projh402:​wis|Data Science and Engineering]]
 +  * [[teaching:​projh402:​ia|Artificial Intelligence]]
 +  * [[teaching:​projh402:​or|Operational Research and Decision Aid]]
 
teaching/projh402.1538460806.txt.gz · Last modified: 2018/10/02 08:13 by svsummer