A fast Bayesian Network library for modeling and optimization tasks
Gruppi di ricerca TESTGROUP - TESTGROUP
Tipo tesi RESEARCH / EXPERIMENTAL
Descrizione Goals: Build a C++ Bayesian Network library resorting to all modern programming paradigms including advanced modelling features and an extremal optimization engine.
The library is going to be composed by two set of tools:
1. The Bayesian Network core: it provides all programming tools to generate and analyze BNs. The core is going to be build resorting to all available programming paradigm: multi-threading, mixed CPU-GPU computations, etc.
2. The Extremal Optimization engine: build above the core, the engine must resort to all analysis capabilities to exploit any kind of multi-objective optimization. The engine will include a meta-programming layer to describe the optimization rules to support the optimization with the maximum flexibility.
Learned Outcomes: Advanced C/C++ programming, multi-thread and mixed computation, Bayesian Theory, Optimization algorithms.
Conoscenze richieste C/C++ programming, basic parallel computing (from Operating Systems lectures)
Scadenza validita proposta 27/07/2020 PROPONI LA TUA CANDIDATURA