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====== Google Summer of Code 2018 ====== | ====== Google Summer of Code 2018 ====== | ||
~~NOTOC~~ | ~~NOTOC~~ | ||
+ | ===== pracmln ===== | ||
+ | |||
+ | //pracmln// is a toolbox for statistical relational learning (SRL) and | ||
+ | reasoning and as such also includes tools for standard probabilistic | ||
+ | graphical models. //pracmln// is an implementation of Markov logic networks (MLN) | ||
+ | that supports efficient learning and inference in relational domains. | ||
+ | Its learning and inference engines are entirely written in the Python | ||
+ | programming language. Markov logic networks generalize both first-order | ||
+ | logic and probabilistic graphical models and have proven successful | ||
+ | in many real-world applications such as natural-language understanding | ||
+ | and robot perception. This makes MLNs one of the most general and most | ||
+ | powerful representation formalisms for uncertain knowledge. | ||
+ | |||
+ | //pracmln// was designed with the particular needs of technical systems in | ||
+ | mind. Our methods are geared towards practical applicability and can | ||
+ | easily be integrated into other applications. The availability of | ||
+ | graphical tools makes both learning or inference sessions a | ||
+ | user-friendly experience. Scripting support enables automation, and | ||
+ | a browser-based [[http:// | ||
+ | familiar with MLNs. | ||
+ | |||
+ | //pracmln// is an open-source project hosted on [[https:// | ||
+ | project page ([[http:// | ||
+ | and tutorials that facilitate getting started with MLNs. It is provided as a pip | ||
+ | package in the Python package index ([[https:// | ||
+ | |||
+ | ==== Topic 1: Markov logic networks in Python ==== | ||
+ | |||
+ | [[http:// | ||
+ | |||
+ | |||
+ | **Main Objective: | ||
+ | Python. The main objective of this project is to port the | ||
+ | computationally heavy parts of the learning and inference algorithms to | ||
+ | Cython (cython.org), | ||
+ | compilation of Python modules to C libraries. Cython allows to add | ||
+ | static type declarations to Python, which can significantly speed up | ||
+ | execution (up to a factor of 1000 compared to regular Python code). | ||
+ | |||
+ | As most of the Python libraries for machine learning and scientific | ||
+ | computing (e.g. scikit-learn, | ||
+ | it is expected that the practical applicability of Markov logic networks | ||
+ | will substanially be pushed to more demanding real-world scenarios. | ||
+ | |||
+ | **Task Difficulty: | ||
+ | solving this task properly requires understanding and experience in | ||
+ | gradient-based optimization, | ||
+ | |||
+ | **Requirements: | ||
+ | language (CPython/ | ||
+ | (ideally SRL technques and logic) | ||
+ | |||
+ | **Expected Results:** The core components of pracmln, i.e. the learning | ||
+ | and inference modules are expected to be ported to the Cython language | ||
+ | exploiting the means of implementational optimization provided by | ||
+ | Cython. | ||
+ | **Contact: | ||
===== Proposed Topics ===== | ===== Proposed Topics ===== | ||
In the following, we list our proposals for the Google Summer of Code topics that contribute to the aforementioned open-source projects. | In the following, we list our proposals for the Google Summer of Code topics that contribute to the aforementioned open-source projects. |
Prof. Dr. hc. Michael Beetz PhD
Head of Institute
Contact via
Andrea Cowley
assistant to Prof. Beetz
ai-office@cs.uni-bremen.de
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