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"Topic": models, code, and papers

Reproducible Pattern Recognition Research: The Case of Optimistic SSL

Dec 27, 2016
Jesse H. Krijthe, Marco Loog

In this paper, we discuss the approaches we took and trade-offs involved in making a paper on a conceptual topic in pattern recognition research fully reproducible. We discuss our definition of reproducibility, the tools used, how the analysis was set up, show some examples of alternative analyses the code enables and discuss our views on reproducibility.

* Presented at RRPR 2016: 1st Workshop on Reproducible Research in Pattern Recognition 

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Network Routing Optimization Using Swarm Intelligence

Aug 17, 2015
Mohamed A. El Galil

The aim of this paper is to highlight and explore a traditional problem, which is the minimum spanning tree, and finding the shortest-path in network routing, by using Swarm Intelligence. This work to be considered as an investigation topic with combination between operations research, discrete mathematics, and evolutionary computing aiming to solve one of networking problems.

* 10 Pages 

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Automatic Discourse Segmentation: Review and Perspectives

May 01, 2020
Iria da Cunha, Juan-Manuel Torres-Moreno

Multilingual discourse parsing is a very prominent research topic. The first stage for discourse parsing is discourse segmentation. The study reported in this article addresses a review of two on-line available discourse segmenters (for English and Portuguese). We evaluate the possibility of developing similar discourse segmenters for Spanish, French and African languages.

* International Workshop on African Human Language Technologies. 17-20 Jan 2010 
* 5 pages, 1 figure 

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Towards a Heuristic Categorization of Prepositional Phrases in English with WordNet

Feb 04, 2010
Frank Rudzicz, Serguei A. Mokhov

This document discusses an approach and its rudimentary realization towards automatic classification of PPs; the topic, that has not received as much attention in NLP as NPs and VPs. The approach is a rule-based heuristics outlined in several levels of our research. There are 7 semantic categories of PPs considered in this document that we are able to classify from an annotated corpus.

* 8 pages; 4 tables; 1 figure; a year 2003 report 

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Centering in Dynamic Semantics

Jul 14, 1998
Daniel Hardt

Centering theory posits a discourse center, a distinguished discourse entity that is the topic of a discourse. A simplified version of this theory is developed in a Dynamic Semantics framework. In the resulting system, the mechanism of center shift allows a simple, elegant analysis of a variety of phenomena involving sloppy identity in ellipsis and ``paycheck pronouns''.

* Proceedings of COLING 96, Copenhagen, Denmark 

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Proceedings of The 38th Annual Workshop of the Austrian Association for Pattern Recognition (ÖAGM), 2014

Apr 30, 2014
Vladimir Kolmogorov, Christoph Lampert, Emilie Morvant, Rustem Takhanov

The 38th Annual Workshop of the Austrian Association for Pattern Recognition (\"OAGM) will be held at IST Austria, on May 22-23, 2014. The workshop provides a platform for researchers and industry to discuss traditional and new areas of computer vision. This year the main topic is: Pattern Recognition: interdisciplinary challenges and opportunities.


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Neuro-Symbolic Artificial Intelligence: Current Trends

May 14, 2021
Md Kamruzzaman Sarker, Lu Zhou, Aaron Eberhart, Pascal Hitzler

Neuro-Symbolic Artificial Intelligence -- the combination of symbolic methods with methods that are based on artificial neural networks -- has a long-standing history. In this article, we provide a structured overview of current trends, by means of categorizing recent publications from key conferences. The article is meant to serve as a convenient starting point for research on the general topic.

* under review 

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Neuro-Symbolic Artificial Intelligence Current Trends

May 11, 2021
Md Kamruzzaman Sarker, Lu Zhou, Aaron Eberhart, Pascal Hitzler

Neuro-Symbolic Artificial Intelligence -- the combination of symbolic methods with methods that are based on artificial neural networks -- has a long-standing history. In this article, we provide a structured overview of current trends, by means of categorizing recent publications from key conferences. The article is meant to serve as a convenient starting point for research on the general topic.

* under review 

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Towards Learning Fine-Grained Disentangled Representations from Speech

Aug 08, 2018
Yuan Gong, Christian Poellabauer

Learning disentangled representations of high-dimensional data is currently an active research area. However, compared to the field of computer vision, less work has been done for speech processing. In this paper, we provide a review of two representative efforts on this topic and propose the novel concept of fine-grained disentangled speech representation learning.


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An Introduction to Johnson-Lindenstrauss Transforms

Feb 28, 2021
Casper Benjamin Freksen

Johnson--Lindenstrauss Transforms are powerful tools for reducing the dimensionality of data while preserving key characteristics of that data, and they have found use in many fields from machine learning to differential privacy and more. This note explains what they are; it gives an overview of their use and their development since they were introduced in the 1980s; and it provides many references should the reader wish to explore these topics more deeply.

* The text was previously a main part of the introduction of my PhD thesis, but it has been adapted to be self contained and serve as a (hopefully good) starting point for readers interested in the topic 

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