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Physical Sciences and Mathematics Commons™
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- 3d object recognition (1)
- Active vision (1)
- Data mining information extraction (1)
- Game theory (1)
- Knowledge discovery (1)
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- Local search engine (1)
- Machine learning (1)
- Machine vision (1)
- Nash equilibrium (1)
- Natural language processing (1)
- Object recognition (1)
- Peripheral-foveal vision (1)
- Reinforcement learning (1)
- Scene reconstruction (1)
- Stereo correspondence (1)
- Text mining (1)
- Topical crawling (1)
- Topical relevancy (1)
- Transfer learning (1)
- Two-player games (1)
- Vertical search engine (1)
- Zero-sum games (1)
Articles 1 - 6 of 6
Full-Text Articles in Physical Sciences and Mathematics
A Survey Of Transfer Learning Methods For Reinforcement Learning, Nicholas Bone
A Survey Of Transfer Learning Methods For Reinforcement Learning, Nicholas Bone
Computer Science Graduate and Undergraduate Student Scholarship
Transfer Learning (TL) is the branch of Machine Learning concerned with improving performance on a target task by leveraging knowledge from a related (and usually already learned) source task. TL is potentially applicable to any learning task, but in this survey we consider TL in a Reinforcement Learning (RL) context. TL is inspired by psychology; humans constantly apply previous knowledge to new tasks, but such transfer has traditionally been very difficult for—or ignored by—machine learning applications. The goals of TL are to facilitate faster and better learning of new tasks by applying past experience where appropriate, and to enable autonomous …
Finding Nash Equilibria In Two-Player, Zero Sum Games, Jeffrey Wimpee
Finding Nash Equilibria In Two-Player, Zero Sum Games, Jeffrey Wimpee
Computer Science Graduate and Undergraduate Student Scholarship
In many games, it is desirable to find strategies for all players that simultaneously maximize their respective worst-case payoffs. A set of strategies satisfying this criterion is called a Nash equilibrium. Because the search space of possible strategies grows rapidly as the size of the game increases, specialized algorithms are needed to efficiently find Nash equilibria. In this paper, current equilibrium-finding methods are presented and key areas for future work are identified. The first algorithm, due to Koller, Megiddo, and von Stengel, computes standard Nash equilibria in two-player, zero-sum games. The second algorithm, due to Miltersen and Sorensen, extends the …
Machine Vision: A Survey, David Phillips
Machine Vision: A Survey, David Phillips
Computer Science Graduate and Undergraduate Student Scholarship
This paper surveys the field of machine vision from a computer science perspective. It is written to act as an introduction to the field and presents the reader with references to specific implementations. Machine vision is a complex and developing field that can be broken into the three stages: stereo correspondence, scene reconstruction, and object recognition. We present the techniques and general approaches to each of these stages and summarize the future direction of research.
Information Extraction In Text Mining, Matt Mulins
Information Extraction In Text Mining, Matt Mulins
Computer Science Graduate and Undergraduate Student Scholarship
Text mining’s goal, simply put, is to derive information from text. Using multitudes of technologies from overlapping fields like Data Mining and Natural Language Processing we can yield knowledge from our text and facilitate other processing. Information Extraction (IE) plays a large part in text mining when we need to extract this data. In this survey we concern ourselves with general methods borrowed from other fields, with lower-level NLP techniques, IE methods, text representation models, and categorization techniques, and with specific implementations of some of these methods. Finally, with our new understanding of the field we can discuss a proposal …
Developing Web Crawlers For Vertical Search Engines: A Survey Of The Current Research, Pedro Huitema
Developing Web Crawlers For Vertical Search Engines: A Survey Of The Current Research, Pedro Huitema
Computer Science Graduate and Undergraduate Student Scholarship
Vertical search engines allow users to query for information within a subset of documents relevant to a pre-determined topic (Chakrabarti, 1999). One challenging aspect to deploying a vertical search engine is building a Web crawler that distinguishes relevant documents from non-relevant documents. In this research, we describe and analyze various methods to crawl relevant documents for vertical search engines, and we examine ways to apply these methods to building a local search engine. In a typical crawl cycle for a vertical search engine, the crawler grabs a URL from the URL frontier, downloads content from the URL, and determines the …
Combined Object Recognition Approaches For Mobile Robotics, Rusty Gerard
Combined Object Recognition Approaches For Mobile Robotics, Rusty Gerard
Computer Science Graduate and Undergraduate Student Scholarship
There are numerous solutions to simple object recognition problems when the machine is operating under strict environmental conditions (such as lighting). Object recognition in real-world environments poses greater difficulty however. Ideally mobile robots will function in real-world environments without the aid of fiduciary identifiers. More robust methods are therefore needed to perform object recognition reliably. A combined approach of multiple techniques improves recognition results. Active vision and peripheral-foveal vision—systems that are designed to improve the information gathered for the purposes of object recognition—are examined. In addition to active vision and peripheral-foveal vision, five object recognition methods that either make use …