Browse by Subject "machine learning"

  • Chang, Allan; Amir, Eyal (2005-11)
    We present new algorithms for learning a logical model of actions' effects and preconditions in partially observable domains. The algorithms maintain a logical representation of the set of possible action models after each ...

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  • Klementiev, Alexandre A. (2010-01-06)
    Recent technological advances have facilitated the collection and distribution of a plethora of increasingly diverse and complex data. Supervised learning has been able to provide the toolbox of choice for exploiting it ...

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  • Zhang, Yanjun; Cui, Hong; Burkell, Jacquelyn; Mercer, Robert E. (iSchools, 2014-03-01)
    As health care information proliferates on the web, the content quality is varied and difficult to assess, partially due to the large volume and the dynamicity. This paper reports an automated approach in which the quality ...

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  • Li, Xiaoming (2006-08)
    The growing complexity of modern processors has made the generation of highly efficient code increasingly difficult. Manual code generation is very time consuming, but it is often the only choice since the code generated ...

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  • Kejriwal, Mayank (2011-12)
    In this thesis, we investigate techniques for the automatic transcription of handwritten text in digitally scanned United States Census forms from the 1930s. We experimentally show that Word Spotting techniques like Dynamic ...

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  • Choi, Erik; Kitzie, Vanessa; Shah, Chirag (iSchools, 2013-02)
    While social question-answering (SQA) services are becoming increasingly popular, there is often an issue of unsatisfactory or missing information for a question posed by an information seeker. This study creates a model ...

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  • Nimon, Kim; Caragea, Cornelia; Oswald, Frederick L. (iSchools, 2013-02)
    Meta-analysis is a principled statistical approach for summarizing quantitative information reported across studies within a research domain of interest. Although the results of meta-analyses can be highly informative for ...

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  • Sukumar, Pritam (2013-08-22)
    This thesis presents an investigation of the Collection of Parts Model for object categorization. Multiclass categorization is performed using the Collections of Parts model. Results using Support Vector Machines, L1 ...

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  • Candido, Salvatore J. (2011-08-25)
    We propose a new method for learning policies for large, partially observable Markov decision processes (POMDPs) that require long time horizons for planning. Computing optimal policies for POMDPs is an intractable problem ...

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  • Jiang, Chong (2011-01-14)
    In this thesis, we consider the problem of multi-armed bandits with a large number of correlated arms. We assume that the arms have Bernoulli distributed rewards, independent across arms and across time, where the ...

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  • Carrasco Kind, Matias (2015-01-21)
    With the growth of large photometric surveys, accurately estimating photometric redshifts, preferably as a probability density function (PDF), and fully understanding the implicit systematic uncertainties in this process ...

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  • Yan, Jasy Liew Suet; McCracken, Nancy; Crowston, Kevin (iSchools, 2014-03-01)
    Qualitative content analysis is commonly used by social scientists to understand the practices of the groups they study, but it is often infeasible to manually code a large text corpus within a reasonable time frame and ...

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  • Kim, Eric (2015-01-21)
    Machine learning (ML) based inference has recently gained importance as a key kernel in processing massive data in digital signal processing (DSP) systems. Due to the ever increasing complexity of DSP systems, energy-efficient ...

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  • Agarwal, Shivani (2005-05)
    The problem of ranking, in which the goal is to learn a real-valued ranking function that induces a ranking or ordering over an instance space, has recently gained attention in machine learning. A particular setting of ...

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  • Tsai, Shen-Fu (2013-02-03)
    Lack of human prior knowledge is one of the main reasons that the semantic gap still remains when it comes to automatic multimedia understanding. One difference between the human cognition system and state-of-the-art machine ...

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  • Cheng, Hong (2008-05)
    Classification is a core method widely studied in machine learning, statistics, and data mining. A lot of classification methods have been proposed in literature, such as Support Vector Machines, Decision Trees, and Bayesian ...

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  • Mayhew, Stephen (2014-05-30)
    We begin by giving a comprehensive literature review that ties together many fields which have heretofore remained separate. We comment on the approaches from each field and show which algorithms are similar and which are ...

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  • Mahmud, M. M. Hassan (2008-07)
    The aim of transfer learning is to reduce sample complexity required to solve a learning task by using information gained from solving related tasks. Transfer learning has in general been motivated by the observation that ...

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  • Xu, Tianfang (2012-05-22)
    Current analyses of groundwater flow and transport typically rely on a physically-based model (PBM), which is inherently subject to error and uncertainty from multiple sources including model structural error, parameter ...

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  • Demarest, Bradford; Sugimoto, Cassidy R. (iSchools, 2013-02)
    This paper presents the results of a study of disciplinary stylistic differences among dissertation abstracts from physics, psychology, and philosophy. Based on differences in relative frequencies of metadiscourse terms ...

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