Browse by Subject "machine learning"

  • Xu, Xun (2010-06-29)
    In this dissertation we study key problems in face processing, with a focus on the applications in biometrics, including both hard biometrics (i.e. conventional face recognition) and soft biometrics, where demographical ...

    application/pdf

    application/pdfPDF (3Mb)
  • Yoo, Wucherl (2013-02-03)
    Applications may have unintended performance problems in spite of compiler optimizations, because of the complexity of the state of the art hardware technologies. Most modern processors incorporate multiple cores that have ...

    application/pdf

    application/pdfPDF (3Mb)
  • Heidorn, P. Bryan (Published by the Dublin Core Metadata Initiative and Universitätsverlag Göttingen 2008, 2008-09-24)
    This paper describes the information properties of museum specimen labels and machine learning tools to automatically extract Darwin Core (DwC) and other metadata from these labels processed through Optical Character ...

    application/pdf

    application/pdfPDF (435Kb)
  • Do, Quang (2012-09-18)
    In this thesis, we study the importance of background knowledge in relation extraction systems. We not only demonstrate the benefits of leveraging background knowledge to improve the systems' performance but also propose ...

    application/pdf

    application/pdfPDF (614Kb)
  • Nath, Vishnu (2012-05)
    My research deals with incorporating Artificial Intelligence into a humanoid robot by making a cognitive model of the learning process. The goal is to “teach” a robot to fire a gun by allowing it to make small errors and ...

    application/pdf

    application/pdfPDF (2Mb)Restricted to U of Illinois
  • Ratinov, Lev; Roth, Dan; Srikumar, Vivek (2008-01)
    The most fundamental problem in information retrieval is that of interpreting information needs of users, typically expressed in a short query. Using the surface level representation of the query is especially unsatisfactory ...

    application/pdf

    application/pdfPDF (226Kb)
  • Chang, Shiyu (2011-05)
    In this paper, we concentrate on exploring the cross-category knowledge to enhance the information on the target categories with a small number of positive training examples. In many cases, even the intra-category knowledge ...

    application/pdf

    application/pdfPDF (754Kb)Restricted to U of Illinois
  • Lim, Shiau Hong (2009-05-05)
    Incorporating additional information from our prior domain knowledge can be the key to solving difficult classification tasks, especially when the available training data is limited. The crucial stage of feature construction, ...

    application/pdf

    application/pdfPDF (733Kb)
  • Sarmiento, Alejandro (2004-12)
    This work addresses the problem of generating a motion strategy for solving a visibility-based task with a mobile robot equipped with sensors. In particular, the problem is to find a static object -- modeled with a probability ...

    application/pdf

    application/pdfPDF (2Mb)
  • Akbas, Emre (2011-08-26)
    This dissertation is about extracting as well as making use of the structure and hierarchy present in images. We develop a new low-level, multiscale, hierarchical image segmentation algorithm designed to detect image ...

    application/pdf

    application/pdfPDF (13Mb)
  • Crisostomo Romero, Pedro Moises (2011-05-25)
    Hand detection on images has important applications on person activities recognition. This thesis focuses on PASCAL Visual Object Classes (VOC) system for hand detection. VOC has become a popular system for object detection, ...

    application/pdf

    application/pdfPDF (1Mb)
  • Tran, Du; Sorokin, Alexander; Forsyth, David A. (2008-03)
    This paper proposes a metric learning based approach for human activity recognition with two main objectives: (1) reject unfamiliar activities and (2) learn with few examples. We show that our approach outperforms all ...

    application/pdf

    application/pdfPDF (7Mb)
  • Wen, Zhen (2004-07)
    Human faces provide important cues of human activities. Thus they are useful for human-human communication, human-computer interaction (HCI) and intelligent video surveillance. Computational models for face analysis and ...

    application/pdf

    application/pdfPDF (3Mb)
  • Small, Kevin M. (2009-10-02)
    Statistical machine learning has become an integral technology for solving many informatics applications. In particular, corpus-based statistical techniques have emerged as the dominant paradigm for core natural language ...

    application/pdf

    application/pdfPDF (2Mb)
  • Jin, Jing (2014-01-16)
    Traditionally, multiple linear regression has been widely used in the field of organizational science for predictive modeling. Despite its pervasive use, the classical regression model falls short in several aspects, ...

    application/pdf

    application/pdfPDF (2Mb)
  • Heidorn, P. Bryan; Zhang, Qianjin (iSchools, 2013-02)
    The LABELX (Label Annotation through Biodiversity Enhanced Learning) is an extension of the HERBIS NLP system reported previously (Heidorn & Wei, 2008). The objective of the system is to formaly structure output from Optical ...

    application/pdf

    application/pdfPDF (179Kb)
  • Rizzolo, Nicholas (2012-02-06)
    Machine learning (ML) is the study of representations and algorithms used for building functions that improve their behavior with experience. Today, researchers in many domains are applying ML to solve their problems when ...

    application/pdf

    application/pdfPDF (1Mb)
  • Garg, Pranav; Neider, Daniel; Madhusudan, P.; Roth, Dan (2015)
    Inductive invariants can be robustly synthesized using a learning model where the teacher is a program verifier who instructs the learner through concrete program configurations, classified as positive, negative, and ...

    application/pdf

    application/pdfPDF (597Kb)
  • 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 ...

    application/pdf

    application/pdfPDF (197Kb)
  • 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 ...

    application/pdf

    application/pdfPDF (4Mb)