Browse Research and Tech Reports - Computer Science by Subject "machine learning"

  • Rothganger, Fredrick H. (2004-11)
    This thesis introduces a novel representation for three-dimensional (3D) objects in terms of local affine-invariant descriptors of their appearance and the spatial relationships between the corresponding affine regions. ...

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  • 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 ...

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  • 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 ...

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  • Tran, Du; Sorokin, Alexander; Forsyth, David (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 ...

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  • 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 ...

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  • 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 ...

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  • 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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  • 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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  • 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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  • 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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  • 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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