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Filtering by: Creator Si, Qi Remove constraint Creator: Si, Qi Degree Field Computer Science Remove constraint Degree Field: Computer Science

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  • Novelty Detection Under the Multi-Instance Multi-Label Framework

    Creator:
    Lou, Qi
    Abstract:
    Novelty detection plays an important role in machine learning and signal processing. This project studies novelty detection in a new setting where the data object is represented as a bag of instances and associated with multiple class labels, referred to as multi-instance multi-label (MIML) learning. Contrary to the common assumption...
    Resource Type:
    Capstone Project
    Full Text:
    AN ABSTRACT OF THE PROJECT REPORT OF Qi Lou for the degree of Master

  • Leveraging Structures of the Data in Deep Learning

    Creator:
    Li, Xingyi
    Abstract:
    The performance of deep learning frameworks could be significantly improved through considering the particular underlying structures for each dataset. In this thesis, I summarize our three work about boosting the performance of deep learning models through leveraging structures of the data. In the first work, we theoretically justify that, for...
    Resource Type:
    Dissertation
    Full Text:
    Pei, Zeyu You, Anh The Pham, Zeyu You, Thi Tam Nguyen, Thi Kim Phung Lai, Zhongang Qi, Jialin Yuan

  • Supervised Hierarchical Segmentation for Bird Bioacoustics

    Creator:
    Tjahja, Teresa V.
    Abstract:
    Bioacoustics analysis can be used to conduct environmental monitoring by detecting the presence of birds species. This analysis usually involves identifying the species from their calls. In most frameworks, bird song syllables are extracted from audio recordings and individual syllables are input to a classifier to identify the species. Extraction...
    Resource Type:
    Masters Thesis
    Full Text:
    in the solution set S ∗, wi is the weight of segment si, and qi is its predicted quality. Note that

  • Learning hierarchical decomposition rules for planning : an inductive logic programming approach

    Creator:
    Reddy, Chandrasekhara K.
    Abstract:
    Artificial Intelligence (AI) planning techniques have been central to automating a gamut of tasks from the mundane route planning and beer production to the ethereal image processing of space-ship images. Of all the planning techniques, hierarchical- decomposition planning has been the technique most employed in industrial-strength planners. Hierarchical-decomposition planning is...
    Resource Type:
    Dissertation
    Full Text:
    to a path S0 = S; S1; S2; : : : ; St in the state space where S is the start state, and Si, for i 2

  • Individual Fairness Optimization in Machine Learning with Minimax Loss and an Abstain Option

    Creator:
    Behnoudfar, Ali
    Abstract:
    In this thesis, a new learning algorithm is introduced that is targeted towards individual fairness. In order to be individually fair, mispredictions need to be avoided as each such prediction means the learning algorithm was unfair towards some individual. Therefore, achieving individual fairness implies having a perfect classifier, which is...
    Resource Type:
    Masters Thesis
    Full Text:
    max γ n∑ i=1 γsi ∗ φ(f(xi), yi)) (1.2) Therefore, in contrast to described group fairness

  • Structured gradient boosting

    Creator:
    Parker, Charles (Charles Lincoln)
    Abstract:
    The goal of many machine learning problems can be formalized as the creation of a function that can properly classify an input vector, given a set of examples of that function. While this formalism has produced a number of success stories, there are notable situations in which it fails. One...
    Resource Type:
    Dissertation

  • Description and comments on a matrix algebraic method for the determination of isomorphism in pairs of undirected graphs

    Creator:
    Fogg, Ka-Hung
    Abstract:
    This paper describes an investigation of a matrix algebraic method to determine isomorphism in pairs of undirected graphs. The method is described in some detail. The theoretical as well as the practical difficulties are given. It is shown that the method works for some cases. When the adjacency matrix of...
    Resource Type:
    Capstone Project
    Full Text:
    as t com puters c an har dly handle much more th an a graph of si ze 10. For practical situations

  • A generalization of tree automata and its relation to matrix grammars

    Creator:
    Vomocil, David Leo
    Abstract:
    In this thesis we introduce alpha and beta tree acceptors, generalizations of tree automata. The alpha tree acceptors recognize a tree by final symbol and the beta tree acceptors by final state. We show that alpha and beta tree acceptors recognize the same sets of Gorn trees and demonstrate that...
    Resource Type:
    Masters Thesis
    Full Text:
    there exists an i, 1 < i < n such that s = Si and 2) S. < Fr(D) is called the frontier of D

  • Towards Narrative Understanding with Deep Neural Networks and Hidden Markov Models

    Creator:
    Orr, J. Walker
    Abstract:
    Narratives are central to communication and the human experience. For a computer system to understand a narrative, it must be able to identify the key facts or plot elements that describe what happened or how the world has changed. These element are called events;establishing a document’s events and the relationships...
    Resource Type:
    Dissertation

  • Learning ranking functions for efficient search

    Creator:
    Xu, Yuehua
    Abstract:
    This dissertation explores algorithms for learning ranking functions to efficiently solve search problems, with application to automated planning. Specifically, we consider the frameworks of beam search, greedy search, and randomized search, which all aim to maintain tractability at the cost of not guaranteeing completeness nor optimality. Our learning objective for...
    Resource Type:
    Dissertation
    Full Text:
    Problems Our learning problems provide training sets of pairs {〈Si, Pi〉}, where the Si = 〈Ii, si(·), fi