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Filtering by: Creator Strahl, Jordan D. Remove constraint Creator: Strahl, Jordan D. Committee Member Fern, Xiaoli Remove constraint Committee Member: Fern, Xiaoli Resource Type Dissertation Remove constraint Resource Type: Dissertation

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  • Advances in Simultaneous Translation

    Creator:
    Zheng, Renjie
    Abstract:
    Simultaneous translation, which translates concurrently with the source language speech, is widely used in many scenarios including multilateral organizations. However, it is well known to be one of the most challenging tasks for humans due to the simultaneous perception and production in two languages. On the other hand, simultaneous translation...
    Resource Type:
    Dissertation
    Full Text:
    会晤 (d) simultaneous: non-predictive ...wait 2 words... pres. bush ..... wait 5 words ...... met with

  • Efficient training and feature induction in sequential supervised learning

    Creator:
    Hao, Guohua
    Abstract:
    Sequential supervised learning problems arise in many real applications. This dissertation focuses on two important research directions in sequential supervised learning: efficient training and feature induction. In the direction of efficient training, we study the training of conditional random fields (CRFs), which provide a flexible and powerful model for sequential...
    Resource Type:
    Dissertation
    Full Text:
    incorrect modeling assumptions (Ng and Jordan, 2002). McCallum and his collaborators introduced maximum

  • Integrated Intermodal Logistics Network Design

    Creator:
    Ghane-Ezabadi, Mohammad
    Abstract:
    Intermodal freight transportation uses at least two different transportation modes (e.g., truck, rail, ship, air) to move freight loads that are in the same transportation unit (e.g., a shipping container) from origin to destination without handling the goods themselves. The increasing shift to intermodal transportation and the growth of freight...
    Resource Type:
    Dissertation
    Full Text:
    complete networks with load demand for 20% of all possible O-D pairs. ................. 28 Figure 3.1

  • Weak-supervision : Probabilistic Models and Inference

    Creator:
    Pham, Anh
    Abstract:
    In supervised learning, label information can be provided at different levels of granularity. For small datasets, it is possible to acquire a label for each data instance. However, in the big-data regime, this fine granularity approach is prohibitively costly. For example, in semi-supervised learning, only a limited number of samples...
    Resource Type:
    Dissertation
    Full Text:
    original model. (b) The model with new variables. (c) Compute p(Y1b |Xb,w). (d) Com- pute p(Y2b |Xb,w). (e

  • New learning modes for sequential decision making

    Creator:
    Judah, Kshitij
    Abstract:
    This thesis considers the problem in which a teacher is interested in teaching action policies to computer agents for sequential decision making. The vast majority of policy learning algorithms o er teachers little flexibility in how policies are taught. In particular, one of two learning modes is typically considered: 1)...
    Resource Type:
    Dissertation
    Full Text:
    on (a) Cart- pole (b) Bicycle balancing (c) Wargus (d) Driving Domain. . . . . . . . . 80 4.4

  • Domain-Independent Planning for Markov Decision Processes with Factored State and Action Spaces

    Creator:
    Raghavan, Aswin
    Abstract:
    Markov Decision Processes (MDPs) are the de-facto formalism for studying sequential decision making problems with uncertainty, ranging from classical problems such as inventory control and path planning, to more complex problems such as reservoir control under rainfall uncertainty and emergency response optimization for fire and medical emergencies. Most prior research...
    Resource Type:
    Dissertation
    Full Text:
    pruning operator P(D,π) ≡ Pπ(D) for any ADD D and a policy constraint BDD π

  • Machine learning for improving the quality of citizen science data

    Creator:
    Yu, Jun
    Abstract:
    Citizen Science is a paradigm in which volunteers from the general public participate in scientific studies, often by performing data collection. This paradigm is especially useful if the scope of the study is too broad to be performed by a limited number of trained scientists. Although citizen scientists can contribute...
    Resource Type:
    Dissertation
    Full Text:
    : (a) observer, (b) location, (c) visit, and (d) species. Observer information (e.g. name, ID and

  • Towards Direct Simultaneous Speech Translation

    Creator:
    Chen, Junkun
    Abstract:
    Simultaneous speech translation (SimulST) is widely useful in many cross-lingual communication scenarios, including multinational conferences and international traveling. Since text-based simultaneous machine translation (SimulMT) has achieved great success in recent years. The conventional cascaded approach for SimulST uses a pipeline of streaming ASR followed by simultaneous MT but suffers from...
    Resource Type:
    Dissertation
    Full Text:
    reported in Inaguma et al. [46]. Pino et al. [73] use extra D′s,y which includes Librispeech (Ds,x) and

  • Creating, Understanding and Applying Machine Learning Models of Multiple Species

    Creator:
    Griffioen, Arwen Twinkle E.
    Abstract:
    Many problems in ecology and conservation biology can be formulated and solved using machine learning algorithms for multi-label classification. This dissertation addresses three topics related to predicting the distributions of multiple species. It improves existing methods and proposes a new modeling paradigm to address the multi-species, multi-label problem. The first...
    Resource Type:
    Dissertation
    Full Text:
    under Contract No. FA8750-07-D-0185/0004 through the Air Force Research Laboratory (AFRL). Any

  • Parsing with Recurrent Neural Networks

    Creator:
    Cross, James Henry, III
    Abstract:
    Machine learning models for natural language processing have traditionally relied on large numbers of discrete features, built up from atomic categories such as word forms and part-of-speech labels, which are considered completely distinct from each other. Recently however, the advent of dense feature representations coupled with deep learning techniques has...
    Resource Type:
    Dissertation