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  • Anomaly Detection and Probabilistic Diagnosis for Automated Data Quality Control

    Creator:
    Zemicheal, Tadesse H.
    Abstract:
    Advances in sensor technology are greatly expanding the range of quantities that can be measured while simultaneously reducing the cost. However, deployed sensors drift out of calibration and fail, so every sensor network requires quality control procedures to promptly detect these failures. To address these problems, we propose a two-level...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Tadesse H. Zemicheal

  • Power efficient H.264 video decoding in embedded multiprocessor

    Creator:
    Kim, Jihong
    Abstract:
    This thesis presents a novel methodology that enables power efficient video decoding in an embedded system based on MPSoC (Multiprocessor System on Chip). This methodology is a physical combination of parallel processing which reduces power consumption of processors by exploiting thread-level parallelism and Dynamic Voltage Frequency Scaling (DVFS) that allows...
    Resource Type:
    Masters Thesis
    Full Text:
    horizontal integer samples E, F, G, H, I and J, and h is calculated from the six vertical integer samples A

  • AID: An automated detector for gender-inclusivity bugs in OSS project pages

    Creator:
    Chatterjee, Amreeta, Guizani, Mariam, Stevens, Catherine, Emard, Jillian, May, Mary Evelyn, Burnett, Margaret, Ahmed, Iftekhar, and Sarma, Anita
    Abstract:
    The tools and infrastructure used in tech, including Open Source Software (OSS), can embed “inclusivity bugs”—features that disproportionately disadvantage particular groups of contributors. To see whether OSS developers have existing practices to ward off such bugs, we surveyed 266 OSS developers. Our results show that a majority (77%) of developers...
    Resource Type:
    Conference Proceeding
    Full Text:
    would be unable to predict whether information might lie behind the link. This may be why the Nielsen

  • Simulator-Defined MDP Planning with Applications in Natural Resource Management

    Creator:
    Alkaee Taleghan, Majid
    Abstract:
    This work is inspired by problems in natural resource management centered on the challenge of invasive species. Computing optimal management policies for maintaining ecosystem sustainable is challenging. Many ecosystem management problems can be formulated as MDP (Markov Decision Process) planning problems. In a simulator-defined MDP, the Markovian dynamics and rewards...
    Resource Type:
    Dissertation
    Full Text:
    G. Dietterich This work is inspired by problems in natural resource management centered on the

  • Machine Learning Methods for Computational Sustainability

    Creator:
    Liu, Liping
    Abstract:
    Maintaining the sustainability of the earth’s ecosystems has attracted much attention as these ecosystems are facing more and more pressure from human activities. Machine learning can play an important role in promoting sustainability as a large amount of data is being collected from ecosystems. There are at least three important...
    Resource Type:
    Dissertation
    Full Text:
    Methods for Computational Sustainability Abstract approved: Thomas G. Dietterich Maintaining the

  • Protein secondary structure prediction using conditional random fields and profiles

    Creator:
    Shen, Rongkun
    Abstract:
    Protein secondary structure prediction plays a pivotal role in predicting protein folding in three-dimensions. Its task is to assign each residue one of the three secondary structure classes helix, strand, or random coil. This is an instance of the problem of sequential supervised learning in machine learning. This thesis describes...
    Resource Type:
    Masters Thesis
    Full Text:
    Sander (Rost and Sander, 1993): H, G to H; E, B to E; and the remaining to C. Most papers

  • Applying machine learning for prediction, recommendation, and integration

    Creator:
    Bao, Xinlong
    Abstract:
    This dissertation explores the idea of applying machine learning technologies to help computer users find information and better organize electronic resources, by presenting the research work conducted in the following three applications: FolderPredictor, Stacking Recommendation Engines, and Integrating Learning and Reasoning. FolderPredictor is an intelligent desktop software tool that helps...
    Resource Type:
    Dissertation
    Full Text:
    approved: Thomas G. Dietterich This dissertation explores the idea of applying machine learning

  • Constraining Bayesian network learning with qualitative models

    Creator:
    Altendorf, Eric E.
    Abstract:
    Machine learning encompasses probabilistic and statistical techniques that can build models from large quantities of extensional information (examples) with minimal dependence on intensional information (domain knowledge). This focus of machine learning is reflected in the never-ending quest for "off-the-shelf" classifiers. To generalize to unseen data, however, we must make use...
    Resource Type:
    Masters Thesis
    Full Text:
    discrete node X may take G The graphical structure of a Bayesian network Q The qualitative model (i.e

  • Machine learning methods for public policy : simulation, optimization, and visualization

    Creator:
    McGregor, Sean
    Abstract:
    Society faces many complex management problems, particularly in the area of shared public resources such as ecosystems. Existing decision making processes are often guided by personal experience and political ideology rather than state-of-the-art scientific understanding. This dissertation envisions a future in which multiple stakeholders are provided with computational tools for...
    Resource Type:
    Dissertation
    Full Text:
    Methods for Public Policy: Simulation, Optimization, and Visualization Abstract approved: Thomas G

  • Three methods for estimating subpixel cover fractions in coarse resolution imagery

    Creator:
    Damon, Diane L.
    Abstract:
    Coarse resolution imagery, such as that produced by the MODIS instrument, poses the challenge of estimating sub-pixel proportions of di erent land cover types. This problem is di cult because of the variety and variability of vegetation within individual pixels. This thesis describes and compares two existing algorithms for estimating...
    Resource Type:
    Masters Thesis
    Full Text:
    of Master of Science in Computer Science presented on May 28, 2003. Title: Three Methods for

  • Improving automated email tagging with implicit feedback

    Creator:
    Sorower, Mohammad Shahed
    Abstract:
    Machine learning systems are generally trained offline using ground truth data that has been labeled by experts. However, these batch training methods are not a good fit for many applications, especially in the cases where complete ground truth data is not available for offline training. In addition, batch methods do...
    Resource Type:
    Dissertation
    Full Text:
    : Improving Automated Email Tagging with Implicit Feedback Abstract approved: Thomas G. Dietterich Machine

  • Learning MDP action models via discrete mixture trees

    Creator:
    Wynkoop, Michael S.
    Abstract:
    This thesis addresses the problem of learning dynamic Bayesian network (DBN) models to support reinforcement learning. It focuses on learning regression tree models of the conditional probability distributions of the DBNs. Existing algorithms presume that the stochasticity in the domain can be modeled as a deterministic function with additive noise....
    Resource Type:
    Masters Thesis
    Full Text:
    , 2008. Title: Learning MDP Action Models via Discrete Mixture Trees Abstract approved: Thomas G

  • Calibrating recurrent sliding window classifiers for sequential supervised learning

    Creator:
    Joshi, Saket Subhash
    Abstract:
    Sequential supervised learning problems involve assigning a class label to each item in a sequence. Examples include part-of-speech tagging and text-to-speech mapping. A very general-purpose strategy for solving such problems is to construct a recurrent sliding window (RSW) classifier, which maps some window of the input sequence plus some number...
    Resource Type:
    Masters Thesis
    Full Text:
    models may not exactly model the causal relationships between the x's and the y's correctly. In some

  • Sequential supervised learning and conditional random fields

    Creator:
    Ashenfelter, Adam J.
    Abstract:
    Supervised learning is concerned with discovering the relationship between example sets of features and their corresponding classes. The traditional supervised learning formulation assumes that all examples are independent from one another. The order of the examples contains no information. Nonetheless, many problems have a sequential nature. Classifiers for these problems...
    Resource Type:
    Masters Thesis
    Full Text:
    Supervised Learning and Conditional Random Fields. Abstract approved: Thomas G. Dietterich Supervised

  • Electronic Stability of Metal Halide Perovskites

    Creator:
    Hong, Min Ji
    Abstract:
    Despite near unanimous opinion on the consequences of climate change by scientific community, the rate at which carbon is emitted into the atmosphere continues to increase. The need for a clean and sustainable source of energy is therefore one of humankind's most urgent challenges. Solar energy is the most abundant...
    Resource Type:
    Dissertation
    Full Text:
    ) 70°C, (g) 100°C, (h) pristine PbI2

  • A study of methods for fine-grained object classification of arthropod specimens

    Creator:
    Lin, Junyuan
    Abstract:
    Object categorization is one of the fundamental topics in computer vision research. Most current work in object categorization aims to discriminate among generic object classes with gross differences. However, many applications require much finer distinctions. This thesis focuses on the design, evaluation and analysis of learning algorithms for fine- grained...
    Resource Type:
    Masters Thesis
    Full Text:
    function g: Ci g−→ hi, where h ∈ RH During testing, given a testing image Ii and its bag-of-descriptors

  • Learning cost-sensitive diagnostic policies from data

    Creator:
    Zubek, Valentina Bayer
    Abstract:
    In its simplest form, the process of diagnosis is a decision-making process in which the diagnostician performs a sequence of tests culminating in a diagnostic decision. For example, a physician might perform a series of simple measurements (body tem- perature, weight, etc.) and laboratory measurements (white blood count, CT scan,...
    Resource Type:
    Dissertation
    Full Text:
    . Title: Learning Cost-Sensitive Diagnostic Policies from Data. Abstract approved: Thomas G. Dietterich

  • A probabilistic model for anomaly detection in remote sensor streams

    Creator:
    Dereszynski, Ethan W.
    Abstract:
    Remote sensors are becoming the standard for observing and recording ecological data in the field. Such sensors can record data at fine temporal resolutions, and they can operate under extreme conditions prohibitive to human access. Unfortunately, sensor data streams exhibit many kinds of errors ranging from corrupt communications to partial...
    Resource Type:
    Masters Thesis
    Full Text:
    , we first represent each variable’s CPT in terms of its canonical characteristics, g,h, and K. For

  • 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:
    Feature Induction in Sequential Supervised Learning Abstract approved: Thomas G. Dietterich Sequential

  • Probabilistic models for quality control in environmental sensor networks

    Creator:
    Dereszynski, Ethan W.
    Abstract:
    Networks of distributed, remote sensors are providing ecological scientists with a view of our environment that is unprecedented in detail. However, these networks are subject to harsh conditions, which lead to malfunctions in individual sensors and failures in network communications. This behavior manifests as corrupt or missing measurements in the...
    Resource Type:
    Dissertation
    Full Text:
    : Probabilistic Models for Quality Control in Environmental Sensor Networks Abstract approved: Thomas G

  • 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:
    Species Abstract approved: ______________________________________________________ Thomas G

  • Activity recognition in desktop environments

    Creator:
    Shen, Jianqiang
    Abstract:
    Knowledge workers are struggling in the information flood. There is a growing interest in intelligent desktop environments that help knowledge workers organize their daily life. Intelligent desktop environments allow the desktop user to define a set of “activities” that characterize the user’s desktop work. These environments then attempt to identify...
    Resource Type:
    Dissertation
    Full Text:
    i s i n g s t u d e n t s h e n p r o j e c t T a s k T r a c e r c o m m e n t s o n t h e s i

  • Image features and learning algorithms for biological, generic and social object recognition

    Creator:
    Zhang, Wei
    Abstract:
    Automated recognition of object categories in images is a critical step for many real-world computer vision applications. Interest region detectors and region descriptors have been widely employed to tackle the variability of objects in pose, scale, lighting, texture, color, and so on. Different types of object recognition problems usually require...
    Resource Type:
    Dissertation
    Full Text:
    : ______________________________________________________ Thomas G. Dietterich Automated recognition of object categories in images is a critical

  • The Familiarity Hypothesis: Explaining the Behavior of Deep Learning Methods in Out-of-Distribution Detection

    Creator:
    Guyer, Alexander
    Abstract:
    Many object recognition applications require detecting and responding to objects drawn from a different distribution from that of the training data. This task is referred to as out-of-distribution (OOD) detection, and it is often formulated as an outlier detection problem wherein the probability distribution of the known data P(X) is...
    Resource Type:
    Masters Thesis
    Full Text:
    Master of Science in Computer Science presented on May 26, 2022 Title: The Familiarity Hypothesis

  • A Benchmarking Study of Unsupervised Anomaly Detection Algorithms

    Creator:
    Emmott, Andrew F.
    Abstract:
    It is common practice in the unsupervised anomaly detection literature to create experimental benchmarks by sampling from existing supervised learning datasets. We seek to improve this practice by identifying four dimensions important to real-world anomaly detection applications --- point difficulty, clusteredness of anomalies, relevance of features, and relative frequency of...
    Resource Type:
    Masters Thesis
    Full Text:
    . . . . . . . . . . . . . . . . . . . . . 111 G Supplemental Tables for Chapter 7 . . . . . . . . . . . . . . . . . . . 116 LIST OF TABLES

  • Model-based approximation methods for reinforcement learning

    Creator:
    Wang, Xin
    Abstract:
    The thesis focuses on model-based approximation methods for reinforcement learning with large scale applications such as combinatorial optimization problems. First, the thesis proposes two new model-based methods to stablize the value–function approximation for reinforcement learning. The first one is the BFBP algorithm, a batch-like reinforcement learning process which iterates between...
    Resource Type:
    Dissertation
    Full Text:
    of Philosophy in Computer Science presented on May 08, 2006. Title: Model Based Approximation

  • Dynamic Methods to Improve Streaming of H.264 HD Video Over 802.11 Wireless Networks

    Creator:
    Sinky, Mohammed H.
    Abstract:
    Wireless High Definition Video Transmission (WHDVT) over 802.11-based networks enjoys widespread deployment among today's multimedia solutions. Examples include Intel® Wireless Display and Apple Airplay®, to name a few. In these systems, peer-to-peer networks are established over which H.264-encoded video is transported wirelessly to be decoded and played back at the...
    Resource Type:
    Dissertation
    Full Text:
    . c©Copyright by Mohammed H. Sinky May 21, 2015 All Rights Reserved Dynamic Methods to Improve

  • Dynamic and Dual Streaming Methods for H.264 Video and Parallel Performance Modeling

    Creator:
    Johnson, Taylor N.
    Abstract:
    Traditional approaches to streaming H.264 video over a network typically rely on a single method of transport (i.e., reliable or unreliable) and/or use static values for parameters that can have a significant negative impact on the perceptual quality of the received video. This dissertation presents a dynamic method for wireless...
    Resource Type:
    Dissertation
    Full Text:
    ) encoded with H.264 using Main Profile and Level 4.2 can require a data rate of up to 50 Mbps, which may

  • Spatial motion vector recovery in wireless high definition video transmission using H.264 over WLANs

    Creator:
    Gatimu, Kevin
    Abstract:
    Mobile devices are becoming more prevalent and complex. As a result, the wireless communication aspect of these devices is becoming increasingly significant. At the same time, video demands in terms of availability and quality are also on the uprise. High definition (HD) video is the standard of choice for meeting...
    Resource Type:
    Masters Thesis
    Full Text:
    luma block to be predicted M A B C D E F G H I J K L a b c d e f g h i j k l m n o p Mode 0

  • Equivalent circuit modeling of on-chip magnetic devices based on terminal measurements

    Creator:
    Gaskill, Steven G.
    Abstract:
    The addition of thin-film alloy magnetic materials to integrated circuit processing enables a number of novel monolithic circuits. Examples include fully integrated magnetic field sensors, signal and power galvanic isolation circuits, and power supplies on chip (PwrSoC). There are several benefits to integrating these traditionally off-chip devices, including improved manufacturability,...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Steven G. Gaskill for the

  • A methodology to reduce the strain on hydro turbines using advanced life extending control of multiple energy storage systems

    Creator:
    Brosig, Sean G.
    Abstract:
    Over the last 20 years, there has been rapid growth in the amount of installed wind power in the Pacific Northwest, specifically in the Columbia River Gorge. The variable and non-dispatchable nature of this resource requires that it be balanced in some form by other sources on the grid. In...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE THESIS OF Sean G. Brosig for the degree of Master of Science in Electrical and

  • Low-Power 12-bit Quasi-Passive Segmented DAC Implemented in 130nm CMOS Technology

    Creator:
    Pierce, Alexander G.
    Abstract:
    This thesis work proposes a low-power 12-bit digital-to-analog converter (DAC) designed in a 130nm process. The DAC to be presented is of a segmented design where the architecture is split into pipelined and thermometer coded segments. This allows for high linearity and low distortion while maintaining high speed and low...
    Resource Type:
    Masters Thesis
    Full Text:
    cheering me on. I look forward to meeting our son and to see where our lives may take us. I am forever

  • Channel Estimation in TDD MU-MIMO Systems using Sub-Linear Sparse Signal Recovery Algorithms

    Creator:
    Barry, David G.
    Abstract:
    Massive Multiple-User Miltiple-Input Multiple-Output (MU-MIMO) wireless communication systems incorporate promising advanced strong technologies for upcoming 5G communications. To obtain some of the high spectrum and energy e ciencies bonuses brought by MU-MIMO systems, the ability to obtain Channel State information, especially on the receiver side (CSI), is important. To minimize...
    Resource Type:
    Masters Thesis
    Full Text:
    knowledge of the binomial matrix used to construct A, H, we know one of the significant locations in G and

  • Design of on-line arithmetic networks for signal processing applications : a color filter implementation

    Creator:
    Sinky, Mohammed H.
    Abstract:
    Networks of on-line modules for Digital Signal Processing (DSP) applications have been designed and analyzed in many papers. Various arguments have been made for on-line arithmetic over other bit-serial and parallel approaches. However, the majority, if not all of the on-line network implementations presented throughout the literature do not take...
    Resource Type:
    Masters Thesis
    Full Text:
    ) ∗ e ∗ g+ (c/d) ∗ f ∗ h made on-the-fly as digits are being produced such that the result may be

  • Prediction of gene transcription start sites and initiation patterns from DNA sequence content

    Creator:
    Morton, Taj H.
    Abstract:
    The computational identification of gene Transcription Start Sites (TSSs) can provide insights into the regulation and function of genes without performing expensive experiments, particularly in organisms with incomplete annotations. High-resolution general-purpose TSS prediction remains a challenging problem, with little recent progress on the identification and differentiation of TSSs which are...
    Resource Type:
    Masters Thesis
    Full Text:
    D a ta se t C o m b in a ti o n s/ N o te s T h e g ro u p s o f T F s fr o m

  • Evaluating the seismic risk and resilience of an electrical power system

    Creator:
    Chalishazar, Vishvas H.
    Abstract:
    The Pacific Northwest is part of the "Ring of Fire," which is well-known for heavy seismic activity. Numerous active faults in the area have encouraged electric grid managers in the region to more deeply contemplate and proactively intervene to support grid resilience. This research introduces Monte Carlo (MC) based power...
    Resource Type:
    Dissertation
    Full Text:
    are as follows: p[H|A] denotes the probability of a given Asset (A) experiencing a typical Hazard (H1

  • Distributed OpenCL : a platform for distributed, heterogeneous computing for domain scientists

    Creator:
    Dillon, William H.
    Abstract:
    It is possible to purchase, for as little as $10,000, a cluster of computers with the capability to rival the supercomputers of only a few years ago. Now, users that have little to no experience developing distributed applications or managing a cluster are in a position to do so. To...
    Resource Type:
    Dissertation
    Full Text:
    William H. Dillon for the degree of Doctor of Philosophy in Computer Science presented on May 29, 2012

  • Re-understanding Finite-State Representations of Recurrent Policy Networks

    Creator:
    Danesh, Mohamad H.
    Abstract:
    We propose an approach for understanding control policies represented as recurrent neural networks. Recent work has approached this problem by transforming such recurrent policy networks into finite-state machines (FSM) and then analyzing the equivalent minimized FSM. While this led to interesting insights, the minimization process can obscure a deeper understanding...
    Resource Type:
    Masters Thesis
    Full Text:
    n in g A ft er M in im iz at io n N h N o D ec is . P o in ts S ta te s O b s. P er f

  • Novel design and implementation of a permanent magnet linear tubular generator for ocean wave energy conversion

    Creator:
    Prudell, Joseph H.
    Abstract:
    The world’s energy consumption is growing at an alarming rate and the need for renewable energy is apparent now more than ever. Estimates have shown that optimization of the extraction of energy from the ocean could significantly aid the world’s quest for sustainable and affordable energy services for all. From...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE THESIS OF Joseph H. Prudell for the degree of Master of Science in Electrical

  • Novel control of a permanent magnet linear generator for ocean wave energy applications

    Creator:
    VanderMeulen, Aaron H.
    Abstract:
    Wave energy conversion devices are a rapidly growing interest worldwide for the potential to harness a sustainable and renewable energy source. Due to the oscillatory nature of ocean waves, the power generated from a permanent magnet linear generator (PMLG) for ocean wave energy conversion is pulsed. Focusing on direct drive...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE THESIS OF Aaron H. VanderMeulen for the degree of Master of Science in

  • 5th-Order Elliptic LPF Using Passive Charge Compensation Technique (PCC) Design

    Creator:
    Tsai, Cheng H.
    Abstract:
    The passive charge compensation (PCC) technique was introduced for switched capacitor (SC) circuit to increase the slew rate and enhance the linearity performance, as PCC techniques are used on the Delta-Sigma modulator (DSM) in ADC circuitry. The PCC technique of the project was applied to the design of a SC...
    Resource Type:
    Masters Thesis
    Full Text:
    function H(s) of the filter shown in Figure 2.2 can be written as follows. 4 𝐻(𝑠

  • GenderMag’s Socio-Technical Artifacts “Grow up” To Expand GenderMag’s Impact

    Creator:
    Bhuva, Brijesh H.
    Abstract:
    This project report presents an implementation of a GenderMag Recorder's Assistant from a semi-working state to a fully working Chrome web store application. In addition, this project report also discusses the persona customization option and limitations and how the persona tool eases the process of persona customization. For results, we...
    Resource Type:
    Capstone Project
    Full Text:
    GenderMag’s Impact by Brijesh H. Bhuva M.S., Oregon State University, 2020 March 2020

  • Monte Carlo Tree Search with Fixed and Adaptive Abstractions

    Creator:
    Hostetler, Jesse A.
    Abstract:
    Monte Carlo tree search (MCTS) is a class of online planning algorithms for Markov decision processes (MDPs) and related models that has found success in challenging applications. In the online planning approach, the agent makes a decision in the current state by performing a limited forward search over possible futures...
    Resource Type:
    Dissertation
    Full Text:
    set H∗(M, s0) = {s0}×A×S×· · · . Note that H∗(M, s0) may be infinite even though S is finite. The set

  • Explanations and Processes to Enable Humans to Assess AI with Respect to Manipulable Properties

    Creator:
    Dodge, Jonathan E.
    Abstract:
    Assessing AI systems is difficult. Humans rely on AI systems in increasing ways, both visible and invisible, meaning a variety of stakeholders need a variety of assessment tools (e.g., a professional auditor, a developer, and an end user all have different needs). We posit that it is possible to provide...
    Resource Type:
    Dissertation
    Full Text:
    . . . . . . . . . . . . . 159 F Log Appendix - Computing a target tensor with CNN Agent . . . . . . . . 162 G How to

  • An enhanced swing differential Colpitts CMOS VCO for low-voltage operation

    Creator:
    Farahbakhshian, Farhad
    Abstract:
    An enhanced swing differential Colpitts VCO (ESDC-VCO) dramatically improves the swing of a Colpitts VCO by allowing the signal to swing below ground and above the supply voltage. Fabricated in a 1P8M 0.13 um CMOS process, the ESDC-VCO operates at 4.9GHz with a 0.475-V supply and consumes 2.7mW. The measured...
    Resource Type:
    Masters Thesis
    Full Text:
    –329, May. 2005. [19] S. J. Yun, S. B. Shin, H. C. Choi, and S. G. Lee, “A 1mW current-reuse CMOS

  • Timing jitter and phase noise in electronic oscillators

    Creator:
    Zhang, Chengwei
    Abstract:
    In the first part of this dissertation, low frequency l/f or flicker noise in the frequency range of Hz to kHz has been identified and demonstrated to be described by temperature fluctuations in heat conduction in bipolar transistors operated at higher power densities. This noise phenomenon is not described by...
    Resource Type:
    Dissertation
    Full Text:
    wireless communication systems. At lower frequencies or lower power densities flicker noise may still

  • Integrating learning and search for structured prediction

    Creator:
    Doppa, Janardhan Rao
    Abstract:
    We are witnessing the rise of the data-driven science paradigm, in which massive amounts of data - much of it collected as a side-effect of ordinary human activity - can be analyzed to make sense of the data and to make useful predictions. To fully realize the promise of this...
    Resource Type:
    Dissertation
    Full Text:
    guided by a learned heuristic function H until a fixed number of alternative solutions has been

  • Multi-criteria average reward reinforcement learning

    Creator:
    Natarajan, Sriraam
    Abstract:
    Reinforcement learning (RL) is the study of systems that learn from interaction with their environment. The current framework of Reinforcement Learning is based on receiving scalar rewards, which the agent aims to maximize. But in many real world situations, tradeoffs must be made among multiple objectives. This necessitates the use...
    Resource Type:
    Masters Thesis
    Full Text:
    ) s,a) +- s,a) + (jmm F(s,a))/N(s,a) (g) If a is a greedy action, ' (1 ) + (s, a) (s) + c f- (h) 7t

  • Learning and Improving Policies for Probabilistic Planning Problems

    Creator:
    Issakkimuthu, Murugeswari
    Abstract:
    In this work, we study the problem of learning and improving policies for probabilistic planning problems. In the first part, we train neural network policies for probabilistic planning problems modeled as factored Markov decision problems. The objective is to train problem-specific neural networks via supervised learning to imitate the action...
    Resource Type:
    Dissertation
    Full Text:
    practice, we may have more time to make action decisions than what we need to just apply a reactive policy

  • 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
    Full Text:
    important correction. I am thankful for Dr. Thomas G. Dietterich and Dr. Alix Gitelman both for their