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...
With sequential computing technology reaching its speed limits, parallel processing is emerging as the key to very-high-speed computation. However, developing a parallel program is by no means a simple task; neither is analyzing the performance of parallel programs.
C* is a high-level data-parallel language that hides explicit message passing and...
"Collaborative filtering algorithms’ performances have been evaluated using a variety of metrics.
These metrics, such as Mean Absolute Error and Precision, have often ignored recommendations for
which they do not have data. Ignoring these recommendations has provided numbers which do not
accurately represent the user experience. Qualitatively we have seen...
Advances in deep learning based image processing have led to their adoption for a wide range of applications, and in tow with these developments is a dramatic increase in the availability of high quality datasets. With this comes the need to accelerate and scale deep learning applications in order to...
Reasoning about any realistic domain always involves a degree of uncertainty.
Probabilistic inference in belief networks is one effective way of reasoning under
uncertainty. Efficiency is critical in applying this technique, and many researchers
have been working on this topic. This thesis is the report of our research in this...
We present a novel multi-objective optimization methodology built upon a multi-agent blackboard framework. This multi-agent blackboard system (MABS) synthesizes blackboard architectures, multi-agent environments, and optimization theory. The blackboard architecture creates the framework for initializing, storing, and solving a multi-objective optimization problem. Multiple agents allow for an optimization problem to be...
Domain-independent automated planning is concerned with computing a sequence of actions that can transform an initial state into a desired goal state. Resource production domains form an interesting class of such problems, in that they typically require reasoning about concurrent durative-actions with continuous effects while minimizing some cost function. Although...
Automatic music transcription (AMT) is the task, given an acoustic representation of music, to recover a symbolic notation of the written notes expressed by the sound. Transcribing music with multiple notes sounding simultaneously is difficult for both humans and machines. Much existing work on AMT has focused on suitable acoustic...
The purpose of this article is to explore student reasoning with regard to problems in logic, particularly those related to the Principle of Mathematical Induction (PMI). The five case studies presented build off of work done by other researchers, most notably Dubinsky and Harel, who both looked at how students'...
This paper addresses the high model complexity and overconfident frame labeling of state-of-the-art (SOTA) action segmenters. Their complexity is typically justified by the need to sequentially refine action segmentation through multiple stages of a deep architecture. However, this multistage refinement does not take into account uncertainty of frame labeling predicted...
Semi-supervised clustering aims to improve clustering performance by considering user supervision in the form of pairwise constraints. In this paper, we study the active learning problem of selecting pairwise must-link and cannot-link constraints for semisupervised clustering. We consider active learning in an iterative manner where in each iteration queries are...
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...
There is growing commercial interest in the use of unmanned aerial vehicles (UAVs) in urban environments, specifically for package delivery applications. However, the size, complexity and sheer numbers of expected UAVs makes conventional air traffic management that relies on human air traffic controllers infeasible. To enable UAVs to safely and...
Markov Decision Process (MDP) is a well-known framework for devising the optimal decision making strategies under uncertainty. Typically, the decision maker assumes a stationary environment which is characterized by a time-invariant transition probability matrix. However, in many real-world scenarios, this assumption is not justified, thus the optimal strategy might not...
The appropriate separation of concerns is a fundamental engineering principle. A concern, for software developers, is that which must be represented by code in a program; by extension, separation of concerns is the ability to represent a single concern in a single appropriate programming language construct. Advanced separation of concerns...
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...
Global Positioning Systems have allowed for precise timing of power system measurements over wide areas. This newly found capability has the potential to provide much greater insight into the operation of the power system and its response to contingencies, but few analytical techniques currently exist that provide enough robustness and...
We consider the problem of strategic adversarial planning in a Real-Time Strategy (RTS) game. Strategic adversarial planning is the generation of a network of high-level tasks to satisfy goals while anticipating an adversary's actions. In this thesis we describe an abstract state and action space used for planning in an...
Voltage converters or charge pumps find their use in many circuits. They are extensively used in hand held devices as cell phones, pagers, PDA's and laptops. Some of the important issues relating to design of voltage regulators for handheld devices are size, efficiency and noise. Another important factor to be...
We model the popular board game of Clue as an MDP and evaluate Monte-Carlo policy rollout in a simulated environment pitting different agents and policies against each other. We describe the choices we made in the representation, along with some of the problems we encountered along the way. We find...
Manufacturing technology has continuously evolved and advanced over the past century; this has led to an increase in the production of consumer and industrial goods driven by simultaneous growth in population and wealth. Despite the resulting economic and labor growth, environmental impacts of manufacturing have increased dramatically due to the...
In Intense Pulsed Light (IPL) sintering, pulsed large-area visible light from a xenon lamp is absorbed by nanoparticle films or patterns and converted to heat, resulting in rapid sintering of the nanoparticles. This work experimentally characterizes IPL sintering of silver nanoparticle films. A newly observed turning point in the evolution...
Causal inference is an important analytical tool to bridge the gap between prediction and decision-making. However, learning a causal network solely from data is a challenging task. In this work, various techniques have been explored for a better and improved causal network learning from data. Firstly, the problem of learning...
Anomaly detection has been used in variety of applications in practice, including cyber-security, fraud detection and detecting faults in safety critical systems, etc. Anomaly detectors produce a ranked list of statistical anomalies, which are typically examined by human analysts in order to extract the actual anomalies of interest. Unfortunately, most...
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...
There are growing interests in designing polynomial-time approximation schemes (PTAS) for optimization problems in planar graphs. Many NP-hard problems are shown to admit PTAS in planar graphs in the last decade, including Steiner tree, Steiner forest, two- edge-connected subgraphs and so on. We follow this research line and study several...
Changes in the global climate and forest management practices have given rise to increasing numbers and severity of wildfires. More than five million acres burned in the United States in 2017, while in Canada 7.4 million acres burned. In particular, an increasing amount of dead woody biomass is a key...
Recent advancements in joining operations and additive manufacturing now allow complex metal parts to be built up from raw materials, as opposed to being machined down from solid blocks. This not only opens up the design space, but also allows for much more efficient manufacturing. By decomposing a complex part...
Top-performing approaches to embodied AI tasks like point-goal navigation often rely on training agents via reinforcement learning over tens of millions (or even billions) of experiential steps – learning neural agents that map directly from visual observations to actions. In this work, we question whether these extreme training durations are...
Bayesian Optimization (BO) methods are often used to optimize an unknown function f(•) that is costly to evaluate. They typically work in an iterative manner. In each iteration, given a set of observation points, BO algorithms select k ≥ 1 points to be evaluated. The results of those points are...
The first edition of the Highway Safety Manual (HSM) provides a quantitative
approach to predict the safety of transportation facilities based on the recently
developed scientific methods. This approach, known as the predictive method, was
developed for several states in the United States. Due to differences in driver
population, weather...
Our goal is to build a system to model the RNA sequences that reveals their structural information by using efficient dynamic programming algorithms and deep learning approaches. We aim to 1) achieve linear-time for RNA secondary structure prediction based on existing minimum free energy models; 2) utilize deep neural networks...
Learning Analytics and other branches of Educational Research such as Computing Education Research (CER) implicitly assume that students, especially college students, have no barriers to access learning platforms or software packages. This assumption may be attributed to such pervasive beliefs such as "everyone has a device", or "everyone can access...
Situated cognition theory emphasizes the role that social and material contexts have on learning and knowledge application. Several studies of engineering workplace environments have noted differences between the social and material contexts of the workplace and those of undergraduate engineering education. No existing research has studied the social and material...
This dissertation incorporates coalition formation and probabilistic planning towards a domain-independent automated planning solution scalable to multiple heterogeneous robots in complex domains. The first research direction investigates the effectiveness of Task Fusion and introduces heuristics that improve task allocation and result in better quality plans, while requiring lower computational cost...
Knowledge compilation improves search-intensive problem-solvers that are easily specified but inefficient. One promising approach improves efficiency by constructing a database of problem-instance/best-action pairs that replace problem-solving search with efficient lookup. The database is constructed by reverse enumeration- expanding the complete search space backwards, from the terminal problem instances. This approach...
CREEDA-BG (Crop Rotation Economic and Environmental Decision-Aid Budget Generator) is a web-based enterprise budgeting tool that allows a user to manage information on her fields, rotations, crops, and operations, and to view estimates of income and expenses. The user can then use this information to evaluate alternative plans and make...
Autonomous multiagent teams can be used in complex exploration tasks to both expedite the exploration and improve the efficiency. However, use of multiagent systems presents additional challenges. Specifically, in domains where the agents' actions are tightly coupled, coordinating multiple agents to achieve cooperative behavior at the group level is difficult....
We investigate the data collection problem in sensor networks. The network consists of a number of stationary sensors deployed at different sites for sensing and storing data locally. A mobile element moves from sites to sites to collect data from the sensors periodically. There are different costs associated with the...
We explore the application of deep learning to the disparate fields of natural language processing and computational biology. Both the sentences uttered by humans as well as the RNA and protein sequences found within the cells of their bodies can be considered formal languages in computer science, as sets of...
Accessing information on the Web has become ingrained into our daily lives, and we seek information from many different sources, including conference and journal publications, personal web pages, and others. Increasingly, web-based information retrieval systems such as web-based search engines, library on-line catalog systems, and subscription-based federated search systems are...
A thesis presented on the determination of factors related to deposition, clearance, and dosimetry of the ICRP 30 lung model as related to smoking. Variations in calculations used to determine radiation doses leave a need to determine a standard method to determine absorbed dose from smoking. Standard parameters are used...
Environmental and regulatory concerns are causing confined animal feeding operations (CAFO's) to account for phosphorous content when applying wastewater to agricultural fields for disposal. In most cases this requires more land to spread the waste onto so that the phosphorous needs of the crop are not exceeded. A mobile process...
In spite of wide spread adoption of the internet technology in teaching and learning, little research exists on the use and the effect of web incorporation in teaching and learning. Immediate clarification of how, when, and for whom the web integration in education is beneficial is needed. This qualitative study...
The purpose of the present investigation was to develop an adaptive teaching model for an interactive computer-assisted instruction (CAT) program and to evaluate the effectiveness of the implementation of individualized examples or individualized
examples in personalized contexts. Translating word problems into equations provided the context for the CAT investigation. Four...
Constructing a panorama from a set of videos is a long-standing problem in computer vision. A panorama represents an enhanced still-image representation of an entire scene captured in a set of videos, where each video shows only a part of the scene. Importantly, a panorama shows only the scene background,...
With edge rates of high speed digital devices pushing into the sub-nano second
range, interconnections with the associated packages play a major role in determining
the speed, size and performance of digital circuits and systems. The purpose of this
study is to develop experimental techniques based on time domain peeling...
Monte-Carlo planning algorithms such as UCT make decisions at each step by
intelligently expanding a single search tree given the available time and then
selecting the best root action. Recent work has provided evidence that it can be
advantageous to instead construct an ensemble of search trees and make a...
Remote sensing is the most practical way to acquire large amounts of land cover data for monitoring and understanding environmental change, so it is important to be able to map land cover from imagery. Maps defining land cover patches as polygons rather than pixels greatly improve processing efficiency in models...