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Articles 1 - 15 of 15
Full-Text Articles in Theory and Algorithms
Small Approximate Pareto Sets With Quality Bounds, William Bailey
Small Approximate Pareto Sets With Quality Bounds, William Bailey
Theses and Dissertations--Computer Science
We present and empirically characterize a general, parallel, heuristic algorithm for computing small ε-Pareto sets. The algorithm can be used as part of a decision support tool for settings in which computing points in objective space is computationally expensive. We use the graph clearing problem, a formalization of indirect organ exchange markets, as a prototypical example setting. We characterize the performance of the algorithm through ε-Pareto set size, ε value provided, and parallel speedup achieved. Our results show that the algorithm's combination of parallel speedup and small ε-Pareto sets is sufficient to be appealing in settings requiring manual review (i.e., …
The Basil Technique: Bias Adaptive Statistical Inference Learning Agents For Learning From Human Feedback, Jonathan Indigo Watson
The Basil Technique: Bias Adaptive Statistical Inference Learning Agents For Learning From Human Feedback, Jonathan Indigo Watson
Theses and Dissertations--Computer Science
We introduce a novel approach for learning behaviors using human-provided feedback that is subject to systematic bias. Our method, known as BASIL, models the feedback signal as a combination of a heuristic evaluation of an action's utility and a probabilistically-drawn bias value, characterized by unknown parameters. We present both the general framework for our technique and specific algorithms for biases drawn from a normal distribution. We evaluate our approach across various environments and tasks, comparing it to interactive and non-interactive machine learning methods, including deep learning techniques, using human trainers and a synthetic oracle with feedback distorted to varying degrees. …
Improving Connectivity For Remote Cancer Patient Symptom Monitoring And Reporting In Rural Medically Underserved Regions, Esther Max-Onakpoya
Improving Connectivity For Remote Cancer Patient Symptom Monitoring And Reporting In Rural Medically Underserved Regions, Esther Max-Onakpoya
Theses and Dissertations--Computer Science
Rural residents are often faced with many disparities when compared to their urban counterparts. Two key areas where these disparities are apparent are access to health and Internet services. Improved access to healthcare services has the potential to increase residents' quality of life and life expectancy. Additionally, improved access to Internet services can create significant social returns in increasing job and educational opportunities, and improving access to healthcare. Therefore, this dissertation focuses on the intersection between access to Internet and healthcare services in rural areas. More specifically, it attempts to analyze systems that can be used to improve Internet access …
Peer-To-Peer Energy Trading In Smart Residential Environment With User Behavioral Modeling, Ashutosh Timilsina
Peer-To-Peer Energy Trading In Smart Residential Environment With User Behavioral Modeling, Ashutosh Timilsina
Theses and Dissertations--Computer Science
Electric power systems are transforming from a centralized unidirectional market to a decentralized open market. With this shift, the end-users have the possibility to actively participate in local energy exchanges, with or without the involvement of the main grid. Rapidly reducing prices for Renewable Energy Technologies (RETs), supported by their ease of installation and operation, with the facilitation of Electric Vehicles (EV) and Smart Grid (SG) technologies to make bidirectional flow of energy possible, has contributed to this changing landscape in the distribution side of the traditional power grid.
Trading energy among users in a decentralized fashion has been referred …
The Performance Optimization Of Asp Solving Based On Encoding Rewriting And Encoding Selection, Liu Liu
The Performance Optimization Of Asp Solving Based On Encoding Rewriting And Encoding Selection, Liu Liu
Theses and Dissertations--Computer Science
Answer set programming (ASP) has long been used for modeling and solving hard search problems. These problems are modeled in ASP as encodings, a collection of rules that declaratively describe the logic of the problem without explicitly listing how to solve it. It is common that the same problem has several different but equivalent encodings in ASP. Experience shows that the performance of these ASP encodings may vary greatly from instance to instance when processed by current state-of-the-art ASP grounder/solver systems. In particular, it is rarely the case that one encoding outperforms all others. Moreover, running an ASP system on …
Matrix Interpretations And Tools For Investigating Even Functionals, Benjamin Stringer
Matrix Interpretations And Tools For Investigating Even Functionals, Benjamin Stringer
Theses and Dissertations--Computer Science
Even functionals are a set of polynomials evaluated on the terms of hollow symmetric matrices. Their properties lend themselves to applications such as counting subgraph embeddings in generic (weighted or unweighted) host graphs and computing moments of binary quadratic forms, which occur in combinatorial optimization. This research focuses primarily on counting subgraph embeddings, which is traditionally accomplished with brute-force algorithms or algorithms curated for special types of graphs. Even functionals provide a method for counting subgraphs algebraically in time proportional to matrix multiplication and is not restricted to particular graph types. Counting subgraph embeddings can be accomplished by evaluating a …
Novel Hedonic Games And Stability Notions, Jacob Schlueter
Novel Hedonic Games And Stability Notions, Jacob Schlueter
Theses and Dissertations--Computer Science
We present here work on matching problems, namely hedonic games, also known as coalition formation games. We introduce two classes of hedonic games, Super Altruistic Hedonic Games (SAHGs) and Anchored Team Formation Games (ATFGs), and investigate the computational complexity of finding optimal partitions of agents into coalitions, or finding - or determining the existence of - stable coalition structures. We introduce a new stability notion for hedonic games and examine its relation to core and Nash stability for several classes of hedonic games.
Representing And Learning Preferences Over Combinatorial Domains, Michael Huelsman
Representing And Learning Preferences Over Combinatorial Domains, Michael Huelsman
Theses and Dissertations--Computer Science
Agents make decisions based on their preferences. Thus, to predict their decisions one has to learn the agent's preferences. A key step in the learning process is selecting a model to represent those preferences. We studied this problem by borrowing techniques from the algorithm selection problem to analyze preference example sets and select the most appropriate preference representation for learning. We approached this problem in multiple steps.
First, we determined which representations to consider. For this problem we developed the notion of preference representation language subsumption, which compares representations based on their expressive power. Subsumption creates a hierarchy of preference …
Optimal Gateway Placement In Low-Cost Smart Cities, Oluwashina Madamori
Optimal Gateway Placement In Low-Cost Smart Cities, Oluwashina Madamori
Theses and Dissertations--Computer Science
Rapid urbanization burdens city infrastructure and creates the need for local governments to maximize the usage of resources to serve its citizens. Smart city projects aim to alleviate the urbanization problem by deploying a vast amount of Internet-of-things (IoT) devices to monitor and manage environmental conditions and infrastructure. However, smart city projects can be extremely expensive to deploy and manage partly due to the cost of providing Internet connectivity via 5G or WiFi to IoT devices. This thesis proposes the use of delay tolerant networks (DTNs) as a backbone for smart city communication; enabling developing communities to become smart cities …
Learning To Map The Visual And Auditory World, Tawfiq Salem
Learning To Map The Visual And Auditory World, Tawfiq Salem
Theses and Dissertations--Computer Science
The appearance of the world varies dramatically not only from place to place but also from hour to hour and month to month. Billions of images that capture this complex relationship are uploaded to social-media websites every day and often are associated with precise time and location metadata. This rich source of data can be beneficial to improve our understanding of the globe. In this work, we propose a general framework that uses these publicly available images for constructing dense maps of different ground-level attributes from overhead imagery. In particular, we use well-defined probabilistic models and a weakly-supervised, multi-task training …
Ultra-Fast And Memory-Efficient Lookups For Cloud, Networked Systems, And Massive Data Management, Ye Yu
Ultra-Fast And Memory-Efficient Lookups For Cloud, Networked Systems, And Massive Data Management, Ye Yu
Theses and Dissertations--Computer Science
Systems that process big data (e.g., high-traffic networks and large-scale storage) prefer data structures and algorithms with small memory and fast processing speed. Efficient and fast algorithms play an essential role in system design, despite the improvement of hardware. This dissertation is organized around a novel algorithm called Othello Hashing. Othello Hashing supports ultra-fast and memory-efficient key-value lookup, and it fits the requirements of the core algorithms of many large-scale systems and big data applications. Using Othello hashing, combined with domain expertise in cloud, computer networks, big data, and bioinformatics, I developed the following applications that resolve several major …
Bi-Objective Optimization Of Kidney Exchanges, Siyao Xu
Bi-Objective Optimization Of Kidney Exchanges, Siyao Xu
Theses and Dissertations--Computer Science
Matching people to their preferences is an algorithmic topic with real world applications. One such application is the kidney exchange. The best "cure" for patients whose kidneys are failing is to replace it with a healthy one. Unfortunately, biological factors (e.g., blood type) constrain the number of possible replacements. Kidney exchanges seek to alleviate some of this pressure by allowing donors to give their kidney to a patient besides the one they most care about and in turn the donor for that patient gives her kidney to the patient that this first donor most cares about. Roth et al.~first discussed …
Topics On Register Synthesis Problems, Weihua Liu
Topics On Register Synthesis Problems, Weihua Liu
Theses and Dissertations--Computer Science
Pseudo-random sequences are ubiquitous in modern electronics and information technology. High speed generators of such sequences play essential roles in various engineering applications, such as stream ciphers, radar systems, multiple access systems, and quasi-Monte-Carlo simulation. Given a short prefix of a sequence, it is undesirable to have an efficient algorithm that can synthesize a generator which can predict the whole sequence. Otherwise, a cryptanalytic attack can be launched against the system based on that given sequence.
Linear feedback shift registers (LFSRs) are the most widely studied pseudorandom sequence generators. The LFSR synthesis problem can be solved by the Berlekamp-Massey algorithm, …
Modeling, Learning And Reasoning About Preference Trees Over Combinatorial Domains, Xudong Liu
Modeling, Learning And Reasoning About Preference Trees Over Combinatorial Domains, Xudong Liu
Theses and Dissertations--Computer Science
In my Ph.D. dissertation, I have studied problems arising in various aspects of preferences: preference modeling, preference learning, and preference reasoning, when preferences concern outcomes ranging over combinatorial domains. Preferences is a major research component in artificial intelligence (AI) and decision theory, and is closely related to the social choice theory considered by economists and political scientists. In my dissertation, I have exploited emerging connections between preferences in AI and social choice theory. Most of my research is on qualitative preference representations that extend and combine existing formalisms such as conditional preference nets, lexicographic preference trees, answer-set optimization programs, possibilistic …
Automatic Detection Of Abnormal Behavior In Computing Systems, James Frank Roberts
Automatic Detection Of Abnormal Behavior In Computing Systems, James Frank Roberts
Theses and Dissertations--Computer Science
I present RAACD, a software suite that detects misbehaving computers in large computing systems and presents information about those machines to the system administrator. I build this system using preexisting anomaly detection techniques. I evaluate my methods using simple synthesized data, real data containing coerced abnormal behavior, and real data containing naturally occurring abnormal behavior. I find that the system adequately detects abnormal behavior and significantly reduces the amount of uninteresting computer health data presented to a system administrator.