BYU CS Combined Feed

Michael R. Smith's MS Thesis Defense/PhD Qualifying Presentation

Computer Science Department — Wed, 04 Nov 2009 11:53:30 -0700

An Empirical Study of Instance Hardness

ABSTRACT:

Most widely accepted measures of performance for learning algorithms, such as accuracy and area under the ROC curve, provide information about behavior at the data set level. They say nothing about which instances are misclassified, whether two learning algorithms with the same classification accuracy on a data set misclassify the same instances, or whether there are instances misclassified by all learning algorithms. These questions about behavior at the instance level motivate our empirical analysis of instance hardness, a measure of expected classification accuracy for an instance. We analyze the classification of 57 data sets using 9 learning algorithms. Of the over 175000 instances investigated, 5% are misclassified by all 9 of the considered learning algorithms, and 15% are misclassified by at least half. We find that the major cause of misclassification for hard instances is class overlap, manifested as outliers and border points which can be exacerbated by class skew. We analyze these causes and show to what extent each leads to misclassifications, both in isolation and jointly. 19.8% of all misclassified instances are outliers, 71.3% are border points, and 21% belong to a minority class. We also find that 91.6% of all outliers and 38.3% of all border points are misclassified whereas only 3.5% of instances without class overlap are misclassified. We propose a set of heuristics to predict when an instance will be hard to correctly classify. Additionally, we analyze how different learning algorithms perform on tasks with varying degrees of outliers, border points and class skew.

Daniel Adams' MS Thesis Defense

Computer Science Department — Wed, 04 Nov 2009 11:47:56 -0700

Feature-Based Interactive Terrain Sketching

ABSTRACT:

Procedural generation techniques are able to quickly and cheaply produce large areas of terrain. However, these techniques produce results that are not easily directable and often require artists to edit the results by hand to achieve the desired layout. This paper proposes a sketch-based system for controlling fractal terrain that allows for a wide variety of terrain feature types. Artists sketch features rather than constrained points or elevations. The system is interactive, provides quick on-demand previews of the terrain, and allows for iterative design modifications. Interaction between features is handled in a realistic fashion. An arbitrary vertex insertion order midpoint displacement algorithm is also described which provides the necessary flexibility and constraints for the terrain generation system.

Tim van der Horst's PhD Dissertation Defense

Computer Science Department — Mon, 26 Oct 2009 11:24:27 -0600

Convenient Decentralized Authentication using Passwords

ABSTRACT:

Proof of email address ownership is typically required to create an account and to reset a password when it is forgotten. Despite its shortcomings (e.g., latency, vulnerability to passive attack), this approach is a practical solution to the difficult problem of authenticating strangers on the Internet.

This research utilizes this emergent, lightweight relationship with email providers to offload primary user authentication from service providers; thus reducing the need for service provider-specific passwords. Our goal is to provide decentralized authentication that maintains the convenience and portability of passwords, while improving its assurances (especially against phishing). Also, as existing approaches to online decentralized authentication are typically geared for web-based logins, our new protocols are designed to unify user authentication across the application and network (especially wireless) layers.

New CS Course: CS 401R sec 1 Fundamentals of Information Retrieval

Computer Science Department — Wed, 21 Oct 2009 08:43:02 -0600

The Computer Science Department is pleased to announce the new CS 401R course that will be offered winter semesters. This course, titled Fundamentals of Information Retrieval will be taught by Dennis Ng winter semester 2010 on Tuesdays and Thursdays from 3-4:15 p.m.

Course:            401R sec 1
Course Title:    Fundamentals of Information Retrieval
Time:               Tuesdays and Thursdays 3-4:15pm Winter 2010
Instructor:        Dennis Ng
Credits:            3
Textbook:         Search Engines: Information Retrieval in Practice

Course Objectives
·      To learn the concepts and terminology of information retrieval (IR) systems.
·      To study the design methodologies and design issues of IR systems.
·      To understand the fundamental IR models, which include the Boolean, Vector Space, Probabilistic models, and evaluation strategies of IR systems
·      To examine various query processing and refinement techniques
·      To survey various topics related to IR systems, including classification and clustering, social search, relevance feedback, ranking, indexing, etc.

Technical Résumé Seminar - An Employer's Perspective

Computer Science Department — Fri, 02 Oct 2009 15:29:35 -0600

Tuesday, October 6, 2009 at 3 p.m.
3365 TMCB (CS Conference Room)

What are technical managers looking for in a technical résumé? What makes a résumé stand out? How can you create an opening? What are the10 deadly sins of interviewing? Discover the answer to these and other questions at this seminar by a hiring manager from Lawrence Livermore National Laboratory. The presenter will also be available following the seminar to look at résumés and give blunt one on one advice to students.

Darrel Whitney is the Software Quality Assurance Manager and Technical Recruiter at Lawrence Livermore National Laboratory in Livermore,California. During his career he has been a student employee incomputational physics, software developer, software quality engineer, project leader, group leader, and division leader. He has extensive experience in the hiring process at LLNL. He has been recruiting at BYU since 2001. Darrel holds a BS in Physics from BYU, and two MS degrees from the University of California at Davis in Applied Science and Computational Science.

Career Fair Preview

Computer Science Department — Fri, 02 Oct 2009 15:25:07 -0600

Don’t miss the opportunity to meet personally with representatives from across the spectrum of the computer science industry. You can plan for your future, learn more about the opportunities awaiting you after graduation, begin the process of networking and making contacts in the industry, and grab a doughnut...all without leaving the Talmage Building! The Career Fair Preview will be Tuesday, October 6 at 12 noon in 1170 TMCB. Companies attending: Avalanche Disney Interactive Studios, LDS Church Department of Information and Communication, and National Instruments. For more information, contact the CS Department at csoffice@cs.byu.edu.

CS Technical Career Fair Preview

Computer Science Department — Fri, 02 Oct 2009 15:16:20 -0600

Do not miss the opportunity to meet personally with representatives from across the spectrum of the computer science industry. You can plan for your future, learn more about the opportunities awaiting you after graduation, begin the process of networking and making contacts in the industry, and grab a doughnut...all without leaving the Talmage Building! The Career Fair Preview will be Tuesday, October 6 at 12 noon in 1170 TMCB. Companies attending: Avalanche Disney Interactive Studios, LDS Church Department of Information and Communication, and National Instruments. For more information, contact the CS Department at csoffice@cs.byu.edu.

The BYU Technical Career Fair will be in the Wilkinson Student Center on October 7 from 10 a.m. to 3 p.m. All Computer Science students, as well as other technical majors, are invited to attend.

As of September 15, the following companies are attending the Technical Career Fair: Aero Vironment Inc.; AMC Logistics Leadership Center; Apple, Inc.; Applied Sinal; Avalanche Disney Interactive Studios; Batten & Shaw, Inc.; BD Medical, Bechtel Mrine propulsion Corp.; Celanese; Centex Homes, The Church of Jesus Christ of Latter-day Saints Department of Informtion and Communication; Clearwater Analytics; Dannon Company; Dow Chemical; Dresser; Electrical Consultants, Inc.; ExxonMobil; Fairchild Semiconductor; Fast Enterprises; FBI Federal Highway Administration; First Quality Information; FM Global; GE Energy; Goldman Sachs & Co.; Geneva Rock Products; Gore; Graymont; Harder Mechanical Contractos, Inc.; Hewlett-Packard Company; Hill AFB; Hilton Hotels; Horrocks Engineers, Inc.; IM Flash; J-U-B Engineers, Inc.; Kiewitt; L-3 Communications; Lawrence Livermore National; Laboratory; Layton Construction; Lockheed Martin; MasterControl; McCarthy Buildin Companies, Inc.; Michael Baker Jr., Inc.; Microsoft Corporation; MIT Lincoln Labs; Moxtek, Inc.; National Instruments; NAVAIR; Naval Reactors Facility, Bettis Lab; Neovest; Nicholson construction Co.; Northrop Grumman Corp.; National Security Agency; Omniture; On Semiconductors; Parived Solutions; Parsons Brinkerhoff; Pratt & Whitney Rocketdyne; Procter & Gamble; Puget Sound Navel Shipyard; Raytheon; Rincon Research Corp.; Rio Tinto; Sirsidynix; Solstice Enterprise Softwre, Inc.; Southwest Gas Corportion; Stryker Endoscopy; Union Telephone/Union Wireless; URS Corporation; URS - Washinton Division; USAA, US Army; US Public Health Service; US Navy; Valero Energy Corporation; Vanir Construction; Wal-Mart; and Xactware.

Kenneth Sundberg's PhD Dissertation Proposal

Computer Science Department — Wed, 30 Sep 2009 16:35:25 -0600

Partition Based Phylogenetic Search

ABSTRACT:

Evolutionary relationships are of critical importance in modern biology. Thus the process of inferring these relationships, phylogenetic search, is an important problem. This problem is known to be NP-Hard, and so heuristic methods are needed. This work proposes a new understanding of the solution space and exploiting this understanding looks to develop new search techniques.

Kenneth Sundberg's Research Area Exam

Computer Science Department — Wed, 30 Sep 2009 16:25:51 -0600

ABSTRACT:

Phylogenetic Search, a computationally difficult problem (NP-Hard), is of use to a wide variety of biological problems. This problem has been attacked through a number of heuristic methods,most notably hill climbing. Other heuristics such as genetic algorithms and simulated annealing have also been applied. However, work continues as there remain problems of interest that lie outside of current capabilities. A new direction in the field is the study of treespace as a whole, in an effort to devise new search techniques. This review contains a discussion of all these techniques, the major programs which implement them, and an in depth review of the most commonly used algorithm TBR.

Heather Chan's MS Thesis Proposal

Computer Science Department — Tue, 29 Sep 2009 16:31:38 -0600

Gene Network Inference and Expression Prediction Using Recurrent Networks

ABSTRACT:

We propose the use of recurrent neural networks to perform gene network in- ference and gene expression prediction. Recurrent neural networks are mathematical tools for nonlinear statistical data modeling, and they can represent important tem- poral information that is crucial to the problem of modeling gene regulation. We use a hybrid of particle swarm optimization and differential evolution to overcome the classic obstacle in training recurrent neural networks, which is the tendency to get stuck in local minima during training. We also adapt a previous statistical method for extracting network regulations from a dynamic Bayesian model and apply it to our recurrent neural network model to help discover biological meanings in inferred networks. Success in the modeling of gene regulation and prediction of gene expres- sion will lead to more rapid research and development of effective medicines, earlier diagnosis and treatment of adverse conditions, and vast advancements in the field of biology. Preliminary results on the SOS Repair dataset show striking success in accurate prediction of gene expression levels.