Index Catalog // ScholarsArchive@OSU

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:: Christopher K. Mathews for his continuous support and considerateness. I thank my wife Li Li, my lovely

Learning to Estimate Multi-Relation Aggregation Functions

Creator:: Jadhav, Rashmi Suresh
Abstract:: Multi-relation aggregation queries process the join operator before computing the aggregation function. This join is arguably the most costly operation since traditional join algorithms spend majority of their time trying to join the parts of the relations that do not generate any output tuples. This causes slow response times with...
Resource Type:: Masters Thesis

Improving the Effectiveness of Answering Keyword Queries Using Effective Subsets

Creator:: Khodadadi, Abtin
Abstract:: Most database users do not know formal query languages, such as SQL, and prefer to express their information needs using usable query languages, such as keyword queries. Keyword queries, however, are inherently ambiguous and challenging for the database systems to understand and answer effectively. We propose a novel approach to...
Resource Type:: Capstone Project
Full Text:: Bibliography [1] Sameer Agarwal, Barzan Mozafari, Aurojit Panda, Henry Milner, Samuel Madden, and Ion Stoica

Collaborative Online Learning For Join Processing

Creator:: Xie, Mian
Abstract:: Relational binary operators, such as join, are arguably the most costly and frequently used operations in relational data systems. In many join algorithms, the majority of the process time is spent on scanning and attempting to join the parts of the relations that do not satisfy the join condition and...
Resource Type:: Capstone Project

Redesigning the Structure and Access Paths of Databases for Effective and Efficient Query Processing

Creator:: Ghadakchi, Vahid
Abstract:: Many database users are not familiar with formal query languages, the concept of schema, or the exact content of their database. Thus, it is challenging for these users to formulate their information needs over semi-structured and structured databases. To address this problem, researchers have proposed usable query interfaces over which...
Resource Type:: Dissertation

Predicting and Improving Throughput, Responsiveness and Battery Life of Computer Systems by Machine Learning

Creator:: Li, Yunfan
Abstract:: The Machine Learning (ML) algorithms are increasingly explored in varies of fields including designing and optimizing computer systems. Recent research, such as optimizing memory/cache prefetching by ML training or predicting traffic pattern in throughput processors, also exhibits a promising future of introducing ML into computer system design and optimization. Throughput...
Resource Type:: Dissertation

Bayesian optimization with empirical constraints

Creator:: Azimi, Javad
Abstract:: 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...
Resource Type:: Dissertation

Structured gradient boosting

Creator:: Parker, Charles (Charles Lincoln)
Abstract:: The goal of many machine learning problems can be formalized as the creation of a function that can properly classify an input vector, given a set of examples of that function. While this formalism has produced a number of success stories, there are notable situations in which it fails. One...
Resource Type:: Dissertation

Representationally Robust and Scalable Learning over Relational Databases

Creator:: Picado Leiva, Jose Manuel
Abstract:: Learning novel concepts from relational databases is an important problem with applications in several disciplines, such as data management, natural language processing, and bioinformatics. For a learning algorithm to be effective, the input data should be clean and in some desired representation. However, real-world data is usually heterogeneous – the...
Resource Type:: Dissertation

ScholarsArchive@OSU

Protein secondary structure prediction using conditional random fields and profiles

Learning to Estimate Multi-Relation Aggregation Functions

Improving the Effectiveness of Answering Keyword Queries Using Effective Subsets

Collaborative Online Learning For Join Processing

Redesigning the Structure and Access Paths of Databases for Effective and Efficient Query Processing

Predicting and Improving Throughput, Responsiveness and Battery Life of Computer Systems by Machine Learning

Bayesian optimization with empirical constraints

Structured gradient boosting

Representationally Robust and Scalable Learning over Relational Databases

Limit your search

Academic Affiliation

Advisor

Commencement Year

Committee Member

Creator

Contributor

Date

Decade

Degree Field

Degree Level

Degree Name

File Format

Language

License

Non-Academic Affiliation

Peer Reviewed

Resource Type

Rights Statement

Subject

Search Constraints

Search Results

Limit your search