Index Catalog // ScholarsArchive@OSU

Integrating rich user feedback into intelligent user interfaces

Creator:: Oregon State University. Dept. of Computer Science, Stumpf, Simone, Sullivan, Erin, Fitzhenry, Erin, Oberst, Ian, Wong, Weng-Keen, and Burnett, Margaret, 1949-
Abstract:: The potential for machine learning systems to improve via a mutually beneficial exchange of information with users has yet to be explored in much detail. Previously, we found that users were willing to provide a generous amount of rich feedback to machine learning systems, and that the types of some...
Resource Type:: Research Paper
Full Text:: (2006), 86-92. 24. Stumpf S, Rajaram V, Li L, Burnett M, Dietterich T, Sullivan E, Drummond R

Toward harnessing user feedback for machine learning

Creator:: Stumpf, Simone, Rajaram, Vidya, Li, Lida, Burnett, Margaret, 1949-, Dietterich, Thomas Glen, Sullivan, Erin, Drummond, Russell, and Herlocker, Jonathan Lee
Abstract:: There has been little research into how end users might be able to communicate advice to machine learning systems. If this resource--the users themselves--could somehow work hand-in-hand with machine learning systems, the accuracy of learning systems could be improved and the users' understanding and trust of the system could improve...
Resource Type:: Technical Report
Full Text:: Simone Stumpf, Vidya Rajaram, Lida Li, Margaret Burnett, Thomas Dietterich, Erin Sullivan, Russell

Interacting meaningfully with machine learning systems : three experiments

Creator:: Oregon State University. Dept. of Computer Science, Stumpf, Simone, Rajaram, Vidya, Li, Lida, Wong, Weng-Keen, Burnett, Margaret, 1949-, Dietterich, Thomas Glen, Sullivan, Erin, and Herlocker, Jonathan Lee
Abstract:: Although machine learning is becoming commonly used in today's software, there has been little research into how end users might interact with machine learning systems, beyond communicating simple "right/wrong" judgments. If the users themselves could somehow work hand-in-hand with machine learning systems, the accuracy of learning systems could be improved...
Resource Type:: Research Paper
Full Text:: , Lida Li, Weng-Keen Wong, Margaret Burnett, Thomas Dietterich, Erin Sullivan, Jonathan Herlocker

On the Role of Spatial Clustering Algorithms in Building Species Distribution Models from Community Science Data

Creator:: Roth, Mark
Abstract:: This paper discusses opportunities for developments in spatial clustering methods to help leverage broad scale community science data for building species distribution models (SDMs). SDMs are critical tools that inform the science and policy needed to mitigate the impacts of climate change on biodiversity. Community science data span spatial and...
Resource Type:: Capstone Project
Full Text:: (Sullivan et al., 2014). eBirders report checklists of how many of each species they observed, and they

Machine learning for improving the quality of citizen science data

Creator:: Yu, Jun
Abstract:: Citizen Science is a paradigm in which volunteers from the general public participate in scientific studies, often by performing data collection. This paradigm is especially useful if the scope of the study is too broad to be performed by a limited number of trained scientists. Although citizen scientists can contribute...
Resource Type:: Dissertation
Full Text:: , Brian Sullivan, Chris Wood, Jeff Gerbracht and Steve Kelling. Thanks to their supports in my research

Toward end-user debugging of machine-learned programs

Creator:: Kulesza, Todd
Abstract:: The results of a machine learning from user behavior can be thought of as a program, and like all programs, it may need to be debugged. Providing ways for the user to debug it matters because without the ability to fix errors, users may find that the learned program’s errors...
Resource Type:: Masters Thesis
Full Text:: answer to Table 2’s second question (with dynamically- replaced text in ) is: The message

Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale

Creator:: Hooper, Samuel
Abstract:: Developing accurate predictive distribution models requires adequately representing relevant spatial and temporal scales, as these scales are ultimately reflective of the relationships between distributions and influential environmental conditions. In this research, we considered both spatial and temporal scale and the influence each has on predicting broad-scale distributions of two disparate...
Resource Type:: Masters Thesis
Full Text:: . References Addicott, John F., John M. Aho, Michael F. Antolin, Dianna K. Padilla, John S. Richardson, and

Investigating Transcriptional Control of Specialized Gene Expression in Plants

Creator:: Fraser, Valerie N.
Abstract:: Specialized or secondary metabolism is a collection of pathways and small molecules that, while beneficial to an organism, are not strictly necessary for survival. Plants use secondary metabolites to, among other things, attract pollinators, defend against biotic and abiotic stressors, and form symbioses. Natural products from plants have seen an...
Resource Type:: Dissertation
Full Text:: closer to the TSS than TF1’s—and this causes the gene to express in root. 4 In addition

Personalizing machine learning systems with explanatory debugging

Creator:: Kulesza, Todd
Abstract:: How can end users efficiently influence the predictions that machine learning systems make on their behalf? Traditional systems rely on users to provide examples of how they want the learning system to behave, but this is not always practical for the user, nor efficient for the learning system. This dissertation...
Resource Type:: Dissertation

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:: k|α̂k) as the prior of each θk and integrate out all θk-s. Given 14 a test point xt, the

ScholarsArchive@OSU

Integrating rich user feedback into intelligent user interfaces

Toward harnessing user feedback for machine learning

Interacting meaningfully with machine learning systems : three experiments

On the Role of Spatial Clustering Algorithms in Building Species Distribution Models from Community Science Data

Machine learning for improving the quality of citizen science data

Toward end-user debugging of machine-learned programs

Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale

Investigating Transcriptional Control of Specialized Gene Expression in Plants

Personalizing machine learning systems with explanatory debugging

Machine Learning Methods for Computational Sustainability

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