We present a meta-model as a process maturity framework that can be effectively used to
identify the key practices to initiate and sustain a software process improvement effort
focused on a single process area. Our approach moves away from the overall software
development process and computation of maturity levels and...
This paper introduces the even-odd POMDP an approximation to POMDPs Partially Observable Markov Decision Problems in which the world is assumed to be fully observable every other time step. This approximation works well for problems with a delayed need to observe. The even-odd POMDP can be converted into an equivalent...
This paper introduces the even-odd POMDP, an approximation to POMDPs in which the world is assumed to be fully observable every other time step. The even-odd POMDP can be converted into an equivalent MDP, the
2MDP, whose value function, V*[subscript 2MDP], can be combined online with a 2-step lookahead search...
This paper presents an empirical approach for measuring and characterizing the responsiveness of a character to changes in goal. Our approach is based on keeping track of the character's progress towards a frequently changing goal. A "distance-to-goal" function is defined to measure the progress. We then calculate an asymptotic proportion...
Spreadsheet languages, which include commercial spreadsheets and various research systems, have proven to be flexible tools in many settings. Research shows, however, that spreadsheets often contain faults. This thesis presents an integrated testing and fault localization methodology for spreadsheets. This methodology allows spreadsheet developers to engage in modeless development, testing...
Many software maintenance problems are caused by using text editors to change programs. A more systematic and reliable way of performing program updates is to express changes with an update language. In particular, updates should preserve the syntax- and type-correctness of the transformed object programs. We describe an update calculus...
Many machine learning applications require
classifiers that minimize an asymmetric cost
function rather than the misclassification
rate, and several recent papers have addressed
this problem. However, these papers
have either applied no statistical testing
or have applied statistical methods that are
not appropriate for the cost-sensitive setting.
Without good statistical...
This paper studies cluster ensembles for high dimensional data clustering. We examine three different approaches to constructing cluster ensembles. To address high dimensionality, we focus on ensemble construction methods that build on two popular dimension reduction techniques, random projection and principal component analysis (PCA). We present evidence showing that ensembles...
Can collaborative filtering be successfully applied to digital
libraries in a manner that improves the effectiveness of the
library? Collaborative filtering systems remove the limitation of
traditional content-based search interfaces by using individuals to
evaluate and recommend information. We introduce an approach
where a digital library user specifies their need...