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ESEM
2007
ACM
15 years 4 months ago
Effort Prediction in Iterative Software Development Processes -- Incremental Versus Global Prediction Models
Estimation of development effort without imposing overhead on the project and the development team is of paramount importance for any software company. This study proposes a new e...
Pekka Abrahamsson, Raimund Moser, Witold Pedrycz, ...
128
Voted
ESEM
2007
ACM
15 years 4 months ago
The Effects of Over and Under Sampling on Fault-prone Module Detection
The goal of this paper is to improve the prediction performance of fault-prone module prediction models (fault-proneness models) by employing over/under sampling methods, which ar...
Yasutaka Kamei, Akito Monden, Shinsuke Matsumoto, ...
87
Voted
SIGIR
2010
ACM
15 years 4 months ago
Multilabel classification with meta-level features
Effective learning in multi-label classification (MLC) requires an ate level of abstraction for representing the relationship between each instance and multiple categories. Curren...
Siddharth Gopal, Yiming Yang
106
Voted
ECAI
2006
Springer
15 years 4 months ago
Least Squares SVM for Least Squares TD Learning
Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...
Tobias Jung, Daniel Polani
106
Voted
ECML
2006
Springer
15 years 4 months ago
Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Sébastien Jodogne, Cyril Briquet, Justus H....