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ESANN
2007
15 years 7 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
EMNLP
2008
15 years 7 months ago
Modeling Annotators: A Generative Approach to Learning from Annotator Rationales
A human annotator can provide hints to a machine learner by highlighting contextual "rationales" for each of his or her annotations (Zaidan et al., 2007). How can one ex...
Omar Zaidan, Jason Eisner
LREC
2008
139views Education» more  LREC 2008»
15 years 7 months ago
Identification of Comparable Argument-Head Relations in Parallel Corpora
We present the machine learning framework that we are developing, in order to support explorative search for non-trivial linguistic configurations in low-density languages (langua...
Kathrin Spreyer, Jonas Kuhn, Bettina Schrader
NIPS
2008
15 years 7 months ago
Natural Image Denoising with Convolutional Networks
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
Viren Jain, H. Sebastian Seung
SDM
2008
SIAM
122views Data Mining» more  SDM 2008»
15 years 7 months ago
Type-Independent Correction of Sample Selection Bias via Structural Discovery and Re-balancing
Sample selection bias is a common problem in many real world applications, where training data are obtained under realistic constraints that make them follow a different distribut...
Jiangtao Ren, Xiaoxiao Shi, Wei Fan, Philip S. Yu