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EMNLP
2008
13 years 9 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
MSOM
2007
118views more  MSOM 2007»
13 years 7 months ago
What Can Be Learned from Classical Inventory Models? A Cross-Industry Exploratory Investigation
: Classical inventory models offer a variety of insights into the optimal way to manage inventories of individual products. However, top managers and industry analysts are often co...
Sergey Rumyantsev, Serguei Netessine
INTERSPEECH
2010
13 years 2 months ago
Data-dependent evaluator modeling and its application to emotional valence classification from speech
Practical supervised learning scenarios involving subjectively evaluated data have multiple evaluators, each giving their noisy version of the hidden ground truth. Majority logic ...
Kartik Audhkhasi, Shrikanth S. Narayanan
ICCV
2009
IEEE
15 years 21 days ago
Learning Pedestrian Dynamics from the Real World
In this paper we describe a method to learn parameters which govern pedestrian motion by observing video data. Our learning framework is based on variational mode learning and a...
Paul Scovanner, Marshall Tappen
CVPR
2007
IEEE
14 years 9 months ago
Multi-Layer Background Subtraction Based on Color and Texture
In this paper, we propose a robust multi-layer background subtraction technique which takes advantages of local texture features represented by local binary patterns (LBP) and pho...
Jian Yao, Jean-Marc Odobez