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» A Framework for Multiple-Instance Learning
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ECAI
2008
Springer
15 years 5 months ago
Learning Functional Object-Categories from a Relational Spatio-Temporal Representation
Abstract. We propose a framework that learns functional objectes from spatio-temporal data sets such as those abstracted from video. The data is represented as one activity graph t...
Muralikrishna Sridhar, Anthony G. Cohn, David C. H...
136
Voted
BIS
2008
132views Business» more  BIS 2008»
15 years 5 months ago
Evaluate - An Innovative Service for Learning Performance Monitoring in Businesses
In this paper we present Evaluate, a platform for learning performance monitoring. Evaluate manages a number of artefacts that can be used to monitor learning performance, like met...
Bernd Simon, Kasra Seirafi, Asmund Realfsen, Mark ...
NIPS
2008
15 years 5 months ago
Supervised Dictionary Learning
It is now well established that sparse signal models are well suited for restoration tasks and can be effectively learned from audio, image, and video data. Recent research has be...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
NAACL
2007
15 years 5 months ago
Data-Driven Graph Construction for Semi-Supervised Graph-Based Learning in NLP
Graph-based semi-supervised learning has recently emerged as a promising approach to data-sparse learning problems in natural language processing. All graph-based algorithms rely ...
Andrei Alexandrescu, Katrin Kirchhoff
124
Voted
NAACL
2007
15 years 5 months ago
Using "Annotator Rationales" to Improve Machine Learning for Text Categorization
We propose a new framework for supervised machine learning. Our goal is to learn from smaller amounts of supervised training data, by collecting a richer kind of training data: an...
Omar Zaidan, Jason Eisner, Christine D. Piatko