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» Evaluating learning algorithms and classifiers
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JMLR
2010
121views more  JMLR 2010»
13 years 5 months ago
Sparse Semi-supervised Learning Using Conjugate Functions
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...
Shiliang Sun, John Shawe-Taylor
SIGIR
2011
ACM
13 years 1 months ago
Learning to rank from a noisy crowd
We study how to best use crowdsourced relevance judgments learning to rank [1, 7]. We integrate two lines of prior work: unreliable crowd-based binary annotation for binary classi...
Abhimanu Kumar, Matthew Lease
AAAI
2012
12 years 20 days ago
Learning Games from Videos Guided by Descriptive Complexity
In recent years, several systems have been proposed that learn the rules of a simple card or board game solely from visual demonstration. These systems were constructed for speciï...
Lukasz Kaiser
ATAL
2007
Springer
14 years 4 months ago
Sharing experiences to learn user characteristics in dynamic environments with sparse data
This paper investigates the problem of estimating the value of probabilistic parameters needed for decision making in environments in which an agent, operating within a multi-agen...
David Sarne, Barbara J. Grosz
CVPR
2009
IEEE
15 years 5 months ago
Unsupervised Learning of Hierarchical Spatial Structures In Images
The visual world demonstrates organized spatial patterns, among objects or regions in a scene, object-parts in an object, and low-level features in object-parts. These classes o...
Devi Parikh (Carnegie Mellon University), C. Lawre...