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» Learning to learn with the informative vector machine
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NIPS
2007
15 years 8 months ago
Stability Bounds for Non-i.i.d. Processes
The notion of algorithmic stability has been used effectively in the past to derive tight generalization bounds. A key advantage of these bounds is that they are designed for spec...
Mehryar Mohri, Afshin Rostamizadeh
JMLR
2010
119views more  JMLR 2010»
15 years 1 months ago
The Coding Divergence for Measuring the Complexity of Separating Two Sets
In this paper we integrate two essential processes, discretization of continuous data and learning of a model that explains them, towards fully computational machine learning from...
Mahito Sugiyama, Akihiro Yamamoto
ICASSP
2010
IEEE
15 years 7 months ago
Sparse signal recovery in the presence of correlated multiple measurement vectors
Sparse signal recovery algorithms utilizing multiple measurement vectors (MMVs) are known to have better performance compared to the single measurement vector case. However, curre...
Zhilin Zhang, Bhaskar D. Rao

Publication
233views
14 years 5 months ago
Sparse reward processes
We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained duri...
Christos Dimitrakakis
ICML
2009
IEEE
16 years 1 months ago
A novel lexicalized HMM-based learning framework for web opinion mining
Merchants selling products on the Web often ask their customers to share their opinions and hands-on experiences on products they have purchased. As e-commerce is becoming more an...
Wei Jin, Hung Hay Ho