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» Online Learning of Approximate Dependency Parsing Algorithms
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FOCS
2008
IEEE
14 years 2 months ago
What Can We Learn Privately?
Learning problems form an important category of computational tasks that generalizes many of the computations researchers apply to large real-life data sets. We ask: what concept ...
Shiva Prasad Kasiviswanathan, Homin K. Lee, Kobbi ...
PR
2008
123views more  PR 2008»
13 years 7 months ago
Extensions of vector quantization for incremental clustering
In this paper, we extend the conventional vector quantization by incorporating a vigilance parameter, which steers the tradeoff between plasticity and stability during incremental...
Edwin Lughofer
COLT
2000
Springer
13 years 12 months ago
The Computational Complexity of Densest Region Detection
We investigate the computational complexity of the task of detecting dense regions of an unknown distribution from un-labeled samples of this distribution. We introduce a formal l...
Shai Ben-David, Nadav Eiron, Hans-Ulrich Simon
CVPR
2007
IEEE
14 years 9 months ago
Element Rearrangement for Tensor-Based Subspace Learning
The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
Shuicheng Yan, Dong Xu, Stephen Lin, Thomas S. Hua...
MIR
2010
ACM
264views Multimedia» more  MIR 2010»
14 years 2 months ago
Quest for relevant tags using local interaction networks and visual content
Typical tag recommendation systems for photos shared on social networks such as Flickr, use visual content analysis, collaborative filtering or personalization strategies to prod...
Neela Sawant, Ritendra Datta, Jia Li, James Ze Wan...