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» Structural Modelling with Sparse Kernels
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CGF
2010
111views more  CGF 2010»
14 years 10 months ago
One Point Isometric Matching with the Heat Kernel
A common operation in many geometry processing algorithms consists of finding correspondences between pairs of shapes by finding structure-preserving maps between them. A particul...
Maks Ovsjanikov, Quentin Mérigot, Facundo M...
NIPS
2004
14 years 11 months ago
An Application of Boosting to Graph Classification
This paper presents an application of Boosting for classifying labeled graphs, general structures for modeling a number of real-world data, such as chemical compounds, natural lan...
Taku Kudo, Eisaku Maeda, Yuji Matsumoto
PPOPP
2010
ACM
15 years 7 months ago
Scalable communication protocols for dynamic sparse data exchange
Many large-scale parallel programs follow a bulk synchronous parallel (BSP) structure with distinct computation and communication phases. Although the communication phase in such ...
Torsten Hoefler, Christian Siebert, Andrew Lumsdai...
KDD
2009
ACM
192views Data Mining» more  KDD 2009»
15 years 4 months ago
Primal sparse Max-margin Markov networks
Max-margin Markov networks (M3 N) have shown great promise in structured prediction and relational learning. Due to the KKT conditions, the M3 N enjoys dual sparsity. However, the...
Jun Zhu, Eric P. Xing, Bo Zhang
PRIB
2010
Springer
192views Bioinformatics» more  PRIB 2010»
14 years 8 months ago
Structured Output Prediction of Anti-cancer Drug Activity
We present a structured output prediction approach for classifying potential anti-cancer drugs. Our QSAR model takes as input a description of a molecule and predicts the activity...
Hongyu Su, Markus Heinonen, Juho Rousu