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» Structural Modelling with Sparse Kernels
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ICML
2004
IEEE
15 years 3 months ago
Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs
We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
Hisashi Kashima, Yuta Tsuboi
TLCA
1995
Springer
15 years 1 months ago
Typed Operational Semantics
operator abstraction is a language construct relevant to object oriented programming languages and to ML2000, the successor to Standard ML. In this paper, we introduce Fω ≤, a ...
Healfdene Goguen
SC
2005
ACM
15 years 3 months ago
Dynamic Data-Driven Inversion For Terascale Simulations: Real-Time Identification Of Airborne Contaminants
In contrast to traditional terascale simulations that have known, fixed data inputs, dynamic data-driven (DDD) applications are characterized by unknown data and informed by dynam...
Volkan Akcelik, George Biros, Andrei Draganescu, J...
ICDM
2007
IEEE
289views Data Mining» more  ICDM 2007»
15 years 4 months ago
Latent Dirichlet Conditional Naive-Bayes Models
In spite of the popularity of probabilistic mixture models for latent structure discovery from data, mixture models do not have a natural mechanism for handling sparsity, where ea...
Arindam Banerjee, Hanhuai Shan
CSB
2003
IEEE
176views Bioinformatics» more  CSB 2003»
15 years 3 months ago
3D Structural Homology Detection via Unassigned Residual Dipolar Couplings
Recognition of a protein’s fold provides valuable information about its function. While many sequence-based homology prediction methods exist, an important challenge remains: tw...
Christopher James Langmead, Bruce Randall Donald