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» Optimizing Complex Loss Functions in Structured Prediction
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CVPR
2008
IEEE
15 years 11 months ago
Learning for stereo vision using the structured support vector machine
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
Yunpeng Li, Daniel P. Huttenlocher
LION
2009
Springer
135views Optimization» more  LION 2009»
15 years 4 months ago
Neural Network Pairwise Interaction Fields for Protein Model Quality Assessment
We present a new knowledge-based Model Quality Assessment Program (MQAP) at the residue level which evaluates single protein structure models. We use a tree representation of the ...
Alberto J. M. Martin, Alessandro Vullo, Gianluca P...
80
Voted
ICML
2008
IEEE
15 years 10 months ago
Accurate max-margin training for structured output spaces
Tsochantaridis et al. (2005) proposed two formulations for maximum margin training of structured spaces: margin scaling and slack scaling. While margin scaling has been extensivel...
Sunita Sarawagi, Rahul Gupta
91
Voted
ICWS
2009
IEEE
14 years 7 months ago
Discovery of Optimized Web Service Configurations Using a Hybrid Semantic and Statistical Approach
We present a Semantic Optimized Service Discovery (SemOSD) approach capable of handling Web service search requests on a fine-grained level of detail where we augment semantic ser...
Maciej Zaremba, Jacek Migdal, Manfred Hauswirth
79
Voted
TSP
2008
92views more  TSP 2008»
14 years 9 months ago
Distributed Structures, Sequential Optimization, and Quantization for Detection
Abstract--In the design of distributed quantization systems one inevitably confronts two types of constraints--those imposed by a distributed system's structure and those impo...
Michael A. Lexa, Don H. Johnson