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» The Combining Classifier: To Train or Not to Train
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TIP
2010
255views more  TIP 2010»
13 years 2 days ago
Image Super-Resolution Via Sparse Representation
This paper presents a new approach to single-image superresolution, based on sparse signal representation. Research on image statistics suggests that image patches can be wellrepre...
Jianchao Yang, John Wright, Thomas S. Huang, Yi Ma
ICASSP
2011
IEEE
12 years 9 months ago
Collaborative sources identification in mixed signals via hierarchical sparse modeling
A collaborative framework for detecting the different sources in mixed signals is presented in this paper. The approach is based on CHiLasso, a convex collaborative hierarchical s...
Pablo Sprechmann, Ignacio Ramírez, Pablo Ca...
IJPP
2011
115views more  IJPP 2011»
12 years 8 months ago
Milepost GCC: Machine Learning Enabled Self-tuning Compiler
Tuning compiler optimizations for rapidly evolving hardware makes porting and extending an optimizing compiler for each new platform extremely challenging. Iterative optimization i...
Grigori Fursin, Yuriy Kashnikov, Abdul Wahid Memon...
IUI
2011
ACM
12 years 8 months ago
ChemInk: a natural real-time recognition system for chemical drawings
We describe a new sketch recognition framework for chemical structure drawings that combines multiple levels of visual features using a jointly trained conditional random field. ...
Tom Y. Ouyang, Randall Davis
IAAI
2011
12 years 5 months ago
NewsFinder: Automating an Artificial Intelligence News Service
NewsFinder automates the steps involved in finding, selecting and publishing news stories that meet subjective judgments of relevance and interest to the Artificial Intelligence c...
Liang Dong, Reid G. Smith, Bruce G. Buchanan