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ACL
1998
15 years 2 months ago
Experiments with Learning Parsing Heuristics
Any large language processing software relies in its operation on heuristic decisions concerning the strategy of processing. These decisions are usually "hard-wired" int...
Sylvain Delisle, Sylvain Létourneau, Stan M...
AIME
1997
Springer
15 years 5 months ago
Detecting Very Early Stages of Dementia from Normal Aging with Machine Learning Methods
We used Machine Learning (ML) methods to learn the best decision rules to distinguish normal brain aging from the earliest stages of dementia using subsamples of 198 normal and 244...
William Rodman Shankle, Subramani Mani, Michael J....
NIPS
2007
15 years 2 months ago
A General Boosting Method and its Application to Learning Ranking Functions for Web Search
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
Zhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier C...
SEMWEB
2010
Springer
14 years 11 months ago
Supporting Natural Language Processing with Background Knowledge: Coreference Resolution Case
Systems based on statistical and machine learning methods have been shown to be extremely effective and scalable for the analysis of large amount of textual data. However, in the r...
Volha Bryl, Claudio Giuliano, Luciano Serafini, Ka...
JMLR
2010
143views more  JMLR 2010»
14 years 12 months ago
A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning
We extend the well-known BFGS quasi-Newton method and its memory-limited variant LBFGS to the optimization of nonsmooth convex objectives. This is done in a rigorous fashion by ge...
Jin Yu, S. V. N. Vishwanathan, Simon Günter, ...