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NIPS
2007
15 years 8 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...
SODA
2001
ACM
79views Algorithms» more  SODA 2001»
15 years 8 months ago
Learning Markov networks: maximum bounded tree-width graphs
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
David R. Karger, Nathan Srebro
AIME
2003
Springer
15 years 11 months ago
Learning-Free Text Categorization
In this paper, we report on the fusion of simple retrieval strategies with thesaural resources in order to perform large-scale text categorization tasks. Unlike most related system...
Patrick Ruch, Robert H. Baud, Antoine Geissbü...
KDD
2010
ACM
242views Data Mining» more  KDD 2010»
15 years 8 months ago
A scalable two-stage approach for a class of dimensionality reduction techniques
Dimensionality reduction plays an important role in many data mining applications involving high-dimensional data. Many existing dimensionality reduction techniques can be formula...
Liang Sun, Betul Ceran, Jieping Ye
COLT
2010
Springer
15 years 4 months ago
Toward Learning Gaussian Mixtures with Arbitrary Separation
In recent years analysis of complexity of learning Gaussian mixture models from sampled data has received significant attention in computational machine learning and theory commun...
Mikhail Belkin, Kaushik Sinha