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NIPS
2007
13 years 6 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...
SSPR
1998
Springer
13 years 9 months ago
Distribution Free Decomposition of Multivariate Data
: We present a practical approach to nonparametric cluster analysis of large data sets. The number of clusters and the cluster centres are automatically derived by mode seeking wit...
Dorin Comaniciu, Peter Meer
ICDM
2010
IEEE
167views Data Mining» more  ICDM 2010»
13 years 2 months ago
Averaged Stochastic Gradient Descent with Feedback: An Accurate, Robust, and Fast Training Method
On large datasets, the popular training approach has been stochastic gradient descent (SGD). This paper proposes a modification of SGD, called averaged SGD with feedback (ASF), tha...
Xu Sun, Hisashi Kashima, Takuya Matsuzaki, Naonori...
CCE
2004
13 years 4 months ago
A decomposition method for synthesizing complex column configurations using tray-by-tray GDP models
This paper describes an optimization procedure for the synthesis of complex distillation configurations. A superstructure based on the Reversible Distillation Sequence Model (RDSM...
Mariana Barttfeld, Pío A. Aguirre, Ignacio ...
TSP
2010
12 years 11 months ago
Improved dual decomposition based optimization for DSL dynamic spectrum management
Dynamic spectrum management (DSM) has been recognized as a key technology to significantly improve the performance of digital subscriber line (DSL) broadband access networks. The b...
Paschalis Tsiaflakis, Ion Necoara, Johan A. K. Suy...