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» Solving Hierarchical Optimization Problems Using MOEAs
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ICVGIP
2004
15 years 1 months ago
A Robust Nonparametric Estimation Framework for Implicit Image Models
Robust model fitting is important for computer vision tasks due to the occurrence of multiple model instances, and, unknown nature of noise. The linear errors-in-variables (EIV) m...
Himanshu Arora, Maneesh Singh, Narendra Ahuja
ISLPED
2006
ACM
99views Hardware» more  ISLPED 2006»
15 years 6 months ago
Thermal via allocation for 3D ICs considering temporally and spatially variant thermal power
All existing methods for thermal-via allocation are based on a steady-state thermal analysis and may lead to excessive number of thermal vias. This paper develops an accurate and ...
Hao Yu, Yiyu Shi, Lei He, Tanay Karnik
IR
2010
14 years 11 months ago
Adapting boosting for information retrieval measures
Abstract We present a new ranking algorithm that combines the strengths of two previous methods: boosted tree classification, and LambdaRank, which has been shown to be empiricall...
Qiang Wu, Christopher J. C. Burges, Krysta Marie S...
127
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SIAMIS
2010
190views more  SIAMIS 2010»
14 years 7 months ago
Analysis and Generalizations of the Linearized Bregman Method
This paper analyzes and improves the linearized Bregman method for solving the basis pursuit and related sparse optimization problems. The analysis shows that the linearized Bregma...
Wotao Yin
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
15 years 4 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing