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» Global Optimization for Value Function Approximation
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JMLR
2010
143views more  JMLR 2010»
15 years 25 days 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, ...
107
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AVSS
2006
IEEE
15 years 8 months ago
A Random Field Model for Improved Feature Extraction and Tracking
This paper presents a novel method for illuminationinvariant and contrast preserving feature extraction, aimed at improving performance of tracking under complex light condition. ...
Xiaotong Yuan, Stan Z. Li
121
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DAC
2006
ACM
16 years 3 months ago
Generation of yield-aware Pareto surfaces for hierarchical circuit design space exploration
Pareto surfaces in the performance space determine the range of feasible performance values for a circuit topology in a given technology. We present a non-dominated sorting based ...
Saurabh K. Tiwary, Pragati K. Tiwary, Rob A. Ruten...
114
Voted
ESIAT
2009
IEEE
15 years 5 days ago
An Image Mosaics Algorithm Based on Improved Phase Correlation
An image mosaics algorithm based on improved phase correlation is proposed in this paper. The improved phase correlation improves on the conventional phase correlation in three asp...
Zhang Jing, Wang Chang-shun, Liao Wu-ling
AAAI
2006
15 years 3 months ago
Efficient L1 Regularized Logistic Regression
L1 regularized logistic regression is now a workhorse of machine learning: it is widely used for many classification problems, particularly ones with many features. L1 regularized...
Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. N...