Sciweavers

ICML
2004
IEEE
13 years 9 months ago
Optimising area under the ROC curve using gradient descent
This paper introduces RankOpt, a linear binary classifier which optimises the area under the ROC curve (the AUC). Unlike standard binary classifiers, RankOpt adopts the AUC stat...
Alan Herschtal, Bhavani Raskutti
ATAL
2005
Springer
13 years 9 months ago
Optimal status sets of heterogeneous agent programs
There are many situations where an agent can perform one of several sets of actions in responses to changes in its environment, and the agent chooses to perform the set of actions...
Bogdan Stroe, V. S. Subrahmanian, Sudeshna Dasgupt...
LPAR
2005
Springer
13 years 9 months ago
Another Complete Local Search Method for SAT
Local search algorithms are one of the effective methods for solving hard combinatorial problems. However, a serious problem of this approach is that the search often traps at loca...
Haiou Shen, Hantao Zhang
GECCO
2005
Springer
138views Optimization» more  GECCO 2005»
13 years 9 months ago
Promising infeasibility and multiple offspring incorporated to differential evolution for constrained optimization
In this paper, we incorporate a diversity mechanism to the differential evolution algorithm to solve constrained optimization problems without using a penalty function. The aim is...
Efrén Mezura-Montes, Jesús Vel&aacut...
EMMCVPR
2005
Springer
13 years 9 months ago
Increasing Efficiency of SVM by Adaptively Penalizing Outliers
In this paper, a novel training method is proposed to increase the classification efficiency of support vector machine (SVM). The efficiency of the SVM is determined by the number ...
Yiqiang Zhan, Dinggang Shen
AUSAI
2005
Springer
13 years 9 months ago
K-Optimal Pattern Discovery: An Efficient and Effective Approach to Exploratory Data Mining
Most data-mining techniques seek a single model that optimizes an objective function with respect to the data. In many real-world applications several models will equally optimize...
Geoffrey I. Webb
APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
13 years 9 months ago
Sampling Bounds for Stochastic Optimization
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Moses Charikar, Chandra Chekuri, Martin Pál
ASPDAC
2005
ACM
117views Hardware» more  ASPDAC 2005»
13 years 9 months ago
Dynamic symmetry-breaking for improved Boolean optimization
With impressive progress in Boolean Satisfiability (SAT) solving and several extensions to pseudo-Boolean (PB) constraints, many applications that use SAT, such as highperformanc...
Fadi A. Aloul, Arathi Ramani, Igor L. Markov, Kare...
CEC
2005
IEEE
13 years 9 months ago
Adaptive cluster covering and evolutionary approach: comparison, differences and similarities
In case the objective function to be minimized is not known analytically and no assumption can be made about the single extremum, global optimization (GO) methods must be used. Pap...
Dimitri P. Solomatine
ROBIO
2006
IEEE
153views Robotics» more  ROBIO 2006»
13 years 9 months ago
GA-based Feature Subset Selection for Myoelectric Classification
– This paper presents an ongoing investigation to select optimal subset of features from set of well-known myoelectric signals (MES) features in time and frequency domains. Four ...
Mohammadreza Asghari Oskoei, Huosheng Hu