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Operator-valued Kernels for Learning from Functional Response Data
In this paper we consider the problems of supervised classification and regression in the case where attributes and labels are functions: a data is represented by a set of functions, and the label isExpand
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Sparse Temporal Difference Learning Using LASSO
We consider the problem of on-line value function estimation in reinforcement learning. We concentrate on the function approximator to use. To try to break the curse of dimensionality, we focus onExpand
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Online Clustering of Processes
The problem of online clustering is considered in the case where each data point is a sequence generated by a stationary ergodic process. Data arrive in an online fashion so that the sample receivedExpand
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Consistent Algorithms for Clustering Time Series
The problem of clustering is considered for the case where every point is a time series. The time series are either given in one batch (offline setting), or they are allowed to grow with time and newExpand
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A Generalized Kernel Approach to Structured Output Learning
We study the problem of structured output learning from a regression perspective. We first provide a general formulation of the kernel dependency estimation (KDE) approach to this problem usingExpand
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A Bit-Wise Epistasis Measure for Binary Search Spaces
The epistatic variance has been introduced by Davidor as a tool for the evaluation of interdependences between genes, thus possibly giving clues about the difficulty of optimizing functions withExpand
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Fitness Landscapes and Performance of Meta-Heuristics
We perform a statistical analysis of the structure of the search space of some planar, euclidian instances of the traveling salesman problem. We want to depict this structure from the point of viewExpand
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Managing advertising campaigns — an approximate planning approach
We consider the problem of displaying commercial advertisements on web pages, in the “cost per click” model. The advertisement server has to learn the appeal of each type of visitor for the differentExpand
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Bandits attack function optimization
We consider function optimization as a sequential decision making problem under the budget constraint. Such constraint limits the number of objective function evaluations allowed during theExpand
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