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ECML
2006
Springer
15 years 5 months ago
Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Sébastien Jodogne, Cyril Briquet, Justus H....
EDBT
2006
ACM
154views Database» more  EDBT 2006»
15 years 5 months ago
Approximation Techniques to Enable Dimensionality Reduction for Voronoi-Based Nearest Neighbor Search
Utilizing spatial index structures on secondary memory for nearest neighbor search in high-dimensional data spaces has been the subject of much research. With the potential to host...
Christoph Brochhaus, Marc Wichterich, Thomas Seidl
NIPS
2000
15 years 3 months ago
A New Approximate Maximal Margin Classification Algorithm
A new incremental learning algorithm is described which approximates the maximal margin hyperplane w.r.t. norm p 2 for a set of linearly separable data. Our algorithm, called alm...
Claudio Gentile
ATAL
2010
Springer
15 years 3 months ago
Finding approximate competitive equilibria: efficient and fair course allocation
In the course allocation problem, a university administrator seeks to efficiently and fairly allocate schedules of over-demanded courses to students with heterogeneous preferences...
Abraham Othman, Tuomas Sandholm, Eric Budish
FOCM
2007
55views more  FOCM 2007»
15 years 1 months ago
On Location and Approximation of Clusters of Zeros: Case of Embedding Dimension One
Isolated multiple zeros or clusters of zeros of analytic maps with several variables are known to be difficult to locate and approximate. This article is in the vein of the α-theo...
Marc Giusti, Grégoire Lecerf, Bruno Salvy, ...