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SIGMOD
2002
ACM
246views Database» more  SIGMOD 2002»
14 years 10 months ago
Hierarchical subspace sampling: a unified framework for high dimensional data reduction, selectivity estimation and nearest neig
With the increased abilities for automated data collection made possible by modern technology, the typical sizes of data collections have continued to grow in recent years. In suc...
Charu C. Aggarwal
HYBRID
2009
Springer
14 years 4 months ago
Computation of Discrete Abstractions of Arbitrary Memory Span for Nonlinear Sampled Systems
ion of discrete abstractions of arbitrary memory span for nonlinear sampled systems Gunther Reißig⋆ Technische Universit¨at Berlin, Fakult¨at Elektrotechnik und Informatik, He...
Gunther Reißig
ICRA
2007
IEEE
160views Robotics» more  ICRA 2007»
14 years 4 months ago
Adaptive Sampling for Multi-Robot Wide-Area Exploration
— The exploration problem is a central issue in mobile robotics. A complete coverage is not practical if the environment is large with a few small hotspots, and the sampling cost...
Kian Hsiang Low, Geoffrey J. Gordon, John M. Dolan...
COLT
2000
Springer
14 years 2 months ago
On the Convergence Rate of Good-Turing Estimators
Good-Turing adjustments of word frequencies are an important tool in natural language modeling. In particular, for any sample of words, there is a set of words not occuring in tha...
David A. McAllester, Robert E. Schapire
ACL
1994
13 years 11 months ago
A Markov Language Learning Model for Finite Parameter Spaces
This paper shows how to formally characterize language learning in a finite parameter space as a Markov structure, hnportant new language learning results follow directly: explici...
Partha Niyogi, Robert C. Berwick