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IJRR
2011
126views more  IJRR 2011»
13 years 2 months ago
Optimization and learning for rough terrain legged locomotion
We present a novel approach to legged locomotion over rough terrain that is thoroughly rooted in optimization. This approach relies on a hierarchy of fast, anytime algorithms to p...
Matthew Zucker, Nathan D. Ratliff, Martin Stolle, ...
IROS
2009
IEEE
150views Robotics» more  IROS 2009»
14 years 2 months ago
Learning locomotion over rough terrain using terrain templates
— We address the problem of foothold selection in robotic legged locomotion over very rough terrain. The difficulty of the problem we address here is comparable to that of human...
Mrinal Kalakrishnan, Jonas Buchli, Peter Pastor, S...
FOCS
2009
IEEE
14 years 2 months ago
Constructing Small-Bias Sets from Algebraic-Geometric Codes
We give an explicit construction of an -biased set over k bits of size O k 2 log(1/ ) 5/4 . This improves upon previous explicit constructions when is roughly (ignoring logarith
Avraham Ben-Aroya, Amnon Ta-Shma
RSCTC
2004
Springer
110views Fuzzy Logic» more  RSCTC 2004»
14 years 1 months ago
A Graded Applicability of Rules
We address the problem of rough applicability of rules within the framework of approximation spaces. The graded applicability of a rule for an object of an approximation space, int...
Anna Gomolinska
SIGMOD
2004
ACM
144views Database» more  SIGMOD 2004»
14 years 7 months ago
Diamond in the Rough: Finding Hierarchical Heavy Hitters in Multi-Dimensional Data
Data items archived in data warehouses or those that arrive online as streams typically have attributes which take values from multiple hierarchies (e.g., time and geographic loca...
Graham Cormode, Flip Korn, S. Muthukrishnan, Dives...