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» On Exact Learning from Random Walk
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FOCS
1994
IEEE
15 years 3 months ago
The Power of Team Exploration: Two Robots Can Learn Unlabeled Directed Graphs
We show that two cooperating robots can learn exactly any strongly-connected directed graph with n indistinguishable nodes in expected time polynomial in n. We introduce a new typ...
Michael A. Bender, Donna K. Slonim
JSAC
2010
188views more  JSAC 2010»
14 years 6 months ago
Random-walk based approach to detect clone attacks in wireless sensor networks
Abstract--Wireless sensor networks (WSNs) deployed in hostile environments are vulnerable to clone attacks. In such attack, an adversary compromises a few nodes, replicates them, a...
Yingpei Zeng, Jiannong Cao, Shigeng Zhang, Shanqin...

Publication
252views
15 years 2 months ago
Context models on sequences of covers
We present a class of models that, via a simple construction, enables exact, incremental, non-parametric, polynomial-time, Bayesian inference of conditional measures. The approac...
Christos Dimitrakakis
CORR
2006
Springer
151views Education» more  CORR 2006»
14 years 11 months ago
Graph Laplacians and their convergence on random neighborhood graphs
Given a sample from a probability measure with support on a submanifold in Euclidean space one can construct a neighborhood graph which can be seen as an approximation of the subm...
Matthias Hein, Jean-Yves Audibert, Ulrike von Luxb...
INFORMS
2010
125views more  INFORMS 2010»
14 years 10 months ago
Combining Exact and Heuristic Approaches for the Capacitated Fixed-Charge Network Flow Problem
We develop a solution approach for the fixed charge network flow problem (FCNF) that produces provably high-quality solutions quickly. The solution approach combines mathematica...
Mike Hewitt, George L. Nemhauser, Martin W. P. Sav...