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» On Exact Learning from Random Walk
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FOCS
1994
IEEE
13 years 11 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»
13 years 2 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
13 years 10 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»
13 years 7 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»
13 years 5 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...