We present a set of algorithms that recovers detailed building surface structures from large sets of urban images containing severe occlusions and lighting variations. An iterative weighted-average algorithm is introduced to recover high-quality consensus facade texture. 2D and 3D methods are combined to extract microstructures, facilitating urban model refinement and visualization. Keywords— t...

Consensus is the most basic agreement problem encountered in faulttolerant distributed computing: each process proposes a value and non-faulty processes must agree on the same value, which has to be one of the proposed values. While this problem is impossible to solve in asynchronous systems prone to process crash failures, it can be solved in synchronous (round-based) systems where all but one...

This paper addresses the problem of detecting Byzantine faults in linear randomized gossip algorithms, where the selection of the dynamics matrix is stochastic. A Byzantine fault is a disturbance signal injected by an attacker to corrupt the states of the nodes. We propose the use of Set-Valued Observers (SVOs) to detect if the state observations are compatible with the system dynamics for the ...

We study an n-player averaging process with dynamics subject to controls and adversarial disturbances. The model arises in two distinct application domains: i) coalitional games with transferable utilities (TU) and ii) opinion propagation. We study conditions under which the average allocations achieve robust consensus to some predefined target set.

This work analyzes distributed linear averaging within a connected network of sensors that each track the stationary distribution of an ergodic Markov chain with a slowly switching regime. Our approach is based on a two-time-scale stochastic approximation. A hyperparameter modeled as a Markov chain on a slower time-scale modulates the regime of each observed Markov chain. The average of all cur...

This paper models the incentives created by career concerns for opinion-producing agents. We ...nd that career concerns can create an incentive for exaggeration or anti-herding, since high-ability agents will have opinions that are more di¤erent from the consensus on average and potential clients will learn more quickly about how di¤erent an agent’s opinions are from the consensus on average th...

The purpose of this paper is to use Bahadur’s asymptotic relative efficiency measure to compare the performance of various tests of autoregressive (AR) versus moving average (MA) error processes in regression models. Tests to be examined include non-nested procedures of the models against each other, and classical procedures based upon testing both the AR and MA error processes against the more...

We compare the consensus problem with the uniform consensus problem in synchronous systems. In contrast to consensus, uniform consensus is not solvable in synchronous systems with byzantine failures. This still holds for the omission failure model if a majority of processes may be faulty. For the crash failure model, both consensus and uniform consensus are solvable, no matter how many processe...

Average consensus develops with multi-agent systems where consensus is a vital aspect in coordination and cooperation [5]. It is a linear iteration scheme where each node updates its value as a linear weighted combination of the values received from neighbors and its own. Consensus can be guaranteed by appropriately designing the weights used in the linear schemes. However, the characteristics ...

Average consensus develops with multi-agent systems where consensus is a vital aspect in coordination and cooperation [5]. It is a linear iteration scheme where each node updates its value as a linear weighted combination of the values received from neighbors and its own. Consensus can be guaranteed by appropriately designing the weights used in the linear schemes. However, the characteristics ...