By Kurt Mehlhorn (auth.), Tiziana Calamoneri, Irene Finocchi, Giuseppe F. Italiano (eds.)

This booklet constitutes the refereed complaints of the sixth Italian convention on Algorithms and Computation, CIAC 2006, held in Rome, Italy, in may well 2006.

The 33 revised complete papers provided including three invited papers have been rigorously reviewed and chosen from eighty submissions. one of the themes addressed are sequential, parallel and allotted algorithms, information buildings, approximation algorithms, randomized algorithms, online algorithms, graph algorithms, research of algorithms, set of rules engineering, algorithmic video game thought, computational biology, computational complexity, verbal exchange networks, computational geometry, cryptography, discrete optimization, graph drawing, mathematical programming, and quantum algorithms.

**Read or Download Algorithms and Complexity: 6th Italian Conference, CIAC 2006, Rome, Italy, May 29-31, 2006. Proceedings PDF**

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**Extra resources for Algorithms and Complexity: 6th Italian Conference, CIAC 2006, Rome, Italy, May 29-31, 2006. Proceedings**

**Sample text**

Since ε = 1/6d, by Claim 3 we get that each rectangle is 1/3-covered by (x, y). A cover is obtained by scaling as follows. Let x (S) = 3x(S) for every S ∈ S, and y (u) = 3y(u) for every u ∈ U. Clearly, every rectangle is covered by (x , y ). Moreover, by Obs. 3 an integral y such that (x , y ) is a cover can by computed in polynomial time. It remains to show that (x , y ) is a 6d-approximation. It suﬃces to show that x (S) ≤ 6d · x(S), for every S ∈ H ∪ L∗ . If x(S) ≥ 1/3 then, x (S) ≤ 3x(S) + 1 ≤ 6x(S).

Blunck and J. Vahrenhold Computing the Repeated Median Line Estimator The repeated median line estimator is an estimator for line-ﬁtting, which is even more robust with respect to data outliers—see [14] and the references therein. The repeated median line estimator is obtained by ﬁrst computing, for each input point pi the line mi with median slope among all n − 1 lines induced by pi and another point in P \ {pi }. Among all such lines mi , the line m that realizes the line with median slope is selected as the repeated median line estimator.

Rawitz, and S. Shahar Deﬁnition 3. Let (x, y) and (x, y ) be partial covers. We say that y dominates y if (i) fy (u) ≥ fy (u), for every u ∈ U, and (ii) fy (S) ≥ fy (S), for every S ∈ S. We write y y to denote that y dominates y. Observation 4. Let (x, y) denote a partial cover. Then one can ﬁnd in polynomial time a maximum vector y with respect to x that also dominates y. Proof. We use an augmenting path algorithm to compute a maximum ﬂow f in Nx starting with fy . The ﬂow f induces the desired vector y y since saturating an augmenting path from s to t never decreases the ﬂow in edges exiting s, or in edges entering t.