
New Lower Bounds for the Number of Pseudoline Arrangements
Arrangements of lines and pseudolines are fundamental objects in discret...
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Finding a Mediocre Player
Consider a totally ordered set S of n elements; as an example, a set of ...
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Contention Resolution with Predictions
In this paper, we consider contention resolution algorithms that are aug...
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Strategies for Stable Merge Sorting
We introduce new stable, natural merge sort algorithms, called 2merge s...
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InstanceOptimality in the Noisy Valueand ComparisonModel  Accept, Accept, Strong Accept: Which Papers get in?
Motivated by crowdsourced computation, peergrading, and recommendation ...
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All Classical Adversary Methods are Equivalent for Total Functions
We show that all known classical adversary lower bounds on randomized qu...
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Fragile Complexity of Adaptive Algorithms
The fragile complexity of a comparisonbased algorithm is f(n) if each i...
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Fragile Complexity of ComparisonBased Algorithms
We initiate a study of algorithms with a focus on the computational complexity of individual elements, and introduce the fragile complexity of comparisonbased algorithms as the maximal number of comparisons any individual element takes part in. We give a number of upper and lower bounds on the fragile complexity for fundamental problems, including Minimum, Selection, Sorting and Heap Construction. The results include both deterministic and randomized upper and lower bounds, and demonstrate a separation between the two settings for a number of problems. The depth of a comparator network is a straightforward upper bound on the worst case fragile complexity of the corresponding fragile algorithm. We prove that fragile complexity is a different and strictly easier property than the depth of comparator networks, in the sense that for some problems a fragile complexity equal to the best network depth can be achieved with less total work and that with randomization, even a lower fragile complexity is possible.
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