56 research outputs found
Linear Time Runs Over General Ordered Alphabets
A run in a string is a maximal periodic substring. For example, the string
contains the runs
and . There are less than runs in any
length- string, and computing all runs for a string over a linearly-sortable
alphabet takes time (Bannai et al., SODA 2015). Kosolobov
conjectured that there also exists a linear time runs algorithm for general
ordered alphabets (Inf. Process. Lett. 2016). The conjecture was almost proven
by Crochemore et al., who presented an time algorithm
(where is the extremely slowly growing inverse Ackermann function).
We show how to achieve time by exploiting combinatorial
properties of the Lyndon array, thus proving Kosolobov's conjecture.Comment: This work has been submitted to ICALP 202
Everywhere complex sequences and the probabilistic method
The main subject of the paper is everywhere complex sequences. An everywhere complex sequence is a sequence that does not contain substrings of Kolmogorov complexity less than alpha n-O(1) where n is the length of the substring and alpha is a constant between 0 and 1.
First, we prove that no randomized algorithm can produce an everywhere complex sequence with positive probability.
On the other hand, for weaker notions of everywhere complex sequences the situation is different. For example, there is a probabilistic algorithm that produces (with probability 1) sequences whose substrings of length have complexity sqrt(n) - O(1).
Finally, one may replace the complexity of a substring (in the definition of everywhere complex sequences) by its conditional complexity when the position is given. This gives a stronger notion of everywhere complex sequence, and no randomized algorithm can produce (with positive probability) such a sequence even if alpha n is replaced by sqrt(n), log*(n) or any other monotone unbounded computable function
Visibly Pushdown Languages over Sliding Windows
We investigate the class of visibly pushdown languages in the sliding window model. A sliding window algorithm for a language L receives a stream of symbols and has to decide at each time step whether the suffix of length n belongs to L or not. The window size n is either a fixed number (in the fixed-size model) or can be controlled by an adversary in a limited way (in the variable-size model). The main result of this paper states that for every visibly pushdown language the space complexity in the variable-size sliding window model is either constant, logarithmic or linear in the window size. This extends previous results for regular languages
Lyndon Arrays in Sublinear Time
?} with ? ? n. In this case, the string can be stored in O(n log ?) bits (or O(n / log_? n) words) of memory, and reading it takes only O(n / log_? n) time. We show that O(n / log_? n) time and words of space suffice to compute the succinct 2n-bit version of the Lyndon array. The time is optimal for w = O(log n). The algorithm uses precomputed lookup tables to perform significant parts of the computation in constant time. This is possible due to properties of periodic substrings, which we carefully analyze to achieve the desired result. We envision that the algorithm has applications in the computation of runs (maximal periodic substrings), where the Lyndon array plays a central role in both theoretically and practically fast algorithms
Computing Approximate Pure Nash Equilibria in Shapley Value Weighted Congestion Games
We study the computation of approximate pure Nash equilibria in Shapley value
(SV) weighted congestion games, introduced in [19]. This class of games
considers weighted congestion games in which Shapley values are used as an
alternative (to proportional shares) for distributing the total cost of each
resource among its users. We focus on the interesting subclass of such games
with polynomial resource cost functions and present an algorithm that computes
approximate pure Nash equilibria with a polynomial number of strategy updates.
Since computing a single strategy update is hard, we apply sampling techniques
which allow us to achieve polynomial running time. The algorithm builds on the
algorithmic ideas of [7], however, to the best of our knowledge, this is the
first algorithmic result on computation of approximate equilibria using other
than proportional shares as player costs in this setting. We present a novel
relation that approximates the Shapley value of a player by her proportional
share and vice versa. As side results, we upper bound the approximate price of
anarchy of such games and significantly improve the best known factor for
computing approximate pure Nash equilibria in weighted congestion games of [7].Comment: The final publication is available at Springer via
http://dx.doi.org/10.1007/978-3-319-71924-5_1
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