20,358 research outputs found
New development: Directly elected mayors in Italy: creating a strong leader doesn’t mean creating strong leadership
More than 20 years after their introduction, directly elected mayors are key players in Italian urban governance. This article explains the main effects of this reform on local government systems and provides lessons for other countries considering directly elected mayors
Existence of equilibria in countable games: an algebraic approach
Although mixed extensions of finite games always admit equilibria, this is
not the case for countable games, the best-known example being Wald's
pick-the-larger-integer game. Several authors have provided conditions for the
existence of equilibria in infinite games. These conditions are typically of
topological nature and are rarely applicable to countable games. Here we
establish an existence result for the equilibrium of countable games when the
strategy sets are a countable group and the payoffs are functions of the group
operation. In order to obtain the existence of equilibria, finitely additive
mixed strategies have to be allowed. This creates a problem of selection of a
product measure of mixed strategies. We propose a family of such selections and
prove existence of an equilibrium that does not depend on the selection. As a
byproduct we show that if finitely additive mixed strategies are allowed, then
Wald's game admits an equilibrium. We also prove existence of equilibria for
nontrivial extensions of matching-pennies and rock-scissors-paper. Finally we
extend the main results to uncountable games
Computing LZ77 in Run-Compressed Space
In this paper, we show that the LZ77 factorization of a text T {\in\Sigma^n}
can be computed in O(R log n) bits of working space and O(n log R) time, R
being the number of runs in the Burrows-Wheeler transform of T reversed. For
extremely repetitive inputs, the working space can be as low as O(log n) bits:
exponentially smaller than the text itself. As a direct consequence of our
result, we show that a class of repetition-aware self-indexes based on a
combination of run-length encoded BWT and LZ77 can be built in asymptotically
optimal O(R + z) words of working space, z being the size of the LZ77 parsing
Fully-Functional Suffix Trees and Optimal Text Searching in BWT-runs Bounded Space
Indexing highly repetitive texts - such as genomic databases, software
repositories and versioned text collections - has become an important problem
since the turn of the millennium. A relevant compressibility measure for
repetitive texts is r, the number of runs in their Burrows-Wheeler Transforms
(BWTs). One of the earliest indexes for repetitive collections, the Run-Length
FM-index, used O(r) space and was able to efficiently count the number of
occurrences of a pattern of length m in the text (in loglogarithmic time per
pattern symbol, with current techniques). However, it was unable to locate the
positions of those occurrences efficiently within a space bounded in terms of
r. In this paper we close this long-standing problem, showing how to extend the
Run-Length FM-index so that it can locate the occ occurrences efficiently
within O(r) space (in loglogarithmic time each), and reaching optimal time, O(m
+ occ), within O(r log log w ({\sigma} + n/r)) space, for a text of length n
over an alphabet of size {\sigma} on a RAM machine with words of w =
{\Omega}(log n) bits. Within that space, our index can also count in optimal
time, O(m). Multiplying the space by O(w/ log {\sigma}), we support count and
locate in O(dm log({\sigma})/we) and O(dm log({\sigma})/we + occ) time, which
is optimal in the packed setting and had not been obtained before in compressed
space. We also describe a structure using O(r log(n/r)) space that replaces the
text and extracts any text substring of length ` in almost-optimal time
O(log(n/r) + ` log({\sigma})/w). Within that space, we similarly provide direct
access to suffix array, inverse suffix array, and longest common prefix array
cells, and extend these capabilities to full suffix tree functionality,
typically in O(log(n/r)) time per operation.Comment: submitted version; optimal count and locate in smaller space: O(r log
log_w(n/r + sigma)
Optimal control of continuous-time Markov chains with noise-free observation
We consider an infinite horizon optimal control problem for a continuous-time
Markov chain in a finite set with noise-free partial observation. The
observation process is defined as , , where is a
given map defined on . The observation is noise-free in the sense that the
only source of randomness is the process itself. The aim is to minimize a
discounted cost functional and study the associated value function . After
transforming the control problem with partial observation into one with
complete observation (the separated problem) using filtering equations, we
provide a link between the value function associated to the latter control
problem and the original value function . Then, we present two different
characterizations of (and indirectly of ): on one hand as the unique
fixed point of a suitably defined contraction mapping and on the other hand as
the unique constrained viscosity solution (in the sense of Soner) of a HJB
integro-differential equation. Under suitable assumptions, we finally prove the
existence of an optimal control
Path-dependent equations and viscosity solutions in infinite dimension
Path-dependent PDEs (PPDEs) are natural objects to study when one deals with
non Markovian models. Recently, after the introduction of the so-called
pathwise (or functional or Dupire) calculus (see [15]), in the case of
finite-dimensional underlying space various papers have been devoted to
studying the well-posedness of such kind of equations, both from the point of
view of regular solutions (see e.g. [15, 9]) and viscosity solutions (see e.g.
[16]). In this paper, motivated by the study of models driven by path-dependent
stochastic PDEs, we give a first well-posedness result for viscosity solutions
of PPDEs when the underlying space is a separable Hilbert space. We also
observe that, in contrast with the finite-dimensional case, our well-posedness
result, even in the Markovian case, applies to equations which cannot be
treated, up to now, with the known theory of viscosity solutions.Comment: To appear in the Annals of Probabilit
On data skewness, stragglers, and MapReduce progress indicators
We tackle the problem of predicting the performance of MapReduce
applications, designing accurate progress indicators that keep programmers
informed on the percentage of completed computation time during the execution
of a job. Through extensive experiments, we show that state-of-the-art progress
indicators (including the one provided by Hadoop) can be seriously harmed by
data skewness, load unbalancing, and straggling tasks. This is mainly due to
their implicit assumption that the running time depends linearly on the input
size. We thus design a novel profile-guided progress indicator, called
NearestFit, that operates without the linear hypothesis assumption and exploits
a careful combination of nearest neighbor regression and statistical curve
fitting techniques. Our theoretical progress model requires fine-grained
profile data, that can be very difficult to manage in practice. To overcome
this issue, we resort to computing accurate approximations for some of the
quantities used in our model through space- and time-efficient data streaming
algorithms. We implemented NearestFit on top of Hadoop 2.6.0. An extensive
empirical assessment over the Amazon EC2 platform on a variety of real-world
benchmarks shows that NearestFit is practical w.r.t. space and time overheads
and that its accuracy is generally very good, even in scenarios where
competitors incur non-negligible errors and wide prediction fluctuations.
Overall, NearestFit significantly improves the current state-of-art on progress
analysis for MapReduce
Implementing international monetary cooperation through inflation targeting
This paper presents a two-country dynamic general equilibrium model with imperfect competition and nominal price rigidities in which productivity shocks coexist with markup shocks. After analyzing the features of the optimal cooperative solution, we show that this allocation can be implemented in a strategic context through inflation-targeting regimes. Under these regimes, each monetary authority minimizes a quadratic loss function that targets only domestic targets, namely, GDP inflation and the output gap
Paying Positive to Go Negative: Advertisers' Competition and Media Reports
This paper analyzes a two-sided market for news where advertisers may pay a media outlet to conceal negative information about the quality of their own product (paying positive to avoid negative) and/or to disclose negative information about the quality of their competitors' products (paying positive to go negative). We show that whether advertisers have negative consequences on the accuracy of news reports or not ultimately depends on the extent of correlation among advertisers' products.
Specifically, the lower the correlation among the qualities of the advertisers' products, the (weakly) higher the accuracy of the media outlet' reports. Moreover, when advertisers' products are correlated, a higher degree of competition in the market of the advertisers' products may decrease the accuracy of the media outlet's reports
Succinct Partial Sums and Fenwick Trees
We consider the well-studied partial sums problem in succint space where one
is to maintain an array of n k-bit integers subject to updates such that
partial sums queries can be efficiently answered. We present two succint
versions of the Fenwick Tree - which is known for its simplicity and
practicality. Our results hold in the encoding model where one is allowed to
reuse the space from the input data. Our main result is the first that only
requires nk + o(n) bits of space while still supporting sum/update in O(log_b
n) / O(b log_b n) time where 2 <= b <= log^O(1) n. The second result shows how
optimal time for sum/update can be achieved while only slightly increasing the
space usage to nk + o(nk) bits. Beyond Fenwick Trees, the results are primarily
based on bit-packing and sampling - making them very practical - and they also
allow for simple optimal parallelization
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