3,840 research outputs found
Clustering as an example of optimizing arbitrarily chosen objective functions
This paper is a reflection upon a common practice of solving various types of learning problems by optimizing arbitrarily chosen criteria in the hope that they are well correlated with the criterion actually used for assessment of the results. This issue has been investigated using clustering as an example, hence a unified view of clustering as an optimization problem is first proposed, stemming from the belief that typical design choices in clustering, like the number of clusters or similarity measure can be, and often are suboptimal, also from the point of view of clustering quality measures later used for algorithm comparison and ranking. In order to illustrate our point we propose a generalized clustering framework and provide a proof-of-concept using standard benchmark datasets and two popular clustering methods for comparison
Proximal humeral fractures with a severe varus deformity treated by fixation with a locking plate
The Time Machine: A Simulation Approach for Stochastic Trees
In the following paper we consider a simulation technique for stochastic
trees. One of the most important areas in computational genetics is the
calculation and subsequent maximization of the likelihood function associated
to such models. This typically consists of using importance sampling (IS) and
sequential Monte Carlo (SMC) techniques. The approach proceeds by simulating
the tree, backward in time from observed data, to a most recent common ancestor
(MRCA). However, in many cases, the computational time and variance of
estimators are often too high to make standard approaches useful. In this paper
we propose to stop the simulation, subsequently yielding biased estimates of
the likelihood surface. The bias is investigated from a theoretical point of
view. Results from simulation studies are also given to investigate the balance
between loss of accuracy, saving in computing time and variance reduction.Comment: 22 Pages, 5 Figure
Statistical significance of communities in networks
Nodes in real-world networks are usually organized in local modules. These
groups, called communities, are intuitively defined as sub-graphs with a larger
density of internal connections than of external links. In this work, we
introduce a new measure aimed at quantifying the statistical significance of
single communities. Extreme and Order Statistics are used to predict the
statistics associated with individual clusters in random graphs. These
distributions allows us to define one community significance as the probability
that a generic clustering algorithm finds such a group in a random graph. The
method is successfully applied in the case of real-world networks for the
evaluation of the significance of their communities.Comment: 9 pages, 8 figures, 2 tables. The software to calculate the C-score
can be found at http://filrad.homelinux.org/cscor
Biased tomography schemes: an objective approach
We report on an intrinsic relationship between the maximum-likelihood
quantum-state estimation and the representation of the signal. A quantum
analogy of the transfer function determines the space where the reconstruction
should be done without the need for any ad hoc truncations of the Hilbert
space. An illustration of this method is provided by a simple yet practically
important tomography of an optical signal registered by realistic binary
detectors.Comment: 4 pages, 3 figures, accepted in PR
The Retail FX Trader: Random Trading and the Negative Sum Game
With the internet boom of early 2000 making access to trading the Foreign Exchange (FX) market far simpler for members of the general public, the growth of 'retail' FX trading continues, with daily transaction volumes as high as $200 billion. Potential new entrants to the retail FX trading world may come from the recent UK pension deregulations, further increasing the volumes. The attraction of FX trading is that it offers high returns and whilst it has been understood that it is high-risk in nature, the rewards are seen as being commensurately high for the 'skilled and knowledgeable' trader who has an edge over other market participants. This paper analyses a number of independent sources of data and previous research, to examine the profitability of the Retail FX trader and compares the results with that of a simulated random trading models. This paper finds evidence to suggest that whilst approximately 20% of traders can expect to end up with a profitable account, around 40% might expect their account to be subject to a margin call. This paper finds a strong correlation between the overall profitability of traders and impact of the cost of the bid-ask spread, whilst finding little if any evidence that retail FX traders, when viewed as a group, are achieving results better than that from random trading
Replicators in Fine-grained Environment: Adaptation and Polymorphism
Selection in a time-periodic environment is modeled via the two-player
replicator dynamics. For sufficiently fast environmental changes, this is
reduced to a multi-player replicator dynamics in a constant environment. The
two-player terms correspond to the time-averaged payoffs, while the three and
four-player terms arise from the adaptation of the morphs to their varying
environment. Such multi-player (adaptive) terms can induce a stable
polymorphism. The establishment of the polymorphism in partnership games
[genetic selection] is accompanied by decreasing mean fitness of the
population.Comment: 4 pages, 2 figure
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