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1109.3688
|
Artificial Skin Ridges Enhance Local Tactile Shape Discrimination
|
physics.med-ph cs.RO physics.ins-det
|
One of the fundamental requirements for an artificial hand to successfully
grasp and manipulate an object is to be able to distinguish different objects'
shapes and, more specifically, the objects' surface curvatures. In this study,
we investigate the possibility of enhancing the curvature detection of embedded
tactile sensors by proposing a ridged fingertip structure, simulating human
fingerprints. In addition, a curvature detection approach based on machine
learning methods is proposed to provide the embedded sensors with the ability
to discriminate the surface curvature of different objects. For this purpose, a
set of experiments were carried out to collect tactile signals from a 2 \times
2 tactile sensor array, then the signals were processed and used for learning
algorithms. To achieve the best possible performance for our machine learning
approach, three different learning algorithms of Na\"ive Bayes (NB), Artificial
Neural Networks (ANN), and Support Vector Machines (SVM) were implemented and
compared for various parameters. Finally, the most accurate method was selected
to evaluate the proposed skin structure in recognition of three different
curvatures. The results showed an accuracy rate of 97.5% in surface curvature
discrimination.
|
1109.3700
|
Contradiction measures and specificity degrees of basic belief
assignments
|
cs.AI
|
In the theory of belief functions, many measures of uncertainty have been
introduced. However, it is not always easy to understand what these measures
really try to represent. In this paper, we re-interpret some measures of
uncertainty in the theory of belief functions. We present some interests and
drawbacks of the existing measures. On these observations, we introduce a
measure of contradiction. Therefore, we present some degrees of non-specificity
and Bayesianity of a mass. We propose a degree of specificity based on the
distance between a mass and its most specific associated mass. We also show how
to use the degree of specificity to measure the specificity of a fusion rule.
Illustrations on simple examples are given.
|
1109.3701
|
Active Ranking using Pairwise Comparisons
|
cs.LG cs.IT math.IT stat.ML
|
This paper examines the problem of ranking a collection of objects using
pairwise comparisons (rankings of two objects). In general, the ranking of $n$
objects can be identified by standard sorting methods using $n log_2 n$
pairwise comparisons. We are interested in natural situations in which
relationships among the objects may allow for ranking using far fewer pairwise
comparisons. Specifically, we assume that the objects can be embedded into a
$d$-dimensional Euclidean space and that the rankings reflect their relative
distances from a common reference point in $R^d$. We show that under this
assumption the number of possible rankings grows like $n^{2d}$ and demonstrate
an algorithm that can identify a randomly selected ranking using just slightly
more than $d log n$ adaptively selected pairwise comparisons, on average. If
instead the comparisons are chosen at random, then almost all pairwise
comparisons must be made in order to identify any ranking. In addition, we
propose a robust, error-tolerant algorithm that only requires that the pairwise
comparisons are probably correct. Experimental studies with synthetic and real
datasets support the conclusions of our theoretical analysis.
|
1109.3702
|
Agent-Based Modeling of Intracellular Transport
|
q-bio.SC cs.MA nlin.PS
|
We develop an agent-based model of the motion and pattern formation of
vesicles. These intracellular particles can be found in four different modes of
(undirected and directed) motion and can fuse with other vesicles. While the
size of vesicles follows a log-normal distribution that changes over time due
to fusion processes, their spatial distribution gives rise to distinct
patterns. Their occurrence depends on the concentration of proteins which are
synthesized based on the transcriptional activities of some genes. Hence,
differences in these spatio-temporal vesicle patterns allow indirect
conclusions about the (unknown) impact of these genes.
By means of agent-based computer simulations we are able to reproduce such
patterns on real temporal and spatial scales. Our modeling approach is based on
Brownian agents with an internal degree of freedom, $\theta$, that represents
the different modes of motion. Conditions inside the cell are modeled by an
effective potential that differs for agents dependent on their value $\theta$.
Agent's motion in this effective potential is modeled by an overdampted
Langevin equation, changes of $\theta$ are modeled as stochastic transitions
with values obtained from experiments, and fusion events are modeled as
space-dependent stochastic transitions. Our results for the spatio-temporal
vesicle patterns can be used for a statistical comparison with experiments. We
also derive hypotheses of how the silencing of some genes may affect the
intracellular transport, and point to generalizations of the model.
|
1109.3714
|
High-dimensional regression with noisy and missing data: Provable
guarantees with nonconvexity
|
math.ST cs.IT math.IT stat.ML stat.TH
|
Although the standard formulations of prediction problems involve
fully-observed and noiseless data drawn in an i.i.d. manner, many applications
involve noisy and/or missing data, possibly involving dependence, as well. We
study these issues in the context of high-dimensional sparse linear regression,
and propose novel estimators for the cases of noisy, missing and/or dependent
data. Many standard approaches to noisy or missing data, such as those using
the EM algorithm, lead to optimization problems that are inherently nonconvex,
and it is difficult to establish theoretical guarantees on practical
algorithms. While our approach also involves optimizing nonconvex programs, we
are able to both analyze the statistical error associated with any global
optimum, and more surprisingly, to prove that a simple algorithm based on
projected gradient descent will converge in polynomial time to a small
neighborhood of the set of all global minimizers. On the statistical side, we
provide nonasymptotic bounds that hold with high probability for the cases of
noisy, missing and/or dependent data. On the computational side, we prove that
under the same types of conditions required for statistical consistency, the
projected gradient descent algorithm is guaranteed to converge at a geometric
rate to a near-global minimizer. We illustrate these theoretical predictions
with simulations, showing close agreement with the predicted scalings.
|
1109.3737
|
Learning where to Attend with Deep Architectures for Image Tracking
|
cs.AI
|
We discuss an attentional model for simultaneous object tracking and
recognition that is driven by gaze data. Motivated by theories of perception,
the model consists of two interacting pathways: identity and control, intended
to mirror the what and where pathways in neuroscience models. The identity
pathway models object appearance and performs classification using deep
(factored)-Restricted Boltzmann Machines. At each point in time the
observations consist of foveated images, with decaying resolution toward the
periphery of the gaze. The control pathway models the location, orientation,
scale and speed of the attended object. The posterior distribution of these
states is estimated with particle filtering. Deeper in the control pathway, we
encounter an attentional mechanism that learns to select gazes so as to
minimize tracking uncertainty. Unlike in our previous work, we introduce gaze
selection strategies which operate in the presence of partial information and
on a continuous action space. We show that a straightforward extension of the
existing approach to the partial information setting results in poor
performance, and we propose an alternative method based on modeling the reward
surface as a Gaussian Process. This approach gives good performance in the
presence of partial information and allows us to expand the action space from a
small, discrete set of fixation points to a continuous domain.
|
1109.3745
|
A KdV-like advection-dispersion equation with some remarkable properties
|
nlin.PS cs.NE math.AP physics.flu-dyn
|
We discuss a new non-linear PDE, u_t + (2 u_xx/u) u_x = epsilon u_xxx,
invariant under scaling of dependent variable and referred to here as SIdV. It
is one of the simplest such translation and space-time reflection-symmetric
first order advection-dispersion equations. This PDE (with dispersion
coefficient unity) was discovered in a genetic programming search for equations
sharing the KdV solitary wave solution. It provides a bridge between non-linear
advection, diffusion and dispersion. Special cases include the mKdV and linear
dispersive equations. We identify two conservation laws, though initial
investigations indicate that SIdV does not follow from a polynomial Lagrangian
of the KdV sort. Nevertheless, it possesses solitary and periodic travelling
waves. Moreover, numerical simulations reveal recurrence properties usually
associated with integrable systems. KdV and SIdV are the simplest in an
infinite dimensional family of equations sharing the KdV solitary wave. SIdV
and its generalizations may serve as a testing ground for numerical and
analytical techniques and be a rich source for further explorations.
|
1109.3765
|
New Principles of Coordination in Large-scale Micro- and
Molecular-Robotic Groups
|
cs.RO
|
Micro- and molecular-robotic systems act as large-scale swarms. Capabilities
of sensing, communication and information processing are very limited on these
scales. This short position paper describes a swarm-based minimalistic
approach, which can be applied for coordinating collective behavior in such
systems.
|
1109.3767
|
Generalised Object Detection and Semantic Analysis: Casino Example using
Matlab
|
cs.CV
|
Matlab version 7.1 had been used to detect playing cards on a Casino table
and the suits and ranks of these cards had been identified. The process gives
an example of an application of computer vision to a problem where rectangular
objects are to be detected and the information content of the objects are
extracted out. In the case of playing cards, it is the suit and rank of each
card. The image processing system is done in two passes. Pass 1 detects
rectangular shapes and template matched with a template of the left and right
edges of the cards. Pass 2 extracts the suit and rank of the cards by matching
the top left portion of the card that contains both rank and suit information,
with stored templates of ranks and suits of the playing cards using a series of
if-then statements.
|
1109.3772
|
A numerical solution to the minimum-time control problem for linear
discrete-time systems
|
cs.SY math.OC
|
The minimum-time control problem consists in finding a control policy that
will drive a given dynamic system from a given initial state to a given target
state (or a set of states) as quickly as possible. This is a well-known
challenging problem in optimal control theory for which closed-form solutions
exist only for a few systems of small dimensions. This paper presents a very
generic solution to the minimum-time problem for arbitrary discrete-time linear
systems. It is a numerical solution based on sparse optimization, that is the
minimization of the number of nonzero elements in the state sequence over a
fixed control horizon. We consider both single input and multiple inputs
systems. An important observation is that, contrary to the continuous-time
case, the minimum-time control for discrete-time systems is not necessarily
entirely bang-bang.
|
1109.3781
|
Distributed Robust Control of Linear Multi-Agent Systems with Parameter
Uncertainties
|
cs.SY math.OC
|
This paper considers the distributed robust control problems of uncertain
linear multi-agent systems with undirected communication topologies. It is
assumed that the agents have identical nominal dynamics while subject to
different norm-bounded parameter uncertainties, leading to weakly heterogeneous
multi-agent systems. Distributed controllers are designed for both continuous-
and discrete-time multi-agent systems, based on the relative states of
neighboring agents and a subset of absolute states of the agents. It is shown
for both the continuous- and discrete-time cases that the distributed robust
control problems under such controllers in the sense of quadratic stability are
equivalent to the $H_\infty$ control problems of a set of decoupled linear
systems having the same dimensions as a single agent. A two-step algorithm is
presented to construct the distributed controller for the continuous-time case,
which does not involve any conservatism and meanwhile decouples the feedback
gain design from the communication topology. Furthermore, a sufficient
existence condition in terms of linear matrix inequalities is derived for the
distributed discrete-time controller. Finally, the distributed robust
$H_\infty$ control problems of uncertain linear multi-agent systems subject to
external disturbances are discussed.
|
1109.3782
|
Robust Topology Optimization of Truss with regard to Volume
|
math.OC cs.SY
|
A common problem in the optimization of structures is the handling of
uncertainties in the parameters. If the parameters appear in the constraints,
the uncertainties can lead to an infinite number of constraints. Usually the
constraints have to be approximated by finite expressions to generate a
computable problem. Here, using the example of the topology optimization of a
truss, a method is proposed to deal with such uncertainties by using robust
optimization techniques, leading to an approach without the necessity of any
approximation. With adequately chosen load cases, the final expression is
equivalent to the multiple load case. Simple numerical examples of typical
problems illustrate the application of the method.
|
1109.3791
|
WebCloud: Recruiting web browsers for content distribution
|
cs.SI
|
We are at the beginning of a shift in how content is created and exchanged
over the web. While content was previously created primarily by a small set of
entities, today, individual users -- empowered by devices like digital cameras
and services like online social networks -- are creating content that
represents a significant fraction of Internet traffic. As a result, content
today is increasingly generated and exchanged at the edge of the network.
Unfortunately, the existing techniques and infrastructure that are still used
to serve this content, such as centralized content distribution networks, are
ill-suited for these new patterns of content exchange. In this paper, we take a
first step towards addressing this situation by introducing WebCloud, a content
distribution system for online social networking sites that works by re-
purposing web browsers to help serve content. In other words, when a user
browses content, WebCloud tries to fetch it from one of that user's friend's
browsers, instead of from the social networking site. The result is a more
direct exchange of content ; essentially, WebCloud leverages the spatial and
temporal locality of interest between social network users. Because WebCloud is
built using techniques already present in many web browsers, it can be applied
today to many social networking sites. We demonstrate the practicality of
WebCloud with microbenchmarks, simulations, and a prototype deployment.
|
1109.3798
|
Charge-Balanced Minimum-Power Controls for Spiking Neuron Oscillators
|
math.OC cs.SY math.DS q-bio.NC
|
In this paper, we study the optimal control of phase models for spiking
neuron oscillators. We focus on the design of minimum-power current stimuli
that elicit spikes in neurons at desired times. We furthermore take the
charge-balanced constraint into account because in practice undesirable side
effects may occur due to the accumulation of electric charge resulting from
external stimuli. Charge-balanced minimum-power controls are derived for a
general phase model using the maximum principle, where the cases with unbounded
and bounded control amplitude are examined. The latter is of practical
importance since phase models are more accurate for weak forcing. The developed
optimal control strategies are then applied to both mathematically ideal and
experimentally observed phase models to demonstrate their applicability,
including the phase model for the widely studied Hodgkin-Huxley equations.
|
1109.3799
|
Consensus of Multi-Agent Systems with General Linear and Lipschitz
Nonlinear Dynamics Using Distributed Adaptive Protocols
|
cs.SY math.OC
|
This paper considers the distributed consensus problems for multi-agent
systems with general linear and Lipschitz nonlinear dynamics. Distributed
relative-state consensus protocols with an adaptive law for adjusting the
coupling weights between neighboring agents are designed for both the linear
and nonlinear cases, under which consensus is reached for all undirected
connected communication graphs. Extensions to the case with a leader-follower
communication graph are further studied. In contrast to the existing results in
the literature, the adaptive consensus protocols here can be implemented by
each agent in a fully distributed fashion without using any global information.
|
1109.3800
|
MacWilliams type identities for some new $m$-spotty weight enumerators
|
cs.IT math.IT
|
Past few years have seen an extensive use of high-density RAM chips with wide
I/O data (e.g., 16, 32, 64 bits) in computer memory systems. These chips are
highly vulnerable to a special type of byte error, called an $m$-spotty byte
error, which can be effectively detected or corrected using byte error-control
codes. In this paper, we present joint $m$-spotty weight enumerator and split
$m$-spotty weight enumerator for byte error-control codes over the ring of
integers modulo $\ell$ ($\ell \geq 2$ is an integer) and over arbitrary finite
fields. We also derive MacWilliams type identities for each of the
aforementioned enumerators and discuss some of their applications.
|
1109.3804
|
Quantum Hypothesis Testing and Non-Equilibrium Statistical Mechanics
|
math-ph cs.IT math.IT math.MP quant-ph
|
We extend the mathematical theory of quantum hypothesis testing to the
general $W^*$-algebraic setting and explore its relation with recent
developments in non-equilibrium quantum statistical mechanics. In particular,
we relate the large deviation principle for the full counting statistics of
entropy flow to quantum hypothesis testing of the arrow of time.
|
1109.3827
|
Online Robust Subspace Tracking from Partial Information
|
cs.IT cs.CV cs.SY math.IT math.OC stat.ML
|
This paper presents GRASTA (Grassmannian Robust Adaptive Subspace Tracking
Algorithm), an efficient and robust online algorithm for tracking subspaces
from highly incomplete information. The algorithm uses a robust $l^1$-norm cost
function in order to estimate and track non-stationary subspaces when the
streaming data vectors are corrupted with outliers. We apply GRASTA to the
problems of robust matrix completion and real-time separation of background
from foreground in video. In this second application, we show that GRASTA
performs high-quality separation of moving objects from background at
exceptional speeds: In one popular benchmark video example, GRASTA achieves a
rate of 57 frames per second, even when run in MATLAB on a personal laptop.
|
1109.3838
|
Distributed Consensus of Linear Multi-Agent Systems with Adaptive
Dynamic Protocols
|
cs.SY math.OC
|
This paper considers the distributed consensus problem of multi-agent systems
with general continuous-time linear dynamics. Two distributed adaptive dynamic
consensus protocols are proposed, based on the relative output information of
neighboring agents. One protocol assigns an adaptive coupling weight to each
edge in the communication graph while the other uses an adaptive coupling
weight for each node. These two adaptive protocols are designed to ensure that
consensus is reached in a fully distributed fashion for any undirected
connected communication graphs without using any global information. A
sufficient condition for the existence of these adaptive protocols is that each
agent is stabilizable and detectable. The cases with leader-follower and
switching communication graphs are also studied.
|
1109.3841
|
Limits on the Benefits of Energy Storage for Renewable Integration
|
math.OC cs.SY
|
The high variability of renewable energy resources presents significant
challenges to the operation of the electric power grid. Conventional generators
can be used to mitigate this variability but are costly to operate and produce
carbon emissions. Energy storage provides a more environmentally friendly
alternative, but is costly to deploy in large amounts. This paper studies the
limits on the benefits of energy storage to renewable energy: How effective is
storage at mitigating the adverse effects of renewable energy variability? How
much storage is needed? What are the optimal control policies for operating
storage? To provide answers to these questions, we first formulate the power
flow in a single-bus power system with storage as an infinite horizon
stochastic program. We find the optimal policies for arbitrary net renewable
generation process when the cost function is the average conventional
generation (environmental cost) and when it is the average loss of load
probability (reliability cost). We obtain more refined results by considering
the multi-timescale operation of the power system. We view the power flow in
each timescale as the superposition of a predicted (deterministic) component
and an prediction error (residual) component and formulate the residual power
flow problem as an infinite horizon dynamic program. Assuming that the net
generation prediction error is an IID process, we quantify the asymptotic
benefits of storage. With the additional assumption of Laplace distributed
prediction error, we obtain closed form expressions for the stationary
distribution of storage and conventional generation. Finally, we propose a
two-threshold policy that trades off conventional generation saving with loss
of load probability. We illustrate our results and corroborate the IID and
Laplace assumptions numerically using datasets from CAISO and NREL.
|
1109.3843
|
Fast approximation of matrix coherence and statistical leverage
|
cs.DS cs.DM cs.LG
|
The statistical leverage scores of a matrix $A$ are the squared row-norms of
the matrix containing its (top) left singular vectors and the coherence is the
largest leverage score. These quantities are of interest in recently-popular
problems such as matrix completion and Nystr\"{o}m-based low-rank matrix
approximation as well as in large-scale statistical data analysis applications
more generally; moreover, they are of interest since they define the key
structural nonuniformity that must be dealt with in developing fast randomized
matrix algorithms. Our main result is a randomized algorithm that takes as
input an arbitrary $n \times d$ matrix $A$, with $n \gg d$, and that returns as
output relative-error approximations to all $n$ of the statistical leverage
scores. The proposed algorithm runs (under assumptions on the precise values of
$n$ and $d$) in $O(n d \log n)$ time, as opposed to the $O(nd^2)$ time required
by the na\"{i}ve algorithm that involves computing an orthogonal basis for the
range of $A$. Our analysis may be viewed in terms of computing a relative-error
approximation to an underconstrained least-squares approximation problem, or,
relatedly, it may be viewed as an application of Johnson-Lindenstrauss type
ideas. Several practically-important extensions of our basic result are also
described, including the approximation of so-called cross-leverage scores, the
extension of these ideas to matrices with $n \approx d$, and the extension to
streaming environments.
|
1109.3850
|
Digital (co)homology modules and digital Pontryagin algebras
|
cs.CV
|
In the current study, we explore digital homology and cohomology modules, and
investigate their fundamental properties on pointed digital images. We also
examine pointed digital Hopf spaces and base point preserving digital Hopf
functions between the pointed digital Hopf spaces with suitable digital
multiplications, and explore the digital primitive homology and cohomology
classes, the digital Pontryagin algebras and coalgebras on the digital Hopf
spaces as digital images.
|
1109.3863
|
An observability for parabolic equations from a measurable set in time
|
math.AP cs.SY math.OC
|
This paper presents a new observability estimate for parabolic equations in
$\Omega\times(0,T)$, where $\Omega$ is a convex domain. The observation region
is restricted over a product set of an open nonempty subset of $\Omega$ and a
subset of positive measure in $(0,T)$. This estimate is derived with the aid of
a quantitative unique continuation at one point in time. Applications to the
bang-bang property for norm and time optimal control problems are provided.
|
1109.3876
|
Two-Dimensional Tail-Biting Convolutional Codes
|
cs.IT math.IT
|
The multidimensional convolutional codes are an extension of the notion of
convolutional codes (CCs) to several dimensions of time. This paper explores
the class of two-dimensional convolutional codes (2D CCs) and 2D tail-biting
convolutional codes (2D TBCCs), in particular, from several aspects. First, we
derive several basic algebraic properties of these codes, applying algebraic
methods in order to find bijective encoders, create parity check matrices and
to inverse encoders. Next, we discuss the minimum distance and weight
distribution properties of these codes. Extending an existing tree-search
algorithm to two dimensions, we apply it to find codes with high minimum
distance. Word-error probability asymptotes for sample codes are given and
compared with other codes. The results of this approach suggest that 2D TBCCs
can perform better than comparable 1D TBCCs or other codes. We then present
several novel iterative suboptimal algorithms for soft decoding 2D CCs, which
are based on belief propagation. Two main approaches to decoding are
considered. We first focus on a decoder which extends the concept of trellis
decoding to two dimensions. Second, we investigate algorithms which use the
code's parity check matrices. We apply conventional BP in the parity domain,
but improve it with a novel modification. Next, we test the generalized belief
propagation (GBP) algorithm. Performance results are presented and compared
with optimum decoding techniques and bounds. The results show that our
suboptimal algorithms achieve respectable results, in some cases coming as
close as 0.2dB from optimal (maximum-likelihood) decoding. However for some of
the codes there is still a large gap from the optimal decoder.
|
1109.3887
|
An Algorithmic Approach to Information and Meaning
|
cs.IT math.IT
|
I will survey some matters of relevance to a philosophical discussion of
information, taking into account developments in algorithmic information theory
(AIT). I will propose that meaning is deep in the sense of Bennett's logical
depth, and that algorithmic probability may provide the stability needed for a
robust algorithmic definition of meaning, one that takes into consideration the
interpretation and the recipient's own knowledge encoded in the story attached
to a message.
|
1109.3911
|
Benefits of Bias: Towards Better Characterization of Network Sampling
|
cs.SI physics.soc-ph
|
From social networks to P2P systems, network sampling arises in many
settings. We present a detailed study on the nature of biases in network
sampling strategies to shed light on how best to sample from networks. We
investigate connections between specific biases and various measures of
structural representativeness. We show that certain biases are, in fact,
beneficial for many applications, as they "push" the sampling process towards
inclusion of desired properties. Finally, we describe how these sampling biases
can be exploited in several, real-world applications including disease outbreak
detection and market research.
|
1109.3940
|
Learning Discriminative Metrics via Generative Models and Kernel
Learning
|
cs.LG cs.AI stat.ME stat.ML
|
Metrics specifying distances between data points can be learned in a
discriminative manner or from generative models. In this paper, we show how to
unify generative and discriminative learning of metrics via a kernel learning
framework. Specifically, we learn local metrics optimized from parametric
generative models. These are then used as base kernels to construct a global
kernel that minimizes a discriminative training criterion. We consider both
linear and nonlinear combinations of local metric kernels. Our empirical
results show that these combinations significantly improve performance on
classification tasks. The proposed learning algorithm is also very efficient,
achieving order of magnitude speedup in training time compared to previous
discriminative baseline methods.
|
1109.3948
|
The Projection Method for Reaching Consensus and the Regularized Power
Limit of a Stochastic Matrix
|
cs.MA cs.NI cs.SY math.OC math.PR
|
In the coordination/consensus problem for multi-agent systems, a well-known
condition of achieving consensus is the presence of a spanning arborescence in
the communication digraph. The paper deals with the discrete consensus problem
in the case where this condition is not satisfied. A characterization of the
subspace $T_P$ of initial opinions (where $P$ is the influence matrix) that
\emph{ensure} consensus in the DeGroot model is given. We propose a method of
coordination that consists of: (1) the transformation of the vector of initial
opinions into a vector belonging to $T_P$ by orthogonal projection and (2)
subsequent iterations of the transformation $P.$ The properties of this method
are studied. It is shown that for any non-periodic stochastic matrix $P,$ the
resulting matrix of the orthogonal projection method can be treated as a
regularized power limit of $P.$
|
1109.3952
|
Gaussian Two-way Relay Channel with Private Information for the Relay
|
cs.IT math.IT
|
We introduce a generalized two-way relay channel where two sources exchange
information (not necessarily of the same rate) with help from a relay, and each
source additionally sends private information to the relay. We consider the
Gaussian setting where all point-to-point links are Gaussian channels. For this
channel, we consider a two-phase protocol consisting of a multiple access
channel (MAC) phase and a broadcast channel (BC) phase. We propose a general
decode-and-forward (DF) scheme where the MAC phase is related to computation
over MAC, while the BC phase is related to BC with receiver side information.
In the MAC phase, we time share a capacity-achieving code for the MAC and a
superposition code with a lattice code as its component code. We show that the
proposed DF scheme is near optimal for any channel conditions, in that it
achieves rates within half bit of the capacity region of the two-phase
protocol.
|
1109.3989
|
The SeaLion has Landed: An IDE for Answer-Set Programming---Preliminary
Report
|
cs.PL cs.AI
|
We report about the current state and designated features of the tool
SeaLion, aimed to serve as an integrated development environment (IDE) for
answer-set programming (ASP). A main goal of SeaLion is to provide a
user-friendly environment for supporting a developer to write, evaluate, debug,
and test answer-set programs. To this end, new support techniques have to be
developed that suit the requirements of the answer-set semantics and meet the
constraints of practical applicability. In this respect, SeaLion benefits from
the research results of a project on methods and methodologies for answer-set
program development in whose context SeaLion is realised. Currently, the tool
provides source-code editors for the languages of Gringo and DLV that offer
syntax highlighting, syntax checking, and a visual program outline. Further
implemented features are support for external solvers and visualisation as well
as visual editing of answer sets. SeaLion comes as a plugin of the popular
Eclipse platform and provides itself interfaces for future extensions of the
IDE.
|
1109.3994
|
k-means Approach to the Karhunen-Loeve Transform
|
cs.IT math.IT math.ST stat.TH
|
We present a simultaneous generalization of the well-known Karhunen-Loeve
(PCA) and k-means algorithms. The basic idea lies in approximating the data
with k affine subspaces of a given dimension n. In the case n=0 we obtain the
classical k-means, while for k=1 we obtain PCA algorithm. We show that for some
data exploration problems this method gives better result then either of the
classical approaches.
|
1109.4032
|
Error estimates for finite difference approximations of American put
option price
|
q-fin.CP cs.SY math.NA math.OC math.PR q-fin.PR
|
Finite difference approximations to multi-asset American put option price are
considered. The assets are modelled as a multi-dimensional diffusion process
with variable drift and volatility. Approximation error of order one quarter
with respect to the time discretisation parameter and one half with respect to
the space discretisation parameter is proved by reformulating the corresponding
optimal stopping problem as a solution of a degenerate Hamilton-Jacobi-Bellman
equation. Furthermore, the error arising from restricting the discrete problem
to a finite grid by reducing the original problem to a bounded domain is
estimated.
|
1109.4074
|
Secure Multiplex Coding Over Interference Channel with Confidential
Messages
|
cs.IT math.IT
|
In this paper, inner and outer bounds on the capacity region of two-user
interference channels with two confidential messages have been proposed. By
adding secure multiplex coding to the error correction method in [15] which
achieves the best achievable capacity region for interference channel up to
now, we have shown that the improved secure capacity region compared with [2]
now is the whole Han-Kobayashi region. In addition, this construction not only
removes the rate loss incurred by adding dummy messages to achieve security,
but also change the original weak security condition in [2] to strong security.
Then the equivocation rate for a collection of secret messages has also been
evaluated, when the length of the message is finite or the information rate is
high, our result provides a good approximation for bounding the worst case
equivocation rate. Our results can be readily extended to the Gaussian
interference channel with little efforts.
|
1109.4095
|
Kara: A System for Visualising and Visual Editing of Interpretations for
Answer-Set Programs
|
cs.LO cs.AI cs.GR cs.PL
|
In answer-set programming (ASP), the solutions of a problem are encoded in
dedicated models, called answer sets, of a logical theory. These answer sets
are computed from the program that represents the theory by means of an ASP
solver and returned to the user as sets of ground first-order literals. As this
type of representation is often cumbersome for the user to interpret, tools
like ASPVIZ and IDPDraw were developed that allow for visualising answer sets.
The tool Kara, introduced in this paper, follows these approaches, using ASP
itself as a language for defining visualisations of interpretations. Unlike
existing tools that position graphic primitives according to static coordinates
only, Kara allows for more high-level specifications, supporting graph
structures, grids, and relative positioning of graphical elements. Moreover,
generalising the functionality of previous tools, Kara provides modifiable
visualisations such that interpretations can be manipulated by graphically
editing their visualisations. This is realised by resorting to abductive
reasoning techniques. Kara is part of SeaLion, a forthcoming integrated
development environment (IDE) for ASP.
|
1109.4102
|
Storage Size Determination for Grid-Connected Photovoltaic Systems
|
math.OC cs.SY
|
In this paper, we study the problem of determining the size of battery
storage used in grid-connected photovoltaic (PV) systems. In our setting,
electricity is generated from PV and is used to supply the demand from loads.
Excess electricity generated from the PV can be stored in a battery to be used
later on, and electricity must be purchased from the electric grid if the PV
generation and battery discharging cannot meet the demand. Due to the
time-of-use electricity pricing, electricity can also be purchased from the
grid when the price is low, and be sold back to the grid when the price is
high. The objective is to minimize the cost associated with purchasing from (or
selling back to) the electric grid and the battery capacity loss while at the
same time satisfying the load and reducing the peak electricity purchase from
the grid. Essentially, the objective function depends on the chosen battery
size. We want to find a unique critical value (denoted as $C_{ref}^c$) of the
battery size such that the total cost remains the same if the battery size is
larger than or equal to $C_{ref}^c$, and the cost is strictly larger if the
battery size is smaller than $C_{ref}^c$. We obtain a criterion for evaluating
the economic value of batteries compared to purchasing electricity from the
grid, propose lower and upper bounds on $C_{ref}^c$, and introduce an efficient
algorithm for calculating its value; these results are validated via
simulations.
|
1109.4104
|
VOGCLUSTERS: an example of DAME web application
|
astro-ph.IM cs.DB
|
We present the alpha release of the VOGCLUSTERS web application, specialized
for data and text mining on globular clusters. It is one of the web2.0
technology based services of Data Mining & Exploration (DAME) Program, devoted
to mine and explore heterogeneous information related to globular clusters
data.
|
1109.4173
|
Energy-Efficient Full Diversity Collaborative Unitary Space-Time Block
Code Design via Unique Factorization of Signals
|
cs.IT math.IT
|
In this paper, a novel concept called a \textit{uniquely factorable
constellation pair} (UFCP) is proposed for the systematic design of a
noncoherent full diversity collaborative unitary space-time block code by
normalizing two Alamouti codes for a wireless communication system having two
transmitter antennas and a single receiver antenna. It is proved that such a
unitary UFCP code assures the unique identification of both channel
coefficients and transmitted signals in a noise-free case as well as full
diversity for the noncoherent maximum likelihood (ML) receiver in a noise case.
To further improve error performance, an optimal unitary UFCP code is designed
by appropriately and uniquely factorizing a pair of energy-efficient cross
quadrature amplitude modulation (QAM) constellations to maximize the coding
gain subject to a transmission bit rate constraint. After a deep investigation
of the fractional coding gain function, a technical approach developed in this
paper to maximizing the coding gain is to carefully design an energy scale to
compress the first three largest energy points in the corner of the QAM
constellations in the denominator of the objective as well as carefully design
a constellation triple forming two UFCPs, with one collaborating with the other
two so as to make the accumulated minimum Euclidean distance along the two
transmitter antennas in the numerator of the objective as large as possible and
at the same time, to avoid as many corner points of the QAM constellations with
the largest energy as possible to achieve the minimum of the numerator. In
other words, the optimal coding gain is attained by intelligent constellations
collaboration and efficient energy compression.
|
1109.4179
|
FemtoCaching: Wireless Video Content Delivery through Distributed
Caching Helpers
|
cs.NI cs.IT math.IT
|
Video on-demand streaming from Internet-based servers is becoming one of the
most important services offered by wireless networks today. In order to improve
the area spectral efficiency of video transmission in cellular systems, small
cells heterogeneous architectures (e.g., femtocells, WiFi off-loading) are
being proposed, such that video traffic to nomadic users can be handled by
short-range links to the nearest small cell access points (referred to as
"helpers"). As the helper deployment density increases, the backhaul capacity
becomes the system bottleneck. In order to alleviate such bottleneck we propose
a system where helpers with low-rate backhaul but high storage capacity cache
popular video files. Files not available from helpers are transmitted by the
cellular base station. We analyze the optimum way of assigning files to the
helpers, in order to minimize the expected downloading time for files. We
distinguish between the uncoded case (where only complete files are stored) and
the coded case, where segments of Fountain-encoded versions of the video files
are stored at helpers. We show that the uncoded optimum file assignment is
NP-hard, and develop a greedy strategy that is provably within a factor 2 of
the optimum. Further, for a special case we provide an efficient algorithm
achieving a provably better approximation ratio of $1-(1-1/d)^d$, where $d$ is
the maximum number of helpers a user can be connected to. We also show that the
coded optimum cache assignment problem is convex that can be further reduced to
a linear program. We present numerical results comparing the proposed schemes.
|
1109.4201
|
Production and Network Formation Games with Content Heterogeneity
|
cs.SI cs.GT physics.soc-ph
|
Online social networks (e.g. Facebook, Twitter, Youtube) provide a popular,
cost-effective and scalable framework for sharing user-generated contents. This
paper addresses the intrinsic incentive problems residing in social networks
using a game-theoretic model where individual users selfishly trade off the
costs of forming links (i.e. whom they interact with) and producing contents
personally against the potential rewards from doing so. Departing from the
assumption that contents produced by difference users is perfectly
substitutable, we explicitly consider heterogeneity in user-generated contents
and study how it influences users' behavior and the structure of social
networks. Given content heterogeneity, we rigorously prove that when the
population of a social network is sufficiently large, every (strict)
non-cooperative equilibrium should consist of either a symmetric network
topology where each user produces the same amount of content and has the same
degree, or a two-level hierarchical topology with all users belonging to either
of the two types: influencers who produce large amounts of contents and
subscribers who produce small amounts of contents and get most of their
contents from influencers. Meanwhile, the law of the few disappears in such
networks. Moreover, we prove that the social optimum is always achieved by
networks with symmetric topologies, where the sum of users' utilities is
maximized. To provide users with incentives for producing and mutually sharing
the socially optimal amount of contents, a pricing scheme is proposed, with
which we show that the social optimum can be achieved as a non-cooperative
equilibrium with the pricing of content acquisition and link formation.
|
1109.4221
|
Three Cases of Connectivity and Global Information Transfer in Robot
Swarms
|
cs.RO
|
In this work we consider three different cases of robot-robot interactions
and resulting global information transfer in robot swarms. These mechanisms
define cooperative properties of the system and can be used for designing
collective behavior. These three cases are demonstrated and discussed based on
experiments in a swarm of microrobots "Jasmine".
|
1109.4257
|
Offering A Product Recommendation System in E-commerce
|
cs.IR
|
This paper proposes a number of explicit and implicit ratings in product
recommendation system for Business-to-customer e-commerce purposes. The system
recommends the products to a new user. It depends on the purchase pattern of
previous users whose purchase pattern is close to that of a user who asks for a
recommendation. The system is based on weighted cosine similarity measure to
find out the closest user profile among the profiles of all users in database.
It also implements Association rule mining rule in recommending the products.
Also, this product recommendation system takes into consideration the time of
transaction of purchasing the items, thus eliminating sequence recognition
problem. Experimental result shows for implicit rating, the proposed method
gives acceptable performance in recommending the products. It also shows
introduction of association rule improves the performance measure of
recommendation system.
|
1109.4288
|
Adding Logical Operators to Tree Pattern Queries on Graph-Structured
Data
|
cs.DB
|
As data are increasingly modeled as graphs for expressing complex
relationships, the tree pattern query on graph-structured data becomes an
important type of queries in real-world applications. Most practical query
languages, such as XQuery and SPARQL, support logical expressions using
logical-AND/OR/NOT operators to define structural constraints of tree patterns.
In this paper, (1) we propose generalized tree pattern queries (GTPQs) over
graph-structured data, which fully support propositional logic of structural
constraints. (2) We make a thorough study of fundamental problems including
satisfiability, containment and minimization, and analyze the computational
complexity and the decision procedures of these problems. (3) We propose a
compact graph representation of intermediate results and a pruning approach to
reduce the size of intermediate results and the number of join operations --
two factors that often impair the efficiency of traditional algorithms for
evaluating tree pattern queries. (4) We present an efficient algorithm for
evaluating GTPQs using 3-hop as the underlying reachability index. (5)
Experiments on both real-life and synthetic data sets demonstrate the
effectiveness and efficiency of our algorithm, from several times to orders of
magnitude faster than state-of-the-art algorithms in terms of evaluation time,
even for traditional tree pattern queries with only conjunctive operations.
|
1109.4299
|
One-bit compressed sensing by linear programming
|
cs.IT math.IT math.PR
|
We give the first computationally tractable and almost optimal solution to
the problem of one-bit compressed sensing, showing how to accurately recover an
s-sparse vector x in R^n from the signs of O(s log^2(n/s)) random linear
measurements of x. The recovery is achieved by a simple linear program. This
result extends to approximately sparse vectors x. Our result is universal in
the sense that with high probability, one measurement scheme will successfully
recover all sparse vectors simultaneously. The argument is based on solving an
equivalent geometric problem on random hyperplane tessellations.
|
1109.4305
|
Strategy of Competition between Two Groups based on a Contrarian Opinion
Model
|
physics.data-an cs.SI physics.soc-ph
|
We introduce a contrarian opinion (CO) model in which a fraction p of
contrarians within a group holds a strong opinion opposite to the opinion held
by the rest of the group. At the initial stage, stable clusters of two
opinions, A and B exist. Then we introduce contrarians which hold a strong B
opinion into the opinion A group. Through their interactions, the contrarians
are able to decrease the size of the largest A opinion cluster, and even
destroy it. We see this kind of method in operation, e.g when companies send
free new products to potential customers in order to convince them to adopt the
product and influence others. We study the CO model, using two different
strategies, on both ER and scale-free networks. In strategy I, the contrarians
are positioned at random. In strategy II, the contrarians are chosen to be the
highest degrees nodes. We find that for both strategies the size of the largest
A cluster decreases to zero as p increases as in a phase transition. At a
critical threshold value p_c the system undergoes a second-order phase
transition that belongs to the same universality class of mean field
percolation. We find that even for an ER type model, where the degrees of the
nodes are not so distinct, strategy II is significantly more effctive in
reducing the size of the largest A opinion cluster and, at very small values of
p, the largest A opinion cluster is destroyed.
|
1109.4314
|
On the Degrees of Freedom of $K$-User SISO Interference and X Channels
with Delayed CSIT
|
cs.IT math.IT
|
The $K$-user single-input single-output (SISO) AWGN interference channel and
$2\times K$ SISO AWGN X channel are considered where the transmitters have the
delayed channel state information (CSI) through noiseless feedback links.
Multi-phase transmission schemes are proposed for both channels which possess
novel ingredients, namely, multi-phase partial interference nulling,
distributed interference management via user scheduling, and distributed
higher-order symbol generation. The achieved degrees of freedom (DoF) values
are greater than the best previously known DoFs for both channels with delayed
CSI at transmitters.
|
1109.4335
|
Social choice rules driven by propositional logic
|
cs.AI
|
Several rules for social choice are examined from a unifying point of view
that looks at them as procedures for revising a system of degrees of belief in
accordance with certain specified logical constraints. Belief is here a social
attribute, its degrees being measured by the fraction of people who share a
given opinion. Different known rules and some new ones are obtained depending
on which particular constraints are assumed. These constraints allow to model
different notions of choiceness. In particular, we give a new method to deal
with approval-disapproval-preferential voting.
|
1109.4347
|
VC dimension of ellipsoids
|
math.CO cs.LG stat.ML
|
We will establish that the VC dimension of the class of d-dimensional
ellipsoids is (d^2+3d)/2, and that maximum likelihood estimate with N-component
d-dimensional Gaussian mixture models induces a geometric class having VC
dimension at least N(d^2+3d)/2.
Keywords: VC dimension; finite dimensional ellipsoid; Gaussian mixture model
|
1109.4350
|
Subspace Alignment Chains and the Degrees of Freedom of the Three-User
MIMO Interference Channel
|
cs.IT math.IT
|
We show that the 3 user M_T x M_R MIMO interference channel has
d(M,N)=min(M/(2-1/k),N/(2+1/k)) degrees of freedom (DoF) normalized by time,
frequency, and space dimensions, where M=min(M_T,M_R), N=max(M_T,M_R),
k=ceil{M/(N-M)}. While the DoF outer bound is established for every M_T, M_R
value, the achievability is established in general subject to normalization
with respect to spatial-extensions. Given spatial-extensions, the achievability
relies only on linear beamforming based interference alignment schemes with no
need for time/frequency extensions. In the absence of spatial extensions, we
show through examples how essentially the same scheme may be applied over
time/frequency extensions. The central new insight to emerge from this work is
the notion of subspace alignment chains as DoF bottlenecks.
The DoF value d(M,N) is a piecewise linear function of M,N, with either M or
N being the bottleneck within each linear segment. The corner points of these
piecewise linear segments correspond to A={1/2,2/3,3/4,...} and
B={1/3,3/5,5/7,...}. The set A contains all values of M/N and only those for
which there is redundancy in both M and N. The set B contains all values of M/N
and only those for which there is no redundancy in either M or N.
Our results settle the feasibility of linear interference alignment,
introduced by Cenk et al., for the 3 user M_T x M_R MIMO interference channel,
completely for all values of M_T, M_R. Specifically, the linear interference
alignment problem (M_T x M_R, d)^3 (as defined in previous work by Cenk et al.)
is feasible if and only if d<=floor{d(M,N)}. With and only with the exception
of the values M/N\in B, we show that for every M/N value there are proper
systems that are not feasible.
Our results show that M/N\in A are the only values for which there is no DoF
benefit of joint processing among co-located antennas at the transmitters or
receivers.
|
1109.4424
|
Statistical physics-based reconstruction in compressed sensing
|
cond-mat.stat-mech cs.IT math.IT
|
Compressed sensing is triggering a major evolution in signal acquisition. It
consists in sampling a sparse signal at low rate and later using computational
power for its exact reconstruction, so that only the necessary information is
measured. Currently used reconstruction techniques are, however, limited to
acquisition rates larger than the true density of the signal. We design a new
procedure which is able to reconstruct exactly the signal with a number of
measurements that approaches the theoretical limit in the limit of large
systems. It is based on the joint use of three essential ingredients: a
probabilistic approach to signal reconstruction, a message-passing algorithm
adapted from belief propagation, and a careful design of the measurement matrix
inspired from the theory of crystal nucleation. The performance of this new
algorithm is analyzed by statistical physics methods. The obtained improvement
is confirmed by numerical studies of several cases.
|
1109.4457
|
Nonlinear Robust Tracking Control of a Quadrotor UAV on SE(3)
|
math.OC cs.SY
|
This paper provides nonlinear tracking control systems for a quadrotor
unmanned aerial vehicle (UAV) that are robust to bounded uncertainties. A
mathematical model of a quadrotor UAV is defined on the special Euclidean
group, and nonlinear output-tracking controllers are developed to follow (1) an
attitude command, and (2) a position command for the vehicle center of mass.
The controlled system has the desirable properties that the tracking errors are
uniformly ultimately bounded, and the size of the ultimate bound can be
arbitrarily reduced by control system parameters. Numerical examples
illustrating complex maneuvers are provided.
|
1109.4474
|
Smart Grid Information Security (IS) Functional Requirement
|
cs.SY
|
It is important to implement safe smart grid environment to enhance people's
lives and livelihoods. This paper provides information on smart grid IS
functional requirement by illustrating some discussion points to the sixteen
identified requirements. This paper introduces the smart grid potential hazards
that can be referred as a triggering factor to improve the system and security
of the entire grid. The background of smart information infrastructure and the
needs for smart grid IS is described with the adoption of hermeneutic circle as
methodology. Grid information technology and security-s session discusses that
grid provides the chance of a simple and transparent access to different
information sources. In addition, the transformation between traditional versus
smart grid networking trend and the IS importance on the communication field
reflects the criticality of grid IS functional requirement identification is
introduces. The smart grid IS functional requirements described in this paper
are general and can be adopted or modified to suit any smart grid system. This
paper has tutorial contents where some related backgrounds were provided,
especially for networking community, covering the cyber security requirement of
smart grid information infrastructure.
|
1109.4487
|
Disentangling Social and Group heterogeneities: Public Goods games on
Complex Networks
|
physics.soc-ph cs.SI
|
In this Letter we present a new perspective for the study of the Public Goods
games on complex networks. The idea of our approach is to consider a realistic
structure for the groups in which Public goods games are played. Instead of
assuming that the social network of contacts self-defines a group structure
with identical topological properties, we disentangle these two interaction
patterns so to deal with systems having groups of definite sizes embedded in
social networks with a tunable degree of heterogeneity. Surpisingly, this
realistic framework, reveals that social heterogeneity may not foster
cooperation depending on the game setting and the updating rule.
|
1109.4499
|
PhaseLift: Exact and Stable Signal Recovery from Magnitude Measurements
via Convex Programming
|
cs.IT math.IT math.NA
|
Suppose we wish to recover a signal x in C^n from m intensity measurements of
the form |<x,z_i>|^2, i = 1, 2,..., m; that is, from data in which phase
information is missing. We prove that if the vectors z_i are sampled
independently and uniformly at random on the unit sphere, then the signal x can
be recovered exactly (up to a global phase factor) by solving a convenient
semidefinite program---a trace-norm minimization problem; this holds with large
probability provided that m is on the order of n log n, and without any
assumption about the signal whatsoever. This novel result demonstrates that in
some instances, the combinatorial phase retrieval problem can be solved by
convex programming techniques. Finally, we also prove that our methodology is
robust vis a vis additive noise.
|
1109.4521
|
Controlling centrality in complex networks
|
physics.soc-ph cond-mat.stat-mech cs.SI physics.data-an
|
Spectral centrality measures allow to identify influential individuals in
social groups, to rank Web pages by their popularity, and even to determine the
impact of scientific researches. The centrality score of a node within a
network crucially depends on the entire pattern of connections, so that the
usual approach is to compute the node centralities once the network structure
is assigned. We face here with the inverse problem, that is, we study how to
modify the centrality scores of the nodes by acting on the structure of a given
network. We prove that there exist particular subsets of nodes, called
controlling sets, which can assign any prescribed set of centrality values to
all the nodes of a graph, by cooperatively tuning the weights of their
out-going links. We show that many large networks from the real world have
surprisingly small controlling sets, containing even less than 5-10% of the
nodes. These results suggest that rankings obtained from spectral centrality
measures have to be considered with extreme care, since they can be easily
controlled and even manipulated by a small group of nodes acting in a
coordinated way.
|
1109.4530
|
Closed-loop control of a reaction-diffusion system
|
math.OC cs.SY
|
A system of a parabolic partial differential equation coupled with ordinary
differential inclusions that arises from a closed-loop control problem for a
thermodynamic process governed by the Allen-Cahn diffusion reaction model is
studied. A feedback law for the closed-loop control is proposed and implemented
in the case of a finite number of control devices located inside the process
domain basing on the process dynamics observed at a finite number of
measurement points. The existence of solutions to the discussed system of
differential equations is proved with the use of a generalization of the
Kakutani fixed point theorem.
|
1109.4531
|
A Probabilistic Approach to Pronunciation by Analogy
|
cs.CL
|
The relationship between written and spoken words is convoluted in languages
with a deep orthography such as English and therefore it is difficult to devise
explicit rules for generating the pronunciations for unseen words.
Pronunciation by analogy (PbA) is a data-driven method of constructing
pronunciations for novel words from concatenated segments of known words and
their pronunciations. PbA performs relatively well with English and outperforms
several other proposed methods. However, the best published word accuracy of
65.5% (for the 20,000 word NETtalk corpus) suggests there is much room for
improvement in it.
Previous PbA algorithms have used several different scoring strategies such
as the product of the frequencies of the component pronunciations of the
segments, or the number of different segmentations that yield the same
pronunciation, and different combinations of these methods, to evaluate the
candidate pronunciations. In this article, we instead propose to use a
probabilistically justified scoring rule. We show that this principled approach
alone yields better accuracy (66.21% for the NETtalk corpus) than any
previously published PbA algorithm. Furthermore, combined with certain ad hoc
modifications motivated by earlier algorithms, the performance climbs up to
66.6%, and further improvements are possible by combining this method with
other methods.
|
1109.4540
|
Manifold estimation and singular deconvolution under Hausdorff loss
|
math.ST cs.LG stat.ML stat.TH
|
We find lower and upper bounds for the risk of estimating a manifold in
Hausdorff distance under several models. We also show that there are close
connections between manifold estimation and the problem of deconvolving a
singular measure.
|
1109.4544
|
Characterization of accessibility for affine connection control systems
at some points with nonzero velocity
|
math.OC cs.SY
|
Affine connection control systems are mechanical control systems that model a
wide range of real systems such as robotic legs, hovercrafts, planar rigid
bodies, rolling pennies, snakeboards and so on. In 1997 the accessibility and a
particular notion of controllability was intrinsically described by A. D. Lewis
and R. Murray at points of zero velocity. Here, we present a novel
generalization of the description of accessibility algebra for those systems at
some points with nonzero velocity as long as the affine connection restricts to
the distribution given by the symmetric closure. The results are used to
describe the accessibility algebra of different mechanical control systems.
|
1109.4564
|
Canonical Estimation in a Rare-Events Regime
|
cs.IT math.IT math.ST stat.TH
|
We propose a general methodology for performing statistical inference within
a `rare-events regime' that was recently suggested by Wagner, Viswanath and
Kulkarni. Our approach allows one to easily establish consistent estimators for
a very large class of canonical estimation problems, in a large alphabet
setting. These include the problems studied in the original paper, such as
entropy and probability estimation, in addition to many other interesting ones.
We particularly illustrate this approach by consistently estimating the size of
the alphabet and the range of the probabilities. We start by proposing an
abstract methodology based on constructing a probability measure with the
desired asymptotic properties. We then demonstrate two concrete constructions
by casting the Good-Turing estimator as a pseudo-empirical measure, and by
using the theory of mixture model estimation.
|
1109.4587
|
Bandlimited Intensity Modulation
|
cs.IT math.IT
|
In this paper, the design and analysis of a new bandwidth-efficient signaling
method over the bandlimited intensity-modulated direct-detection (IM/DD)
channel is presented. The channel can be modeled as a bandlimited channel with
nonnegative input and additive white Gaussian noise (AWGN). Due to the
nonnegativity constraint, standard methods for coherent bandlimited channels
cannot be applied here. Previously established techniques for the IM/DD channel
require bandwidth twice the required bandwidth over the conventional coherent
channel. We propose a method to transmit without intersymbol interference in a
bandwidth no larger than the bit rate. This is done by combining Nyquist or
root-Nyquist pulses with a constant bias and using higher-order modulation
formats. In fact, we can transmit with a bandwidth equal to that of coherent
transmission. A trade-off between the required average optical power and the
bandwidth is investigated. Depending on the bandwidth required, the most
power-efficient transmission is obtained by the parametric linear pulse, the
so-called "better than Nyquist" pulse, or the root-raised cosine pulse.
|
1109.4590
|
Constructing and sampling directed graphs with given degree sequences
|
physics.soc-ph cond-mat.stat-mech cs.DS cs.SI
|
The interactions between the components of complex networks are often
directed. Proper modeling of such systems frequently requires the construction
of ensembles of digraphs with a given sequence of in- and out-degrees. As the
number of simple labeled graphs with a given degree sequence is typically very
large even for short sequences, sampling methods are needed for statistical
studies. Currently, there are two main classes of methods that generate
samples. One of the existing methods first generates a restricted class of
graphs, then uses a Markov Chain Monte-Carlo algorithm based on edge swaps to
generate other realizations. As the mixing time of this process is still
unknown, the independence of the samples is not well controlled. The other
class of methods is based on the Configuration Model that may lead to
unacceptably many sample rejections due to self-loops and multiple edges. Here
we present an algorithm that can directly construct all possible realizations
of a given bi-degree sequence by simple digraphs. Our method is rejection free,
guarantees the independence of the constructed samples, and provides their
weight. The weights can then be used to compute statistical averages of network
observables as if they were obtained from uniformly distributed sampling, or
from any other chosen distribution.
|
1109.4599
|
On the Diversity Order and Coding Gain of Multi-Source Multi-Relay
Cooperative Wireless Networks with Binary Network Coding
|
cs.IT math.IT
|
In this paper, a multi-source multi-relay cooperative wireless network with
binary modulation and binary network coding is studied. The system model
encompasses: i) a demodulate-and-forward protocol at the relays, where the
received packets are forwarded regardless of their reliability; and ii) a
maximum-likelihood optimum demodulator at the destination, which accounts for
possible demodulations errors at the relays. An asymptotically-tight and
closed-form expression of the end-to-end error probability is derived, which
clearly showcases diversity order and coding gain of each source. Unlike other
papers available in the literature, the proposed framework has three main
distinguishable features: i) it is useful for general network topologies and
arbitrary binary encoding vectors; ii) it shows how network code and two-hop
forwarding protocol affect diversity order and coding gain; and ii) it accounts
for realistic fading channels and demodulation errors at the relays. The
framework provides three main conclusions: i) each source achieves a diversity
order equal to the separation vector of the network code; ii) the coding gain
of each source decreases with the number of mixed packets at the relays; and
iii) if the destination cannot take into account demodulation errors at the
relays, it loses approximately half of the diversity order.
|
1109.4603
|
Explicit Approximations of the Gaussian Kernel
|
cs.AI
|
We investigate training and using Gaussian kernel SVMs by approximating the
kernel with an explicit finite- dimensional polynomial feature representation
based on the Taylor expansion of the exponential. Although not as efficient as
the recently-proposed random Fourier features [Rahimi and Recht, 2007] in terms
of the number of features, we show how this polynomial representation can
provide a better approximation in terms of the computational cost involved.
This makes our "Taylor features" especially attractive for use on very large
data sets, in conjunction with online or stochastic training.
|
1109.4609
|
Memristive fuzzy edge detector
|
cs.NE cs.AI cs.AR cs.LG
|
Fuzzy inference systems always suffer from the lack of efficient structures
or platforms for their hardware implementation. In this paper, we tried to
overcome this problem by proposing new method for the implementation of those
fuzzy inference systems which use fuzzy rule base to make inference. To achieve
this goal, we have designed a multi-layer neuro-fuzzy computing system based on
the memristor crossbar structure by introducing some new concepts like fuzzy
minterms. Although many applications can be realized through the use of our
proposed system, in this study we show how the fuzzy XOR function can be
constructed and how it can be used to extract edges from grayscale images. Our
memristive fuzzy edge detector (implemented in analog form) compared with other
common edge detectors has this advantage that it can extract edges of any given
image all at once in real-time.
|
1109.4623
|
Outlier detection in default logics: the tractability/intractability
frontier
|
cs.AI cs.CC cs.LO
|
In default theories, outliers denote sets of literals featuring unexpected
properties. In previous papers, we have defined outliers in default logics and
investigated their formal properties. Specifically, we have looked into the
computational complexity of outlier detection problems and proved that while
they are generally intractable, interesting tractable cases can be singled out.
Following those results, we study here the tractability frontier in outlier
detection problems, by analyzing it with respect to (i) the considered outlier
detection problem, (ii) the reference default logic fragment, and (iii) the
adopted notion of outlier. As for point (i), we shall consider three problems
of increasing complexity, called Outlier-Witness Recognition, Outlier
Recognition and Outlier Existence, respectively. As for point (ii), as we look
for conditions under which outlier detection can be done efficiently, attention
will be limited to subsets of Disjunction-free propositional default theories.
As for point (iii), we shall refer to both the notion of outlier of [ABP08] and
a new and more restrictive one, called strong outlier. After complexity
results, we present a polynomial time algorithm for enumerating all strong
outliers of bounded size in an quasi-acyclic normal unary default theory. Some
of our tractability results rely on the Incremental Lemma that provides
conditions for a deafult logic fragment to have a monotonic behavior. Finally,
in order to show that the simple fragments of DL we deal with are still rich
enough to solve interesting problems and, therefore, the tractability results
that we prove are interesting not only on the mere theoretical side, insights
into the expressive capabilities of these fragments are provided, by showing
that normal unary theories express all NL queries, hereby indirectly answering
a question raised by Kautz and Selman.
|
1109.4627
|
Distributed Recursive Least-Squares: Stability and Performance Analysis
|
cs.NI cs.SY math.OC
|
The recursive least-squares (RLS) algorithm has well-documented merits for
reducing complexity and storage requirements, when it comes to online
estimation of stationary signals as well as for tracking slowly-varying
nonstationary processes. In this paper, a distributed recursive least-squares
(D-RLS) algorithm is developed for cooperative estimation using ad hoc wireless
sensor networks. Distributed iterations are obtained by minimizing a separable
reformulation of the exponentially-weighted least-squares cost, using the
alternating-minimization algorithm. Sensors carry out reduced-complexity tasks
locally, and exchange messages with one-hop neighbors to consent on the
network-wide estimates adaptively. A steady-state mean-square error (MSE)
performance analysis of D-RLS is conducted, by studying a stochastically-driven
`averaged' system that approximates the D-RLS dynamics asymptotically in time.
For sensor observations that are linearly related to the time-invariant
parameter vector sought, the simplifying independence setting assumptions
facilitate deriving accurate closed-form expressions for the MSE steady-state
values. The problems of mean- and MSE-sense stability of D-RLS are also
investigated, and easily-checkable sufficient conditions are derived under
which a steady-state is attained. Without resorting to diminishing step-sizes
which compromise the tracking ability of D-RLS, stability ensures that per
sensor estimates hover inside a ball of finite radius centered at the true
parameter vector, with high-probability, even when inter-sensor communication
links are noisy. Interestingly, computer simulations demonstrate that the
theoretical findings are accurate also in the pragmatic settings whereby
sensors acquire temporally-correlated data.
|
1109.4631
|
Random Sequential Renormalization and Agglomerative Percolation in
Networks: Application to Erd"os-R'enyi and Scale-free Graphs
|
cond-mat.stat-mech cs.SI physics.soc-ph
|
We study the statistical behavior under random sequential
renormalization(RSR) of several network models including Erd"os R'enyi (ER)
graphs, scale-free networks and an annealed model (AM) related to ER graphs. In
RSR the network is locally coarse grained by choosing at each renormalization
step a node at random and joining it to all its neighbors. Compared to previous
(quasi-)parallel renormalization methods [C.Song et.al], RSR allows a more
fine-grained analysis of the renormalization group (RG) flow, and unravels new
features, that were not discussed in the previous analyses. In particular we
find that all networks exhibit a second order transition in their RG flow. This
phase transition is associated with the emergence of a giant hub and can be
viewed as a new variant of percolation, called agglomerative percolation. We
claim that this transition exists also in previous graph renormalization
schemes and explains some of the scaling laws seen there. For critical trees it
happens as N/N0 -> 0 in the limit of large systems (where N0 is the initial
size of the graph and N its size at a given RSR step). In contrast, it happens
at finite N/N0 in sparse ER graphs and in the annealed model, while it happens
for N/N0 -> 1 on scale-free networks. Critical exponents seem to depend on the
type of the graph but not on the average degree and obey usual scaling
relations for percolation phenomena. For the annealed model they agree with the
exponents obtained from a mean-field theory. At late times, the networks
exhibit a star-like structure in agreement with the results of Radicchi et. al.
While degree distributions are of main interest when regarding the scheme as
network renormalization, mass distributions (which are more relevant when
considering 'supernodes' as clusters) are much easier to study using the fast
Newman-Ziff algorithm for percolation, allowing us to obtain very high
statistics.
|
1109.4654
|
Distributed Protocols for Interference Management in Cooperative
Networks
|
cs.IT cs.NI math.IT
|
In scenarios where devices are too small to support MIMO antenna arrays,
symbol-level cooperation may be used to pool the resources of distributed
single-antenna devices to create a virtual MIMO antenna array. We address
design fundamentals for distributed cooperative protocols where relays have an
incomplete view of network information. A key issue in distributed networks is
potential loss in spatial reuse due to the increased radio footprint of flows
with cooperative relays. Hence, local gains from cooperation have to balance
against network level losses. By using a novel binary network model that
simplifies the space over which cooperative protocols must be designed, we
develop a mechanism for the systematic and computational development of
cooperative protocols as functions of the amount of network state information
available at relay nodes. Through extensive network analysis and simulations,
we demonstrate the successful application of this method to a series of
protocols that span a range of network information availability at cooperative
relays.
|
1109.4668
|
Robust estimation of latent tree graphical models: Inferring hidden
states with inexact parameters
|
math.PR cs.LG math.ST q-bio.PE stat.TH
|
Latent tree graphical models are widely used in computational biology, signal
and image processing, and network tomography. Here we design a new efficient,
estimation procedure for latent tree models, including Gaussian and discrete,
reversible models, that significantly improves on previous sample requirement
bounds. Our techniques are based on a new hidden state estimator which is
robust to inaccuracies in estimated parameters. More precisely, we prove that
latent tree models can be estimated with high probability in the so-called
Kesten-Stigum regime with $O(log^2 n)$ samples where $n$ is the number of
nodes.
|
1109.4680
|
The Push Algorithm for Spectral Ranking
|
cs.SI cs.DS physics.soc-ph
|
The push algorithm was proposed first by Jeh and Widom in the context of
personalized PageRank computations (albeit the name "push algorithm" was
actually used by Andersen, Chung and Lang in a subsequent paper). In this note
we describe the algorithm at a level of generality that make the computation of
the spectral ranking of any nonnegative matrix possible. Actually, the main
contribution of this note is that the description is very simple (almost
trivial), and it requires only a few elementary linear-algebra computations.
Along the way, we give new precise ways of estimating the convergence of the
algorithm, and describe some of the contribution of the existing literature,
which again turn out to be immediate when recast in our framework.
|
1109.4683
|
Detachable Object Detection: Segmentation and Depth Ordering From
Short-Baseline Video
|
cs.CV
|
We describe an approach for segmenting an image into regions that correspond
to surfaces in the scene that are partially surrounded by the medium. It
integrates both appearance and motion statistics into a cost functional, that
is seeded with occluded regions and minimized efficiently by solving a linear
programming problem. Where a short observation time is insufficient to
determine whether the object is detachable, the results of the minimization can
be used to seed a more costly optimization based on a longer sequence of video
data. The result is an entirely unsupervised scheme to detect and segment an
arbitrary and unknown number of objects. We test our scheme to highlight the
potential, as well as limitations, of our approach.
|
1109.4684
|
Exhaustive and Efficient Constraint Propagation: A Semi-Supervised
Learning Perspective and Its Applications
|
cs.AI cs.LG
|
This paper presents a novel pairwise constraint propagation approach by
decomposing the challenging constraint propagation problem into a set of
independent semi-supervised learning subproblems which can be solved in
quadratic time using label propagation based on k-nearest neighbor graphs.
Considering that this time cost is proportional to the number of all possible
pairwise constraints, our approach actually provides an efficient solution for
exhaustively propagating pairwise constraints throughout the entire dataset.
The resulting exhaustive set of propagated pairwise constraints are further
used to adjust the similarity matrix for constrained spectral clustering. Other
than the traditional constraint propagation on single-source data, our approach
is also extended to more challenging constraint propagation on multi-source
data where each pairwise constraint is defined over a pair of data points from
different sources. This multi-source constraint propagation has an important
application to cross-modal multimedia retrieval. Extensive results have shown
the superior performance of our approach.
|
1109.4744
|
Probabilistic prototype models for attributed graphs
|
cs.CV
|
This contribution proposes a new approach towards developing a class of
probabilistic methods for classifying attributed graphs. The key concept is
random attributed graph, which is defined as an attributed graph whose nodes
and edges are annotated by random variables. Every node/edge has two random
processes associated with it- occurence probability and the probability
distribution over the attribute values. These are estimated within the maximum
likelihood framework. The likelihood of a random attributed graph to generate
an outcome graph is used as a feature for classification. The proposed approach
is fast and robust to noise.
|
1109.4770
|
On the algebraic representation of selected optimal non-linear binary
codes
|
cs.IT math.CO math.IT
|
Revisiting an approach by Conway and Sloane we investigate a collection of
optimal non-linear binary codes and represent them as (non-linear) codes over
Z4. The Fourier transform will be used in order to analyze these codes, which
leads to a new algebraic representation involving subgroups of the group of
units in a certain ring.
One of our results is a new representation of Best's (10, 40, 4) code as a
coset of a subgroup in the group of invertible elements of the group ring
Z4[Z5]. This yields a particularly simple algebraic decoding algorithm for this
code.
The technique at hand is further applied to analyze Julin's (12, 144, 4) code
and the (12, 24, 12) Hadamard code. It can also be used in order to construct a
(non-optimal) binary (14, 56, 6) code.
|
1109.4803
|
Suppression effect on explosive percolations
|
physics.soc-ph cond-mat.stat-mech cs.SI
|
When a group of people unknown to each other meet and familiarize among
themselves, over time they form a community on a macroscopic scale. This
phenomenon can be understood in the context of percolation transition (PT) of
networks, which takes place continuously in the classical random graph model.
Recently, a modified model was introduced in which the formation of the
community was suppressed. Then the PT occurs explosively at a delayed
transition time. Whether the explosive PT is indeed discontinuous or continuous
becomes controversial. Here we show that type of PT depends on a detailed
dynamic rule. Thus, when the dynamic rule is designed to suppress the growth of
overall clusters, then the explosive PT could be discontinuous.
|
1109.4856
|
On the Information Loss in Memoryless Systems: The Multivariate Case
|
cs.IT math.IT nlin.SI
|
In this work we give a concise definition of information loss from a
system-theoretic point of view. Based on this definition, we analyze the
information loss in static input-output systems subject to a continuous-valued
input. For a certain class of multiple-input, multiple-output systems the
information loss is quantified. An interpretation of this loss is accompanied
by upper bounds which are simple to evaluate.
Finally, a class of systems is identified for which the information loss is
necessarily infinite. Quantizers and limiters are shown to belong to this
class.
|
1109.4900
|
Evaluating links through spectral decomposition
|
physics.soc-ph cs.SI
|
Spectral decomposition has been rarely used to investigate complex networks.
In this work we apply this concept in order to define two types of
link-directed attacks while quantifying their respective effects on the
topology. Several other types of more traditional attacks are also adopted and
compared. These attacks had substantially diverse effects, depending on each
specific network (models and real-world structures). It is also showed that the
spectral-based attacks have special effect in affecting the transitivity of the
networks.
|
1109.4906
|
Automatic transcription of 17th century English text in Contemporary
English with NooJ: Method and Evaluation
|
cs.CL
|
Since 2006 we have undertaken to describe the differences between 17th
century English and contemporary English thanks to NLP software. Studying a
corpus spanning the whole century (tales of English travellers in the Ottoman
Empire in the 17th century, Mary Astell's essay A Serious Proposal to the
Ladies and other literary texts) has enabled us to highlight various lexical,
morphological or grammatical singularities. Thanks to the NooJ linguistic
platform, we created dictionaries indexing the lexical variants and their
transcription in CE. The latter is often the result of the validation of forms
recognized dynamically by morphological graphs. We also built syntactical
graphs aimed at transcribing certain archaic forms in contemporary English. Our
previous research implied a succession of elementary steps alternating textual
analysis and result validation. We managed to provide examples of
transcriptions, but we have not created a global tool for automatic
transcription. Therefore we need to focus on the results we have obtained so
far, study the conditions for creating such a tool, and analyze possible
difficulties. In this paper, we will be discussing the technical and linguistic
aspects we have not yet covered in our previous work. We are using the results
of previous research and proposing a transcription method for words or
sequences identified as archaic.
|
1109.4909
|
Sparse Online Low-Rank Projection and Outlier Rejection (SOLO) for 3-D
Rigid-Body Motion Registration
|
cs.CV
|
Motivated by an emerging theory of robust low-rank matrix representation, in
this paper, we introduce a novel solution for online rigid-body motion
registration. The goal is to develop algorithmic techniques that enable a
robust, real-time motion registration solution suitable for low-cost, portable
3-D camera devices. Assuming 3-D image features are tracked via a standard
tracker, the algorithm first utilizes Robust PCA to initialize a low-rank shape
representation of the rigid body. Robust PCA finds the global optimal solution
of the initialization, while its complexity is comparable to singular value
decomposition. In the online update stage, we propose a more efficient
algorithm for sparse subspace projection to sequentially project new feature
observations onto the shape subspace. The lightweight update stage guarantees
the real-time performance of the solution while maintaining good registration
even when the image sequence is contaminated by noise, gross data corruption,
outlying features, and missing data. The state-of-the-art accuracy of the
solution is validated through extensive simulation and a real-world experiment,
while the system enjoys one to two orders of magnitude speed-up compared to
well-established RANSAC solutions. The new algorithm will be released online to
aid peer evaluation.
|
1109.4920
|
Beyond pixels and regions: A non local patch means (NLPM) method for
content-level restoration, enhancement, and reconstruction of degraded
document images
|
cs.CV cs.IR
|
A patch-based non-local restoration and reconstruction method for
preprocessing degraded document images is introduced. The method collects
relative data from the whole input image, while the image data are first
represented by a content-level descriptor based on patches. This
patch-equivalent representation of the input image is then corrected based on
similar patches identified using a modified genetic algorithm (GA) resulting in
a low computational load. The corrected patch-equivalent is then converted to
the output restored image. The fact that the method uses the patches at the
content level allows it to incorporate high-level restoration in an objective
and self-sufficient way. The method has been applied to several degraded
document images, including the DIBCO'09 contest dataset with promising results.
|
1109.4928
|
RPA: Probabilistic analysis of probe performance and robust
summarization
|
cs.CE stat.AP stat.ML
|
Probe-level models have led to improved performance in microarray studies but
the various sources of probe-level contamination are still poorly understood.
Data-driven analysis of probe performance can be used to quantify the
uncertainty in individual probes and to highlight the relative contribution of
different noise sources. Improved understanding of the probe-level effects can
lead to improved preprocessing techniques and microarray design.
We have implemented probabilistic tools for probe performance analysis and
summarization on short oligonucleotide arrays. In contrast to standard
preprocessing approaches, the methods provide quantitative estimates of
probe-specific noise and affinity terms and tools to investigate these
parameters. Tools to incorporate prior information of the probes in the
analysis are provided as well. Comparisons to known probe-level error sources
and spike-in data sets validate the approach.
Implementation is freely available in R/BioConductor:
http://www.bioconductor.org/packages/release/bioc/html/RPA.html
|
1109.4960
|
Distributed Linear Parameter Estimation: Asymptotically Efficient
Adaptive Strategies
|
math.OC cs.SY math.PR math.ST stat.TH
|
The paper considers the problem of distributed adaptive linear parameter
estimation in multi-agent inference networks. Local sensing model information
is only partially available at the agents and inter-agent communication is
assumed to be unpredictable. The paper develops a generic mixed time-scale
stochastic procedure consisting of simultaneous distributed learning and
estimation, in which the agents adaptively assess their relative observation
quality over time and fuse the innovations accordingly. Under rather weak
assumptions on the statistical model and the inter-agent communication, it is
shown that, by properly tuning the consensus potential with respect to the
innovation potential, the asymptotic information rate loss incurred in the
learning process may be made negligible. As such, it is shown that the agent
estimates are asymptotically efficient, in that their asymptotic covariance
coincides with that of a centralized estimator (the inverse of the centralized
Fisher information rate for Gaussian systems) with perfect global model
information and having access to all observations at all times. The proof
techniques are mainly based on convergence arguments for non-Markovian mixed
time scale stochastic approximation procedures. Several approximation results
developed in the process are of independent interest.
|
1109.4979
|
Latent Semantic Learning with Structured Sparse Representation for Human
Action Recognition
|
cs.MM cs.AI cs.LG
|
This paper proposes a novel latent semantic learning method for extracting
high-level features (i.e. latent semantics) from a large vocabulary of abundant
mid-level features (i.e. visual keywords) with structured sparse
representation, which can help to bridge the semantic gap in the challenging
task of human action recognition. To discover the manifold structure of
midlevel features, we develop a spectral embedding approach to latent semantic
learning based on L1-graph, without the need to tune any parameter for graph
construction as a key step of manifold learning. More importantly, we construct
the L1-graph with structured sparse representation, which can be obtained by
structured sparse coding with its structured sparsity ensured by novel L1-norm
hypergraph regularization over mid-level features. In the new embedding space,
we learn latent semantics automatically from abundant mid-level features
through spectral clustering. The learnt latent semantics can be readily used
for human action recognition with SVM by defining a histogram intersection
kernel. Different from the traditional latent semantic analysis based on topic
models, our latent semantic learning method can explore the manifold structure
of mid-level features in both L1-graph construction and spectral embedding,
which results in compact but discriminative high-level features. The
experimental results on the commonly used KTH action dataset and unconstrained
YouTube action dataset show the superior performance of our method.
|
1109.4994
|
The finite-state character of physical dynamics
|
quant-ph cs.IT gr-qc hep-th math-ph math.IT math.MP
|
Finite physical systems have only a finite amount of distinct state. This
finiteness is fundamental in statistical mechanics, where the maximum number of
distinct states compatible with macroscopic constraints defines entropy. Here
we show that finiteness of distinct state is similarly fundamental in ordinary
mechanics: energy and momentum are defined by the maximum number of distinct
states possible in a given time or distance. More generally, any moment of
energy or momentum bounds distinct states in time or space. These results
generalize both the Nyquist bandwidth-bound on distinct values in classical
signals, and quantum uncertainty bounds. The new certainty bounds are achieved
by finite-bandwidth evolutions in which time and space are effectively
discrete, including quantum evolutions that are effectively classical. Since
energy and momentum count distinct states, they are defined in finite-state
dynamics, and they relate classical mechanics to finite-state evolution.
|
1109.4995
|
Quantum emulation of classical dynamics
|
quant-ph cs.IT math.IT nlin.CG
|
In statistical mechanics, it is well known that finite-state classical
lattice models can be recast as quantum models, with distinct classical
configurations identified with orthogonal basis states. This mapping makes
classical statistical mechanics on a lattice a special case of quantum
statistical mechanics, and classical combinatorial entropy a special case of
quantum entropy.
In a similar manner, finite-state classical dynamics can be recast as
finite-energy quantum dynamics. This mapping translates continuous quantities,
concepts and machinery of quantum mechanics into a simplified finite-state
context in which they have a purely classical and combinatorial interpretation.
For example, in this mapping quantum average energy becomes the classical
update rate.
Interpolation theory and communication theory help explain the truce achieved
here between perfect classical determinism and quantum uncertainty, and between
discrete and continuous dynamics.
|
1109.5002
|
Alignment-free phylogenetic reconstruction: Sample complexity via a
branching process analysis
|
math.PR cs.CE cs.DS math.ST q-bio.PE stat.TH
|
We present an efficient phylogenetic reconstruction algorithm allowing
insertions and deletions which provably achieves a sequence-length requirement
(or sample complexity) growing polynomially in the number of taxa. Our
algorithm is distance-based, that is, it relies on pairwise sequence
comparisons. More importantly, our approach largely bypasses the difficult
problem of multiple sequence alignment.
|
1109.5005
|
Robust Linear Transceiver Design for Multi-Hop Non-Regenerative MIMO
Relaying Systems
|
cs.IT math.IT
|
In this paper, optimal linear transceiver designs for multi-hop
amplify-and-forward (AF) Multiple-input Multiple-out (MIMO) relaying systems
with Gaussian distributed channel estimation errors are investigated. Some
commonly used transceiver design criteria are unified into a single
matrix-variate optimization problem. With novel applications of majorization
theory and properties of matrix-variate function, the optimal structure of
robust transceiver is first derived. Based on the optimal structure, the
original transceiver design problems are reduced to much simpler problems with
only scalar variables whose solutions are readily obtained by iterative
water-filling algorithms. The performance advantages of the proposed robust
designs are demonstrated by the simulation results.
|
1109.5053
|
A New Approach to Design Graph Based Search Engine for Multiple Domains
Using Different Ontologies
|
cs.IR
|
Search Engine has become a major tool for searching any information from the
World Wide Web (WWW). While searching the huge digital library available in the
WWW, every effort is made to retrieve the most relevant results. But in WWW
majority of the Web pages are in HTML format and there are no such tags which
tells the crawler to find any specific domain. To find more relevant result we
use Ontology for that particular domain. If we are working with multiple
domains then we use multiple ontologies. Now in order to design a domain
specific search engine for multiple domains, crawler must crawl through the
domain specific Web pages in the WWW according to the predefined ontologies.
|
1109.5072
|
Analysis of first prototype universal intelligence tests: evaluating and
comparing AI algorithms and humans
|
cs.AI
|
Today, available methods that assess AI systems are focused on using
empirical techniques to measure the performance of algorithms in some specific
tasks (e.g., playing chess, solving mazes or land a helicopter). However, these
methods are not appropriate if we want to evaluate the general intelligence of
AI and, even less, if we compare it with human intelligence. The ANYNT project
has designed a new method of evaluation that tries to assess AI systems using
well known computational notions and problems which are as general as possible.
This new method serves to assess general intelligence (which allows us to learn
how to solve any new kind of problem we face) and not only to evaluate
performance on a set of specific tasks. This method not only focuses on
measuring the intelligence of algorithms, but also to assess any intelligent
system (human beings, animals, AI, aliens?,...), and letting us to place their
results on the same scale and, therefore, to be able to compare them. This new
approach will allow us (in the future) to evaluate and compare any kind of
intelligent system known or even to build/find, be it artificial or biological.
This master thesis aims at ensuring that this new method provides consistent
results when evaluating AI algorithms, this is done through the design and
implementation of prototypes of universal intelligence tests and their
application to different intelligent systems (AI algorithms and humans beings).
From the study we analyze whether the results obtained by two different
intelligent systems are properly located on the same scale and we propose
changes and refinements to these prototypes in order to, in the future, being
able to achieve a truly universal intelligence test.
|
1109.5078
|
Application of distances between terms for flat and hierarchical data
|
cs.LG
|
In machine learning, distance-based algorithms, and other approaches, use
information that is represented by propositional data. However, this kind of
representation can be quite restrictive and, in many cases, it requires more
complex structures in order to represent data in a more natural way. Terms are
the basis for functional and logic programming representation. Distances
between terms are a useful tool not only to compare terms, but also to
determine the search space in many of these applications. This dissertation
applies distances between terms, exploiting the features of each distance and
the possibility to compare from propositional data types to hierarchical
representations. The distances between terms are applied through the k-NN
(k-nearest neighbor) classification algorithm using XML as a common language
representation. To be able to represent these data in an XML structure and to
take advantage of the benefits of distance between terms, it is necessary to
apply some transformations. These transformations allow the conversion of flat
data into hierarchical data represented in XML, using some techniques based on
intuitive associations between the names and values of variables and
associations based on attribute similarity.
Several experiments with the distances between terms of Nienhuys-Cheng and
Estruch et al. were performed. In the case of originally propositional data,
these distances are compared to the Euclidean distance. In all cases, the
experiments were performed with the distance-weighted k-nearest neighbor
algorithm, using several exponents for the attraction function (weighted
distance). It can be seen that in some cases, the term distances can
significantly improve the results on approaches applied to flat
representations.
|
1109.5083
|
A Mathematical Approach to Balanced Tanner Graph Enumeration
|
cs.IT math.CO math.IT
|
This paper summarizes our latest understanding and results about the
application of the Mathematics Of Enumeration to Tanner Graphs that have a
regular structure called Balanced Tanner Graphs. Some preliminaries of
permutation groups have been presented followed by various enumeration
theorems, and finally our approach for enumeration of Balanced Tanner Graphs
has been explained, and several open questions have been raised.
|
1109.5114
|
Improvements on "Fast space-variant elliptical filtering using box
splines"
|
cs.CV
|
It is well-known that box filters can be efficiently computed using
pre-integrations and local finite-differences
[Crow1984,Heckbert1986,Viola2001]. By generalizing this idea and by combining
it with a non-standard variant of the Central Limit Theorem, a constant-time or
O(1) algorithm was proposed in [Chaudhury2010] that allowed one to perform
space-variant filtering using Gaussian-like kernels. The algorithm was based on
the observation that both isotropic and anisotropic Gaussians could be
approximated using certain bivariate splines called box splines. The attractive
feature of the algorithm was that it allowed one to continuously control the
shape and size (covariance) of the filter, and that it had a fixed
computational cost per pixel, irrespective of the size of the filter. The
algorithm, however, offered a limited control on the covariance and accuracy of
the Gaussian approximation. In this work, we propose some improvements by
appropriately modifying the algorithm in [Chaudhury2010].
|
1109.5120
|
Algorithms for Enumerating Balanced Tanner Graphs
|
cs.IT math.IT
|
This summarizes our latest understanding and results about the algorithms for
enumerating Tanner Graphs that have a regular structure called Balanced Tanner
Graphs. Enumeration algorithms for Balanced Tanner Graphs based upon Cyclic
Permutation Groups have been developed in this paper. A constrained enumeration
algorithm that enumerates Balanced Tanner Graphs that have a relatively larger
length of minimum cycle has been described.
|
1109.5222
|
Completion Time in Multi-Access Channel: An Information Theoretic
Perspective
|
cs.IT math.IT
|
In a multi-access channel, completion time refers to the number of channel
uses required for users, each with some given fixed bit pool, to complete the
transmission of all their data bits. In this paper, the characterization of the
completion time region is based on the concept of constrained rates, where
users' rates are defined over possibly different number of channel uses. An
information theoretic formulation of completion time is given and the
completion time region is then established for two-user Gaussian multi-access
channel, which, analogous to capacity region, characterizes all possible
trade-offs between users' completion times.
|
1109.5229
|
Distributed Algorithms for Optimal Power Flow Problem
|
math.OC cs.SY
|
Optimal power flow (OPF) is an important problem for power generation and it
is in general non-convex. With the employment of renewable energy, it will be
desirable if OPF can be solved very efficiently so its solution can be used in
real time. With some special network structure, e.g. trees, the problem has
been shown to have a zero duality gap and the convex dual problem yields the
optimal solution. In this paper, we propose a primal and a dual algorithm to
coordinate the smaller subproblems decomposed from the convexified OPF. We can
arrange the subproblems to be solved sequentially and cumulatively in a central
node or solved in parallel in distributed nodes. We test the algorithms on IEEE
radial distribution test feeders, some random tree-structured networks, and the
IEEE transmission system benchmarks. Simulation results show that the
computation time can be improved dramatically with our algorithms over the
centralized approach of solving the problem without decomposition, especially
in tree-structured problems. The computation time grows linearly with the
problem size with the cumulative approach while the distributed one can have
size-independent computation time.
|
1109.5231
|
Noise Tolerance under Risk Minimization
|
cs.LG
|
In this paper we explore noise tolerant learning of classifiers. We formulate
the problem as follows. We assume that there is an ${\bf unobservable}$
training set which is noise-free. The actual training set given to the learning
algorithm is obtained from this ideal data set by corrupting the class label of
each example. The probability that the class label of an example is corrupted
is a function of the feature vector of the example. This would account for most
kinds of noisy data one encounters in practice. We say that a learning method
is noise tolerant if the classifiers learnt with the ideal noise-free data and
with noisy data, both have the same classification accuracy on the noise-free
data. In this paper we analyze the noise tolerance properties of risk
minimization (under different loss functions), which is a generic method for
learning classifiers. We show that risk minimization under 0-1 loss function
has impressive noise tolerance properties and that under squared error loss is
tolerant only to uniform noise; risk minimization under other loss functions is
not noise tolerant. We conclude the paper with some discussion on implications
of these theoretical results.
|
1109.5235
|
Social Contagion Theory: Examining Dynamic Social Networks and Human
Behavior
|
cs.SI physics.soc-ph
|
Here, we review the research we have done on social contagion. We describe
the methods we have employed (and the assumptions they have entailed) in order
to examine several datasets with complementary strengths and weaknesses,
including the Framingham Heart Study, the National Longitudinal Study of
Adolescent Health, and other observational and experimental datasets that we
and others have collected. We describe the regularities that led us to propose
that human social networks may exhibit a "three degrees of influence" property,
and we review statistical approaches we have used to characterize
inter-personal influence with respect to phenomena as diverse as obesity,
smoking, cooperation, and happiness. We do not claim that this work is the
final word, but we do believe that it provides some novel, informative, and
stimulating evidence regarding social contagion in longitudinally followed
networks. Along with other scholars, we are working to develop new methods for
identifying causal effects using social network data, and we believe that this
area is ripe for statistical development as current methods have known and
often unavoidable limitations.
|
1109.5240
|
A Continuous Feedback Optimal Control based on Second-Variations for
Problems with Control Constraints
|
math.OC cs.SY
|
The paper describes a continuous second-variation algorithm to solve optimal
control problems where the control is defined on a closed set. A second order
expansion of a Lagrangian provides linear updates of the control to construct a
locally feedback optimal control of the problem. Since the process involves a
backward and a forward stage, which require storing trajectories, a method has
been devised to accurately store continuous solutions of ordinary differential
equations. Thanks to the continuous approach, the method adapts implicitly the
numerical time mesh. The novel method is demonstrated on bang-bang optimal
control problems, showing the suitability of the method to identify
automatically optimal switching points in the control.
|
1109.5241
|
Curse of dimensionality reduction in max-plus based approximation
methods: theoretical estimates and improved pruning algorithms
|
math.OC cs.SY
|
Max-plus based methods have been recently developed to approximate the value
function of possibly high dimensional optimal control problems. A critical step
of these methods consists in approximating a function by a supremum of a small
number of functions (max-plus "basis functions") taken from a prescribed
dictionary. We study several variants of this approximation problem, which we
show to be continuous versions of the facility location and $k$-center
combinatorial optimization problems, in which the connection costs arise from a
Bregman distance. We give theoretical error estimates, quantifying the number
of basis functions needed to reach a prescribed accuracy. We derive from our
approach a refinement of the curse of dimensionality free method introduced
previously by McEneaney, with a higher accuracy for a comparable computational
cost.
|
1109.5278
|
Controlling the degree of caution in statistical inference with the
Bayesian and frequentist approaches as opposite extremes
|
math.ST cs.IT math.IT stat.ME stat.TH
|
In statistical practice, whether a Bayesian or frequentist approach is used
in inference depends not only on the availability of prior information but also
on the attitude taken toward partial prior information, with frequentists
tending to be more cautious than Bayesians. The proposed framework defines that
attitude in terms of a specified amount of caution, thereby enabling data
analysis at the level of caution desired and on the basis of any prior
information. The caution parameter represents the attitude toward partial prior
information in much the same way as a loss function represents the attitude
toward risk. When there is very little prior information and nonzero caution,
the resulting inferences correspond to those of the candidate confidence
intervals and p-values that are most similar to the credible intervals and
hypothesis probabilities of the specified Bayesian posterior. On the other
hand, in the presence of a known physical distribution of the parameter,
inferences are based only on the corresponding physical posterior. In those
extremes of either negligible prior information or complete prior information,
inferences do not depend on the degree of caution. Partial prior information
between those two extremes leads to intermediate inferences that are more
frequentistic to the extent that the caution is high and more Bayesian to the
extent that the caution is low.
|
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