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1108.4940
|
Quantum rate distortion, reverse Shannon theorems, and source-channel
separation
|
quant-ph cs.IT math.IT
|
We derive quantum counterparts of two key theorems of classical information
theory, namely, the rate distortion theorem and the source-channel separation
theorem. The rate-distortion theorem gives the ultimate limits on lossy data
compression, and the source-channel separation theorem implies that a two-stage
protocol consisting of compression and channel coding is optimal for
transmitting a memoryless source over a memoryless channel. In spite of their
importance in the classical domain, there has been surprisingly little work in
these areas for quantum information theory. In the present paper, we prove that
the quantum rate distortion function is given in terms of the regularized
entanglement of purification. We also determine a single-letter expression for
the entanglement-assisted quantum rate distortion function, and we prove that
it serves as a lower bound on the unassisted quantum rate distortion function.
This implies that the unassisted quantum rate distortion function is
non-negative and generally not equal to the coherent information between the
source and distorted output (in spite of Barnum's conjecture that the coherent
information would be relevant here). Moreover, we prove several quantum
source-channel separation theorems. The strongest of these are in the
entanglement-assisted setting, in which we establish a necessary and sufficient
codition for transmitting a memoryless source over a memoryless quantum channel
up to a given distortion.
|
1108.4942
|
Making Use of Advances in Answer-Set Programming for Abstract
Argumentation Systems
|
cs.AI
|
Dung's famous abstract argumentation frameworks represent the core formalism
for many problems and applications in the field of argumentation which
significantly evolved within the last decade. Recent work in the field has thus
focused on implementations for these frameworks, whereby one of the main
approaches is to use Answer-Set Programming (ASP). While some of the
argumentation semantics can be nicely expressed within the ASP language, others
required rather cumbersome encoding techniques. Recent advances in ASP systems,
in particular, the metasp optimization frontend for the ASP-package
gringo/claspD provides direct commands to filter answer sets satisfying certain
subset-minimality (or -maximality) constraints. This allows for much simpler
encodings compared to the ones in standard ASP language. In this paper, we
experimentally compare the original encodings (for the argumentation semantics
based on preferred, semi-stable, and respectively, stage extensions) with new
metasp encodings. Moreover, we provide novel encodings for the recently
introduced resolution-based grounded semantics. Our experimental results
indicate that the metasp approach works well in those cases where the
complexity of the encoded problem is adequately mirrored within the metasp
approach.
|
1108.4961
|
Non-trivial two-armed partial-monitoring games are bandits
|
cs.LG
|
We consider online learning in partial-monitoring games against an oblivious
adversary. We show that when the number of actions available to the learner is
two and the game is nontrivial then it is reducible to a bandit-like game and
thus the minimax regret is $\Theta(\sqrt{T})$.
|
1108.4973
|
Learning from Complex Systems: On the Roles of Entropy and Fisher
Information in Pairwise Isotropic Gaussian Markov Random Fields
|
cs.IT cs.AI cs.CV math.IT stat.CO
|
Markov Random Field models are powerful tools for the study of complex
systems. However, little is known about how the interactions between the
elements of such systems are encoded, especially from an information-theoretic
perspective. In this paper, our goal is to enlight the connection between
Fisher information, Shannon entropy, information geometry and the behavior of
complex systems modeled by isotropic pairwise Gaussian Markov random fields. We
propose analytical expressions to compute local and global versions of these
measures using Besag's pseudo-likelihood function, characterizing the system's
behavior through its \emph{Fisher curve}, a parametric trajectory accross the
information space that provides a geometric representation for the study of
complex systems. Computational experiments show how the proposed tools can be
useful in extrating relevant information from complex patterns. The obtained
results quantify and support our main conclusion, which is: in terms of
information, moving towards higher entropy states (A --> B) is different from
moving towards lower entropy states (B --> A), since the \emph{Fisher curves}
are not the same given a natural orientation (the direction of time).
|
1108.4982
|
Synthesis of anisotropic suboptimal controllers by convex optimization
|
cs.SY math.OC
|
This paper considers a disturbance attenuation problem for a linear discrete
time invariant system under random disturbances with imprecisely known
probability distributions. The statistical uncertainty is measured in terms of
relative entropy using the mean anisotropy functional. The disturbance
attenuation capabilities of the system are quantified by the anisotropic norm
which is a stochastic counterpart of the H-infinity norm. The designed
anisotropic suboptimal controller generally is a dynamic fixed-order
output-feedback compensator which is required to stabilize the closed-loop
system and keep its anisotropic norm below a prescribed threshold value.
|
1108.5002
|
Verbal Characterization of Probabilistic Clusters using Minimal
Discriminative Propositions
|
cs.AI
|
In a knowledge discovery process, interpretation and evaluation of the mined
results are indispensable in practice. In the case of data clustering, however,
it is often difficult to see in what aspect each cluster has been formed. This
paper proposes a method for automatic and objective characterization or
"verbalization" of the clusters obtained by mixture models, in which we collect
conjunctions of propositions (attribute-value pairs) that help us interpret or
evaluate the clusters. The proposed method provides us with a new, in-depth and
consistent tool for cluster interpretation/evaluation, and works for various
types of datasets including continuous attributes and missing values.
Experimental results with a couple of standard datasets exhibit the utility of
the proposed method, and the importance of the feedbacks from the
interpretation/evaluation step.
|
1108.5016
|
Une analyse bas\'ee sur la S-DRT pour la mod\'elisation de dialogues
pathologiques
|
cs.CL cs.AI
|
In this article, we present a corpus of dialogues between a schizophrenic
speaker and an interlocutor who drives the dialogue. We had identified specific
discontinuities for paranoid schizophrenics. We propose a modeling of these
discontinuities with S-DRT (its pragmatic part)
|
1108.5017
|
Event in Compositional Dynamic Semantics
|
cs.CL cs.AI cs.LO
|
We present a framework which constructs an event-style dis- course semantics.
The discourse dynamics are encoded in continuation semantics and various
rhetorical relations are embedded in the resulting interpretation of the
framework. We assume discourse and sentence are distinct semantic objects, that
play different roles in meaning evalua- tion. Moreover, two sets of composition
functions, for handling different discourse relations, are introduced. The
paper first gives the necessary background and motivation for event and dynamic
semantics, then the framework with detailed examples will be introduced.
|
1108.5019
|
Prescribing the motion of a set of particles in a 3D perfect fluid
|
math.AP cs.SY math.OC
|
We establish a result concerning the so-called Lagrangian controllability of
the Euler equation for incompressible perfect fluids in dimension 3. More
precisely we consider a connected bounded domain of R^3 and two smooth
contractible sets of fluid particles, surrounding the same volume. We prove
that given any initial velocity field, one can find a boundary control and a
time interval such that the corresponding solution of the Euler equation makes
the first of the two sets approximately reach the second one.
|
1108.5025
|
Robust Stackelberg game in communication systems
|
cs.IT cs.GT math.IT
|
This paper studies multi-user communication systems with two groups of users:
leaders which possess system information, and followers which have no system
information using the formulation of Stackelberg games. In such games, the
leaders play and choose their actions based on their information about the
system and the followers choose their actions myopically according to their
observations of the aggregate impact of other users. However, obtaining the
exact value of these parameters is not practical in communication systems. To
study the effect of uncertainty and preserve the players' utilities in these
conditions, we introduce a robust equilibrium for Stackelberg games. In this
framework, the leaders' information and the followers' observations are
uncertain parameters, and the leaders and the followers choose their actions by
solving the worst-case robust optimizations. We show that the followers'
uncertain parameters always increase the leaders' utilities and decrease the
followers' utilities. Conversely, the leaders' uncertain information reduces
the leaders' utilities and increases the followers' utilities. We illustrate
our theoretical results with the numerical results obtained based on the power
control games in the interference channels.
|
1108.5027
|
Encoding Phases using Commutativity and Non-commutativity in a Logical
Framework
|
cs.CL cs.AI cs.LO
|
This article presents an extension of Minimalist Categorial Gram- mars (MCG)
to encode Chomsky's phases. These grammars are based on Par- tially Commutative
Logic (PCL) and encode properties of Minimalist Grammars (MG) of Stabler. The
first implementation of MCG were using both non- commutative properties (to
respect the linear word order in an utterance) and commutative ones (to model
features of different constituents). Here, we pro- pose to adding Chomsky's
phases with the non-commutative tensor product of the logic. Then we could give
account of the PIC just by using logical prop- erties of the framework.
|
1108.5037
|
Orthonormal Expansion l1-Minimization Algorithms for Compressed Sensing
|
cs.IT cs.SY math.IT math.OC
|
Compressed sensing aims at reconstructing sparse signals from significantly
reduced number of samples, and a popular reconstruction approach is
$\ell_1$-norm minimization. In this correspondence, a method called orthonormal
expansion is presented to reformulate the basis pursuit problem for noiseless
compressed sensing. Two algorithms are proposed based on convex optimization:
one exactly solves the problem and the other is a relaxed version of the first
one. The latter can be considered as a modified iterative soft thresholding
algorithm and is easy to implement. Numerical simulation shows that, in dealing
with noise-free measurements of sparse signals, the relaxed version is
accurate, fast and competitive to the recent state-of-the-art algorithms. Its
practical application is demonstrated in a more general case where signals of
interest are approximately sparse and measurements are contaminated with noise.
|
1108.5052
|
On the Quality of Wireless Network Connectivity
|
cs.NI cs.IT math.IT
|
Despite intensive research in the area of network connectivity, there is an
important category of problems that remain unsolved: how to measure the quality
of connectivity of a wireless multi-hop network which has a realistic number of
nodes, not necessarily large enough to warrant the use of asymptotic analysis,
and has unreliable connections, reflecting the inherent unreliable
characteristics of wireless communications? The quality of connectivity
measures how easily and reliably a packet sent by a node can reach another
node. It complements the use of \emph{capacity} to measure the quality of a
network in saturated traffic scenarios and provides a native measure of the
quality of (end-to-end) network connections. In this paper, we explore the use
of probabilistic connectivity matrix as a possible tool to measure the quality
of network connectivity. Some interesting properties of the probabilistic
connectivity matrix and their connections to the quality of connectivity are
demonstrated. We argue that the largest eigenvalue of the probabilistic
connectivity matrix can serve as a good measure of the quality of network
connectivity.
|
1108.5095
|
RBO Protocol: Broadcasting Huge Databases for Tiny Receivers
|
cs.DS cs.DB cs.DC cs.DM cs.NI
|
We propose a protocol (called RBO) for broadcasting long streams of
single-packet messages over radio channel for tiny, battery powered, receivers.
The messages are labeled by the keys from some linearly ordered set. The sender
repeatedly broadcasts a sequence of many (possibly millions) of messages, while
each receiver is interested in reception of a message with a specified key
within this sequence. The transmission is arranged so that the receiver can
wake up in arbitrary moment and find the nearest transmission of its searched
message. Even if it does not know the position of the message in the sequence,
it needs only to receive a small number of (the headers of) other messages to
locate it properly. Thus it can save energy by keeping the radio switched off
most of the time. We show that bit-reversal permutation has "recursive
bisection properties" and, as a consequence, RBO can be implemented very
efficiently with only constant number of $\log_2 n$-bit variables, where $n$ is
the total number of messages in the sequence. The total number of the required
receptions is at most $2\log_2 n +2$ in the model with perfect synchronization.
The basic procedure of RBO (computation of the time slot for the next required
reception) requires only $O(\log^3 n)$ bit-wise operations. We propose
implementation mechanisms for realistic model (with imperfect synchronization),
for operating systems (such as e.g. TinyOS).
|
1108.5096
|
Minimalist Grammars and Minimalist Categorial Grammars, definitions
toward inclusion of generated languages
|
cs.CL
|
Stabler proposes an implementation of the Chomskyan Minimalist Program,
Chomsky 95 with Minimalist Grammars - MG, Stabler 97. This framework inherits a
long linguistic tradition. But the semantic calculus is more easily added if
one uses the Curry-Howard isomorphism. Minimalist Categorial Grammars - MCG,
based on an extension of the Lambek calculus, the mixed logic, were introduced
to provide a theoretically-motivated syntax-semantics interface, Amblard 07. In
this article, we give full definitions of MG with algebraic tree descriptions
and of MCG, and take the first steps towards giving a proof of inclusion of
their generated languages.
|
1108.5104
|
Improved Linear Programming Bounds on Sizes of Constant-Weight Codes
|
cs.IT math.IT
|
Let $A(n,d,w)$ be the largest possible size of an $(n,d,w)$ constant-weight
binary code. By adding new constraints to Delsarte linear programming, we
obtain twenty three new upper bounds on $A(n,d,w)$ for $n \leq 28$. The used
techniques allow us to give a simple proof of an important theorem of Delsarte
which makes linear programming possible for binary codes.
|
1108.5128
|
Digital Self Triggered Robust Control of Nonlinear Systems
|
math.OC cs.SY
|
In this paper we develop novel results on self triggering control of
nonlinear systems, subject to perturbations and actuation delays. First,
considering an unperturbed nonlinear system with bounded actuation delays, we
provide conditions that guarantee the existence of a self triggering control
strategy stabilizing the closed--loop system. Then, considering parameter
uncertainties, disturbances, and bounded actuation delays, we provide
conditions guaranteeing the existence of a self triggering strategy, that keeps
the state arbitrarily close to the equilibrium point. In both cases, we provide
a methodology for the computation of the next execution time. We show on an
example the relevant benefits obtained with this approach, in terms of energy
consumption, with respect to control algorithms based on a constant sampling,
with a sensible reduction of the average sampling time.
|
1108.5140
|
A convex formulation of strict anisotropic norm bounded real lemma
|
cs.SY math.OC
|
This paper is aimed at extending the H-infinity Bounded Real Lemma to
stochastic systems under random disturbances with imprecisely known probability
distributions. The statistical uncertainty is measured in entropy theoretic
terms using the mean anisotropy functional. The disturbance attenuation
capabilities of the system are quantified by the anisotropic norm which is a
stochastic counterpart of the H-infinity norm. A state-space sufficient
criterion for the anisotropic norm of a linear discrete time invariant system
to be bounded by a given threshold value is derived. The resulting Strict
Anisotropic Norm Bounded Real Lemma involves an inequality on the determinant
of a positive definite matrix and a linear matrix inequality. It is shown that
slight reformulation of these conditions allows the anisotropic norm of a
system to be efficiently computed via convex optimization.
|
1108.5147
|
To Switch or Not To Switch: Understanding Social Influence in
Recommender Systems
|
cs.CY cs.HC cs.SI physics.soc-ph
|
We designed and ran an experiment to test how often people's choices are
reversed by others' recommendations when facing different levels of
confirmation and conformity pressures. In our experiment participants were
first asked to provide their preferences between pairs of items. They were then
asked to make second choices about the same pairs with knowledge of others'
preferences. Our results show that others people's opinions significantly sway
people's own choices. The influence is stronger when people are required to
make their second decision sometime later (22.4%) than immediately (14.1%).
Moreover, people are most likely to reverse their choices when facing a
moderate number of opposing opinions. Finally, the time people spend making the
first decision significantly predicts whether they will reverse their decisions
later on, while demographics such as age and gender do not. These results have
implications for consumer behavior research as well as online marketing
strategies.
|
1108.5192
|
Positivity of the English language
|
physics.soc-ph cs.CL
|
Over the last million years, human language has emerged and evolved as a
fundamental instrument of social communication and semiotic representation.
People use language in part to convey emotional information, leading to the
central and contingent questions: (1) What is the emotional spectrum of natural
language? and (2) Are natural languages neutrally, positively, or negatively
biased? Here, we report that the human-perceived positivity of over 10,000 of
the most frequently used English words exhibits a clear positive bias. More
deeply, we characterize and quantify distributions of word positivity for four
large and distinct corpora, demonstrating that their form is broadly invariant
with respect to frequency of word use.
|
1108.5212
|
Deinterleaving Finite Memory Processes via Penalized Maximum Likelihood
|
cs.IT math.IT
|
We study the problem of deinterleaving a set of finite-memory (Markov)
processes over disjoint finite alphabets, which have been randomly interleaved
by a finite-memory switch. The deinterleaver has access to a sample of the
resulting interleaved process, but no knowledge of the number or structure of
the component Markov processes, or of the switch. We study conditions for
uniqueness of the interleaved representation of a process, showing that certain
switch configurations, as well as memoryless component processes, can cause
ambiguities in the representation. We show that a deinterleaving scheme based
on minimizing a penalized maximum-likelihood cost function is strongly
consistent, in the sense of reconstructing, almost surely as the observed
sequence length tends to infinity, a set of component and switch Markov
processes compatible with the original interleaved process. Furthermore, under
certain conditions on the structure of the switch (including the special case
of a memoryless switch), we show that the scheme recovers \emph{all} possible
interleaved representations of the original process. Experimental results are
presented demonstrating that the proposed scheme performs well in practice,
even for relatively short input samples.
|
1108.5217
|
An Experimental Comparison of PMSPrune and Other Algorithms for Motif
Search
|
q-bio.QM cs.CE q-bio.GN
|
Extracting meaningful patterns from voluminous amount of biological data is a
very big challenge. Motifs are biological patterns of great interest to
biologists. Many different versions of the motif finding problem have been
identified by researchers. Examples include the Planted $(l, d)$ Motif version,
those based on position-specific score matrices, etc. A comparative study of
the various motif search algorithms is very important for several reasons. For
example, we could identify the strengths and weaknesses of each. As a result,
we might be able to devise hybrids that will perform better than the individual
components. In this paper we (either directly or indirectly) compare the
performance of PMSprune (an algorithm based on the $(l, d)$ motif model) and
several other algorithms in terms of seven measures and using well established
benchmarks
In this paper, we (directly or indirectly) compare the quality of motifs
predicted by PMSprune and 14 other algorithms. We have employed several
benchmark datasets including the one used by Tompa, et.al. These comparisons
show that the performance of PMSprune is competitive when compared to the other
14 algorithms tested.
We have compared (directly or indirectly) the performance of PMSprune and 14
other algorithms using the Benchmark dataset provided by Tompa, et.al. It is
observed that both PMSprune and DME (an algorithm based on position-specific
score matrices) in general perform better than the 13 algorithms reported in
Tompa et. al.. Subsequently we have compared PMSprune and DME on other
benchmark data sets including ChIP-Chip, ChIP-seq, and ABS. Between PMSprune
and DME, PMSprune performs better than DME on six measures. DME performs better
than PMSprune on one measure (namely, specificity).
|
1108.5248
|
Optimal Coalition Structures in Cooperative Graph Games
|
cs.GT cs.MA
|
Representation languages for coalitional games are a key research area in
algorithmic game theory. There is an inherent tradeoff between how general a
language is, allowing it to capture more elaborate games, and how hard it is
computationally to optimize and solve such games. One prominent such language
is the simple yet expressive Weighted Graph Games (WGGs) representation [14],
which maintains knowledge about synergies between agents in the form of an edge
weighted graph.
We consider the problem of finding the optimal coalition structure in WGGs.
The agents in such games are vertices in a graph, and the value of a coalition
is the sum of the weights of the edges present between coalition members. The
optimal coalition structure is a partition of the agents to coalitions, that
maximizes the sum of utilities obtained by the coalitions. We show that finding
the optimal coalition structure is not only hard for general graphs, but is
also intractable for restricted families such as planar graphs which are
amenable for many other combinatorial problems. We then provide algorithms with
constant factor approximations for planar, minor-free and bounded degree
graphs.
|
1108.5250
|
Single-trial EEG Discrimination between Wrist and Finger Movement
Imagery and Execution in a Sensorimotor BCI
|
cs.AI
|
A brain-computer interface (BCI) may be used to control a prosthetic or
orthotic hand using neural activity from the brain. The core of this
sensorimotor BCI lies in the interpretation of the neural information extracted
from electroencephalogram (EEG). It is desired to improve on the interpretation
of EEG to allow people with neuromuscular disorders to perform daily
activities. This paper investigates the possibility of discriminating between
the EEG associated with wrist and finger movements. The EEG was recorded from
test subjects as they executed and imagined five essential hand movements using
both hands. Independent component analysis (ICA) and time-frequency techniques
were used to extract spectral features based on event-related
(de)synchronisation (ERD/ERS), while the Bhattacharyya distance (BD) was used
for feature reduction. Mahalanobis distance (MD) clustering and artificial
neural networks (ANN) were used as classifiers and obtained average accuracies
of 65 % and 71 % respectively. This shows that EEG discrimination between wrist
and finger movements is possible. The research introduces a new combination of
motor tasks to BCI research.
|
1108.5253
|
A Frequent Closed Itemsets Lattice-based Approach for Mining Minimal
Non-Redundant Association Rules
|
cs.DB
|
There are many algorithms developed for improvement the time of mining
frequent itemsets (FI) or frequent closed itemsets (FCI). However, the
algorithms which deal with the time of generating association rules were not
put in deep research. In reality, in case of a database containing many FI/FCI
(from ten thousands up to millions), the time of generating association rules
is much larger than that of mining FI/FCI. Therefore, this paper presents an
application of frequent closed itemsets lattice (FCIL) for mining minimal
non-redundant association rules (MNAR) to reduce a lot of time for generating
rules. Firstly, we use CHARM-L for building FCIL. After that, based on FCIL, an
algorithm for fast generating MNAR will be proposed. Experimental results show
that the proposed algorithm is much faster than frequent itemsets lattice-based
algorithm in the mining time.
|
1108.5316
|
Link Failure Detection in Multi-hop Control Networks
|
math.OC cs.NI cs.SY
|
A Multi-hop Control Network (MCN) consists of a plant where the communication
between sensors, actuators and computational unit is supported by a wireless
multi-hop communication network, and data flow is performed using scheduling
and routing of sensing and actuation data. We characterize the problem of
detecting the failure of links of the radio connectivity graph and provide
necessary and sufficient conditions on the plant dynamics and on the
communication protocol. We also provide a methodology to \emph{explicitly}
design the network topology, scheduling and routing of a communication protocol
in order to satisfy the above conditions.
|
1108.5355
|
A tale of many cities: universal patterns in human urban mobility
|
physics.soc-ph cs.SI
|
The advent of geographic online social networks such as Foursquare, where
users voluntarily signal their current location, opens the door to powerful
studies on human movement. In particular the fine granularity of the location
data, with GPS accuracy down to 10 meters, and the worldwide scale of
Foursquare adoption are unprecedented. In this paper we study urban mobility
patterns of people in several metropolitan cities around the globe by analyzing
a large set of Foursquare users. Surprisingly, while there are variations in
human movement in different cities, our analysis shows that those are
predominantly due to different distributions of places across different urban
environments. Moreover, a universal law for human mobility is identified, which
isolates as a key component the rank-distance, factoring in the number of
places between origin and destination, rather than pure physical distance, as
considered in some previous works. Building on our findings, we also show how a
rank-based movement model accurately captures real human movements in different
cities. Our results shed new light on the driving factors of urban human
mobility, with potential applications for urban planning, location-based
advertisement and even social studies.
|
1108.5359
|
Solving Principal Component Pursuit in Linear Time via $l_1$ Filtering
|
cs.NA cs.CV
|
In the past decades, exactly recovering the intrinsic data structure from
corrupted observations, which is known as robust principal component analysis
(RPCA), has attracted tremendous interests and found many applications in
computer vision. Recently, this problem has been formulated as recovering a
low-rank component and a sparse component from the observed data matrix. It is
proved that under some suitable conditions, this problem can be exactly solved
by principal component pursuit (PCP), i.e., minimizing a combination of nuclear
norm and $l_1$ norm. Most of the existing methods for solving PCP require
singular value decompositions (SVD) of the data matrix, resulting in a high
computational complexity, hence preventing the applications of RPCA to very
large scale computer vision problems. In this paper, we propose a novel
algorithm, called $l_1$ filtering, for \emph{exactly} solving PCP with an
$O(r^2(m+n))$ complexity, where $m\times n$ is the size of data matrix and $r$
is the rank of the matrix to recover, which is supposed to be much smaller than
$m$ and $n$. Moreover, $l_1$ filtering is \emph{highly parallelizable}. It is
the first algorithm that can \emph{exactly} solve a nuclear norm minimization
problem in \emph{linear time} (with respect to the data size). Experiments on
both synthetic data and real applications testify to the great advantage of
$l_1$ filtering in speed over state-of-the-art algorithms.
|
1108.5387
|
Un metodo estable para la evaluacion de la complejidad algoritmica de
cadenas cortas
|
cs.CC cs.IT math.IT
|
It is discussed and surveyed a numerical method proposed before, that
alternative to the usual compression method, provides an approximation to the
algorithmic (Kolmogorov) complexity, particularly useful for short strings for
which compression methods simply fail. The method shows to be stable enough and
useful to conceive and compare patterns in an algorithmic models. (article in
Spanish)
|
1108.5395
|
Noise Covariance Properties in Dual-Tree Wavelet Decompositions
|
math.ST cs.CV stat.TH
|
Dual-tree wavelet decompositions have recently gained much popularity, mainly
due to their ability to provide an accurate directional analysis of images
combined with a reduced redundancy. When the decomposition of a random process
is performed -- which occurs in particular when an additive noise is corrupting
the signal to be analyzed -- it is useful to characterize the statistical
properties of the dual-tree wavelet coefficients of this process. As dual-tree
decompositions constitute overcomplete frame expansions, correlation structures
are introduced among the coefficients, even when a white noise is analyzed. In
this paper, we show that it is possible to provide an accurate description of
the covariance properties of the dual-tree coefficients of a wide-sense
stationary process. The expressions of the (cross-)covariance sequences of the
coefficients are derived in the one and two-dimensional cases. Asymptotic
results are also provided, allowing to predict the behaviour of the
second-order moments for large lag values or at coarse resolution. In addition,
the cross-correlations between the primal and dual wavelets, which play a
primary role in our theoretical analysis, are calculated for a number of
classical wavelet families. Simulation results are finally provided to validate
these results.
|
1108.5397
|
Prediction of peptide bonding affinity: kernel methods for nonlinear
modeling
|
stat.ML cs.LG q-bio.QM
|
This paper presents regression models obtained from a process of blind
prediction of peptide binding affinity from provided descriptors for several
distinct datasets as part of the 2006 Comparative Evaluation of Prediction
Algorithms (COEPRA) contest. This paper finds that kernel partial least
squares, a nonlinear partial least squares (PLS) algorithm, outperforms PLS,
and that the incorporation of transferable atom equivalent features improves
predictive capability.
|
1108.5431
|
Providing information can be a stable non-cooperative evolutionary
strategy
|
q-bio.PE cs.NE
|
Human language is still an embarrassment for evolutionary theory, as the
speaker's benefit remains unclear. The willingness to communicate information
is shown here to be an evolutionary stable strategy (ESS), even if acquiring
original information from the environment involves significant cost and
communicating it provides no material benefit to addressees. In this study,
communication is used to advertise the emitter's ability to obtain novel
information. We found that communication strategies can take two forms,
competitive and uniform, that these two strategies are stable and that they
necessarily coexist.
|
1108.5450
|
Deterministic multidimensional growth model for small-world networks
|
physics.data-an cs.SI
|
We proposed a deterministic multidimensional growth model for small-world
networks. The model can characterize the distinguishing properties of many
real-life networks with geometric space structure. Our results show the model
possesses small-world effect: larger clustering coefficient and smaller
characteristic path length. We also obtain some accurate results for its
properties including degree distribution, clustering coefficient and network
diameter and discuss them. It is also worth noting that we get an accurate
analytical expression for calculating the characteristic path length. We verify
numerically and experimentally these main features.
|
1108.5451
|
A Uniform Fixpoint Approach to the Implementation of Inference Methods
for Deductive Databases
|
cs.DB
|
Within the research area of deductive databases three different database
tasks have been deeply investigated: query evaluation, update propagation and
view updating. Over the last thirty years various inference mechanisms have
been proposed for realizing these main functionalities of a rule-based system.
However, these inference mechanisms have been rarely used in commercial DB
systems until now. One important reason for this is the lack of a uniform
approach well-suited for implementation in an SQL-based system. In this paper,
we present such a uniform approach in form of a new version of the soft
consequence operator. Additionally, we present improved transformation-based
approaches to query optimization and update propagation and view updating which
are all using this operator as underlying evaluation mechanism.
|
1108.5460
|
Personalized Web Services for Web Information Extraction
|
cs.IR
|
The field of information extraction from the Web emerged with the growth of
the Web and the multiplication of online data sources. This paper is an
analysis of information extraction methods. It presents a service oriented
approach for web information extraction considering both web data management
and extraction services. Then we propose an SOA based architecture to enhance
flexibility and on-the-fly modification of web extraction services. An
implementation of the proposed architecture is proposed on the middleware level
of Java Enterprise Edition (JEE) servers.
|
1108.5475
|
The Dimension of Subcode-Subfields of Shortened Generalized Reed Solomon
Codes
|
cs.IT math.IT
|
Reed-Solomon (RS) codes are among the most ubiquitous codes due to their good
parameters as well as efficient encoding and decoding procedures. However, RS
codes suffer from having a fixed length. In many applications where the length
is static, the appropriate length can be obtained by an RS code by shortening
or puncturing. Generalized Reed-Solomon (GRS) codes are a generalization of RS
codes, whose subfield-subcodes are extensively studied. In this paper we show
that a particular class of GRS codes produces many subfield-subcodes with large
dimension. An algorithm for searching through the codes is presented as well as
a list of new codes obtained from this method.
|
1108.5491
|
Improving Ranking Using Quantum Probability
|
cs.IR cs.ET cs.LG physics.data-an
|
The paper shows that ranking information units by quantum probability differs
from ranking them by classical probability provided the same data used for
parameter estimation. As probability of detection (also known as recall or
power) and probability of false alarm (also known as fallout or size) measure
the quality of ranking, we point out and show that ranking by quantum
probability yields higher probability of detection than ranking by classical
probability provided a given probability of false alarm and the same parameter
estimation data. As quantum probability provided more effective detectors than
classical probability within other domains that data management, we conjecture
that, the system that can implement subspace-based detectors shall be more
effective than a system which implements a set-based detectors, the
effectiveness being calculated as expected recall estimated over the
probability of detection and expected fallout estimated over the probability of
false alarm.
|
1108.5505
|
Event-triggered and self-triggered stabilization of distributed
networked control systems
|
math.OC cs.SY
|
Event-triggered and self-triggered control have recently been proposed as
implementation strategies that considerably reduce the resources required for
control. Although most of the work so far has focused on closing a single
control loop, some researchers have started to investigate how these new
implementation strategies can be applied when closing multiple-feedback loops
in the presence of physically distributed sensors and actuators. In this paper,
we consider a scenario where the distributed sensors, actuators, and
controllers communicate via a shared wired channel. We use our recent
prescriptive framework for the event-triggered control of nonlinear systems to
develop novel policies suitable for the considered distributed scenario.
Afterwards, we explain how self-triggering rules can be deduced from the
developed event-triggered strategies.
|
1108.5514
|
Strategic Learning and Robust Protocol Design for Online Communities
with Selfish Users
|
cs.LG cs.GT cs.SI
|
This paper focuses on analyzing the free-riding behavior of self-interested
users in online communities. Hence, traditional optimization methods for
communities composed of compliant users such as network utility maximization
cannot be applied here. In our prior work, we show how social reciprocation
protocols can be designed in online communities which have populations
consisting of a continuum of users and are stationary under stochastic
permutations. Under these assumptions, we are able to prove that users
voluntarily comply with the pre-determined social norms and cooperate with
other users in the community by providing their services. In this paper, we
generalize the study by analyzing the interactions of self-interested users in
online communities with finite populations and are not stationary. To optimize
their long-term performance based on their knowledge, users adapt their
strategies to play their best response by solving individual stochastic control
problems. The best-response dynamic introduces a stochastic dynamic process in
the community, in which the strategies of users evolve over time. We then
investigate the long-term evolution of a community, and prove that the
community will converge to stochastically stable equilibria which are stable
against stochastic permutations. Understanding the evolution of a community
provides protocol designers with guidelines for designing social norms in which
no user has incentives to adapt its strategy and deviate from the prescribed
protocol, thereby ensuring that the adopted protocol will enable the community
to achieve the optimal social welfare.
|
1108.5515
|
Robustness of a Tree-like Network of Interdependent Networks
|
physics.data-an cs.SI physics.soc-ph
|
In reality, many real-world networks interact with and depend on other
networks. We develop an analytical framework for studying interacting networks
and present an exact percolation law for a network of $n$ interdependent
networks (NON). We present a general framework to study the dynamics of the
cascading failures process at each step caused by an initial failure occurring
in the NON system. We study and compare both $n$ coupled Erd\H{o}s-R\'{e}nyi
(ER) graphs and $n$ coupled random regular (RR) graphs. We found recently [Gao
et. al. arXive:1010.5829] that for an NON composed of $n$ ER networks each of
average degree $k$, the giant component, $P_{\infty}$, is given by
$P_{\infty}=p[1-\exp(-kP_{\infty})]^n$ where $1-p$ is the initial fraction of
removed nodes. Our general result coincides for $n=1$ with the known
Erd\H{o}s-R\'{e}nyi second-order phase transition at a threshold, $p=p_c$, for
a single network. For $n=2$ the general result for $P_{\infty}$ corresponds to
the $n=2$ result [Buldyrev et. al., Nature, 464, (2010)]. Similar to the ER
NON, for $n=1$ the percolation transition at $p_c$, is of second order while
for any $n>1$ it is of first order. The first order percolation transition in
both ER and RR (for $n>1$) is accompanied by cascading failures between the
networks due to their interdependencies. However, we find that the robustness
of $n$ coupled RR networks of degree $k$ is dramatically higher compared to the
$n$ coupled ER networks of average degree $k$. While for ER NON there exists a
critical minimum average degree $k=k_{\min}$, that increases with $n$, below
which the system collapses, there is no such analogous $k_{\min}$ for RR NON
system.
|
1108.5520
|
A sentiment analysis of Singapore Presidential Election 2011 using
Twitter data with census correction
|
stat.AP cs.CL cs.SI
|
Sentiment analysis is a new area in text analytics where it focuses on the
analysis and understanding of the emotions from the text patterns. This new
form of analysis has been widely adopted in customer relation management
especially in the context of complaint management. With increasing level of
interest in this technology, more and more companies are adopting it and using
it to champion their marketing efforts. However, sentiment analysis using
twitter has remained extremely difficult to manage due to the sampling bias. In
this paper, we will discuss about the application of using reweighting
techniques in conjunction with online sentiment divisions to predict the vote
percentage that individual candidate will receive. There will be in depth
discussion about the various aspects using sentiment analysis to predict
outcomes as well as the potential pitfalls in the estimation due to the
anonymous nature of the internet.
|
1108.5533
|
A Remark on the Lasso and the Dantzig Selector
|
math.ST cs.IT math.FA math.IT stat.TH
|
This article investigates a new parameter for the high-dimensional regression
with noise: the distortion. This latter has attracted a lot of attention
recently with the appearance of new deterministic constructions of
'almost'-Euclidean sections of the L1-ball. It measures how far is the
intersection between the kernel of the design matrix and the unit L1-ball from
an L2-ball. We show that the distortion holds enough information to derive
oracle inequalities (i.e. a comparison to an ideal situation where one knows
the s largest coefficients of the target) for the lasso and the Dantzig
selector.
|
1108.5543
|
Multi-Robot Organisms: State of the Art
|
cs.RO cs.NE cs.SY
|
This paper represents the state of the art development on the field of
artificial multi-robot organisms. It briefly considers mechatronic development,
sensor and computational equipment, software framework and introduces one of
the Grand Challenges for swarm and reconfigurable robotics.
|
1108.5547
|
Instantons causing iterative decoding to cycle
|
cs.IT math.IT
|
It is speculated that the most probable channel noise realizations
(instantons) that cause the iterative decoding of low-density parity-check
codes to fail make the decoding not to converge. The Wiberg's formula is
generalized for the case when the part of a computational tree that contributes
to the output at its center is ambiguous. Two methods of finding the instantons
for large number of iterations are presented and tested on Tanner's [155, 64,
20] code and Gaussian channel. The inherently dynamic instanton with effective
distance of 11.475333 is found.
|
1108.5567
|
Parsing Combinatory Categorial Grammar with Answer Set Programming:
Preliminary Report
|
cs.AI cs.CL
|
Combinatory categorial grammar (CCG) is a grammar formalism used for natural
language parsing. CCG assigns structured lexical categories to words and uses a
small set of combinatory rules to combine these categories to parse a sentence.
In this work we propose and implement a new approach to CCG parsing that relies
on a prominent knowledge representation formalism, answer set programming (ASP)
- a declarative programming paradigm. We formulate the task of CCG parsing as a
planning problem and use an ASP computational tool to compute solutions that
correspond to valid parses. Compared to other approaches, there is no need to
implement a specific parsing algorithm using such a declarative method. Our
approach aims at producing all semantically distinct parse trees for a given
sentence. From this goal, normalization and efficiency issues arise, and we
deal with them by combining and extending existing strategies. We have
implemented a CCG parsing tool kit - AspCcgTk - that uses ASP as its main
computational means. The C&C supertagger can be used as a preprocessor within
AspCcgTk, which allows us to achieve wide-coverage natural language parsing.
|
1108.5575
|
Getting Beyond the State of the Art of Information Retrieval with
Quantum Theory
|
cs.IR cs.LG physics.data-an
|
According to the probability ranking principle, the document set with the
highest values of probability of relevance optimizes information retrieval
effectiveness given the probabilities are estimated as accurately as possible.
The key point of this principle is the separation of the document set into two
subsets with a given level of fallout and with the highest recall. If subsets
of set measures are replaced by subspaces and space measures, we obtain an
alternative theory stemming from Quantum Theory. That theory is named after
vector probability because vectors represent event like sets do in classical
probability. The paper shows that the separation into vector subspaces is more
effective than the separation into subsets with the same available evidence.
The result is proved mathematically and verified experimentally. In general,
the paper suggests that quantum theory is not only a source of rhetoric
inspiration, but is a sufficient condition to improve retrieval effectiveness
in a principled way.
|
1108.5586
|
FdConfig: A Constraint-Based Interactive Product Configurator
|
cs.AI
|
We present a constraint-based approach to interactive product configuration.
Our configurator tool FdConfig is based on feature models for the
representation of the product domain. Such models can be directly mapped into
constraint satisfaction problems and dealt with by appropriate constraint
solvers. During the interactive configuration process the user generates new
constraints as a result of his configuration decisions and even may retract
constraints posted earlier. We discuss the configuration process, explain the
underlying techniques and show optimizations.
|
1108.5592
|
A Performance Study of Data Mining Techniques: Multiple Linear
Regression vs. Factor Analysis
|
cs.DB
|
The growing volume of data usually creates an interesting challenge for the
need of data analysis tools that discover regularities in these data. Data
mining has emerged as disciplines that contribute tools for data analysis,
discovery of hidden knowledge, and autonomous decision making in many
application domains. The purpose of this study is to compare the performance of
two data mining techniques viz., factor analysis and multiple linear regression
for different sample sizes on three unique sets of data. The performance of the
two data mining techniques is compared on following parameters like mean square
error (MSE), R-square, R-Square adjusted, condition number, root mean square
error(RMSE), number of variables included in the prediction model, modified
coefficient of efficiency, F-value, and test of normality. These parameters
have been computed using various data mining tools like SPSS, XLstat, Stata,
and MS-Excel. It is seen that for all the given dataset, factor analysis
outperform multiple linear regression. But the absolute value of prediction
accuracy varied between the three datasets indicating that the data
distribution and data characteristics play a major role in choosing the correct
prediction technique.
|
1108.5593
|
Unsteady Hydromagnetic Flow of Viscoelastic Fluid down an Open Inclined
Channel
|
physics.flu-dyn cs.CE
|
In this paper, we study the unsteady hydromagnetic flow of a Walter's fluid
(Model B') down an open inclined channel of width 2a and depth d under gravity,
the walls of the channel being normal to the surface of the bottom under the
influence of a uniform transverse magnetic field. A uniform tangential stress
is applied at the free surface in the direction of flow. We have evaluated the
velocity distribution by using Laplace transform and finite Fourier Sine
transform technique. The velocity distribution has been obtained taking
different form of time dependent pressure gradient g(t), viz., i) constant ii)
exponential decreasing function of time and iii) Cosine function of time. The
effects of magnetic parameter M, Reynolds number R and the viscoelastic
parameter K are discussed on the velocity distribution in three different
cases.
|
1108.5619
|
Modification of GTD from Flat File Format to OLAP for Data Mining
|
cs.DB
|
This document is part of original research work by the authors in a bid to
explore new fields for applying Data Mining Techniques. The sample data is part
of a large data set from University of Maryland (UMD) and outlines how more
meaningful patterns can be discovered by preprocessing the data in the form of
OLAP cubes.
|
1108.5622
|
Optimization of Lyapunov Invariants in Verification of Software Systems
(Extended Version)
|
cs.SY cs.SE math.OC
|
The paper proposes a control-theoretic framework for verification of
numerical software systems, and puts forward software verification as an
important application of control and systems theory. The idea is to transfer
Lyapunov functions and the associated computational techniques from control
systems analysis and convex optimization to verification of various software
safety and performance specifications. These include but are not limited to
absence of overflow, absence of division-by-zero, termination in finite time,
presence of dead-code, and certain user-specified assertions. Central to this
framework are Lyapunov invariants. These are properly constructed functions of
the program variables, and satisfy certain properties-resembling those of
Lyapunov functions-along the execution trace. The search for the invariants can
be formulated as a convex optimization problem. If the associated optimization
problem is feasible, the result is a certificate for the specification.
|
1108.5624
|
Multi-Robot Searching Algorithm Using Levy Flight and Artificial
Potential Field
|
cs.RO cs.SY
|
An efficient search algorithm is very crucial in robotic area, especially for
exploration missions, where the target availability is unknown and the
condition of the environment is highly unpredictable. In a very large
environment, it is not sufficient to scan an area or volume by a single robot,
multiple robots should be involved to perform the collective exploration. In
this paper, we propose to combine bio-inspired search algorithm called Levy
flight and artificial potential field method to perform an efficient searching
algorithm for multi-robot applications. The main focus of this work is not only
to prove the concept or to measure the efficiency of the algorithm by
experiments, but also to develop an appropriate generic framework to be
implemented both in simulation and on real robotic platforms. Several
experiments, which compare different search algorithms, are also performed.
|
1108.5626
|
Nested HEX-Programs
|
cs.AI
|
Answer-Set Programming (ASP) is an established declarative programming
paradigm. However, classical ASP lacks subprogram calls as in procedural
programming, and access to external computations (like remote procedure calls)
in general. The feature is desired for increasing modularity and---assuming
proper access in place---(meta-)reasoning over subprogram results. While
HEX-programs extend classical ASP with external source access, they do not
support calls of (sub-)programs upfront. We present nested HEX-programs, which
extend HEX-programs to serve the desired feature, in a user-friendly manner.
Notably, the answer sets of called sub-programs can be individually accessed.
This is particularly useful for applications that need to reason over answer
sets like belief set merging, user-defined aggregate functions, or preferences
of answer sets.
|
1108.5643
|
Collective Adaptive Systems: Challenges Beyond Evolvability
|
cs.ET cs.CY cs.NE
|
This position paper overviews several challenges of collective adaptive
systems, which are beyond the research objectives of current top-projects in
ICT, and especially in FET, initiatives. The attention is paid not only to
challenges and new research topics, but also to their impact and potential
breakthroughs in information and communication technologies.
|
1108.5667
|
A prototype of a knowledge-based programming environment
|
cs.AI cs.LO
|
In this paper we present a proposal for a knowledge-based programming
environment. In such an environment, declarative background knowledge,
procedures, and concrete data are represented in suitable languages and
combined in a flexible manner. This leads to a highly declarative programming
style. We illustrate our approach on an example and report about our prototype
implementation.
|
1108.5668
|
Datum-Wise Classification: A Sequential Approach to Sparsity
|
cs.AI cs.LG
|
We propose a novel classification technique whose aim is to select an
appropriate representation for each datapoint, in contrast to the usual
approach of selecting a representation encompassing the whole dataset. This
datum-wise representation is found by using a sparsity inducing empirical risk,
which is a relaxation of the standard L 0 regularized risk. The classification
problem is modeled as a sequential decision process that sequentially chooses,
for each datapoint, which features to use before classifying. Datum-Wise
Classification extends naturally to multi-class tasks, and we describe a
specific case where our inference has equivalent complexity to a traditional
linear classifier, while still using a variable number of features. We compare
our classifier to classical L 1 regularized linear models (L 1-SVM and LARS) on
a set of common binary and multi-class datasets and show that for an equal
average number of features used we can get improved performance using our
method.
|
1108.5703
|
Web Pages Clustering: A New Approach
|
cs.IR
|
The rapid growth of web has resulted in vast volume of information.
Information availability at a rapid speed to the user is vital. English
language (or any for that matter) has lot of ambiguity in the usage of words.
So there is no guarantee that a keyword based search engine will provide the
required results. This paper introduces the use of dictionary (standardised) to
obtain the context with which a keyword is used and in turn cluster the results
based on this context. These ideas can be merged with a metasearch engine to
enhance the search efficiency.
|
1108.5710
|
Generalized Fast Approximate Energy Minimization via Graph Cuts:
Alpha-Expansion Beta-Shrink Moves
|
cs.CV cs.AI
|
We present alpha-expansion beta-shrink moves, a simple generalization of the
widely-used alpha-beta swap and alpha-expansion algorithms for approximate
energy minimization. We show that in a certain sense, these moves dominate both
alpha-beta-swap and alpha-expansion moves, but unlike previous generalizations
the new moves require no additional assumptions and are still solvable in
polynomial-time. We show promising experimental results with the new moves,
which we believe could be used in any context where alpha-expansions are
currently employed.
|
1108.5717
|
Structure Selection from Streaming Relational Data
|
cs.AI
|
Statistical relational learning techniques have been successfully applied in
a wide range of relational domains. In most of these applications, the human
designers capitalized on their background knowledge by following a
trial-and-error trajectory, where relational features are manually defined by a
human engineer, parameters are learned for those features on the training data,
the resulting model is validated, and the cycle repeats as the engineer adjusts
the set of features. This paper seeks to streamline application development in
large relational domains by introducing a light-weight approach that
efficiently evaluates relational features on pieces of the relational graph
that are streamed to it one at a time. We evaluate our approach on two social
media tasks and demonstrate that it leads to more accurate models that are
learned faster.
|
1108.5719
|
Computational topology for configuration spaces of hard disks
|
math.AT cs.RO math-ph math.MP
|
We explore the topology of configuration spaces of hard disks experimentally,
and show that several changes in the topology can already be observed with a
small number of particles. The results illustrate a theorem of Baryshnikov,
Bubenik, and Kahle that critical points correspond to configurations of disks
with balanced mechanical stresses, and suggest conjectures about the asymptotic
topology as the number of disks tends to infinity.
|
1108.5720
|
Conjugate Variables as a Resource in Signal and Image Processing
|
cs.CV physics.data-an quant-ph
|
In this paper we develop a new technique to model joint distributions of
signals. Our technique is based on quantum mechanical conjugate variables. We
show that the transition probability of quantum states leads to a distance
function on the signals. This distance function obeys the triangle inequality
on all quantum states and becomes a metric on pure quantum states. Treating
signals as conjugate variables allows us to create a new approach to segment
them.
Keywords: Quantum information, transition probability, Euclidean distance,
Fubini-study metric, Bhattacharyya coefficients, conjugate variable,
signal/sensor fusion, signal and image segmentation.
|
1108.5724
|
On the Stability of Linear Discrete-Time Fuzzy Systems
|
cs.SY math.OC
|
In this paper the linear and stationary Discrete-time systems with state
variables and dynamic coefficients represented by fuzzy numbers are studied,
providing some stability criteria, and characterizing the bounds of the set of
solutions in the case of positive systems.
|
1108.5756
|
Sensitivity And Out-Of-Sample Error in Continuous Time Data Assimilation
|
physics.ao-ph cs.SY math.OC
|
Data assimilation refers to the problem of finding trajectories of a
prescribed dynamical model in such a way that the output of the model (usually
some function of the model states) follows a given time series of observations.
Typically though, these two requirements cannot both be met at the same
time--tracking the observations is not possible without the trajectory
deviating from the proposed model equations, while adherence to the model
requires deviations from the observations. Thus, data assimilation faces a
trade-off. In this contribution, the sensitivity of the data assimilation with
respect to perturbations in the observations is identified as the parameter
which controls the trade-off. A relation between the sensitivity and the
out-of-sample error is established which allows to calculate the latter under
operational conditions. A minimum out-of-sample error is proposed as a
criterion to set an appropriate sensitivity and to settle the discussed
trade-off. Two approaches to data assimilation are considered, namely
variational data assimilation and Newtonian nudging, aka synchronisation.
Numerical examples demonstrate the feasibility of the approach.
|
1108.5781
|
Phase Transition in Distance-Based Phylogeny Reconstruction
|
math.PR cs.CE cs.DS math.ST q-bio.PE stat.TH
|
We introduce a new distance-based phylogeny reconstruction technique which
provably achieves, at sufficiently short branch lengths, a logarithmic
sequence-length requirement---improving significantly over previous polynomial
bounds for distance-based methods and matching existing results for general
methods. The technique is based on an averaging procedure that implicitly
reconstructs ancestral sequences.
In the same token, we extend previous results on phase transitions in
phylogeny reconstruction to general time-reversible models. More precisely, we
show that in the so-called Kesten-Stigum zone (roughly, a region of the
parameter space where ancestral sequences are well approximated by "linear
combinations" of the observed sequences) sequences of length $O(\log n)$
suffice for reconstruction when branch lengths are discretized. Here $n$ is the
number of extant species.
Our results challenge, to some extent, the conventional wisdom that estimates
of evolutionary distances alone carry significantly less information about
phylogenies than full sequence datasets.
|
1108.5784
|
Probability Ranking in Vector Spaces
|
cs.IR cs.LG
|
The Probability Ranking Principle states that the document set with the
highest values of probability of relevance optimizes information retrieval
effectiveness given the probabilities are estimated as accurately as possible.
The key point of the principle is the separation of the document set into two
subsets with a given level of fallout and with the highest recall. The paper
introduces the separation between two vector subspaces and shows that the
separation yields a more effective performance than the optimal separation into
subsets with the same available evidence, the performance being measured with
recall and fallout. The result is proved mathematically and exemplified
experimentally.
|
1108.5794
|
A Constraint Logic Programming Approach for Computing Ordinal
Conditional Functions
|
cs.AI
|
In order to give appropriate semantics to qualitative conditionals of the
form "if A then normally B", ordinal conditional functions (OCFs) ranking the
possible worlds according to their degree of plausibility can be used. An OCF
accepting all conditionals of a knowledge base R can be characterized as the
solution of a constraint satisfaction problem. We present a high-level,
declarative approach using constraint logic programming techniques for solving
this constraint satisfaction problem. In particular, the approach developed
here supports the generation of all minimal solutions; these minimal solutions
are of special interest as they provide a basis for model-based inference from
R.
|
1108.5825
|
Confidentiality-Preserving Data Publishing for Credulous Users by
Extended Abduction
|
cs.AI
|
Publishing private data on external servers incurs the problem of how to
avoid unwanted disclosure of confidential data. We study a problem of
confidentiality in extended disjunctive logic programs and show how it can be
solved by extended abduction. In particular, we analyze how credulous
non-monotonic reasoning affects confidentiality.
|
1108.5837
|
Translating Answer-Set Programs into Bit-Vector Logic
|
cs.AI cs.LO
|
Answer set programming (ASP) is a paradigm for declarative problem solving
where problems are first formalized as rule sets, i.e., answer-set programs, in
a uniform way and then solved by computing answer sets for programs. The
satisfiability modulo theories (SMT) framework follows a similar modelling
philosophy but the syntax is based on extensions of propositional logic rather
than rules. Quite recently, a translation from answer-set programs into
difference logic was provided---enabling the use of particular SMT solvers for
the computation of answer sets. In this paper, the translation is revised for
another SMT fragment, namely that based on fixed-width bit-vector theories.
Thus, even further SMT solvers can be harnessed for the task of computing
answer sets. The results of a preliminary experimental comparison are also
reported. They suggest a level of performance which is similar to that achieved
via difference logic.
|
1108.5838
|
Off-grid Direction of Arrival Estimation Using Sparse Bayesian Inference
|
stat.AP cs.IT math.IT stat.ML
|
Direction of arrival (DOA) estimation is a classical problem in signal
processing with many practical applications. Its research has recently been
advanced owing to the development of methods based on sparse signal
reconstruction. While these methods have shown advantages over conventional
ones, there are still difficulties in practical situations where true DOAs are
not on the discretized sampling grid. To deal with such an off-grid DOA
estimation problem, this paper studies an off-grid model that takes into
account effects of the off-grid DOAs and has a smaller modeling error. An
iterative algorithm is developed based on the off-grid model from a Bayesian
perspective while joint sparsity among different snapshots is exploited by
assuming a Laplace prior for signals at all snapshots. The new approach applies
to both single snapshot and multi-snapshot cases. Numerical simulations show
that the proposed algorithm has improved accuracy in terms of mean squared
estimation error. The algorithm can maintain high estimation accuracy even
under a very coarse sampling grid.
|
1108.5860
|
Linear Operator Inequality and Null Controllability with Vanishing
Energy for unbounded control systems
|
math.OC cs.SY math.AP
|
We consider linear systems on a separable Hilbert space $H$, which are null
controllable at some time $T_0>0$ under the action of a point or boundary
control. Parabolic and hyperbolic control systems usually studied in
applications are special cases. To every initial state $ y_0 \in H$ we
associate the minimal "energy" needed to transfer $ y_0 $ to $ 0 $ in a time $
T \ge T_0$ ("energy" of a control being the square of its $ L^2 $ norm). We
give both necessary and sufficient conditions under which the minimal energy
converges to $ 0 $ for $ T\to+\infty $. This extends to boundary control
systems the concept of null controllability with vanishing energy introduced by
Priola and Zabczyk (Siam J. Control Optim. 42 (2003)) for distributed systems.
The proofs in Priola-Zabczyk paper depend on properties of the associated
Riccati equation, which are not available in the present, general setting. Here
we base our results on new properties of the quadratic regulator problem with
stability and the Linear Operator Inequality.
|
1108.5881
|
Spread Decoding in Extension Fields
|
cs.IT math.IT
|
A spread code is a set of vector spaces of a fixed dimension over a finite
field Fq with certain properties used for random network coding. It can be
constructed in different ways which lead to different decoding algorithms. In
this work we present a new representation of spread codes with a minimum
distance decoding algorithm which is efficient when the codewords, the received
space and the error space have small dimension.
|
1108.5890
|
Coordinating Interfering Transmissions in Cooperative Wireless LANs
|
cs.NI cs.IT math.IT
|
In this paper we present a cooperative medium access control (MAC) protocol
that is designed for a physical layer that can decode interfering transmissions
in distributed wireless networks. The proposed protocol pro-actively enforces
two independent packet transmissions to interfere in a controlled and
cooperative manner. The protocol ensures that when a node desires to transmit a
unicast packet, regardless of the destination, it coordinates with minimal
overhead with relay nodes in order to concurrently transmit over the wireless
channel with a third node. The relay is responsible for allowing packets from
the two selected nodes to interfere only when the desired packets can be
decoded at the appropriate destinations and increase the sum-rate of the
cooperative transmission. In case this is not feasible, classic cooperative or
direct transmission is adopted. To enable distributed, uncoordinated, and
adaptive operation of the protocol, a relay selection mechanism is introduced
so that the optimal relay is selected dynamically and depending on the channel
conditions. The most important advantage of the protocol is that interfering
transmissions can originate from completely independent unicast transmissions
from two senders. We present simulation results that validate the efficacy of
our proposed scheme in terms of throughput and delay.
|
1108.5934
|
The Sznajd model with limited persuasion: competition between
high-reputation and hesitant agents
|
physics.soc-ph cond-mat.stat-mech cs.SI
|
In this work we study a modified version of the two-dimensional Sznajd
sociophysics model. In particular, we consider the effects of agents'
reputations in the persuasion rules. In other words, a high-reputation group
with a common opinion may convince their neighbors with probability $p$, which
induces an increase of the group's reputation. On the other hand, there is
always a probability $q=1-p$ of the neighbors to keep their opinions, which
induces a decrease of the group's reputation. These rules describe a
competition between groups with high reputation and hesitant agents, which
makes the full-consensus states (with all spins pointing in one direction) more
difficult to be reached. As consequences, the usual phase transition does not
occur for $p<p_{c} \sim 0.69$ and the system presents realistic democracy-like
situations, where the majority of spins are aligned in a certain direction, for
a wide range of parameters.
|
1108.5935
|
The Rabin cryptosystem revisited
|
math.NT cs.CR cs.IT math.IT
|
The Rabin public-key cryptosystem is revisited with a focus on the problem of
identifying the encrypted message unambiguously for any pair of primes. In
particular, a deterministic scheme using quartic reciprocity is described that
works for primes congruent 5 modulo 8, a case that was still open. Both
theoretical and practical solutions are presented. The Rabin signature is also
reconsidered and a deterministic padding mechanism is proposed.
|
1108.5943
|
Proof System for Plan Verification under 0-Approximation Semantics
|
cs.AI cs.LO
|
In this paper a proof system is developed for plan verification problems
$\{X\}c\{Y\}$ and $\{X\}c\{KW p\}$ under 0-approximation semantics for
${\mathcal A}_K$. Here, for a plan $c$, two sets $X,Y$ of fluent literals, and
a literal $p$, $\{X\}c\{Y\}$ (resp. $\{X\}c\{KW p\}$) means that all literals
of $Y$ become true (resp. $p$ becomes known) after executing $c$ in any initial
state in which all literals in $X$ are true.Then, soundness and completeness
are proved. The proof system allows verifying plans and generating plans as
well.
|
1108.5974
|
Emotional Analysis of Blogs and Forums Data
|
cs.CL physics.data-an physics.soc-ph
|
We perform a statistical analysis of emotionally annotated comments in two
large online datasets, examining chains of consecutive posts in the
discussions. Using comparisons with randomised data we show that there is a
high level of correlation for the emotional content of messages.
|
1108.6003
|
Characterization and exploitation of community structure in cover song
networks
|
cs.IR cs.MM cs.SI physics.data-an stat.ML
|
The use of community detection algorithms is explored within the framework of
cover song identification, i.e. the automatic detection of different audio
renditions of the same underlying musical piece. Until now, this task has been
posed as a typical query-by-example task, where one submits a query song and
the system retrieves a list of possible matches ranked by their similarity to
the query. In this work, we propose a new approach which uses song communities
to provide more relevant answers to a given query. Starting from the output of
a state-of-the-art system, songs are embedded in a complex weighted network
whose links represent similarity (related musical content). Communities inside
the network are then recognized as groups of covers and this information is
used to enhance the results of the system. In particular, we show that this
approach increases both the coherence and the accuracy of the system.
Furthermore, we provide insight into the internal organization of individual
cover song communities, showing that there is a tendency for the original song
to be central within the community. We postulate that the methods and results
presented here could be relevant to other query-by-example tasks.
|
1108.6007
|
Domain-specific Languages in a Finite Domain Constraint Programming
System
|
cs.AI
|
In this paper, we present domain-specific languages (DSLs) that we devised
for their use in the implementation of a finite domain constraint programming
system, available as library(clpfd) in SWI-Prolog and YAP-Prolog. These DSLs
are used in propagator selection and constraint reification. In these areas,
they lead to concise specifications that are easy to read and reason about. At
compilation time, these specifications are translated to Prolog code, reducing
interpretative run-time overheads. The devised languages can be used in the
implementation of other finite domain constraint solvers as well and may
contribute to their correctness, conciseness and efficiency.
|
1108.6016
|
Improving Entity Resolution with Global Constraints
|
cs.DB cs.IR
|
Some of the greatest advances in web search have come from leveraging
socio-economic properties of online user behavior. Past advances include
PageRank, anchor text, hubs-authorities, and TF-IDF. In this paper, we
investigate another socio-economic property that, to our knowledge, has not yet
been exploited: sites that create lists of entities, such as IMDB and Netflix,
have an incentive to avoid gratuitous duplicates. We leverage this property to
resolve entities across the different web sites, and find that we can obtain
substantial improvements in resolution accuracy. This improvement in accuracy
also translates into robustness, which often reduces the amount of training
data that must be labeled for comparing entities across many sites.
Furthermore, the technique provides robustness when resolving sites that have
some duplicates, even without first removing these duplicates. We present
algorithms with very strong precision and recall, and show that max weight
matching, while appearing to be a natural choice turns out to have poor
performance in some situations. The presented techniques are now being used in
the back-end entity resolution system at a major Internet search engine.
|
1108.6031
|
Robust Adaptive Geometric Tracking Controls on SO(3) with an Application
to the Attitude Dynamics of a Quadrotor UAV
|
math.OC cs.SY
|
This paper provides new results for a robust adaptive tracking control of the
attitude dynamics of a rigid body. Both of the attitude dynamics and the
proposed control system are globally expressed on the special orthogonal group,
to avoid complexities and ambiguities associated with other attitude
representations such as Euler angles or quaternions. By designing an adaptive
law for the inertia matrix of a rigid body, the proposed control system can
asymptotically follow an attitude command without the knowledge of the inertia
matrix, and it is extended to guarantee boundedness of tracking errors in the
presence of unstructured disturbances. These are illustrated by numerical
examples and experiments for the attitude dynamics of a quadrotor UAV.
|
1108.6046
|
Optimal Deterministic Polynomial-Time Data Exchange for Omniscience
|
cs.IT cs.CR math.IT
|
We study the problem of constructing a deterministic polynomial time
algorithm that achieves omniscience, in a rate-optimal manner, among a set of
users that are interested in a common file but each has only partial knowledge
about it as side-information. Assuming that the collective information among
all the users is sufficient to allow the reconstruction of the entire file, the
goal is to minimize the (possibly weighted) amount of bits that these users
need to exchange over a noiseless public channel in order for all of them to
learn the entire file. Using established connections to the multi-terminal
secrecy problem, our algorithm also implies a polynomial-time method for
constructing a maximum size secret shared key in the presence of an
eavesdropper. We consider the following types of side-information settings: (i)
side information in the form of uncoded fragments/packets of the file, where
the users' side-information consists of subsets of the file; (ii) side
information in the form of linearly correlated packets, where the users have
access to linear combinations of the file packets; and (iii) the general
setting where the the users' side-information has an arbitrary (i.i.d.)
correlation structure. Building on results from combinatorial optimization, we
provide a polynomial-time algorithm (in the number of users) that, first finds
the optimal rate allocations among these users, then determines an explicit
transmission scheme (i.e., a description of which user should transmit what
information) for cases (i) and (ii).
|
1108.6088
|
No Internal Regret via Neighborhood Watch
|
cs.LG cs.GT
|
We present an algorithm which attains O(\sqrt{T}) internal (and thus
external) regret for finite games with partial monitoring under the local
observability condition. Recently, this condition has been shown by (Bartok,
Pal, and Szepesvari, 2011) to imply the O(\sqrt{T}) rate for partial monitoring
games against an i.i.d. opponent, and the authors conjectured that the same
holds for non-stochastic adversaries. Our result is in the affirmative, and it
completes the characterization of possible rates for finite partial-monitoring
games, an open question stated by (Cesa-Bianchi, Lugosi, and Stoltz, 2006). Our
regret guarantees also hold for the more general model of partial monitoring
with random signals.
|
1108.6113
|
A New Computationally Efficient Measure of Topological Redundancy of
Biological and Social Networks
|
physics.soc-ph cs.DM cs.SI math.DS q-bio.MN
|
It is well-known that biological and social interaction networks have a
varying degree of redundancy, though a consensus of the precise cause of this
is so far lacking. In this paper, we introduce a topological redundancy measure
for labeled directed networks that is formal, computationally efficient and
applicable to a variety of directed networks such as cellular signaling,
metabolic and social interaction networks. We demonstrate the computational
efficiency of our measure by computing its value and statistical significance
on a number of biological and social networks with up to several thousands of
nodes and edges. Our results suggest a number of interesting observations: (1)
social networks are more redundant that their biological counterparts, (2)
transcriptional networks are less redundant than signaling networks, (3) the
topological redundancy of the C. elegans metabolic network is largely due to
its inclusion of currency metabolites, and (4) the redundancy of signaling
networks is highly (negatively) correlated with the monotonicity of their
dynamics.
|
1108.6114
|
Projective Parameterized Linear Codes Arising from some Matrices and
their Main Parameters
|
cs.IT math.IT
|
In this paper we will estimate the main parameters of some evaluation codes
which are known as projective parameterized codes. We will find the length of
these codes and we will give a formula for the dimension in terms of the
Hilbert function associated to two ideals, one of them being the vanishing
ideal of the projective torus. Also we will find an upper bound for the minimum
distance and, in some cases, we will give some lower bounds for the regularity
index and the minimum distance. These lower bounds work in several cases,
particularly for any projective parameterized code associated to the incidence
matrix of uniform clutters and then they work in the case of graphs.
|
1108.6121
|
The Value of Feedback in Decentralized Detection
|
cs.IT math.IT stat.AP
|
We consider the decentralized binary hypothesis testing problem in networks
with feedback, where some or all of the sensors have access to compressed
summaries of other sensors' observations. We study certain two-message feedback
architectures, in which every sensor sends two messages to a fusion center,
with the second message based on full or partial knowledge of the first
messages of the other sensors. We also study one-message feedback
architectures, in which each sensor sends one message to a fusion center, with
a group of sensors having full or partial knowledge of the messages from the
sensors not in that group. Under either a Neyman-Pearson or a Bayesian
formulation, we show that the asymptotically optimal (in the limit of a large
number of sensors) detection performance (as quantified by error exponents)
does not benefit from the feedback messages, if the fusion center remembers all
sensor messages. However, feedback can improve the Bayesian detection
performance in the one-message feedback architecture if the fusion center has
limited memory; for that case, we determine the corresponding optimal error
exponents.
|
1108.6132
|
Distributed MAC Protocol Supporting Physical-Layer Network Coding
|
cs.NI cs.DC cs.IT math.IT
|
Physical-layer network coding (PNC) is a promising approach for wireless
networks. It allows nodes to transmit simultaneously. Due to the difficulties
of scheduling simultaneous transmissions, existing works on PNC are based on
simplified medium access control (MAC) protocols, which are not applicable to
general multi-hop wireless networks, to the best of our knowledge. In this
paper, we propose a distributed MAC protocol that supports PNC in multi-hop
wireless networks. The proposed MAC protocol is based on the carrier sense
multiple access (CSMA) strategy and can be regarded as an extension to the IEEE
802.11 MAC protocol. In the proposed protocol, each node collects information
on the queue status of its neighboring nodes. When a node finds that there is
an opportunity for some of its neighbors to perform PNC, it notifies its
corresponding neighboring nodes and initiates the process of packet exchange
using PNC, with the node itself as a relay. During the packet exchange process,
the relay also works as a coordinator which coordinates the transmission of
source nodes. Meanwhile, the proposed protocol is compatible with conventional
network coding and conventional transmission schemes. Simulation results show
that the proposed protocol is advantageous in various scenarios of wireless
applications.
|
1108.6146
|
Use of a speed equation for numerical simulation of hydraulic fractures
|
physics.flu-dyn cs.CE
|
The paper treats the propagation of a hydraulically driven crack. We
explicitly write the local speed equation, which facilitates using the theory
of propagating interfaces. It is shown that when neglecting the lag between the
liquid front and the crack tip, the lubrication PDE yields that a solution
satisfies the speed equation identically. This implies that for zero or small
lag, the boundary value problem appears ill-posed when solved numerically. We
suggest e - regularization, which consists in employing the speed equation
together with a prescribed BC on the front to obtain a new BC formulated at a
small distance behind the front rather than on the front itself. It is shown
that - regularization provides accurate and stable results with reasonable time
expense. It is also shown that the speed equation gives a key to proper choice
of unknown functions when solving a hydraulic fracture problem numerically.
|
1108.6150
|
A unified formulation of Gaussian vs. sparse stochastic processes - Part
I: Continuous-domain theory
|
cs.IT math.IT math.PR
|
We introduce a general distributional framework that results in a unifying
description and characterization of a rich variety of continuous-time
stochastic processes. The cornerstone of our approach is an innovation model
that is driven by some generalized white noise process, which may be Gaussian
or not (e.g., Laplace, impulsive Poisson or alpha stable). This allows for a
conceptual decoupling between the correlation properties of the process, which
are imposed by the whitening operator L, and its sparsity pattern which is
determined by the type of noise excitation. The latter is fully specified by a
Levy measure. We show that the range of admissible innovation behavior varies
between the purely Gaussian and super-sparse extremes. We prove that the
corresponding generalized stochastic processes are well-defined mathematically
provided that the (adjoint) inverse of the whitening operator satisfies some Lp
bound for p>=1. We present a novel operator-based method that yields an
explicit characterization of all Levy-driven processes that are solutions of
constant-coefficient stochastic differential equations. When the underlying
system is stable, we recover the family of stationary CARMA processes,
including the Gaussian ones. The approach remains valid when the system is
unstable and leads to the identification of potentially useful generalizations
of the Levy processes, which are sparse and non-stationary. Finally, we show
how we can apply finite difference operators to obtain a stationary
characterization of these processes that is maximally decoupled and stable,
irrespective of the location of the poles in the complex plane.
|
1108.6152
|
A unified formulation of Gaussian vs. sparse stochastic processes - Part
II: Discrete-domain theory
|
cs.IT math.IT math.PR
|
This paper is devoted to the characterization of an extended family of CARMA
(continuous-time autoregressive moving average) processes that are solutions of
stochastic differential equations driven by white Levy innovations. These are
completely specified by: (1) a set of poles and zeros that fixes their
correlation structure, and (2) a canonical infinitely-divisible probability
distribution that controls their degree of sparsity (with the Gaussian model
corresponding to the least sparse scenario). The generalized CARMA processes
are either stationary or non-stationary, depending on the location of the poles
in the complex plane. The most basic non-stationary representatives (with a
single pole at the origin) are the Levy processes, which are the non-Gaussian
counterparts of Brownian motion. We focus on the general analog-to-discrete
conversion problem and introduce a novel spline-based formalism that greatly
simplifies the derivation of the correlation properties and joint probability
distributions of the discrete versions of these processes. We also rely on the
concept of generalized increment process, which suppresses all long range
dependencies, to specify an equivalent discrete-domain innovation model. A
crucial ingredient is the existence of a minimally-supported function
associated with the whitening operator L; this B-spline, which is fundamental
to our formulation, appears in most of our formulas, both at the level of the
correlation and the characteristic function. We make use of these
discrete-domain results to numerically generate illustrative examples of sparse
signals that are consistent with the continuous-domain model.
|
1108.6175
|
Adaptive Locomotion of Multibody Snake-like Robot
|
cs.RO cs.SY
|
This paper represents an adaptive rhythmic control for a snake-like robot
with 25 degrees of freedom. The adaptive gait control is implemented in
algorithmic way in simulation and on a real robot. We investigated behavioral
and energetic properties of this control and a dynamics of different body
segments. It turned out that despite using homogeneous generators, physical
constraints have an inhomogeneous impact on neighbor body segments. By
analytical modeling of such dynamics, it may result in heterogeneous coupling
of oscillators for a rhythmic control and impact scalability and
synchronization effects of gait pattern generators.
|
1108.6185
|
Weighted Reed-Muller codes revisited
|
cs.IT math.IT
|
We consider weighted Reed-Muller codes over point ensemble $S_1
\times...\times S_m$ where $S_i$ needs not be of the same size as $S_j$. For $m
= 2$ we determine optimal weights and analyze in detail what is the impact of
the ratio $|S_1|/|S_2|$ on the minimum distance. In conclusion the weighted
Reed-Muller code construction is much better than its reputation. For a class
of affine variety codes that contains the weighted Reed-Muller codes we then
present two list decoding algorithms. With a small modification one of these
algorithms is able to correct up to 31 errors of the [49, 11, 28] Joyner code.
|
1108.6197
|
Two-Level Fingerprinting Codes: Non-Trivial Constructions
|
cs.IT math.IT
|
We extend the concept of two-level fingerprinting codes, introduced by
Anthapadmanabhan and Barg (2009) in context of traceability (TA) codes, to
other types of fingerprinting codes, namely identifiable parent property (IPP)
codes, secure-frameproof (SFP) codes, and frameproof (FP) codes. We define and
propose the first explicit non-trivial construction for two-level IPP, SFP and
FP codes.
|
1108.6198
|
Decision Support for e-Governance: A Text Mining Approach
|
cs.DB cs.IR
|
Information and communication technology has the capability to improve the
process by which governments involve citizens in formulating public policy and
public projects. Even though much of government regulations may now be in
digital form (and often available online), due to their complexity and
diversity, identifying the ones relevant to a particular context is a
non-trivial task. Similarly, with the advent of a number of electronic online
forums, social networking sites and blogs, the opportunity of gathering
citizens' petitions and stakeholders' views on government policy and proposals
has increased greatly, but the volume and the complexity of analyzing
unstructured data makes this difficult. On the other hand, text mining has come
a long way from simple keyword search, and matured into a discipline capable of
dealing with much more complex tasks. In this paper we discuss how text-mining
techniques can help in retrieval of information and relationships from textual
data sources, thereby assisting policy makers in discovering associations
between policies and citizens' opinions expressed in electronic public forums
and blogs etc. We also present here, an integrated text mining based
architecture for e-governance decision support along with a discussion on the
Indian scenario.
|
1108.6208
|
Coprocessor - a Standalone SAT Preprocessor
|
cs.AI
|
In this work a stand-alone preprocessor for SAT is presented that is able to
perform most of the known preprocessing techniques. Preprocessing a formula in
SAT is important for performance since redundancy can be removed. The
preprocessor is part of the SAT solver riss and is called Coprocessor. Not only
riss, but also MiniSat 2.2 benefit from it, because the SatELite preprocessor
of MiniSat does not implement recent techniques. By using more advanced
techniques, Coprocessor is able to reduce the redundancy in a formula further
and improves the overall solving performance.
|
1108.6211
|
Transfer from Multiple MDPs
|
cs.AI cs.LG
|
Transfer reinforcement learning (RL) methods leverage on the experience
collected on a set of source tasks to speed-up RL algorithms. A simple and
effective approach is to transfer samples from source tasks and include them
into the training set used to solve a given target task. In this paper, we
investigate the theoretical properties of this transfer method and we introduce
novel algorithms adapting the transfer process on the basis of the similarity
between source and target tasks. Finally, we report illustrative experimental
results in a continuous chain problem.
|
1108.6214
|
Likelihood Consensus and Its Application to Distributed Particle
Filtering
|
stat.AP cs.IT math.IT
|
We consider distributed state estimation in a wireless sensor network without
a fusion center. Each sensor performs a global estimation task---based on the
past and current measurements of all sensors---using only local processing and
local communications with its neighbors. In this estimation task, the joint
(all-sensors) likelihood function (JLF) plays a central role as it epitomizes
the measurements of all sensors. We propose a distributed method for computing,
at each sensor, an approximation of the JLF by means of consensus algorithms.
This "likelihood consensus" method is applicable if the local likelihood
functions of the various sensors (viewed as conditional probability density
functions of the local measurements) belong to the exponential family of
distributions. We then use the likelihood consensus method to implement a
distributed particle filter and a distributed Gaussian particle filter. Each
sensor runs a local particle filter, or a local Gaussian particle filter, that
computes a global state estimate. The weight update in each local (Gaussian)
particle filter employs the JLF, which is obtained through the likelihood
consensus scheme. For the distributed Gaussian particle filter, the number of
particles can be significantly reduced by means of an additional consensus
scheme. Simulation results are presented to assess the performance of the
proposed distributed particle filters for a multiple target tracking problem.
|
1108.6223
|
Towards Configuration of applied Web-based information system
|
cs.SE cs.AI cs.DM cs.NI cs.SY math.OC
|
In the paper, combinatorial synthesis of structure for applied Web-based
systems is described. The problem is considered as a combination of selected
design alternatives for system parts/components into a resultant composite
decision (i.e., system configuration design). The solving framework is based on
Hierarchical Morphological Multicriteria Design (HMMD) approach: (i)
multicriteria selection of alternatives for system parts, (ii) composing the
selected alternatives into a resultant combination (while taking into account
ordinal quality of the alternatives above and their compatibility). A
lattice-based discrete space is used to evaluate (to integrate) quality of the
resultant combinations (i.e., composite system decisions or system
configurations). In addition, a simplified solving framework based on
multicriteria multiple choice problem is considered. A multistage design
process to obtain a system trajectory is described as well. The basic applied
example is targeted to an applied Web-based system for a communication service
provider. Two other applications are briefly described (corporate system and
information system for academic application).
|
1108.6239
|
Efficient data compression from statistical physics of codes over finite
fields
|
cs.IT cond-mat.stat-mech math.IT
|
In this paper we discuss a novel data compression technique for binary
symmetric sources based on the cavity method over a Galois Field of order q
(GF(q)). We present a scheme of low complexity and near optimal empirical
performance. The compression step is based on a reduction of sparse low density
parity check codes over GF(q) and is done through the so called reinforced
belief-propagation equations. These reduced codes appear to have a non-trivial
geometrical modification of the space of codewords which makes such compression
computationally feasible. The computational complexity is O(d.n.q.log(q)) per
iteration, where d is the average degree of the check nodes and n is the number
of bits. For our code ensemble, decompression can be done in a time linear in
the code's length by a simple leaf-removal algorithm.
|
1108.6260
|
Structural Routability of n-Pairs Information Networks
|
cs.IT cs.NI cs.SI math.IT
|
Information does not generally behave like a conservative fluid flow in
communication networks with multiple sources and sinks. However, it is often
conceptually and practically useful to be able to associate separate data
streams with each source-sink pair, with only routing and no coding performed
at the network nodes. This raises the question of whether there is a nontrivial
class of network topologies for which achievability is always equivalent to
routability, for any combination of source signals and positive channel
capacities. This chapter considers possibly cyclic, directed, errorless
networks with n source-sink pairs and mutually independent source signals. The
concept of downward dominance is introduced and it is shown that, if the
network topology is downward dominated, then the achievability of a given
combination of source signals and channel capacities implies the existence of a
feasible multicommodity flow.
|
1108.6274
|
Every Formula-Based Logic Program Has a Least Infinite-Valued Model
|
cs.LO cs.AI
|
Every definite logic program has as its meaning a least Herbrand model with
respect to the program-independent ordering "set-inclusion". In the case of
normal logic programs there do not exist least models in general. However,
according to a recent approach by Rondogiannis and Wadge, who consider
infinite-valued models, every normal logic program does have a least model with
respect to a program-independent ordering. We show that this approach can be
extended to formula-based logic programs (i.e., finite sets of rules of the
form A\leftarrowF where A is an atom and F an arbitrary first-order formula).
We construct for a given program P an interpretation M_P and show that it is
the least of all models of P. Keywords: Logic programming, semantics of
programs, negation-as-failure, infinite-valued logics, set theory
|
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