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0801.3703
|
On minimality of convolutional ring encoders
|
cs.IT math.IT
|
Convolutional codes are considered with code sequences modelled as
semi-infinite Laurent series. It is wellknown that a convolutional code C over
a finite group G has a minimal trellis representation that can be derived from
code sequences. It is also wellknown that, for the case that G is a finite
field, any polynomial encoder of C can be algebraically manipulated to yield a
minimal polynomial encoder whose controller canonical realization is a minimal
trellis. In this paper we seek to extend this result to the finite ring case G
= Z_{p^r} by introducing a socalled "p-encoder". We show how to manipulate a
polynomial encoding of a noncatastrophic convolutional code over Z_{p^r} to
produce a particular type of p-encoder ("minimal p-encoder") whose controller
canonical realization is a minimal trellis with nonlinear features. The minimum
number of trellis states is then expressed as p^gamma, where gamma is the sum
of the row degrees of the minimal p-encoder. In particular, we show that any
convolutional code over Z_{p^r} admits a delay-free p-encoder which implies the
novel result that delay-freeness is not a property of the code but of the
encoder, just as in the field case. We conjecture that a similar result holds
with respect to catastrophicity, i.e., any catastrophic convolutional code over
Z_{p^r} admits a noncatastrophic p-encoder.
|
0801.3773
|
Graph-Based Classification of Self-Dual Additive Codes over Finite
Fields
|
cs.IT math.CO math.IT quant-ph
|
Quantum stabilizer states over GF(m) can be represented as self-dual additive
codes over GF(m^2). These codes can be represented as weighted graphs, and
orbits of graphs under the generalized local complementation operation
correspond to equivalence classes of codes. We have previously used this fact
to classify self-dual additive codes over GF(4). In this paper we classify
self-dual additive codes over GF(9), GF(16), and GF(25). Assuming that the
classical MDS conjecture holds, we are able to classify all self-dual additive
MDS codes over GF(9) by using an extension technique. We prove that the minimum
distance of a self-dual additive code is related to the minimum vertex degree
in the associated graph orbit. Circulant graph codes are introduced, and a
computer search reveals that this set contains many strong codes. We show that
some of these codes have highly regular graph representations.
|
0801.3817
|
Robustness Evaluation of Two CCG, a PCFG and a Link Grammar Parsers
|
cs.CL
|
Robustness in a parser refers to an ability to deal with exceptional
phenomena. A parser is robust if it deals with phenomena outside its normal
range of inputs. This paper reports on a series of robustness evaluations of
state-of-the-art parsers in which we concentrated on one aspect of robustness:
its ability to parse sentences containing misspelled words. We propose two
measures for robustness evaluation based on a comparison of a parser's output
for grammatical input sentences and their noisy counterparts. In this paper, we
use these measures to compare the overall robustness of the four evaluated
parsers, and we present an analysis of the decline in parser performance with
increasing error levels. Our results indicate that performance typically
declines tens of percentage units when parsers are presented with texts
containing misspellings. When it was tested on our purpose-built test set of
443 sentences, the best parser in the experiment (C&C parser) was able to
return exactly the same parse tree for the grammatical and ungrammatical
sentences for 60.8%, 34.0% and 14.9% of the sentences with one, two or three
misspelled words respectively.
|
0801.3837
|
Universal Fingerprinting: Capacity and Random-Coding Exponents
|
cs.IT math.IT
|
This paper studies fingerprinting (traitor tracing) games in which the number
of colluders and the collusion channel are unknown. The fingerprints are
embedded into host sequences representing signals to be protected and provide
the receiver with the capability to trace back pirated copies to the colluders.
The colluders and the fingerprint embedder are subject to signal fidelity
constraints. Our problem setup unifies the signal-distortion and Boneh-Shaw
formulations of fingerprinting. The fundamental tradeoffs between fingerprint
codelength, number of users, number of colluders, fidelity constraints, and
decoding reliability are then determined. Several bounds on fingerprinting
capacity have been presented in recent literature. This paper derives exact
capacity formulas and presents a new randomized fingerprinting scheme with the
following properties: (1) the encoder and receiver assume a nominal coalition
size but do not need to know the actual coalition size and the collusion
channel; (2) a tunable parameter $\Delta$ trades off false-positive and
false-negative error exponents; (3) the receiver provides a reliability metric
for its decision; and (4) the scheme is capacity-achieving when the
false-positive exponent $\Delta$ tends to zero and the nominal coalition size
coincides with the actual coalition size.
A fundamental component of the new scheme is the use of a "time-sharing"
randomized sequence. The decoder is a maximum penalized mutual information
decoder, where the significance of each candidate coalition is assessed
relative to a threshold, and the penalty is proportional to the coalition size.
A much simpler {\em threshold decoder} that satisfies properties (1)---(3)
above but not (4) is also given.
|
0801.3864
|
Between conjecture and memento: shaping a collective emotional
perception of the future
|
cs.CL cs.GL
|
Large scale surveys of public mood are costly and often impractical to
perform. However, the web is awash with material indicative of public mood such
as blogs, emails, and web queries. Inexpensive content analysis on such
extensive corpora can be used to assess public mood fluctuations. The work
presented here is concerned with the analysis of the public mood towards the
future. Using an extension of the Profile of Mood States questionnaire, we have
extracted mood indicators from 10,741 emails submitted in 2006 to futureme.org,
a web service that allows its users to send themselves emails to be delivered
at a later date. Our results indicate long-term optimism toward the future, but
medium-term apprehension and confusion.
|
0801.3871
|
On the Scaling Window of Model RB
|
cs.CC cond-mat.stat-mech cs.AI
|
This paper analyzes the scaling window of a random CSP model (i.e. model RB)
for which we can identify the threshold points exactly, denoted by $r_{cr}$ or
$p_{cr}$. For this model, we establish the scaling window
$W(n,\delta)=(r_{-}(n,\delta), r_{+}(n,\delta))$ such that the probability of a
random instance being satisfiable is greater than $1-\delta$ for
$r<r_{-}(n,\delta)$ and is less than $\delta$ for $r>r_{+}(n,\delta)$.
Specifically, we obtain the following result
$$W(n,\delta)=(r_{cr}-\Theta(\frac{1}{n^{1-\epsilon}\ln n}), \
r_{cr}+\Theta(\frac{1}{n\ln n})),$$ where $0\leq\epsilon<1$ is a constant. A
similar result with respect to the other parameter $p$ is also obtained. Since
the instances generated by model RB have been shown to be hard at the
threshold, this is the first attempt, as far as we know, to analyze the scaling
window of such a model with hard instances.
|
0801.3875
|
Towards a Real-Time Data Driven Wildland Fire Model
|
physics.ao-ph cs.CE
|
A wildland fire model based on semi-empirical relations for the spread rate
of a surface fire and post-frontal heat release is coupled with the Weather
Research and Forecasting atmospheric model (WRF). The propagation of the fire
front is implemented by a level set method. Data is assimilated by a morphing
ensemble Kalman filter, which provides amplitude as well as position
corrections. Thermal images of a fire will provide the observations and will be
compared to a synthetic image from the model state.
|
0801.3878
|
Hash Property and Coding Theorems for Sparse Matrices and
Maximum-Likelihood Coding
|
cs.IT math.IT
|
The aim of this paper is to prove the achievability of several coding
problems by using sparse matrices (the maximum column weight grows
logarithmically in the block length) and maximal-likelihood (ML) coding. These
problems are the Slepian-Wolf problem, the Gel'fand-Pinsker problem, the
Wyner-Ziv problem, and the One-helps-one problem (source coding with partial
side information at the decoder). To this end, the notion of a hash property
for an ensemble of functions is introduced and it is proved that an ensemble of
$q$-ary sparse matrices satisfies the hash property. Based on this property, it
is proved that the rate of codes using sparse matrices and maximal-likelihood
(ML) coding can achieve the optimal rate.
|
0801.3880
|
Spectral efficiency and optimal medium access control of random access
systems over large random spreading CDMA
|
cs.IT math.IT
|
This paper analyzes the spectral efficiency as a function of medium access
control (MAC) for large random spreading CDMA random access systems that employ
a linear receiver. It is shown that located at higher than the physical layer,
MAC along with spreading and power allocation can effectively perform spectral
efficiency maximization and near-far mitigation.
|
0801.3908
|
Encoding changing country codes for the Semantic Web with ISO 3166 and
SKOS
|
cs.IR
|
This paper shows how authority files can be encoded for the Semantic Web with
the Simple Knowledge Organisation System (SKOS). In particular the application
of SKOS for encoding the structure, management, and utilization of country
codes as defined in ISO 3166 is demonstrated. The proposed encoding gives a use
case for SKOS that includes features that have only been discussed little so
far, such as multiple notations, nested concept schemes, changes by versioning.
|
0801.3926
|
On the Weight Distribution of the Extended Quadratic Residue Code of
Prime 137
|
cs.IT cs.DM math.IT
|
The Hamming weight enumerator function of the formally self-dual even, binary
extended quadratic residue code of prime p = 8m + 1 is given by Gleason's
theorem for singly-even code. Using this theorem, the Hamming weight
distribution of the extended quadratic residue is completely determined once
the number of codewords of Hamming weight j A_j, for 0 <= j <= 2m, are known.
The smallest prime for which the Hamming weight distribution of the
corresponding extended quadratic residue code is unknown is 137. It is shown in
this paper that, for p=137 A_2m = A_34 may be obtained with out the need of
exhaustive codeword enumeration. After the remainder of A_j required by
Gleason's theorem are computed and independently verified using their
congruences, the Hamming weight distributions of the binary augmented and
extended quadratic residue codes of prime 137 are derived.
|
0801.3971
|
A Bayesian Optimisation Algorithm for the Nurse Scheduling Problem
|
cs.NE cs.CE
|
A Bayesian optimization algorithm for the nurse scheduling problem is
presented, which involves choosing a suitable scheduling rule from a set for
each nurses assignment. Unlike our previous work that used Gas to implement
implicit learning, the learning in the proposed algorithm is explicit, ie.
Eventually, we will be able to identify and mix building blocks directly. The
Bayesian optimization algorithm is applied to implement such explicit learning
by building a Bayesian network of the joint distribution of solutions. The
conditional probability of each variable in the network is computed according
to an initial set of promising solutions. Subsequently, each new instance for
each variable is generated, ie in our case, a new rule string has been
obtained. Another set of rule strings will be generated in this way, some of
which will replace previous strings based on fitness selection. If stopping
conditions are not met, the conditional probabilities for all nodes in the
Bayesian network are updated again using the current set of promising rule
strings. Computational results from 52 real data instances demonstrate the
success of this approach. It is also suggested that the learning mechanism in
the proposed approach might be suitable for other scheduling problems.
|
0801.3983
|
New Upper Bounds on Sizes of Permutation Arrays
|
cs.IT math.IT
|
A permutation array(or code) of length $n$ and distance $d$, denoted by
$(n,d)$ PA, is a set of permutations $C$ from some fixed set of $n$ elements
such that the Hamming distance between distinct members
$\mathbf{x},\mathbf{y}\in C$ is at least $d$. Let $P(n,d)$ denote the maximum
size of an $(n,d)$ PA. New upper bounds on $P(n,d)$ are given. For constant
$\alpha,\beta$ satisfying certain conditions, whenever $d=\beta n^{\alpha}$,
the new upper bounds are asymptotically better than the previous ones.
|
0801.3986
|
New Lower Bounds on Sizes of Permutation Arrays
|
cs.IT math.IT
|
A permutation array(or code) of length $n$ and distance $d$, denoted by
$(n,d)$ PA, is a set of permutations $C$ from some fixed set of $n$ elements
such that the Hamming distance between distinct members
$\mathbf{x},\mathbf{y}\in C$ is at least $d$. Let $P(n,d)$ denote the maximum
size of an $(n,d)$ PA. This correspondence focuses on the lower bound on
$P(n,d)$. First we give three improvements over the Gilbert-Varshamov lower
bounds on $P(n,d)$ by applying the graph theorem framework presented by Jiang
and Vardy. Next we show another two new improved bounds by considering the
covered balls intersections. Finally some new lower bounds for certain values
of $n$ and $d$ are given.
|
0801.3987
|
New Constructions of Permutation Arrays
|
cs.IT math.IT
|
A permutation array(permutation code, PA) of length $n$ and distance $d$,
denoted by $(n,d)$ PA, is a set of permutations $C$ from some fixed set of $n$
elements such that the Hamming distance between distinct members
$\mathbf{x},\mathbf{y}\in C$ is at least $d$. In this correspondence, we
present two constructions of PA from fractional polynomials over finite field,
and a construction of $(n,d)$ PA from permutation group with degree $n$ and
minimal degree $d$. All these new constructions produces some new lower bounds
for PA.
|
0801.4024
|
Set-based complexity and biological information
|
cs.IT cs.CC math.IT q-bio.QM
|
It is not obvious what fraction of all the potential information residing in
the molecules and structures of living systems is significant or meaningful to
the system. Sets of random sequences or identically repeated sequences, for
example, would be expected to contribute little or no useful information to a
cell. This issue of quantitation of information is important since the ebb and
flow of biologically significant information is essential to our quantitative
understanding of biological function and evolution. Motivated specifically by
these problems of biological information, we propose here a class of measures
to quantify the contextual nature of the information in sets of objects, based
on Kolmogorov's intrinsic complexity. Such measures discount both random and
redundant information and are inherent in that they do not require a defined
state space to quantify the information. The maximization of this new measure,
which can be formulated in terms of the universal information distance, appears
to have several useful and interesting properties, some of which we illustrate
with examples.
|
0801.4048
|
High Performance Cooperative Transmission Protocols Based on Multiuser
Detection and Network Coding
|
cs.IT math.IT
|
Cooperative transmission is an emerging communication technique that takes
advantage of the broadcast nature of wireless channels. However, due to low
spectral efficiency and the requirement of orthogonal channels, its potential
for use in future wireless networks is limited. In this paper, by making use of
multiuser detection (MUD) and network coding, cooperative transmission
protocols with high spectral efficiency, diversity order, and coding gain are
developed. Compared with the traditional cooperative transmission protocols
with single-user detection, in which the diversity gain is only for one source
user, the proposed MUD cooperative transmission protocols have the merit that
the improvement of one user's link can also benefit the other users. In
addition, using MUD at the relay provides an environment in which network
coding can be employed. The coding gain and high diversity order can be
obtained by fully utilizing the link between the relay and the destination.
From the analysis and simulation results, it is seen that the proposed
protocols achieve higher diversity gain, better asymptotic efficiency, and
lower bit error rate, compared to traditional MUD schemes and to existing
cooperative transmission protocols. From the simulation results, the
performance of the proposed scheme is near optimal as the performance gap is
0.12dB for average bit error rate (BER) 10^{-6} and 1.04dB for average BER
10^(-3), compared to two performance upper bounds.
|
0801.4061
|
The optimal assignment kernel is not positive definite
|
cs.LG
|
We prove that the optimal assignment kernel, proposed recently as an attempt
to embed labeled graphs and more generally tuples of basic data to a Hilbert
space, is in fact not always positive definite.
|
0801.4119
|
Strategic Alert Throttling for Intrusion Detection Systems
|
cs.NE cs.CR
|
Network intrusion detection systems are themselves becoming targets of
attackers. Alert flood attacks may be used to conceal malicious activity by
hiding it among a deluge of false alerts sent by the attacker. Although these
types of attacks are very hard to stop completely, our aim is to present
techniques that improve alert throughput and capacity to such an extent that
the resources required to successfully mount the attack become prohibitive. The
key idea presented is to combine a token bucket filter with a realtime
correlation algorithm. The proposed algorithm throttles alert output from the
IDS when an attack is detected. The attack graph used in the correlation
algorithm is used to make sure that alerts crucial to forming strategies are
not discarded by throttling.
|
0801.4129
|
Scaling Laws and Techniques in Decentralized Processing of Interfered
Gaussian Channels
|
cs.IT math.IT
|
The scaling laws of the achievable communication rates and the corresponding
upper bounds of distributed reception in the presence of an interfering signal
are investigated. The scheme includes one transmitter communicating to a remote
destination via two relays, which forward messages to the remote destination
through reliable links with finite capacities. The relays receive the
transmission along with some unknown interference. We focus on three common
settings for distributed reception, wherein the scaling laws of the capacity
(the pre-log as the power of the transmitter and the interference are taken to
infinity) are completely characterized. It is shown in most cases that in order
to overcome the interference, a definite amount of information about the
interference needs to be forwarded along with the desired message, to the
destination. It is exemplified in one scenario that the cut-set upper bound is
strictly loose. The results are derived using the cut-set along with a new
bounding technique, which relies on multi letter expressions. Furthermore,
lattices are found to be a useful communication technique in this setting, and
are used to characterize the scaling laws of achievable rates.
|
0801.4190
|
Phylogenies without Branch Bounds: Contracting the Short, Pruning the
Deep
|
q-bio.PE cs.CE cs.DS math.PR math.ST stat.TH
|
We introduce a new phylogenetic reconstruction algorithm which, unlike most
previous rigorous inference techniques, does not rely on assumptions regarding
the branch lengths or the depth of the tree. The algorithm returns a forest
which is guaranteed to contain all edges that are: 1) sufficiently long and 2)
sufficiently close to the leaves. How much of the true tree is recovered
depends on the sequence length provided. The algorithm is distance-based and
runs in polynomial time.
|
0801.4194
|
A statistical mechanical interpretation of algorithmic information
theory
|
cs.IT cs.CC math.IT math.PR quant-ph
|
We develop a statistical mechanical interpretation of algorithmic information
theory by introducing the notion of thermodynamic quantities, such as free
energy, energy, statistical mechanical entropy, and specific heat, into
algorithmic information theory. We investigate the properties of these
quantities by means of program-size complexity from the point of view of
algorithmic randomness. It is then discovered that, in the interpretation, the
temperature plays a role as the compression rate of the values of all these
thermodynamic quantities, which include the temperature itself. Reflecting this
self-referential nature of the compression rate of the temperature, we obtain
fixed point theorems on compression rate.
|
0801.4198
|
Microscopic Analysis for Decoupling Principle of Linear Vector Channel
|
cs.IT math.IT
|
This paper studies the decoupling principle of a linear vector channel, which
is an extension of CDMA and MIMO channels. We show that the scalar-channel
characterization obtained via the decoupling principle is valid not only for
collections of a large number of elements of input vector, as discussed in
previous studies, but also for individual elements of input vector, i.e. the
linear vector channel for individual elements of channel input vector is
decomposed into a bank of independent scalar Gaussian channels in the
large-system limit, where dimensions of channel input and output are both sent
to infinity while their ratio fixed.
|
0801.4287
|
Movie Recommendation Systems Using An Artificial Immune System
|
cs.NE cs.AI
|
We apply the Artificial Immune System (AIS) technology to the Collaborative
Filtering (CF) technology when we build the movie recommendation system. Two
different affinity measure algorithms of AIS, Kendall tau and Weighted Kappa,
are used to calculate the correlation coefficients for this movie
recommendation system. From the testing we think that Weighted Kappa is more
suitable than Kendall tau for movie problems.
|
0801.4305
|
Risk-Seeking versus Risk-Avoiding Investments in Noisy Periodic
Environments
|
q-fin.PM cs.CE physics.soc-ph
|
We study the performance of various agent strategies in an artificial
investment scenario. Agents are equipped with a budget, $x(t)$, and at each
time step invest a particular fraction, $q(t)$, of their budget. The return on
investment (RoI), $r(t)$, is characterized by a periodic function with
different types and levels of noise. Risk-avoiding agents choose their fraction
$q(t)$ proportional to the expected positive RoI, while risk-seeking agents
always choose a maximum value $q_{max}$ if they predict the RoI to be positive
("everything on red"). In addition to these different strategies, agents have
different capabilities to predict the future $r(t)$, dependent on their
internal complexity. Here, we compare 'zero-intelligent' agents using technical
analysis (such as moving least squares) with agents using reinforcement
learning or genetic algorithms to predict $r(t)$. The performance of agents is
measured by their average budget growth after a certain number of time steps.
We present results of extensive computer simulations, which show that, for our
given artificial environment, (i) the risk-seeking strategy outperforms the
risk-avoiding one, and (ii) the genetic algorithm was able to find this optimal
strategy itself, and thus outperforms other prediction approaches considered.
|
0801.4307
|
On Affinity Measures for Artificial Immune System Movie Recommenders
|
cs.NE cs.AI cs.CY
|
We combine Artificial Immune Systems 'AIS', technology with Collaborative
Filtering 'CF' and use it to build a movie recommendation system. We already
know that Artificial Immune Systems work well as movie recommenders from
previous work by Cayzer and Aickelin 3, 4, 5. Here our aim is to investigate
the effect of different affinity measure algorithms for the AIS. Two different
affinity measures, Kendalls Tau and Weighted Kappa, are used to calculate the
correlation coefficients for the movie recommender. We compare the results with
those published previously and show that Weighted Kappa is more suitable than
others for movie problems. We also show that AIS are generally robust movie
recommenders and that, as long as a suitable affinity measure is chosen,
results are good.
|
0801.4312
|
Investigating Artificial Immune Systems For Job Shop Rescheduling In
Changing Environments
|
cs.NE cs.CE
|
Artificial immune system can be used to generate schedules in changing
environments and it has been proven to be more robust than schedules developed
using a genetic algorithm. Good schedules can be produced especially when the
number of the antigens is increased. However, an increase in the range of the
antigens had somehow affected the fitness of the immune system. In this
research, we are trying to improve the result of the system by rescheduling the
same problem using the same method while at the same time maintaining the
robustness of the schedules.
|
0801.4314
|
Artificial Immune Systems (AIS) - A New Paradigm for Heuristic Decision
Making
|
cs.NE cs.AI
|
Over the last few years, more and more heuristic decision making techniques
have been inspired by nature, e.g. evolutionary algorithms, ant colony
optimisation and simulated annealing. More recently, a novel computational
intelligence technique inspired by immunology has emerged, called Artificial
Immune Systems (AIS). This immune system inspired technique has already been
useful in solving some computational problems. In this keynote, we will very
briefly describe the immune system metaphors that are relevant to AIS. We will
then give some illustrative real-world problems suitable for AIS use and show a
step-by-step algorithm walkthrough. A comparison of AIS to other well-known
algorithms and areas for future work will round this keynote off. It should be
noted that as AIS is still a young and evolving field, there is not yet a fixed
algorithm template and hence actual implementations might differ somewhat from
the examples given here.
|
0801.4355
|
TER: A Robot for Remote Ultrasonic Examination: Experimental Evaluations
|
cs.OH cs.RO
|
This chapter:
o Motivates the clinical use of robotic tele-echography
o Introduces the TER system
o Describes technical and clinical evaluations performed with TER
|
0801.4544
|
A Neyman-Pearson Approach to Universal Erasure and List Decoding
|
cs.IT math.IT
|
When information is to be transmitted over an unknown, possibly unreliable
channel, an erasure option at the decoder is desirable. Using
constant-composition random codes, we propose a generalization of Csiszar and
Korner's Maximum Mutual Information decoder with erasure option for discrete
memoryless channels. The new decoder is parameterized by a weighting function
that is designed to optimize the fundamental tradeoff between undetected-error
and erasure exponents for a compound class of channels. The class of weighting
functions may be further enlarged to optimize a similar tradeoff for list
decoders -- in that case, undetected-error probability is replaced with average
number of incorrect messages in the list. Explicit solutions are identified.
The optimal exponents admit simple expressions in terms of the sphere-packing
exponent, at all rates below capacity. For small erasure exponents, these
expressions coincide with those derived by Forney (1968) for symmetric
channels, using Maximum a Posteriori decoding. Thus for those channels at
least, ignorance of the channel law is inconsequential. Conditions for
optimality of the Csiszar-Korner rule and of the simpler
empirical-mutual-information thresholding rule are identified. The error
exponents are evaluated numerically for the binary symmetric channel.
|
0801.4571
|
Is SP BP?
|
cs.IT math.IT
|
The Survey Propagation (SP) algorithm for solving $k$-SAT problems has been
shown recently as an instance of the Belief Propagation (BP) algorithm. In this
paper, we show that for general constraint-satisfaction problems, SP may not be
reducible from BP. We also establish the conditions under which such a
reduction is possible. Along our development, we present a unification of the
existing SP algorithms in terms of a probabilistically interpretable iterative
procedure -- weighted Probabilistic Token Passing.
|
0801.4706
|
A Class of Errorless Codes for Over-loaded Synchronous Wireless and
Optical CDMA Systems
|
cs.IT math.CO math.IT
|
In this paper we introduce a new class of codes for over-loaded synchronous
wireless and optical CDMA systems which increases the number of users for fixed
number of chips without introducing any errors. Equivalently, the chip rate can
be reduced for a given number of users, which implies bandwidth reduction for
downlink wireless systems. An upper bound for the maximum number of users for a
given number of chips is derived. Also, lower and upper bounds for the sum
channel capacity of a binary over-loaded CDMA are derived that can predict the
existence of such over-loaded codes. We also propose a simplified maximum
likelihood method for decoding these types of over-loaded codes. Although a
high percentage of the over-loading factor degrades the system performance in
noisy channels, simulation results show that this degradation is not
significant. More importantly, for moderate values of Eb/N0 (in the range of
6-10 dB) or higher, the proposed codes perform much better than the binary
Welch bound equality sequences.
|
0801.4716
|
Methods to integrate a language model with semantic information for a
word prediction component
|
cs.CL
|
Most current word prediction systems make use of n-gram language models (LM)
to estimate the probability of the following word in a phrase. In the past
years there have been many attempts to enrich such language models with further
syntactic or semantic information. We want to explore the predictive powers of
Latent Semantic Analysis (LSA), a method that has been shown to provide
reliable information on long-distance semantic dependencies between words in a
context. We present and evaluate here several methods that integrate LSA-based
information with a standard language model: a semantic cache, partial
reranking, and different forms of interpolation. We found that all methods show
significant improvements, compared to the 4-gram baseline, and most of them to
a simple cache model as well.
|
0801.4746
|
Concerning Olga, the Beautiful Little Street Dancer (Adjectives as
Higher-Order Polymorphic Functions)
|
cs.CL cs.LO
|
In this paper we suggest a typed compositional seman-tics for nominal
compounds of the form [Adj Noun] that models adjectives as higher-order
polymorphic functions, and where types are assumed to represent concepts in an
ontology that reflects our commonsense view of the world and the way we talk
about it in or-dinary language. In addition to [Adj Noun] compounds our
proposal seems also to suggest a plausible explana-tion for well known
adjective ordering restrictions.
|
0801.4790
|
Information Width
|
cs.DM cs.IT cs.LG math.IT
|
Kolmogorov argued that the concept of information exists also in problems
with no underlying stochastic model (as Shannon's information representation)
for instance, the information contained in an algorithm or in the genome. He
introduced a combinatorial notion of entropy and information $I(x:\sy)$
conveyed by a binary string $x$ about the unknown value of a variable $\sy$.
The current paper poses the following questions: what is the relationship
between the information conveyed by $x$ about $\sy$ to the description
complexity of $x$ ? is there a notion of cost of information ? are there limits
on how efficient $x$ conveys information ?
To answer these questions Kolmogorov's definition is extended and a new
concept termed {\em information width} which is similar to $n$-widths in
approximation theory is introduced. Information of any input source, e.g.,
sample-based, general side-information or a hybrid of both can be evaluated by
a single common formula. An application to the space of binary functions is
considered.
|
0801.4794
|
On the Complexity of Binary Samples
|
cs.DM cs.AI cs.LG
|
Consider a class $\mH$ of binary functions $h: X\to\{-1, +1\}$ on a finite
interval $X=[0, B]\subset \Real$. Define the {\em sample width} of $h$ on a
finite subset (a sample) $S\subset X$ as $\w_S(h) \equiv \min_{x\in S}
|\w_h(x)|$, where $\w_h(x) = h(x) \max\{a\geq 0: h(z)=h(x), x-a\leq z\leq
x+a\}$. Let $\mathbb{S}_\ell$ be the space of all samples in $X$ of cardinality
$\ell$ and consider sets of wide samples, i.e., {\em hypersets} which are
defined as $A_{\beta, h} = \{S\in \mathbb{S}_\ell: \w_{S}(h) \geq \beta\}$.
Through an application of the Sauer-Shelah result on the density of sets an
upper estimate is obtained on the growth function (or trace) of the class
$\{A_{\beta, h}: h\in\mH\}$, $\beta>0$, i.e., on the number of possible
dichotomies obtained by intersecting all hypersets with a fixed collection of
samples $S\in\mathbb{S}_\ell$ of cardinality $m$. The estimate is
$2\sum_{i=0}^{2\lfloor B/(2\beta)\rfloor}{m-\ell\choose i}$.
|
0801.4807
|
Automatic Text Area Segmentation in Natural Images
|
cs.CV
|
We present a hierarchical method for segmenting text areas in natural images.
The method assumes that the text is written with a contrasting color on a more
or less uniform background. But no assumption is made regarding the language or
character set used to write the text. In particular, the text can contain
simple graphics or symbols. The key feature of our approach is that we first
concentrate on finding the background of the text, before testing whether there
is actually text on the background. Since uniform areas are easy to find in
natural images, and since text backgrounds define areas which contain "holes"
(where the text is written) we thus look for uniform areas containing "holes"
and label them as text backgrounds candidates. Each candidate area is then
further tested for the presence of text within its convex hull. We tested our
method on a database of 65 images including English and Urdu text. The method
correctly segmented all the text areas in 63 of these images, and in only 4 of
these were areas that do not contain text also segmented.
|
0802.0003
|
On mobile sets in the binary hypercube
|
math.CO cs.IT math.IT
|
If two distance-3 codes have the same neighborhood, then each of them is
called a mobile set. In the (4k+3)-dimensional binary hypercube, there exists a
mobile set of cardinality 2*6^k that cannot be split into mobile sets of
smaller cardinalities or represented as a natural extension of a mobile set in
a hypercube of smaller dimension. Keywords: mobile set; 1-perfect code.
|
0802.0006
|
New Perspectives and some Celebrated Quantum Inequalities
|
math-ph cs.IT math.IT math.MP
|
Some of the important inequalities associated with quantum entropy are
immediate algebraic consequences of the Hansen-Pedersen-Jensen inequality. A
general argument is given in terms of the matrix perspective of an operator
convex function. A matrix analogue of Mar\'{e}chal's extended perspectives
provides additional inequalities, including a $p+q\leq 1$ result of Lieb.
|
0802.0030
|
Mission impossible: Computing the network coding capacity region
|
cs.IT math.IT
|
One of the main theoretical motivations for the emerging area of network
coding is the achievability of the max-flow/min-cut rate for single source
multicast. This can exceed the rate achievable with routing alone, and is
achievable with linear network codes. The multi-source problem is more
complicated. Computation of its capacity region is equivalent to determination
of the set of all entropy functions $\Gamma^*$, which is non-polyhedral. The
aim of this paper is to demonstrate that this difficulty can arise even in
single source problems. In particular, for single source networks with
hierarchical sink requirements, and for single source networks with secrecy
constraints. In both cases, we exhibit networks whose capacity regions involve
$\Gamma^*$. As in the multi-source case, linear codes are insufficient.
|
0802.0116
|
Shallow Models for Non-Iterative Modal Logics
|
cs.LO cs.AI cs.CC cs.MA
|
The methods used to establish PSPACE-bounds for modal logics can roughly be
grouped into two classes: syntax driven methods establish that exhaustive proof
search can be performed in polynomial space whereas semantic approaches
directly construct shallow models. In this paper, we follow the latter approach
and establish generic PSPACE-bounds for a large and heterogeneous class of
modal logics in a coalgebraic framework. In particular, no complete
axiomatisation of the logic under scrutiny is needed. This does not only
complement our earlier, syntactic, approach conceptually, but also covers a
wide variety of new examples which are difficult to harness by purely syntactic
means. Apart from re-proving known complexity bounds for a large variety of
structurally different logics, we apply our method to obtain previously unknown
PSPACE-bounds for Elgesem's logic of agency and for graded modal logic over
reflexive frames.
|
0802.0130
|
About the true type of smoothers
|
math.OC cs.IT math.IT
|
We employ the variational formulation and the Euler-Lagrange equations to
study the steady-state error in linear non-causal estimators (smoothers). We
give a complete description of the steady-state error for inputs that are
polynomial in time. We show that the steady-state error regime in a smoother is
similar to that in a filter of double the type. This means that the
steady-state error in the optimal smoother is significantly smaller than that
in the Kalman filter. The results reveal a significant advantage of smoothing
over filtering with respect to robustness to model uncertainty.
|
0802.0137
|
Fault-Tolerant Partial Replication in Large-Scale Database Systems
|
cs.DB
|
We investigate a decentralised approach to committing transactions in a
replicated database, under partial replication. Previous protocols either
re-execute transactions entirely and/or compute a total order of transactions.
In contrast, ours applies update values, and orders only conflicting
transactions. It results that transactions execute faster, and distributed
databases commit in small committees. Both effects contribute to preserve
scalability as the number of databases and transactions increase. Our algorithm
ensures serializability, and is live and safe in spite of faults.
|
0802.0179
|
On the Relation Between the Index Coding and the Network Coding Problems
|
cs.IT math.IT
|
In this paper we show that the Index Coding problem captures several
important properties of the more general Network Coding problem. An instance of
the Index Coding problem includes a server that holds a set of information
messages $X=\{x_1,...,x_k\}$ and a set of receivers $R$. Each receiver has some
side information, known to the server, represented by a subset of $X$ and
demands another subset of $X$. The server uses a noiseless communication
channel to broadcast encodings of messages in $X$ to satisfy the receivers'
demands. The goal of the server is to find an encoding scheme that requires the
minimum number of transmissions.
We show that any instance of the Network Coding problem can be efficiently
reduced to an instance of the Index Coding problem. Our reduction shows that
several important properties of the Network Coding problem carry over to the
Index Coding problem. In particular, we prove that both scalar linear and
vector linear codes are insufficient for achieving the minimal number of
transmissions.
|
0802.0251
|
Multi-Layer Perceptrons and Symbolic Data
|
cs.NE
|
In some real world situations, linear models are not sufficient to represent
accurately complex relations between input variables and output variables of a
studied system. Multilayer Perceptrons are one of the most successful
non-linear regression tool but they are unfortunately restricted to inputs and
outputs that belong to a normed vector space. In this chapter, we propose a
general recoding method that allows to use symbolic data both as inputs and
outputs to Multilayer Perceptrons. The recoding is quite simple to implement
and yet provides a flexible framework that allows to deal with almost all
practical cases. The proposed method is illustrated on a real world data set.
|
0802.0252
|
Acc\'el\'eration des cartes auto-organisatrices sur tableau de
dissimilarit\'es par s\'eparation et \'evaluation
|
cs.NE
|
In this paper, a new implementation of the adaptation of Kohonen
self-organising maps (SOM) to dissimilarity matrices is proposed. This
implementation relies on the branch and bound principle to reduce the algorithm
running time. An important property of this new approach is that the obtained
algorithm produces exactly the same results as the standard algorithm.
|
0802.0287
|
A data-driven functional projection approach for the selection of
feature ranges in spectra with ICA or cluster analysis
|
cs.NE
|
Prediction problems from spectra are largely encountered in chemometry. In
addition to accurate predictions, it is often needed to extract information
about which wavelengths in the spectra contribute in an effective way to the
quality of the prediction. This implies to select wavelengths (or wavelength
intervals), a problem associated to variable selection. In this paper, it is
shown how this problem may be tackled in the specific case of smooth (for
example infrared) spectra. The functional character of the spectra (their
smoothness) is taken into account through a functional variable projection
procedure. Contrarily to standard approaches, the projection is performed on a
basis that is driven by the spectra themselves, in order to best fit their
characteristics. The methodology is illustrated by two examples of functional
projection, using Independent Component Analysis and functional variable
clustering, respectively. The performances on two standard infrared spectra
benchmarks are illustrated.
|
0802.0342
|
The Case for Structured Random Codes in Network Capacity Theorems
|
cs.IT math.IT
|
Random coding arguments are the backbone of most channel capacity
achievability proofs. In this paper, we show that in their standard form, such
arguments are insufficient for proving some network capacity theorems:
structured coding arguments, such as random linear or lattice codes, attain
higher rates. Historically, structured codes have been studied as a stepping
stone to practical constructions. However, K\"{o}rner and Marton demonstrated
their usefulness for capacity theorems through the derivation of the optimal
rate region of a distributed functional source coding problem. Here, we use
multicasting over finite field and Gaussian multiple-access networks as
canonical examples to demonstrate that even if we want to send bits over a
network, structured codes succeed where simple random codes fail. Beyond
network coding, we also consider distributed computation over noisy channels
and a special relay-type problem.
|
0802.0351
|
Path Loss Exponent Estimation in a Large Field of Interferers
|
cs.IT math.IT
|
In wireless channels, the path loss exponent (PLE) has a strong impact on the
quality of links, and hence, it needs to be accurately estimated for the
efficient design and operation of wireless networks. In this paper, we address
the problem of PLE estimation in large wireless networks, which is relevant to
several important issues in networked communications such as localization,
energy-efficient routing, and channel access. We consider a large ad hoc
network where nodes are distributed as a homogeneous Poisson point process on
the plane and the channels are subject to Nakagami-m fading. We propose and
discuss three distributed algorithms for estimating the PLE under these
settings which explicitly take into account the interference in the network. In
addition, we provide simulation results to demonstrate the performance of the
algorithms and quantify the estimation errors. We also describe how to estimate
the PLE accurately even in networks with spatially varying PLEs and more
general node distributions.
|
0802.0414
|
The exit problem in optimal non-causal extimation
|
math.OC cs.IT math.IT
|
We study the phenomenon of loss of lock in the optimal non-causal phase
estimation problem, a benchmark problem in nonlinear estimation. Our method is
based on the computation of the asymptotic distribution of the optimal
estimation error in case the number of trajectories in the optimization problem
is finite. The computation is based directly on the minimum noise energy
optimality criterion rather than on state equations of the error, as is the
usual case in the literature. The results include an asymptotic computation of
the mean time to lose lock (MTLL) in the optimal smoother. We show that the
MTLL in the first and second order smoothers is significantly longer than that
in the causal extended Kalman filter.
|
0802.0487
|
Algorithmically independent sequences
|
cs.IT cs.SE math.AG math.IT
|
Two objects are independent if they do not affect each other. Independence is
well-understood in classical information theory, but less in algorithmic
information theory. Working in the framework of algorithmic information theory,
the paper proposes two types of independence for arbitrary infinite binary
sequences and studies their properties. Our two proposed notions of
independence have some of the intuitive properties that one naturally expects.
For example, for every sequence $x$, the set of sequences that are independent
(in the weaker of the two senses) with $x$ has measure one. For both notions of
independence we investigate to what extent pairs of independent sequences, can
be effectively constructed via Turing reductions (from one or more input
sequences). In this respect, we prove several impossibility results. For
example, it is shown that there is no effective way of producing from an
arbitrary sequence with positive constructive Hausdorff dimension two sequences
that are independent (even in the weaker type of independence) and have
super-logarithmic complexity. Finally, a few conjectures and open questions are
discussed.
|
0802.0534
|
Capacity of Wireless Networks within o(log(SNR)) - the Impact of Relays,
Feedback, Cooperation and Full-Duplex Operation
|
cs.IT math.IT
|
Recent work has characterized the sum capacity of
time-varying/frequency-selective wireless interference networks and $X$
networks within $o(\log({SNR}))$, i.e., with an accuracy approaching 100% at
high SNR (signal to noise power ratio). In this paper, we seek similar capacity
characterizations for wireless networks with relays, feedback, full duplex
operation, and transmitter/receiver cooperation through noisy channels. First,
we consider a network with $S$ source nodes, $R$ relay nodes and $D$
destination nodes with random time-varying/frequency-selective channel
coefficients and global channel knowledge at all nodes. We allow full-duplex
operation at all nodes, as well as causal noise-free feedback of all received
signals to all source and relay nodes. The sum capacity of this network is
characterized as $\frac{SD}{S+D-1}\log({SNR})+o(\log({SNR}))$. The implication
of the result is that the capacity benefits of relays, causal feedback,
transmitter/receiver cooperation through physical channels and full duplex
operation become a negligible fraction of the network capacity at high SNR.
Some exceptions to this result are also pointed out in the paper. Second, we
consider a network with $K$ full duplex nodes with an independent message from
every node to every other node in the network. We find that the sum capacity of
this network is bounded below by $\frac{K(K-1)}{2K-2}+o(\log({SNR}))$ and
bounded above by $\frac{K(K-1)}{2K-3}+o(\log({SNR}))$.
|
0802.0554
|
Message-Passing Decoding of Lattices Using Gaussian Mixtures
|
cs.IT math.IT
|
A lattice decoder which represents messages explicitly as a mixture of
Gaussians functions is given. In order to prevent the number of functions in a
mixture from growing as the decoder iterations progress, a method for replacing
N Gaussian functions with M Gaussian functions, with M < N, is given. A squared
distance metric is used to select functions for combining. A pair of selected
Gaussians is replaced by a single Gaussian with the same first and second
moments. The metric can be computed efficiently, and at the same time, the
proposed algorithm empirically gives good results, for example, a dimension 100
lattice has a loss of 0.2 dB in signal-to-noise ratio at a probability of
symbol error of 10^{-5}.
|
0802.0580
|
Rotated and Scaled Alamouti Coding
|
cs.IT math.IT
|
Repetition-based retransmission is used in Alamouti-modulation [1998] for
$2\times 2$ MIMO systems. We propose to use instead of ordinary repetition
so-called "scaled repetition" together with rotation. It is shown that the
rotated and scaled Alamouti code has a hard-decision performance which is only
slightly worse than that of the Golden code [2005], the best known $2\times 2$
space-time code. Decoding the Golden code requires an exhaustive search over
all codewords, while our rotated and scaled Alamouti code can be decoded with
an acceptable complexity however.
|
0802.0738
|
MIMO Networks: the Effects of Interference
|
cs.IT math.IT
|
Multiple-input/multiple-output (MIMO) systems promise enormous capacity
increase and are being considered as one of the key technologies for future
wireless networks. However, the decrease in capacity due to the presence of
interferers in MIMO networks is not well understood. In this paper, we develop
an analytical framework to characterize the capacity of MIMO communication
systems in the presence of multiple MIMO co-channel interferers and noise. We
consider the situation in which transmitters have no information about the
channel and all links undergo Rayleigh fading. We first generalize the known
determinant representation of hypergeometric functions with matrix arguments to
the case when the argument matrices have eigenvalues of arbitrary multiplicity.
This enables the derivation of the distribution of the eigenvalues of Gaussian
quadratic forms and Wishart matrices with arbitrary correlation, with
application to both single user and multiuser MIMO systems. In particular, we
derive the ergodic mutual information for MIMO systems in the presence of
multiple MIMO interferers. Our analysis is valid for any number of interferers,
each with arbitrary number of antennas having possibly unequal power levels.
This framework, therefore, accommodates the study of distributed MIMO systems
and accounts for different positions of the MIMO interferers.
|
0802.0776
|
Distributed Compression for the Uplink of a Backhaul-Constrained
Coordinated Cellular Network
|
cs.IT math.IT
|
We consider a backhaul-constrained coordinated cellular network. That is, a
single-frequency network with $N+1$ multi-antenna base stations (BSs) that
cooperate in order to decode the users' data, and that are linked by means of a
common lossless backhaul, of limited capacity $\mathrm{R}$. To implement
receive cooperation, we propose distributed compression: $N$ BSs, upon
receiving their signals, compress them using a multi-source lossy compression
code. Then, they send the compressed vectors to a central BS, which performs
users' decoding. Distributed Wyner-Ziv coding is proposed to be used, and is
optimally designed in this work. The first part of the paper is devoted to a
network with a unique multi-antenna user, that transmits a predefined Gaussian
space-time codeword. For such a scenario, the compression codebooks at the BSs
are optimized, considering the user's achievable rate as the performance
metric. In particular, for $N = 1$ the optimum codebook distribution is derived
in closed form, while for $N>1$ an iterative algorithm is devised. The second
part of the contribution focusses on the multi-user scenario. For it, the
achievable rate region is obtained by means of the optimum compression
codebooks for sum-rate and weighted sum-rate, respectively.
|
0802.0797
|
Central Limit Theorems for Wavelet Packet Decompositions of Stationary
Random Processes
|
cs.IT math.IT
|
This paper provides central limit theorems for the wavelet packet
decomposition of stationary band-limited random processes. The asymptotic
analysis is performed for the sequences of the wavelet packet coefficients
returned at the nodes of any given path of the $M$-band wavelet packet
decomposition tree. It is shown that if the input process is centred and
strictly stationary, these sequences converge in distribution to white Gaussian
processes when the resolution level increases, provided that the decomposition
filters satisfy a suitable property of regularity. For any given path, the
variance of the limit white Gaussian process directly relates to the value of
the input process power spectral density at a specific frequency.
|
0802.0802
|
On Approximating Frequency Moments of Data Streams with Skewed
Projections
|
cs.DS cs.IT math.IT
|
We propose skewed stable random projections for approximating the pth
frequency moments of dynamic data streams (0<p<=2), which has been frequently
studied in theoretical computer science and database communities. Our method
significantly (or even infinitely when p->1) improves previous methods based on
(symmetric) stable random projections.
Our proposed method is applicable to data streams that are (a) insertion only
(the cash-register model); or (b) always non-negative (the strict Turnstile
model), or (c) eventually non-negative at check points. This is only a minor
restriction for practical applications.
Our method works particularly well when p = 1+/- \Delta and \Delta is small,
which is a practically important scenario. For example, \Delta may be the decay
rate or interest rate, which are usually small. Of course, when \Delta = 0, one
can compute the 1th frequent moment (i.e., the sum) essentially error-free
using a simple couter. Our method may be viewed as a ``genearlized counter'' in
that it can count the total value in the future, taking in account of the
effect of decaying or interest accruement.
In a summary, our contributions are two-fold. (A) This is the first propsal
of skewed stable random projections. (B) Based on first principle, we develop
various statistical estimators for skewed stable distributions, including their
variances and error (tail) probability bounds, and consequently the sample
complexity bounds.
|
0802.0808
|
Turbo Interleaving inside the cdma2000 and W-CDMA Mobile Communication
Systems: A Tutorial
|
cs.IT math.IT
|
In this paper a discussion of the detailed operation of the interleavers used
by the turbo codes defined on the telecommunications standards cdma2000 (3GPP2
C.S0024-B V2.0) and W-CDMA (3GPP TS 25.212 V7.4.0) is presented. Differences in
the approach used by each turbo interleaver as well as dispersion analysis and
frequency analysis are also discussed. Two examples are presented to illustrate
the complete interleaving process defined by each standard. These two
interleaving approaches are also representative for other communications
standards.
|
0802.0823
|
Doubly-Generalized LDPC Codes: Stability Bound over the BEC
|
cs.IT math.IT
|
The iterative decoding threshold of low-density parity-check (LDPC) codes
over the binary erasure channel (BEC) fulfills an upper bound depending only on
the variable and check nodes with minimum distance 2. This bound is a
consequence of the stability condition, and is here referred to as stability
bound. In this paper, a stability bound over the BEC is developed for
doubly-generalized LDPC codes, where the variable and the check nodes can be
generic linear block codes, assuming maximum a posteriori erasure correction at
each node. It is proved that in this generalized context as well the bound
depends only on the variable and check component codes with minimum distance 2.
A condition is also developed, namely the derivative matching condition, under
which the bound is achieved with equality.
|
0802.0835
|
Bit-Optimal Lempel-Ziv compression
|
cs.DS cs.IT math.IT
|
One of the most famous and investigated lossless data-compression scheme is
the one introduced by Lempel and Ziv about 40 years ago. This compression
scheme is known as "dictionary-based compression" and consists of squeezing an
input string by replacing some of its substrings with (shorter) codewords which
are actually pointers to a dictionary of phrases built as the string is
processed. Surprisingly enough, although many fundamental results are nowadays
known about upper bounds on the speed and effectiveness of this compression
process and references therein), ``we are not aware of any parsing scheme that
achieves optimality when the LZ77-dictionary is in use under any constraint on
the codewords other than being of equal length'' [N. Rajpoot and C. Sahinalp.
Handbook of Lossless Data Compression, chapter Dictionary-based data
compression. Academic Press, 2002. pag. 159]. Here optimality means to achieve
the minimum number of bits in compressing each individual input string, without
any assumption on its generating source. In this paper we provide the first
LZ-based compressor which computes the bit-optimal parsing of any input string
in efficient time and optimal space, for a general class of variable-length
codeword encodings which encompasses most of the ones typically used in data
compression and in the design of search engines and compressed indexes.
|
0802.0861
|
Using Bayesian Blocks to Partition Self-Organizing Maps
|
cs.NE
|
Self organizing maps (SOMs) are widely-used for unsupervised classification.
For this application, they must be combined with some partitioning scheme that
can identify boundaries between distinct regions in the maps they produce. We
discuss a novel partitioning scheme for SOMs based on the Bayesian Blocks
segmentation algorithm of Scargle [1998]. This algorithm minimizes a cost
function to identify contiguous regions over which the values of the attributes
can be represented as approximately constant. Because this cost function is
well-defined and largely independent of assumptions regarding the number and
structure of clusters in the original sample space, this partitioning scheme
offers significant advantages over many conventional methods. Sample code is
available.
|
0802.0914
|
Shrinkage Effect in Ancestral Maximum Likelihood
|
q-bio.PE cs.CE math.PR math.ST stat.TH
|
Ancestral maximum likelihood (AML) is a method that simultaneously
reconstructs a phylogenetic tree and ancestral sequences from extant data
(sequences at the leaves). The tree and ancestral sequences maximize the
probability of observing the given data under a Markov model of sequence
evolution, in which branch lengths are also optimized but constrained to take
the same value on any edge across all sequence sites. AML differs from the more
usual form of maximum likelihood (ML) in phylogenetics because ML averages over
all possible ancestral sequences. ML has long been known to be statistically
consistent -- that is, it converges on the correct tree with probability
approaching 1 as the sequence length grows. However, the statistical
consistency of AML has not been formally determined, despite informal remarks
in a literature that dates back 20 years. In this short note we prove a general
result that implies that AML is statistically inconsistent. In particular we
show that AML can `shrink' short edges in a tree, resulting in a tree that has
no internal resolution as the sequence length grows. Our results apply to any
number of taxa.
|
0802.1002
|
New Estimation Procedures for PLS Path Modelling
|
cs.LG
|
Given R groups of numerical variables X1, ... XR, we assume that each group
is the result of one underlying latent variable, and that all latent variables
are bound together through a linear equation system. Moreover, we assume that
some explanatory latent variables may interact pairwise in one or more
equations. We basically consider PLS Path Modelling's algorithm to estimate
both latent variables and the model's coefficients. New "external" estimation
schemes are proposed that draw latent variables towards strong group structures
in a more flexible way. New "internal" estimation schemes are proposed to
enable PLSPM to make good use of variable group complementarity and to deal
with interactions. Application examples are given.
|
0802.1220
|
Complexity of Decoding Positive-Rate Reed-Solomon Codes
|
cs.IT math.IT
|
The complexity of maximal likelihood decoding of the Reed-Solomon codes
$[q-1, k]_q$ is a well known open problem. The only known result in this
direction states that it is at least as hard as the discrete logarithm in some
cases where the information rate unfortunately goes to zero. In this paper, we
remove the rate restriction and prove that the same complexity result holds for
any positive information rate. In particular, this resolves an open problem
left in [4], and rules out the possibility of a polynomial time algorithm for
maximal likelihood decoding problem of Reed-Solomon codes of any rate under a
well known cryptographical hardness assumption. As a side result, we give an
explicit construction of Hamming balls of radius bounded away from the minimum
distance, which contain exponentially many codewords for Reed-Solomon code of
any positive rate less than one. The previous constructions only apply to
Reed-Solomon codes of diminishing rates. We also give an explicit construction
of Hamming balls of relative radius less than 1 which contain subexponentially
many codewords for Reed-Solomon code of rate approaching one.
|
0802.1244
|
Learning Balanced Mixtures of Discrete Distributions with Small Sample
|
cs.LG stat.ML
|
We study the problem of partitioning a small sample of $n$ individuals from a
mixture of $k$ product distributions over a Boolean cube $\{0, 1\}^K$ according
to their distributions. Each distribution is described by a vector of allele
frequencies in $\R^K$. Given two distributions, we use $\gamma$ to denote the
average $\ell_2^2$ distance in frequencies across $K$ dimensions, which
measures the statistical divergence between them. We study the case assuming
that bits are independently distributed across $K$ dimensions. This work
demonstrates that, for a balanced input instance for $k = 2$, a certain
graph-based optimization function returns the correct partition with high
probability, where a weighted graph $G$ is formed over $n$ individuals, whose
pairwise hamming distances between their corresponding bit vectors define the
edge weights, so long as $K = \Omega(\ln n/\gamma)$ and $Kn = \tilde\Omega(\ln
n/\gamma^2)$. The function computes a maximum-weight balanced cut of $G$, where
the weight of a cut is the sum of the weights across all edges in the cut. This
result demonstrates a nice property in the high-dimensional feature space: one
can trade off the number of features that are required with the size of the
sample to accomplish certain tasks like clustering.
|
0802.1258
|
Bayesian Nonlinear Principal Component Analysis Using Random Fields
|
cs.CV cs.LG
|
We propose a novel model for nonlinear dimension reduction motivated by the
probabilistic formulation of principal component analysis. Nonlinearity is
achieved by specifying different transformation matrices at different locations
of the latent space and smoothing the transformation using a Markov random
field type prior. The computation is made feasible by the recent advances in
sampling from von Mises-Fisher distributions.
|
0802.1296
|
On quantum statistics in data analysis
|
cs.IR math.CT quant-ph
|
Originally, quantum probability theory was developed to analyze statistical
phenomena in quantum systems, where classical probability theory does not
apply, because the lattice of measurable sets is not necessarily distributive.
On the other hand, it is well known that the lattices of concepts, that arise
in data analysis, are in general also non-distributive, albeit for completely
different reasons. In his recent book, van Rijsbergen argues that many of the
logical tools developed for quantum systems are also suitable for applications
in information retrieval. I explore the mathematical support for this idea on
an abstract vector space model, covering several forms of data analysis
(information retrieval, data mining, collaborative filtering, formal concept
analysis...), and roughly based on an idea from categorical quantum mechanics.
It turns out that quantum (i.e., noncommutative) probability distributions
arise already in this rudimentary mathematical framework. We show that a
Bell-type inequality must be satisfied by the standard similarity measures, if
they are used for preference predictions. The fact that already a very general,
abstract version of the vector space model yields simple counterexamples for
such inequalities seems to be an indicator of a genuine need for quantum
statistics in data analysis.
|
0802.1306
|
Network as a computer: ranking paths to find flows
|
cs.IR cs.AI math.CT
|
We explore a simple mathematical model of network computation, based on
Markov chains. Similar models apply to a broad range of computational
phenomena, arising in networks of computers, as well as in genetic, and neural
nets, in social networks, and so on. The main problem of interaction with such
spontaneously evolving computational systems is that the data are not uniformly
structured. An interesting approach is to try to extract the semantical content
of the data from their distribution among the nodes. A concept is then
identified by finding the community of nodes that share it. The task of data
structuring is thus reduced to the task of finding the network communities, as
groups of nodes that together perform some non-local data processing. Towards
this goal, we extend the ranking methods from nodes to paths. This allows us to
extract some information about the likely flow biases from the available static
information about the network.
|
0802.1327
|
Exchange of Limits: Why Iterative Decoding Works
|
cs.IT math.IT
|
We consider communication over binary-input memoryless output-symmetric
channels using low-density parity-check codes and message-passing decoding. The
asymptotic (in the length) performance of such a combination for a fixed number
of iterations is given by density evolution. Letting the number of iterations
tend to infinity we get the density evolution threshold, the largest channel
parameter so that the bit error probability tends to zero as a function of the
iterations.
In practice we often work with short codes and perform a large number of
iterations. It is therefore interesting to consider what happens if in the
standard analysis we exchange the order in which the blocklength and the number
of iterations diverge to infinity. In particular, we can ask whether both
limits give the same threshold.
Although empirical observations strongly suggest that the exchange of limits
is valid for all channel parameters, we limit our discussion to channel
parameters below the density evolution threshold. Specifically, we show that
under some suitable technical conditions the bit error probability vanishes
below the density evolution threshold regardless of how the limit is taken.
|
0802.1369
|
Interior-Point Algorithms for Linear-Programming Decoding
|
cs.IT math.IT
|
Interior-point algorithms constitute a very interesting class of algorithms
for solving linear-programming problems. In this paper we study efficient
implementations of such algorithms for solving the linear program that appears
in the linear-programming decoder formulation.
|
0802.1372
|
An integral formula for large random rectangular matrices and its
application to analysis of linear vector channels
|
cs.IT cond-mat.dis-nn math.IT
|
A statistical mechanical framework for analyzing random linear vector
channels is presented in a large system limit. The framework is based on the
assumptions that the left and right singular value bases of the rectangular
channel matrix $\bH$ are generated independently from uniform distributions
over Haar measures and the eigenvalues of $\bH^{\rm T}\bH$ asymptotically
follow a certain specific distribution. These assumptions make it possible to
characterize the communication performance of the channel utilizing an integral
formula with respect to $\bH$, which is analogous to the one introduced by
Marinari {\em et. al.} in {\em J. Phys. A} {\bf 27}, 7647 (1994) for large
random square (symmetric) matrices. A computationally feasible algorithm for
approximately decoding received signals based on the integral formula is also
provided.
|
0802.1380
|
New Bounds for the Capacity Region of the Finite-State Multiple Access
Channel
|
cs.IT math.IT
|
The capacity region of the Finite-State Multiple Access Channel (FS-MAC) with
feedback that may be an arbitrary time-invariant function of the channel output
samples is considered. We provided a sequence of inner and outer bounds for
this region. These bounds are shown to coincide, and hence yield the capacity
region, of FS-MACs where the state process is stationary and ergodic and not
affected by the inputs, and for indecomposable FS-MAC when feedback is not
allowed.
Though the capacity region is `multi-letter' in general, our results yield
explicit conclusions when applied to specific scenarios of interest.
|
0802.1383
|
On Directed Information and Gambling
|
cs.IT math.IT
|
We study the problem of gambling in horse races with causal side information
and show that Massey's directed information characterizes the increment in the
maximum achievable capital growth rate due to the availability of side
information. This result gives a natural interpretation of directed information
$I(Y^n \to X^n)$ as the amount of information that $Y^n$ \emph{causally}
provides about $X^n$. Extensions to stock market portfolio strategies and data
compression with causal side information are also discussed.
|
0802.1393
|
Les Agents comme des interpr\'eteurs Scheme : Sp\'ecification dynamique
par la communication
|
cs.MA cs.AI
|
We proposed in previous papers an extension and an implementation of the
STROBE model, which regards the Agents as Scheme interpreters. These Agents are
able to interpret messages in a dedicated environment including an interpreter
that learns from the current conversation therefore representing evolving
meta-level Agent's knowledge. When the Agent's interpreter is a
nondeterministic one, the dialogues may consist of subsequent refinements of
specifications in the form of constraint sets. The paper presents a worked out
example of dynamic service generation - such as necessary on Grids - by
exploiting STROBE Agents equipped with a nondeterministic interpreter. It shows
how enabling dynamic specification of a problem. Then it illustrates how these
principles could be effective for other applications. Details of the
implementation are not provided here, but are available.
|
0802.1412
|
Extreme Learning Machine for land cover classification
|
cs.NE cs.CV
|
This paper explores the potential of extreme learning machine based
supervised classification algorithm for land cover classification. In
comparison to a backpropagation neural network, which requires setting of
several user-defined parameters and may produce local minima, extreme learning
machine require setting of one parameter and produce a unique solution. ETM+
multispectral data set (England) was used to judge the suitability of extreme
learning machine for remote sensing classifications. A back propagation neural
network was used to compare its performance in term of classification accuracy
and computational cost. Results suggest that the extreme learning machine
perform equally well to back propagation neural network in term of
classification accuracy with this data set. The computational cost using
extreme learning machine is very small in comparison to back propagation neural
network.
|
0802.1430
|
A New Approach to Collaborative Filtering: Operator Estimation with
Spectral Regularization
|
cs.LG
|
We present a general approach for collaborative filtering (CF) using spectral
regularization to learn linear operators from "users" to the "objects" they
rate. Recent low-rank type matrix completion approaches to CF are shown to be
special cases. However, unlike existing regularization based CF methods, our
approach can be used to also incorporate information such as attributes of the
users or the objects -- a limitation of existing regularization based CF
methods. We then provide novel representer theorems that we use to develop new
estimation methods. We provide learning algorithms based on low-rank
decompositions, and test them on a standard CF dataset. The experiments
indicate the advantages of generalizing the existing regularization based CF
methods to incorporate related information about users and objects. Finally, we
show that certain multi-task learning methods can be also seen as special cases
of our proposed approach.
|
0802.1555
|
Constructing Linear Codes with Good Joint Spectra
|
cs.IT math.IT
|
The problem of finding good linear codes for joint source-channel coding
(JSCC) is investigated in this paper. By the code-spectrum approach, it has
been proved in the authors' previous paper that a good linear code for the
authors' JSCC scheme is a code with a good joint spectrum, so the main task in
this paper is to construct linear codes with good joint spectra. First, the
code-spectrum approach is developed further to facilitate the calculation of
spectra. Second, some general principles for constructing good linear codes are
presented. Finally, we propose an explicit construction of linear codes with
good joint spectra based on low density parity check (LDPC) codes and low
density generator matrix (LDGM) codes.
|
0802.1567
|
Universal Coding for Lossless and Lossy Complementary Delivery Problems
|
cs.IT math.IT
|
This paper deals with a coding problem called complementary delivery, where
messages from two correlated sources are jointly encoded and each decoder
reproduces one of two messages using the other message as the side information.
Both lossless and lossy universal complementary delivery coding schemes are
investigated. In the lossless case, it is demonstrated that a universal
complementary delivery code can be constructed by only combining two
Slepian-Wolf codes. Especially, it is shown that a universal lossless
complementary delivery code, for which error probability is exponentially
tight, can be constructed from two linear Slepian-Wolf codes. In the lossy
case, a universal complementary delivery coding scheme based on Wyner-Ziv codes
is proposed. While the proposed scheme cannot attain the optimal
rate-distortion trade-off in general, the rate-loss is upper bounded by a
universal constant under some mild conditions. The proposed schemes allows us
to apply any Slepian-Wolf and Wyner-Ziv codes to complementary delivery coding.
|
0802.1604
|
On the Complexity of Nash Equilibria of Action-Graph Games
|
cs.GT cs.MA
|
We consider the problem of computing Nash Equilibria of action-graph games
(AGGs). AGGs, introduced by Bhat and Leyton-Brown, is a succinct representation
of games that encapsulates both "local" dependencies as in graphical games, and
partial indifference to other agents' identities as in anonymous games, which
occur in many natural settings. This is achieved by specifying a graph on the
set of actions, so that the payoff of an agent for selecting a strategy depends
only on the number of agents playing each of the neighboring strategies in the
action graph. We present a Polynomial Time Approximation Scheme for computing
mixed Nash equilibria of AGGs with constant treewidth and a constant number of
agent types (and an arbitrary number of strategies), together with hardness
results for the cases when either the treewidth or the number of agent types is
unconstrained. In particular, we show that even if the action graph is a tree,
but the number of agent-types is unconstrained, it is NP-complete to decide the
existence of a pure-strategy Nash equilibrium and PPAD-complete to compute a
mixed Nash equilibrium (even an approximate one); similarly for symmetric AGGs
(all agents belong to a single type), if we allow arbitrary treewidth. These
hardness results suggest that, in some sense, our PTAS is as strong of a
positive result as one can expect.
|
0802.1738
|
Characterising through Erasing: A Theoretical Framework for Representing
Documents Inspired by Quantum Theory
|
cs.IR quant-ph
|
The problem of representing text documents within an Information Retrieval
system is formulated as an analogy to the problem of representing the quantum
states of a physical system. Lexical measurements of text are proposed as a way
of representing documents which are akin to physical measurements on quantum
states. Consequently, the representation of the text is only known after
measurements have been made, and because the process of measuring may destroy
parts of the text, the document is characterised through erasure. The
mathematical foundations of such a quantum representation of text are provided
in this position paper as a starting point for indexing and retrieval within a
``quantum like'' Information Retrieval system.
|
0802.1754
|
ARQ for Network Coding
|
cs.IT cs.NI math.IT
|
A new coding and queue management algorithm is proposed for communication
networks that employ linear network coding. The algorithm has the feature that
the encoding process is truly online, as opposed to a block-by-block approach.
The setup assumes a packet erasure broadcast channel with stochastic arrivals
and full feedback, but the proposed scheme is potentially applicable to more
general lossy networks with link-by-link feedback. The algorithm guarantees
that the physical queue size at the sender tracks the backlog in degrees of
freedom (also called the virtual queue size). The new notion of a node "seeing"
a packet is introduced. In terms of this idea, our algorithm may be viewed as a
natural extension of ARQ schemes to coded networks. Our approach, known as the
drop-when-seen algorithm, is compared with a baseline queuing approach called
drop-when-decoded. It is shown that the expected queue size for our approach is
$O(\frac1{1-\rho})$ as opposed to $\Omega(\frac1{(1-\rho)^2})$ for the baseline
approach, where $\rho$ is the load factor.
|
0802.1785
|
Near ML detection using Dijkstra's algorithm with bounded list size over
MIMO channels
|
cs.IT math.IT
|
We propose Dijkstra's algorithm with bounded list size after QR decomposition
for decreasing the computational complexity of near maximum-likelihood (ML)
detection of signals over multiple-input-multiple-output (MIMO) channels. After
that, we compare the performances of proposed algorithm, QR decomposition
M-algorithm (QRD-MLD), and its improvement. When the list size is set to
achieve the almost same symbol error rate (SER) as the QRD-MLD, the proposed
algorithm has smaller average computational complexity.
|
0802.1815
|
A Construction for Constant-Composition Codes
|
cs.IT math.IT
|
By employing the residue polynomials, a construction of constant-composition
codes is given. This construction generalizes the one proposed by Xing[16]. It
turns out that when d=3 this construction gives a lower bound of
constant-composition codes improving the one in [10]. Moreover, for d>3, we
give a lower bound on maximal size of constant-composition codes. In
particular, our bound for d=5 gives the best possible size of
constant-composition codes up to magnitude.
|
0802.1888
|
Multi-hop Cooperative Wireless Networks: Diversity Multiplexing Tradeoff
and Optimal Code Design
|
cs.IT math.IT
|
We consider single-source single-sink (ss-ss) multi-hop networks, with
slow-fading links and single-antenna half-duplex relays. We identify two
families of networks that are multi-hop generalizations of the well-studied
two-hop network: K-Parallel-Path (KPP) networks and layered networks. KPP
networks can be viewed as the union of K node-disjoint parallel relaying paths,
each of length greater than one. KPP networks are then generalized to KPP(I)
networks, which permit interference between paths and to KPP(D) networks, which
possess a direct link from source to sink. We characterize the DMT of these
families of networks completely for K > 3. Layered networks are networks
comprising of relaying layers with edges existing only within the same layer or
between adjacent layers. We prove that a linear DMT between the maximum
diversity d_{max} and the maximum multiplexing gain of 1 is achievable for
fully-connected layered networks. This is shown to be equal to the optimal DMT
if the number of layers is less than 4. For multi-antenna KPP and layered
networks, we provide an achievable DMT region.
For arbitrary ss-ss single-antenna directed-acyclic full-duplex networks, we
prove that a linear tradeoff between maximum diversity and maximum multiplexing
gain is achievable. All protocols in this paper are explicit and use only
amplify and forward (AF) relaying. We also construct codes with short
block-lengths based on cyclic division algebras that achieve the optimal DMT
for all the proposed schemes. Two key implications of the results in the paper
are that the half-duplex constraint does not entail any rate loss for a large
class of networks and that simple AF protocols are often sufficient to attain
the optimal DMT.
|
0802.1893
|
Diversity and Degrees of Freedom of Cooperative Wireless Networks
|
cs.IT math.IT
|
Wireless fading networks with multiple antennas are typically studied
information-theoretically from two different perspectives - the outage
characterization and the ergodic capacity characterization. A key parameter in
the outage characterization of a network is the diversity, whereas a
first-order indicator for the ergodic capacity is the degrees of freedom (DOF),
which is the pre-log coefficient in the capacity expression. In this paper, we
present max-flow min-cut type theorems for computing both the diversity and the
degrees of freedom of arbitrary single-source single-sink multi-antenna
networks. We also show that an amplify-and-forward protocol is sufficient to
achieve this. The degrees of freedom characterization is obtained using a
conversion to a deterministic wireless network for which the capacity was
recently found. We show that the diversity result easily extends to
multi-source multi-sink networks and evaluate the DOF for multi-casting in
single-source multi-sink networks.
|
0802.2001
|
Exploiting problem structure in a genetic algorithm approach to a nurse
rostering problem
|
cs.NE cs.CE
|
There is considerable interest in the use of genetic algorithms to solve
problems arising in the areas of scheduling and timetabling. However, the
classical genetic algorithm paradigm is not well equipped to handle the
conflict between objectives and constraints that typically occurs in such
problems. In order to overcome this, successful implementations frequently make
use of problem specific knowledge. This paper is concerned with the development
of a GA for a nurse rostering problem at a major UK hospital. The structure of
the constraints is used as the basis for a co-evolutionary strategy using
co-operating sub-populations. Problem specific knowledge is also used to define
a system of incentives and disincentives, and a complementary mutation
operator. Empirical results based on 52 weeks of live data show how these
features are able to improve an unsuccessful canonical GA to the point where it
is able to provide a practical solution to the problem
|
0802.2013
|
Throughput-Delay Trade-off for Hierarchical Cooperation in Ad Hoc
Wireless Networks
|
cs.IT math.IT
|
Hierarchical cooperation has recently been shown to achieve better throughput
scaling than classical multihop schemes under certain assumptions on the
channel model in static wireless networks. However, the end-to-end delay of
this scheme turns out to be significantly larger than those of multihop
schemes. A modification of the scheme is proposed here that achieves a
throughput-delay trade-off $D(n)=(\log n)^2 T(n)$ for T(n) between
$\Theta(\sqrt{n}/\log n)$ and $\Theta(n/\log n)$, where D(n) and T(n) are
respectively the average delay per bit and the aggregate throughput in a
network of n nodes. This trade-off complements the previous results of El Gamal
et al., which show that the throughput-delay trade-off for multihop schemes is
given by D(n)=T(n) where T(n) lies between $\Theta(1)$ and $\Theta(\sqrt{n})$.
Meanwhile, the present paper considers the network multiple-access problem,
which may be of interest in its own right.
|
0802.2015
|
Combining Expert Advice Efficiently
|
cs.LG cs.DS cs.IT math.IT
|
We show how models for prediction with expert advice can be defined concisely
and clearly using hidden Markov models (HMMs); standard HMM algorithms can then
be used to efficiently calculate, among other things, how the expert
predictions should be weighted according to the model. We cast many existing
models as HMMs and recover the best known running times in each case. We also
describe two new models: the switch distribution, which was recently developed
to improve Bayesian/Minimum Description Length model selection, and a new
generalisation of the fixed share algorithm based on run-length coding. We give
loss bounds for all models and shed new light on their relationships.
|
0802.2045
|
Blocking Sets in the complement of hyperplane arrangements in projective
space
|
cs.IT math.IT
|
It is well know that the theory of minimal blocking sets is studied by
several author. Another theory which is also studied by a large number of
researchers is the theory of hyperplane arrangements. We can remark that the
affine space $AG(n,q)$ is the complement of the line at infinity in $PG(n,q)$.
Then $AG(n,q)$ can be regarded as the complement of an hyperplane arrangement
in $PG(n,q)$! Therefore the study of blocking sets in the affine space
$AG(n,q)$ is simply the study of blocking sets in the complement of a finite
arrangement in $PG(n,q)$. In this paper the author generalizes this remark
starting to study the problem of existence of blocking sets in the complement
of a given hyperplane arrangement in $PG(n,q)$. As an example she solves the
problem for the case of braid arrangement. Moreover she poses significant
questions on this new and interesting problem.
|
0802.2125
|
Multiple Access Outerbounds and the Inseparability of Parallel
Interference Channels
|
cs.IT math.IT
|
It is known that the capacity of parallel (multi-carrier) Gaussian
point-to-point, multiple access and broadcast channels can be achieved by
separate encoding for each subchannel (carrier) subject to a power allocation
across carriers. In this paper we show that such a separation does not apply to
parallel Gaussian interference channels in general. A counter-example is
provided in the form of a 3 user interference channel where separate encoding
can only achieve a sum capacity of $\log({SNR})+o(\log({SNR}))$ per carrier
while the actual capacity, achieved only by joint-encoding across carriers, is
$3/2\log({SNR}))+o(\log({SNR}))$ per carrier. As a byproduct of our analysis,
we propose a class of multiple-access-outerbounds on the capacity of the 3 user
interference channel.
|
0802.2127
|
New Implementation Framework for Saturation-Based Reasoning
|
cs.AI cs.LO
|
The saturation-based reasoning methods are among the most theoretically
developed ones and are used by most of the state-of-the-art first-order logic
reasoners. In the last decade there was a sharp increase in performance of such
systems, which I attribute to the use of advanced calculi and the intensified
research in implementation techniques. However, nowadays we are witnessing a
slowdown in performance progress, which may be considered as a sign that the
saturation-based technology is reaching its inherent limits. The position I am
trying to put forward in this paper is that such scepticism is premature and a
sharp improvement in performance may potentially be reached by adopting new
architectural principles for saturation. The top-level algorithms and
corresponding designs used in the state-of-the-art saturation-based theorem
provers have (at least) two inherent drawbacks: the insufficient flexibility of
the used inference selection mechanisms and the lack of means for intelligent
prioritising of search directions. In this position paper I analyse these
drawbacks and present two ideas on how they could be overcome. In particular, I
propose a flexible low-cost high-precision mechanism for inference selection,
intended to overcome problems associated with the currently used instances of
clause selection-based procedures. I also outline a method for intelligent
prioritising of search directions, based on probing the search space by
exploring generalised search directions. I discuss some technical issues
related to implementation of the proposed architectural principles and outline
possible solutions.
|
0802.2138
|
Support Vector classifiers for Land Cover Classification
|
cs.NE cs.CV
|
Support vector machines represent a promising development in machine learning
research that is not widely used within the remote sensing community. This
paper reports the results of Multispectral(Landsat-7 ETM+) and Hyperspectral
DAIS)data in which multi-class SVMs are compared with maximum likelihood and
artificial neural network methods in terms of classification accuracy. Our
results show that the SVM achieves a higher level of classification accuracy
than either the maximum likelihood or the neural classifier, and that the
support vector machine can be used with small training datasets and
high-dimensional data.
|
0802.2158
|
A Radar-Shaped Statistic for Testing and Visualizing Uniformity
Properties in Computer Experiments
|
cs.LG math.ST stat.TH
|
In the study of computer codes, filling space as uniformly as possible is
important to describe the complexity of the investigated phenomenon. However,
this property is not conserved by reducing the dimension. Some numeric
experiment designs are conceived in this sense as Latin hypercubes or
orthogonal arrays, but they consider only the projections onto the axes or the
coordinate planes. In this article we introduce a statistic which allows
studying the good distribution of points according to all 1-dimensional
projections. By angularly scanning the domain, we obtain a radar type
representation, allowing the uniformity defects of a design to be identified
with respect to its projections onto straight lines. The advantages of this new
tool are demonstrated on usual examples of space-filling designs (SFD) and a
global statistic independent of the angle of rotation is studied.
|
0802.2159
|
A Distributed Merge and Split Algorithm for Fair Cooperation in Wireless
Networks
|
cs.IT cs.GT math.IT
|
This paper introduces a novel concept from coalitional game theory which
allows the dynamic formation of coalitions among wireless nodes. A simple and
distributed merge and split algorithm for coalition formation is constructed.
This algorithm is applied to study the gains resulting from the cooperation
among single antenna transmitters for virtual MIMO formation. The aim is to
find an ultimate transmitters coalition structure that allows cooperating users
to maximize their utilities while accounting for the cost of coalition
formation. Through this novel game theoretical framework, the wireless network
transmitters are able to self-organize and form a structured network composed
of disjoint stable coalitions. Simulation results show that the proposed
algorithm can improve the average individual user utility by 26.4% as well as
cope with the mobility of the distributed users.
|
0802.2234
|
Textual Fingerprinting with Texts from Parkin, Bassewitz, and Leander
|
cs.CL cs.CR
|
Current research in author profiling to discover a legal author's fingerprint
does not only follow examinations based on statistical parameters only but
include more and more dynamic methods that can learn and that react adaptable
to the specific behavior of an author. But the question on how to appropriately
represent a text is still one of the fundamental tasks, and the problem of
which attribute should be used to fingerprint the author's style is still not
exactly defined. In this work, we focus on linguistic selection of attributes
to fingerprint the style of the authors Parkin, Bassewitz and Leander. We use
texts of the genre Fairy Tale as it has a clear style and texts of a shorter
size with a straightforward story-line and a simple language.
|
0802.2305
|
Compressed Counting
|
cs.IT cs.CC cs.DM cs.DS cs.LG math.IT
|
Counting is among the most fundamental operations in computing. For example,
counting the pth frequency moment has been a very active area of research, in
theoretical computer science, databases, and data mining. When p=1, the task
(i.e., counting the sum) can be accomplished using a simple counter.
Compressed Counting (CC) is proposed for efficiently computing the pth
frequency moment of a data stream signal A_t, where 0<p<=2. CC is applicable if
the streaming data follow the Turnstile model, with the restriction that at the
time t for the evaluation, A_t[i]>= 0, which includes the strict Turnstile
model as a special case. For natural data streams encountered in practice, this
restriction is minor.
The underly technique for CC is what we call skewed stable random
projections, which captures the intuition that, when p=1 a simple counter
suffices, and when p = 1+/\Delta with small \Delta, the sample complexity of a
counter system should be low (continuously as a function of \Delta). We show at
small \Delta the sample complexity (number of projections) k = O(1/\epsilon)
instead of O(1/\epsilon^2).
Compressed Counting can serve a basic building block for other tasks in
statistics and computing, for example, estimation entropies of data streams,
parameter estimations using the method of moments and maximum likelihood.
Finally, another contribution is an algorithm for approximating the
logarithmic norm, \sum_{i=1}^D\log A_t[i], and logarithmic distance. The
logarithmic distance is useful in machine learning practice with heavy-tailed
data.
|
0802.2345
|
On the Frame Error Rate of Transmission Schemes on Quasi-Static Fading
Channels
|
cs.IT math.IT
|
It is known that the frame error rate of turbo codes on quasi-static fading
channels can be accurately approximated using the convergence threshold of the
corresponding iterative decoder. This paper considers quasi-static fading
channels and demonstrates that non-iterative schemes can also be characterized
by a similar threshold based on which their frame error rate can be readily
estimated. In particular, we show that this threshold is a function of the
probability of successful frame detection in additive white Gaussian noise,
normalized by the squared instantaneous signal-to-noise ratio. We apply our
approach to uncoded binary phase shift keying, convolutional coding and turbo
coding and demonstrate that the approximated frame error rate is within 0.4 dB
of the simulation results. Finally, we introduce performance evaluation plots
to explore the impact of the frame size on the performance of the schemes under
investigation.
|
0802.2349
|
Algebraic geometry codes from higher dimensional varieties
|
cs.IT math.IT
|
This paper is a general survey of literature on Goppa-type codes from higher
dimensional algebraic varieties. The construction and several techniques for
estimating the minimum distance are described first. Codes from various classes
of varieties, including Hermitian hypersurfaces, Grassmannians, flag varieties,
ruled surfaces over curves, and Deligne-Lusztig varieties are considered.
Connections with the theories of toric codes and order domains are also briefly
indicated.
|
0802.2360
|
On Maximizing Coverage in Gaussian Relay Networks
|
cs.IT math.IT
|
Results for Gaussian relay channels typically focus on maximizing
transmission rates for given locations of the source, relay and destination. We
introduce an alternative perspective, where the objective is maximizing
coverage for a given rate. The new objective captures the problem of how to
deploy relays to provide a given level of service to a particular geographic
area, where the relay locations become a design parameter that can be
optimized. We evaluate the decode and forward (DF) and compress and forward
(CF) strategies for the relay channel with respect to the new objective of
maximizing coverage. When the objective is maximizing rate, different locations
of the destination favor different strategies. When the objective is coverage
for a given rate, and the relay is able to decode, DF is uniformly superior in
that it provides coverage at any point served by CF. When the channel model is
modified to include random fading, we show that the monotone ordering of
coverage regions is not always maintained. While the coverage provided by DF is
sensitive to changes in the location of the relay and the path loss exponent,
CF exhibits a more graceful degradation with respect to such changes. The
techniques used to approximate coverage regions are new and may be of
independent interest.
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