id stringlengths 9 16 | title stringlengths 4 278 | categories stringlengths 5 104 | abstract stringlengths 6 4.09k |
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cs/0503033 | An Introduction to the Summarization of Evolving Events: Linear and
Non-linear Evolution | cs.CL cs.IR | This paper examines the summarization of events that evolve through time. It
discusses different types of evolution taking into account the time in which
the incidents of an event are happening and the different sources reporting on
the specific event. It proposes an approach for multi-document summarization
which em... |
cs/0503037 | Mining Top-k Approximate Frequent Patterns | cs.DB cs.AI | Frequent pattern (itemset) mining in transactional databases is one of the
most well-studied problems in data mining. One obstacle that limits the
practical usage of frequent pattern mining is the extremely large number of
patterns generated. Such a large size of the output collection makes it
difficult for users to ... |
cs/0503038 | On a Kronecker products sum distance bounds | cs.IT math.IT | A binary linear error correcting codes represented by two code families
Kronecker products sum are considered. The dimension and distance of new code
is investigated. Upper and lower bounds of distance are obtained. Some examples
are given. It is shown that some classic constructions are the private cases of
consider... |
cs/0503040 | Uplink Throughput in a Single-Macrocell/Single-Microcell CDMA System,
with Application to Data Access Points | cs.IT math.IT | This paper studies a two-tier CDMA system in which the microcell base is
converted into a data access point (DAP), i.e., a limited-range base station
that provides high-speed access to one user at a time. The microcell (or DAP)
user operates on the same frequency as the macrocell users and has the same
chip rate. How... |
cs/0503041 | Soft Handoff and Uplink Capacity in a Two-Tier CDMA System | cs.IT math.IT | This paper examines the effect of soft handoff on the uplink user capacity of
a CDMA system consisting of a single macrocell in which a single hotspot
microcell is embedded. The users of these two base stations operate over the
same frequency band. In the soft handoff scenario studied here, both macrocell
and microce... |
cs/0503042 | Uplink User Capacity in a CDMA System with Hotspot Microcells: Effects
of Finite Transmit Power and Dispersion | cs.IT math.IT | This paper examines the uplink user capacity in a two-tier code division
multiple access (CDMA) system with hotspot microcells when user terminal power
is limited and the wireless channel is finitely-dispersive. A
finitely-dispersive channel causes variable fading of the signal power at the
output of the RAKE receive... |
cs/0503043 | Complexity Issues in Finding Succinct Solutions of PSPACE-Complete
Problems | cs.AI cs.CC cs.LO | We study the problem of deciding whether some PSPACE-complete problems have
models of bounded size. Contrary to problems in NP, models of PSPACE-complete
problems may be exponentially large. However, such models may take polynomial
space in a succinct representation. For example, the models of a QBF are
explicitely r... |
cs/0503044 | Generating Hard Satisfiable Formulas by Hiding Solutions Deceptively | cs.AI cond-mat.other cond-mat.stat-mech | To test incomplete search algorithms for constraint satisfaction problems
such as 3-SAT, we need a source of hard, but satisfiable, benchmark instances.
A simple way to do this is to choose a random truth assignment A, and then
choose clauses randomly from among those satisfied by A. However, this method
tends to pro... |
cs/0503046 | Hiding Satisfying Assignments: Two are Better than One | cs.AI cond-mat.dis-nn cond-mat.stat-mech cs.CC | The evaluation of incomplete satisfiability solvers depends critically on the
availability of hard satisfiable instances. A plausible source of such
instances consists of random k-SAT formulas whose clauses are chosen uniformly
from among all clauses satisfying some randomly chosen truth assignment A.
Unfortunately, ... |
cs/0503047 | On Multiflows in Random Unit-Disk Graphs, and the Capacity of Some
Wireless Networks | cs.IT math.IT | We consider the capacity problem for wireless networks. Networks are modeled
as random unit-disk graphs, and the capacity problem is formulated as one of
finding the maximum value of a multicommodity flow. In this paper, we develop a
proof technique based on which we are able to obtain a tight characterization
of the... |
cs/0503052 | Zeta-Dimension | cs.CC cs.IT math.IT | The zeta-dimension of a set A of positive integers is the infimum s such that
the sum of the reciprocals of the s-th powers of the elements of A is finite.
Zeta-dimension serves as a fractal dimension on the positive integers that
extends naturally usefully to discrete lattices such as the set of all integer
lattic... |
cs/0503053 | A hybrid MLP-PNN architecture for fast image superresolution | cs.CV cs.MM | Image superresolution methods process an input image sequence of a scene to
obtain a still image with increased resolution. Classical approaches to this
problem involve complex iterative minimization procedures, typically with high
computational costs. In this paper is proposed a novel algorithm for
super-resolution ... |
cs/0503056 | Semi-automatic vectorization of linear networks on rasterized
cartographic maps | cs.CV cs.MM | A system for semi-automatic vectorization of linear networks (roads, rivers,
etc.) on rasterized cartographic maps is presented. In this system, human
intervention is limited to a graphic, interactive selection of the color
attributes of the information to be obtained. Using this data, the system
performs a prelimina... |
cs/0503058 | On the Stopping Distance and the Stopping Redundancy of Codes | cs.IT cs.DM math.IT | It is now well known that the performance of a linear code $C$ under
iterative decoding on a binary erasure channel (and other channels) is
determined by the size of the smallest stopping set in the Tanner graph for
$C$. Several recent papers refer to this parameter as the \emph{stopping
distance} $s$ of $C$. This is... |
cs/0503059 | Les repr\'{e}sentations g\'{e}n\'{e}tiques d'objets : simples analogies
ou mod\`{e}les pertinents ? Le point de vue de l'
"\'{e}volutique".<br>–––<br>Genetic representations of
objects : simple analogies or efficient models ? The "evolutic" point of view | cs.AI nlin.AO | Depuis une trentaine d'ann\'{e}es, les ing\'{e}nieurs utilisent couramment
des analogies avec l'\'{e}volution naturelle pour optimiser des dispositifs
techniques. Le plus souvent, ces m\'{e}thodes "g\'{e}n\'{e}tiques" ou
"\'{e}volutionnaires" sont consid\'{e}r\'{e}es uniquement du point de vue
pratique, comme des m\'... |
cs/0503061 | Integrity Constraints in Trust Management | cs.CR cs.DB | We introduce the use, monitoring, and enforcement of integrity constraints in
trust management-style authorization systems. We consider what portions of the
policy state must be monitored to detect violations of integrity constraints.
Then we address the fact that not all participants in a trust management system
can... |
cs/0503062 | On the Complexity of Nonrecursive XQuery and Functional Query Languages
on Complex Values | cs.DB cs.CC | This paper studies the complexity of evaluating functional query languages
for complex values such as monad algebra and the recursion-free fragment of
XQuery.
We show that monad algebra with equality restricted to atomic values is
complete for the class TA[2^{O(n)}, O(n)] of problems solvable in linear
exponential ... |
cs/0503063 | Randomly Spread CDMA: Asymptotics via Statistical Physics | cs.IT math.IT | This paper studies randomly spread code-division multiple access (CDMA) and
multiuser detection in the large-system limit using the replica method
developed in statistical physics. Arbitrary input distributions and flat fading
are considered. A generic multiuser detector in the form of the posterior mean
estimator is... |
cs/0503064 | Minimum-Cost Multicast over Coded Packet Networks | cs.IT cs.NI math.IT | We consider the problem of establishing minimum-cost multicast connections
over coded packet networks, i.e. packet networks where the contents of outgoing
packets are arbitrary, causal functions of the contents of received packets. We
consider both wireline and wireless packet networks as well as both static
multicas... |
cs/0503070 | Improved message passing for inference in densely connected systems | cs.IT cond-mat.dis-nn math.IT | An improved inference method for densely connected systems is presented. The
approach is based on passing condensed messages between variables, representing
macroscopic averages of microscopic messages. We extend previous work that
showed promising results in cases where the solution space is contiguous to
cases wher... |
cs/0503071 | Consistency in Models for Distributed Learning under Communication
Constraints | cs.IT cs.LG math.IT | Motivated by sensor networks and other distributed settings, several models
for distributed learning are presented. The models differ from classical works
in statistical pattern recognition by allocating observations of an independent
and identically distributed (i.i.d.) sampling process amongst members of a
network ... |
cs/0503072 | Distributed Learning in Wireless Sensor Networks | cs.IT cs.LG math.IT | The problem of distributed or decentralized detection and estimation in
applications such as wireless sensor networks has often been considered in the
framework of parametric models, in which strong assumptions are made about a
statistical description of nature. In certain applications, such assumptions
are warranted... |
cs/0503076 | Geometric Models of Rolling-Shutter Cameras | cs.CV cs.RO | Cameras with rolling shutters are becoming more common as low-power, low-cost
CMOS sensors are being used more frequently in cameras. The rolling shutter
means that not all scanlines are exposed over the same time interval. The
effects of a rolling shutter are noticeable when either the camera or objects
in the scene... |
cs/0503077 | Weighted Automata in Text and Speech Processing | cs.CL cs.HC | Finite-state automata are a very effective tool in natural language
processing. However, in a variety of applications and especially in speech
precessing, it is necessary to consider more general machines in which arcs are
assigned weights or costs. We briefly describe some of the main theoretical and
algorithmic asp... |
cs/0503078 | Obtaining Membership Functions from a Neuron Fuzzy System extended by
Kohonen Network | cs.NE | This article presents the Neo-Fuzzy-Neuron Modified by Kohonen Network
(NFN-MK), an hybrid computational model that combines fuzzy system technique
and artificial neural networks. Its main task consists in the automatic
generation of membership functions, in particular, triangle forms, aiming a
dynamic modeling of a ... |
cs/0503079 | Space-time databases modeling global semantic networks | cs.IT cs.IR math.IT | This paper represents an approach to creating global knowledge systems, using
new philosophy and infrastructure of global distributed semantic network (frame
knowledge representation system) based on the space-time database construction.
The main idea of the space-time database environment introduced in the paper is
... |
cs/0503081 | An Optimization Model for Outlier Detection in Categorical Data | cs.DB cs.AI | The task of outlier detection is to find small groups of data objects that
are exceptional when compared with rest large amount of data. Detection of such
outliers is important for many applications such as fraud detection and
customer migration. Most existing methods are designed for numeric data. They
will encounte... |
cs/0503082 | Spines of Random Constraint Satisfaction Problems: Definition and
Connection with Computational Complexity | cs.CC cond-mat.dis-nn cs.AI | We study the connection between the order of phase transitions in
combinatorial problems and the complexity of decision algorithms for such
problems. We rigorously show that, for a class of random constraint
satisfaction problems, a limited connection between the two phenomena indeed
exists. Specifically, we extend t... |
cs/0503084 | The Peculiarities of Nonstationary Formation of Inhomogeneous Structures
of Charged Particles in the Electrodiffusion Processes | cs.CE | In this paper the distribution of charged particles is constructed under the
approximation of ambipolar diffusion. The results of mathematical modelling in
two-dimensional case taking into account the velocities of the system are
presented.
|
cs/0503085 | Dynamic Shannon Coding | cs.IT math.IT | We present a new algorithm for dynamic prefix-free coding, based on Shannon
coding. We give a simple analysis and prove a better upper bound on the length
of the encoding produced than the corresponding bound for dynamic Huffman
coding. We show how our algorithm can be modified for efficient
length-restricted coding,... |
cs/0503087 | Dynamic Simulation of Construction Machinery: Towards an Operator Model | cs.CE | In dynamic simulation of complete wheel loaders, one interesting aspect,
specific for the working task, is the momentary power distribution between
drive train and hydraulics, which is balanced by the operator.
This paper presents the initial results to a simulation model of a human
operator. Rather than letting th... |
cs/0503088 | General non-asymptotic and asymptotic formulas in channel resolvability
and identification capacity and their application to wire-tap channel | cs.IT math.IT | Several non-asymptotic formulas are established in channel resolvability and
identification capacity, and they are applied to wire-tap channel. By using
these formulas, the $\epsilon$ capacities of the above three problems are
considered in the most general setting, where no structural assumptions such as
the station... |
cs/0503089 | Second order asymptotics in fixed-length source coding and intrinsic
randomness | cs.IT math.IT | Second order asymptotics of fixed-length source coding and intrinsic
randomness is discussed with a constant error constraint. There was a
difference between optimal rates of fixed-length source coding and intrinsic
randomness, which never occurred in the first order asymptotics. In addition,
the relation between uni... |
cs/0503092 | Monotonic and Nonmonotonic Preference Revision | cs.DB cs.AI | We study here preference revision, considering both the monotonic case where
the original preferences are preserved and the nonmonotonic case where the new
preferences may override the original ones. We use a relational framework in
which preferences are represented using binary relations (not necessarily
finite). We... |
cs/0504001 | Probabilistic and Team PFIN-type Learning: General Properties | cs.LG | We consider the probability hierarchy for Popperian FINite learning and study
the general properties of this hierarchy. We prove that the probability
hierarchy is decidable, i.e. there exists an algorithm that receives p_1 and
p_2 and answers whether PFIN-type learning with the probability of success p_1
is equivalen... |
cs/0504003 | Multiple Description Quantization via Gram-Schmidt Orthogonalization | cs.IT math.IT | The multiple description (MD) problem has received considerable attention as
a model of information transmission over unreliable channels. A general
framework for designing efficient multiple description quantization schemes is
proposed in this paper. We provide a systematic treatment of the El Gamal-Cover
(EGC) achi... |
cs/0504005 | Fast Codes for Large Alphabets | cs.IT math.IT | We address the problem of constructing a fast lossless code in the case when
the source alphabet is large. The main idea of the new scheme may be described
as follows. We group letters with small probabilities in subsets (acting as
super letters) and use time consuming coding for these subsets only, whereas
letters i... |
cs/0504006 | Using Information Theory Approach to Randomness Testing | cs.IT math.IT | We address the problem of detecting deviations of binary sequence from
randomness,which is very important for random number (RNG) and pseudorandom
number generators (PRNG). Namely, we consider a null hypothesis $H_0$ that a
given bit sequence is generated by Bernoulli source with equal probabilities of
0 and 1 and th... |
cs/0504010 | Reversible Fault-Tolerant Logic | cs.IT math.IT quant-ph | It is now widely accepted that the CMOS technology implementing irreversible
logic will hit a scaling limit beyond 2016, and that the increased power
dissipation is a major limiting factor. Reversible computing can potentially
require arbitrarily small amounts of energy. Recently several nano-scale
devices which have... |
cs/0504011 | Average Coset Weight Distribution of Combined LDPC Matrix Ensemble | cs.IT math.IT | In this paper, the average coset weight distribution (ACWD) of structured
ensembles of LDPC (Low-density Parity-Check) matrix, which is called combined
ensembles, is discussed. A combined ensemble is composed of a set of simpler
ensembles such as a regular bipartite ensemble. Two classes of combined
ensembles have pr... |
cs/0504013 | Pseudocodewords of Tanner graphs | cs.IT math.IT | This papers presents a detailed analysis of pseudocodewords of Tanner graphs.
Pseudocodewords arising on the iterative decoder's computation tree are
distinguished from pseudocodewords arising on finite degree lifts. Lower bounds
on the minimum pseudocodeword weight are presented for the BEC, BSC, and AWGN
channel. S... |
cs/0504014 | Network Information Flow with Correlated Sources | cs.IT math.IT | In this paper, we consider a network communications problem in which multiple
correlated sources must be delivered to a single data collector node, over a
network of noisy independent point-to-point channels. We prove that perfect
reconstruction of all the sources at the sink is possible if and only if, for
all parti... |
cs/0504015 | Design of Block Transceivers with Decision Feedback Detection | cs.IT math.IT | This paper presents a method for jointly designing the transmitter-receiver
pair in a block-by-block communication system that employs (intra-block)
decision feedback detection. We provide closed-form expressions for
transmitter-receiver pairs that simultaneously minimize the arithmetic mean
squared error (MSE) at th... |
cs/0504016 | Shortened Array Codes of Large Girth | cs.DM cs.IT math.IT | One approach to designing structured low-density parity-check (LDPC) codes
with large girth is to shorten codes with small girth in such a manner that the
deleted columns of the parity-check matrix contain all the variables involved
in short cycles. This approach is especially effective if the parity-check
matrix of ... |
cs/0504017 | A new SISO algorithm with application to turbo equalization | cs.IT math.IT | In this paper we propose a new soft-input soft-output equalization algorithm,
offering very good performance/complexity tradeoffs. It follows the structure
of the BCJR algorithm, but dynamically constructs a simplified trellis during
the forward recursion. In each trellis section, only the M states with the
strongest... |
cs/0504020 | The Viterbi Algorithm: A Personal History | cs.IT math.IT | The story of the Viterbi algorithm (VA) is told from a personal perspective.
Applications both within and beyond communications are discussed. In brief
summary, the VA has proved to be an extremely important algorithm in a
surprising variety of fields.
|
cs/0504021 | Near Perfect Decoding of LDPC Codes | cs.IT math.IT | Cooperative optimization is a new way for finding global optima of
complicated functions of many variables. It has some important properties not
possessed by any conventional optimization methods. It has been successfully
applied in solving many large scale optimization problems in image processing,
computer vision, ... |
cs/0504022 | A Matter of Opinion: Sentiment Analysis and Business Intelligence
(position paper) | cs.CL | A general-audience introduction to the area of "sentiment analysis", the
computational treatment of subjective, opinion-oriented language (an example
application is determining whether a review is "thumbs up" or "thumbs down").
Some challenges, applications to business-intelligence tasks, and potential
future directi... |
cs/0504024 | Constraint-Based Qualitative Simulation | cs.AI cs.LO | We consider qualitative simulation involving a finite set of qualitative
relations in presence of complete knowledge about their interrelationship. We
show how it can be naturally captured by means of constraints expressed in
temporal logic and constraint satisfaction problems. The constraints relate at
each stage th... |
cs/0504028 | On Extrinsic Information of Good Codes Operating Over Discrete
Memoryless Channels | cs.IT math.IT | We show that the Extrinsic Information about the coded bits of any good
(capacity achieving) code operating over a wide class of discrete memoryless
channels (DMC) is zero when channel capacity is below the code rate and
positive constant otherwise, that is, the Extrinsic Information Transfer (EXIT)
chart is a step f... |
cs/0504030 | Sufficient conditions for convergence of the Sum-Product Algorithm | cs.IT cs.AI math.IT | We derive novel conditions that guarantee convergence of the Sum-Product
algorithm (also known as Loopy Belief Propagation or simply Belief Propagation)
to a unique fixed point, irrespective of the initial messages. The
computational complexity of the conditions is polynomial in the number of
variables. In contrast w... |
cs/0504031 | Convexity Analysis of Snake Models Based on Hamiltonian Formulation | cs.CV cs.GR | This paper presents a convexity analysis for the dynamic snake model based on
the Potential Energy functional and the Hamiltonian formulation of the
classical mechanics. First we see the snake model as a dynamical system whose
singular points are the borders we seek. Next we show that a necessary
condition for a sing... |
cs/0504032 | Critical Point for Maximum Likelihood Decoding of Linear Block Codes | cs.IT math.IT | In this letter, the SNR value at which the error performance curve of a soft
decision maximum likelihood decoder reaches the slope corresponding to the code
minimum distance is determined for a random code. Based on this value, referred
to as the critical point, new insight about soft bounded distance decoding of
ran... |
cs/0504035 | Fitness Uniform Deletion: A Simple Way to Preserve Diversity | cs.NE cs.AI | A commonly experienced problem with population based optimisation methods is
the gradual decline in population diversity that tends to occur over time. This
can slow a system's progress or even halt it completely if the population
converges on a local optimum from which it cannot escape. In this paper we
present the ... |
cs/0504036 | Scientific impact quantity and quality: Analysis of two sources of
bibliographic data | cs.IR cs.DL | Attempts to understand the consequence of any individual scientist's activity
within the long-term trajectory of science is one of the most difficult
questions within the philosophy of science. Because scientific publications
play such as central role in the modern enterprise of science, bibliometric
techniques which... |
cs/0504037 | Bayesian Restoration of Digital Images Employing Markov Chain Monte
Carlo a Review | cs.CV cond-mat.stat-mech physics.comp-ph | A review of Bayesian restoration of digital images based on Monte Carlo
techniques is presented. The topics covered include Likelihood, Prior and
Posterior distributions, Poisson, Binay symmetric channel, and Gaussian channel
models of Likelihood distribution,Ising and Potts spin models of Prior
distribution, restora... |
cs/0504041 | Learning Polynomial Networks for Classification of Clinical
Electroencephalograms | cs.AI cs.NE | We describe a polynomial network technique developed for learning to classify
clinical electroencephalograms (EEGs) presented by noisy features. Using an
evolutionary strategy implemented within Group Method of Data Handling, we
learn classification models which are comprehensively described by sets of
short-term pol... |
cs/0504042 | The Bayesian Decision Tree Technique with a Sweeping Strategy | cs.AI cs.LG | The uncertainty of classification outcomes is of crucial importance for many
safety critical applications including, for example, medical diagnostics. In
such applications the uncertainty of classification can be reliably estimated
within a Bayesian model averaging technique that allows the use of prior
information. ... |
cs/0504043 | Experimental Comparison of Classification Uncertainty for Randomised and
Bayesian Decision Tree Ensembles | cs.AI cs.LG | In this paper we experimentally compare the classification uncertainty of the
randomised Decision Tree (DT) ensemble technique and the Bayesian DT technique
with a restarting strategy on a synthetic dataset as well as on some datasets
commonly used in the machine learning community. For quantitative evaluation of
cla... |
cs/0504046 | On the Entropy Rate of Pattern Processes | cs.IT math.IT | We study the entropy rate of pattern sequences of stochastic processes, and
its relationship to the entropy rate of the original process. We give a
complete characterization of this relationship for i.i.d. processes over
arbitrary alphabets, stationary ergodic processes over discrete alphabets, and
a broad family of ... |
cs/0504047 | Pushdown dimension | cs.IT cs.CC math.IT | This paper develops the theory of pushdown dimension and explores its
relationship with finite-state dimension. Pushdown dimension is trivially
bounded above by finite-state dimension for all sequences, since a pushdown
gambler can simulate any finite-state gambler. We show that for every rational
0 < d < 1, there ex... |
cs/0504049 | Bounds on the Entropy of Patterns of I.I.D. Sequences | cs.IT math.IT | Bounds on the entropy of patterns of sequences generated by independently
identically distributed (i.i.d.) sources are derived. A pattern is a sequence
of indices that contains all consecutive integer indices in increasing order of
first occurrence. If the alphabet of a source that generated a sequence is
unknown, th... |
cs/0504051 | A Scalable Stream-Oriented Framework for Cluster Applications | cs.DC cs.DB cs.NI cs.OS cs.PL | This paper presents a stream-oriented architecture for structuring cluster
applications. Clusters that run applications based on this architecture can
scale to tenths of thousands of nodes with significantly less performance loss
or reliability problems. Our architecture exploits the stream nature of the
data flow an... |
cs/0504052 | Learning Multi-Class Neural-Network Models from Electroencephalograms | cs.NE cs.LG | We describe a new algorithm for learning multi-class neural-network models
from large-scale clinical electroencephalograms (EEGs). This algorithm trains
hidden neurons separately to classify all the pairs of classes. To find best
pairwise classifiers, our algorithm searches for input variables which are
relevant to t... |
cs/0504053 | A Neural-Network Technique for Recognition of Filaments in Solar Images | cs.NE | We describe a new neural-network technique developed for an automated
recognition of solar filaments visible in the hydrogen H-alpha line full disk
spectroheliograms. This technique allows neural networks learn from a few image
fragments labelled manually to recognize the single filaments depicted on a
local backgrou... |
cs/0504054 | Learning from Web: Review of Approaches | cs.NE cs.LG | Knowledge discovery is defined as non-trivial extraction of implicit,
previously unknown and potentially useful information from given data.
Knowledge extraction from web documents deals with unstructured, free-format
documents whose number is enormous and rapidly growing. The artificial neural
networks are well suit... |
cs/0504055 | A Learning Algorithm for Evolving Cascade Neural Networks | cs.NE cs.AI | A new learning algorithm for Evolving Cascade Neural Networks (ECNNs) is
described. An ECNN starts to learn with one input node and then adding new
inputs as well as new hidden neurons evolves it. The trained ECNN has a nearly
minimal number of input and hidden neurons as well as connections. The
algorithm was succes... |
cs/0504056 | Self-Organizing Multilayered Neural Networks of Optimal Complexity | cs.NE cs.AI | The principles of self-organizing the neural networks of optimal complexity
is considered under the unrepresentative learning set. The method of
self-organizing the multi-layered neural networks is offered and used to train
the logical neural networks which were applied to the medical diagnostics.
|
cs/0504057 | Diagnostic Rule Extraction Using Neural Networks | cs.NE cs.AI | The neural networks have trained on incomplete sets that a doctor could
collect. Trained neural networks have correctly classified all the presented
instances. The number of intervals entered for encoding the quantitative
variables is equal two. The number of features as well as the number of neurons
and layers in tr... |
cs/0504058 | Polynomial Neural Networks Learnt to Classify EEG Signals | cs.NE cs.AI | A neural network based technique is presented, which is able to successfully
extract polynomial classification rules from labeled electroencephalogram (EEG)
signals. To represent the classification rules in an analytical form, we use
the polynomial neural networks trained by a modified Group Method of Data
Handling (... |
cs/0504059 | A Neural Network Decision Tree for Learning Concepts from EEG Data | cs.NE cs.AI | To learn the multi-class conceptions from the electroencephalogram (EEG) data
we developed a neural network decision tree (DT), that performs the linear
tests, and a new training algorithm. We found that the known methods fail
inducting the classification models when the data are presented by the features
some of the... |
cs/0504060 | Universal Minimax Discrete Denoising under Channel Uncertainty | cs.IT math.IT | The goal of a denoising algorithm is to recover a signal from its
noise-corrupted observations. Perfect recovery is seldom possible and
performance is measured under a given single-letter fidelity criterion. For
discrete signals corrupted by a known discrete memoryless channel, the DUDE was
recently shown to perform ... |
cs/0504061 | Summarization from Medical Documents: A Survey | cs.CL cs.IR | Objective:
The aim of this paper is to survey the recent work in medical documents
summarization.
Background:
During the last decade, documents summarization got increasing attention by
the AI research community. More recently it also attracted the interest of the
medical research community as well, due to the ... |
cs/0504063 | Selection in Scale-Free Small World | cs.LG cs.IR | In this paper we compare the performance characteristics of our selection
based learning algorithm for Web crawlers with the characteristics of the
reinforcement learning algorithm. The task of the crawlers is to find new
information on the Web. The selection algorithm, called weblog update, modifies
the starting URL... |
cs/0504064 | Neural-Network Techniques for Visual Mining Clinical
Electroencephalograms | cs.AI | In this chapter we describe new neural-network techniques developed for
visual mining clinical electroencephalograms (EEGs), the weak electrical
potentials invoked by brain activity. These techniques exploit fruitful ideas
of Group Method of Data Handling (GMDH). Section 2 briefly describes the
standard neural-networ... |
cs/0504065 | Estimating Classification Uncertainty of Bayesian Decision Tree
Technique on Financial Data | cs.AI | Bayesian averaging over classification models allows the uncertainty of
classification outcomes to be evaluated, which is of crucial importance for
making reliable decisions in applications such as financial in which risks have
to be estimated. The uncertainty of classification is determined by a trade-off
between th... |
cs/0504066 | Comparison of the Bayesian and Randomised Decision Tree Ensembles within
an Uncertainty Envelope Technique | cs.AI | Multiple Classifier Systems (MCSs) allow evaluation of the uncertainty of
classification outcomes that is of crucial importance for safety critical
applications. The uncertainty of classification is determined by a trade-off
between the amount of data available for training, the classifier diversity and
the required ... |
cs/0504067 | An Evolving Cascade Neural Network Technique for Cleaning Sleep
Electroencephalograms | cs.NE cs.AI | Evolving Cascade Neural Networks (ECNNs) and a new training algorithm capable
of selecting informative features are described. The ECNN initially learns with
one input node and then evolves by adding new inputs as well as new hidden
neurons. The resultant ECNN has a near minimal number of hidden neurons and
inputs. T... |
cs/0504068 | Self-Organization of the Neuron Collective of Optimal Complexity | cs.NE cs.AI | The optimal complexity of neural networks is achieved when the
self-organization principles is used to eliminate the contradictions existing
in accordance with the K. Godel theorem about incompleteness of the systems
based on axiomatics. The principle of S. Beer exterior addition the Heuristic
Group Method of Data Ha... |
cs/0504069 | A Neural-Network Technique to Learn Concepts from Electroencephalograms | cs.NE cs.AI cs.LG | A new technique is presented developed to learn multi-class concepts from
clinical electroencephalograms. A desired concept is represented as a neuronal
computational model consisting of the input, hidden, and output neurons. In
this model the hidden neurons learn independently to classify the
electroencephalogram se... |
cs/0504070 | The Combined Technique for Detection of Artifacts in Clinical
Electroencephalograms of Sleeping Newborns | cs.NE cs.AI cs.LG | In this paper we describe a new method combining the polynomial neural
network and decision tree techniques in order to derive comprehensible
classification rules from clinical electroencephalograms (EEGs) recorded from
sleeping newborns. These EEGs are heavily corrupted by cardiac, eye movement,
muscle and noise art... |
cs/0504071 | Proceedings of the Pacific Knowledge Acquisition Workshop 2004 | cs.AI | Artificial intelligence (AI) research has evolved over the last few decades
and knowledge acquisition research is at the core of AI research. PKAW-04 is
one of three international knowledge acquisition workshops held in the
Pacific-Rim, Canada and Europe over the last two decades. PKAW-04 has a strong
emphasis on inc... |
cs/0504072 | Knowledge Representation Issues in Semantic Graphs for Relationship
Detection | cs.AI physics.soc-ph | An important task for Homeland Security is the prediction of threat
vulnerabilities, such as through the detection of relationships between
seemingly disjoint entities. A structure used for this task is a "semantic
graph", also known as a "relational data graph" or an "attributed relational
graph". These graphs encod... |
cs/0504074 | Metalinguistic Information Extraction for Terminology | cs.CL cs.AI cs.IR | This paper describes and evaluates the Metalinguistic Operation Processor
(MOP) system for automatic compilation of metalinguistic information from
technical and scientific documents. This system is designed to extract
non-standard terminological resources that we have called Metalinguistic
Information Databases (or ... |
cs/0504075 | Dichotomy for Voting Systems | cs.GT cs.CC cs.MA | Scoring protocols are a broad class of voting systems. Each is defined by a
vector $(\alpha_1,\alpha_2,...,\alpha_m)$, $\alpha_1 \geq \alpha_2 \geq >...
\geq \alpha_m$, of integers such that each voter contributes $\alpha_1$ points
to his/her first choice, $\alpha_2$ points to his/her second choice, and so on,
and an... |
cs/0504078 | Adaptive Online Prediction by Following the Perturbed Leader | cs.AI cs.LG | When applying aggregating strategies to Prediction with Expert Advice, the
learning rate must be adaptively tuned. The natural choice of
sqrt(complexity/current loss) renders the analysis of Weighted Majority
derivatives quite complicated. In particular, for arbitrary weights there have
been no results proven so far.... |
cs/0504079 | Prediction of Large Alphabet Processes and Its Application to Adaptive
Source Coding | cs.IT math.IT | The problem of predicting a sequence $x_1,x_2,...$ generated by a discrete
source with unknown statistics is considered. Each letter $x_{t+1}$ is
predicted using information on the word $x_1x_2... x_t$ only. In fact, this
problem is a classical problem which has received much attention. Its history
can be traced back... |
cs/0504080 | Performance of Gaussian Signalling in Non Coherent Rayleigh Fading
Channels | cs.IT math.IT | The mutual information of a discrete time memoryless Rayleigh fading channel
is considered, where neither the transmitter nor the receiver has the knowledge
of the channel state information except the fading statistics. We present the
mutual information of this channel in closed form when the input distribution
is co... |
cs/0504081 | A Decomposition Approach to Multi-Vehicle Cooperative Control | cs.RO | We present methods that generate cooperative strategies for multi-vehicle
control problems using a decomposition approach. By introducing a set of tasks
to be completed by the team of vehicles and a task execution method for each
vehicle, we decomposed the problem into a combinatorial component and a
continuous compo... |
cs/0504085 | Capacity per Unit Energy of Fading Channels with a Peak Constraint | cs.IT math.IT | A discrete-time single-user scalar channel with temporally correlated
Rayleigh fading is analyzed. There is no side information at the transmitter or
the receiver. A simple expression is given for the capacity per unit energy, in
the presence of a peak constraint. The simple formula of Verdu for capacity per
unit cos... |
cs/0504086 | Componentwise Least Squares Support Vector Machines | cs.LG cs.AI | This chapter describes componentwise Least Squares Support Vector Machines
(LS-SVMs) for the estimation of additive models consisting of a sum of
nonlinear components. The primal-dual derivations characterizing LS-SVMs for
the estimation of the additive model result in a single set of linear equations
with size growi... |
cs/0504089 | Universal Similarity | cs.IR cs.AI cs.CL physics.data-an | We survey a new area of parameter-free similarity distance measures useful in
data-mining, pattern recognition, learning and automatic semantics extraction.
Given a family of distances on a set of objects, a distance is universal up to
a certain precision for that family if it minorizes every distance in the
family b... |
cs/0504091 | A Probabilistic Upper Bound on Differential Entropy | cs.IT math.IT | A novel, non-trivial, probabilistic upper bound on the entropy of an unknown
one-dimensional distribution, given the support of the distribution and a
sample from that distribution, is presented. No knowledge beyond the support of
the unknown distribution is required, nor is the distribution required to have
a densit... |
cs/0504099 | The Capacity of Random Ad hoc Networks under a Realistic Link Layer
Model | cs.IT cs.NI math.IT | The problem of determining asymptotic bounds on the capacity of a random ad
hoc network is considered. Previous approaches assumed a threshold-based link
layer model in which a packet transmission is successful if the SINR at the
receiver is greater than a fixed threshold. In reality, the mapping from SINR
to packet ... |
cs/0504100 | A DNA Sequence Compression Algorithm Based on LUT and LZ77 | cs.IT math.IT | This article introduces a new DNA sequence compression algorithm which is
based on LUT and LZ77 algorithm. Combined a LUT-based pre-coding routine and
LZ77 compression routine,this algorithm can approach a compression ratio of
1.9bits \slash base and even lower.The biggest advantage of this algorithm is
fast executio... |
cs/0504101 | Single-solution Random 3-SAT Instances | cs.AI cs.CC cs.DM | We study a class of random 3-SAT instances having exactly one solution. The
properties of this ensemble considerably differ from those of a random 3-SAT
ensemble. It is numerically shown that the running time of several complete and
stochastic local search algorithms monotonically increases as the clause
density is d... |
cs/0504102 | Spectral Orbits and Peak-to-Average Power Ratio of Boolean Functions
with respect to the {I,H,N}^n Transform | cs.IT math.IT | We enumerate the inequivalent self-dual additive codes over GF(4) of
blocklength n, thereby extending the sequence A090899 in The On-Line
Encyclopedia of Integer Sequences from n = 9 to n = 12. These codes have a
well-known interpretation as quantum codes. They can also be represented by
graphs, where a simple graph ... |
cs/0504108 | Cooperative Game Theory within Multi-Agent Systems for Systems
Scheduling | cs.AI cs.MA | Research concerning organization and coordination within multi-agent systems
continues to draw from a variety of architectures and methodologies. The work
presented in this paper combines techniques from game theory and multi-agent
systems to produce self-organizing, polymorphic, lightweight, embedded agents
for syst... |
cs/0505001 | Modelling investment in artificial stock markets: Analytical and
Numerical Results | cs.CE | In this article we study the behavior of a group of economic agents in the
context of cooperative game theory, interacting according to rules based on the
Potts Model with suitable modifications. Each agent can be thought of as
belonging to a chain, where agents can only interact with their nearest
neighbors (periodi... |
cs/0505002 | Tight Lower Bounds for Query Processing on Streaming and External Memory
Data | cs.DB cs.CC | We study a clean machine model for external memory and stream processing. We
show that the number of scans of the external data induces a strict hierarchy
(as long as work space is sufficiently small, e.g., polylogarithmic in the size
of the input). We also show that neither joins nor sorting are feasible if the
prod... |
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