id stringlengths 9 16 | title stringlengths 4 278 | categories stringlengths 5 104 | abstract stringlengths 6 4.09k |
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cs/0209021 | Activities, Context and Ubiquitous Computing | cs.IR | Context and context-awareness provides computing environments with the
ability to usefully adapt the services or information they provide. It is the
ability to implicitly sense and automatically derive the user needs that
separates context-aware applications from traditionally designed applications,
and this makes th... |
cs/0209022 | A Comparison of Different Cognitive Paradigms Using Simple Animats in a
Virtual Laboratory, with Implications to the Notion of Cognition | cs.AI | In this thesis I present a virtual laboratory which implements five different
models for controlling animats: a rule-based system, a behaviour-based system,
a concept-based system, a neural network, and a Braitenberg architecture.
Through different experiments, I compare the performance of the models and
conclude tha... |
cs/0209030 | Extremal Optimization: an Evolutionary Local-Search Algorithm | cs.NE cs.AI | A recently introduced general-purpose heuristic for finding high-quality
solutions for many hard optimization problems is reviewed. The method is
inspired by recent progress in understanding far-from-equilibrium phenomena in
terms of {\em self-organized criticality,} a concept introduced to describe
emergent complexi... |
cs/0210004 | Revising Partially Ordered Beliefs | cs.AI | This paper deals with the revision of partially ordered beliefs. It proposes
a semantic representation of epistemic states by partial pre-orders on
interpretations and a syntactic representation by partially ordered belief
bases. Two revision operations, the revision stemming from the history of
observations and the ... |
cs/0210005 | Positive time fractional derivative | cs.CE | In mathematical modeling of the non-squared frequency-dependent diffusions,
also known as the anomalous diffusions, it is desirable to have a positive real
Fourier transform for the time derivative of arbitrary fractional or odd
integer order. The Fourier transform of the fractional time derivative in the
Riemann-Lio... |
cs/0210007 | Compilability of Abduction | cs.AI cs.CC | Abduction is one of the most important forms of reasoning; it has been
successfully applied to several practical problems such as diagnosis. In this
paper we investigate whether the computational complexity of abduction can be
reduced by an appropriate use of preprocessing. This is motivated by the fact
that part of ... |
cs/0210009 | On the Cell-based Complexity of Recognition of Bounded Configurations by
Finite Dynamic Cellular Automata | cs.CC cs.CV | This paper studies complexity of recognition of classes of bounded
configurations by a generalization of conventional cellular automata (CA) --
finite dynamic cellular automata (FDCA). Inspired by the CA-based models of
biological and computer vision, this study attempts to derive the properties of
a complexity measu... |
cs/0210012 | Selection of future events from a time series in relation to estimations
of forecasting uncertainty | cs.NE | A new general procedure for a priori selection of more predictable events
from a time series of observed variable is proposed. The procedure is
applicable to time series which contains different types of events that feature
significantly different predictability, or, in other words, to heteroskedastic
time series. A ... |
cs/0210018 | User software for the next generation | cs.GR cs.CE | New generations of neutron scattering sources and instrumentation are
providing challenges in data handling for user software. Time-of-Flight
instruments used at pulsed sources typically produce hundreds or thousands of
channels of data for each detector segment. New instruments are being designed
with thousands to h... |
cs/0210023 | Geometric Aspects of Multiagent Systems | cs.MA cs.AI | Recent advances in Multiagent Systems (MAS) and Epistemic Logic within
Distributed Systems Theory, have used various combinatorial structures that
model both the geometry of the systems and the Kripke model structure of models
for the logic. Examining one of the simpler versions of these models,
interpreted systems, ... |
cs/0210025 | An Algorithm for Pattern Discovery in Time Series | cs.LG cs.CL | We present a new algorithm for discovering patterns in time series and other
sequential data. We exhibit a reliable procedure for building the minimal set
of hidden, Markovian states that is statistically capable of producing the
behavior exhibited in the data -- the underlying process's causal states.
Unlike convent... |
cs/0210026 | Encoding a Taxonomy of Web Attacks with Different-Length Vectors | cs.CR cs.AI | Web attacks, i.e. attacks exclusively using the HTTP protocol, are rapidly
becoming one of the fundamental threats for information systems connected to
the Internet. When the attacks suffered by web servers through the years are
analyzed, it is observed that most of them are very similar, using a reduced
number of at... |
cs/0210027 | A uniform approach to logic programming semantics | cs.AI cs.LO | Part of the theory of logic programming and nonmonotonic reasoning concerns
the study of fixed-point semantics for these paradigms. Several different
semantics have been proposed during the last two decades, and some have been
more successful and acknowledged than others. The rationales behind those
various semantics... |
cs/0210028 | Equivalences Among Aggregate Queries with Negation | cs.DB cs.LO | Query equivalence is investigated for disjunctive aggregate queries with
negated subgoals, constants and comparisons. A full characterization of
equivalence is given for the aggregation functions count, max, sum, prod,
toptwo and parity. A related problem is that of determining, for a given
natural number N, whether ... |
cs/0210030 | Intelligence and Cooperative Search by Coupled Local Minimizers | cs.AI cs.MA cs.NE | We show how coupling of local optimization processes can lead to better
solutions than multi-start local optimization consisting of independent runs.
This is achieved by minimizing the average energy cost of the ensemble, subject
to synchronization constraints between the state vectors of the individual
local minimiz... |
cs/0211003 | Evaluation of the Performance of the Markov Blanket Bayesian Classifier
Algorithm | cs.LG | The Markov Blanket Bayesian Classifier is a recently-proposed algorithm for
construction of probabilistic classifiers. This paper presents an empirical
comparison of the MBBC algorithm with three other Bayesian classifiers: Naive
Bayes, Tree-Augmented Naive Bayes and a general Bayesian network. All of these
are imple... |
cs/0211004 | The DLV System for Knowledge Representation and Reasoning | cs.AI cs.LO cs.PL | This paper presents the DLV system, which is widely considered the
state-of-the-art implementation of disjunctive logic programming, and addresses
several aspects. As for problem solving, we provide a formal definition of its
kernel language, function-free disjunctive logic programs (also known as
disjunctive datalog... |
cs/0211005 | Prosody Based Co-analysis for Continuous Recognition of Coverbal
Gestures | cs.CV cs.HC | Although speech and gesture recognition has been studied extensively, all the
successful attempts of combining them in the unified framework were
semantically motivated, e.g., keyword-gesture cooccurrence. Such formulations
inherited the complexity of natural language processing. This paper presents a
Bayesian formul... |
cs/0211006 | Maximing the Margin in the Input Space | cs.AI cs.LG | We propose a novel criterion for support vector machine learning: maximizing
the margin in the input space, not in the feature (Hilbert) space. This
criterion is a discriminative version of the principal curve proposed by Hastie
et al. The criterion is appropriate in particular when the input space is
already a well-... |
cs/0211007 | Approximating Incomplete Kernel Matrices by the em Algorithm | cs.LG | In biological data, it is often the case that observed data are available
only for a subset of samples. When a kernel matrix is derived from such data,
we have to leave the entries for unavailable samples as missing. In this paper,
we make use of a parametric model of kernel matrices, and estimate missing
entries by ... |
cs/0211008 | Can the whole brain be simpler than its "parts"? | cs.AI | This is the first in a series of connected papers discussing the problem of a
dynamically reconfigurable universal learning neurocomputer that could serve as
a computational model for the whole human brain. The whole series is entitled
"The Brain Zero Project. My Brain as a Dynamically Reconfigurable Universal
Learni... |
cs/0211014 | Vanquishing the XCB Question: The Methodology Discovery of the Last
Shortest Single Axiom for the Equivalential Calculus | cs.LO cs.AI | With the inclusion of an effective methodology, this article answers in
detail a question that, for a quarter of a century, remained open despite
intense study by various researchers. Is the formula XCB =
e(x,e(e(e(x,y),e(z,y)),z)) a single axiom for the classical equivalential
calculus when the rules of inference co... |
cs/0211015 | XCB, the Last of the Shortest Single Axioms for the Classical
Equivalential Calculus | cs.LO cs.AI | It has long been an open question whether the formula XCB = EpEEEpqErqr is,
with the rules of substitution and detachment, a single axiom for the classical
equivalential calculus. This paper answers that question affirmatively, thus
completing a search for all such eleven-symbol single axioms that began seventy
years... |
cs/0211017 | Probabilistic Parsing Strategies | cs.CL | We present new results on the relation between purely symbolic context-free
parsing strategies and their probabilistic counter-parts. Such parsing
strategies are seen as constructions of push-down devices from grammars. We
show that preservation of probability distribution is possible under two
conditions, viz. the c... |
cs/0211020 | Monadic Datalog and the Expressive Power of Languages for Web
Information Extraction | cs.DB | Research on information extraction from Web pages (wrapping) has seen much
activity recently (particularly systems implementations), but little work has
been done on formally studying the expressiveness of the formalisms proposed or
on the theoretical foundations of wrapping. In this paper, we first study
monadic dat... |
cs/0211023 | SkyQuery: A WebService Approach to Federate Databases | cs.DB cs.CE | Traditional science searched for new objects and phenomena that led to
discoveries. Tomorrow's science will combine together the large pool of
information in scientific archives and make discoveries. Scienthists are
currently keen to federate together the existing scientific databases. The
major challenge in building... |
cs/0211027 | Adaptive Development of Koncepts in Virtual Animats: Insights into the
Development of Knowledge | cs.AI | As a part of our effort for studying the evolution and development of
cognition, we present results derived from synthetic experimentations in a
virtual laboratory where animats develop koncepts adaptively and ground their
meaning through action. We introduce the term "koncept" to avoid confusions and
ambiguity deriv... |
cs/0211028 | Thinking Adaptive: Towards a Behaviours Virtual Laboratory | cs.AI cs.MA | In this paper we name some of the advantages of virtual laboratories; and
propose that a Behaviours Virtual Laboratory should be useful for both
biologists and AI researchers, offering a new perspective for understanding
adaptive behaviour. We present our development of a Behaviours Virtual
Laboratory, which at this ... |
cs/0211029 | Modelling intracellular signalling networks using behaviour-based
systems and the blackboard architecture | cs.MA q-bio.CB | This paper proposes to model the intracellular signalling networks using a
fusion of behaviour-based systems and the blackboard architecture. In virtue of
this fusion, the model developed by us, which has been named Cellulat, allows
to take account two essential aspects of the intracellular signalling networks:
(1) t... |
cs/0211030 | Integration of Computational Techniques for the Modelling of Signal
Transduction | cs.MA q-bio.CB | A cell can be seen as an adaptive autonomous agent or as a society of
adaptive autonomous agents, where each can exhibit a particular behaviour
depending on its cognitive capabilities. We present an intracellular signalling
model obtained by integrating several computational techniques into an
agent-based paradigm. C... |
cs/0211031 | Redundancy in Logic I: CNF Propositional Formulae | cs.AI cs.CC | A knowledge base is redundant if it contains parts that can be inferred from
the rest of it. We study the problem of checking whether a CNF formula (a set
of clauses) is redundant, that is, it contains clauses that can be derived from
the other ones. Any CNF formula can be made irredundant by deleting some of its
cla... |
cs/0211033 | Propositional satisfiability in declarative programming | cs.LO cs.AI | Answer-set programming (ASP) paradigm is a way of using logic to solve search
problems. Given a search problem, to solve it one designs a theory in the logic
so that models of this theory represent problem solutions. To compute a
solution to a problem one needs to compute a model of the corresponding theory.
Several ... |
cs/0211035 | Monadic Style Control Constructs for Inference Systems | cs.AI cs.PL | Recent advances in programming languages study and design have established a
standard way of grounding computational systems representation in category
theory. These formal results led to a better understanding of issues of control
and side-effects in functional and imperative languages. Another benefit is a
better w... |
cs/0211038 | Dynamic Adjustment of the Motivation Degree in an Action Selection
Mechanism | cs.AI | This paper presents a model for dynamic adjustment of the motivation degree,
using a reinforcement learning approach, in an action selection mechanism
previously developed by the authors. The learning takes place in the
modification of a parameter of the model of combination of internal and
external stimuli. Experime... |
cs/0211039 | Action Selection Properties in a Software Simulated Agent | cs.AI | This article analyses the properties of the Internal Behaviour network, an
action selection mechanism previously proposed by the authors, with the aid of
a simulation developed for such ends. A brief review of the Internal Behaviour
network is followed by the explanation of the implementation of the simulation.
Then,... |
cs/0211040 | A Model for Combination of External and Internal Stimuli in the Action
Selection of an Autonomous Agent | cs.AI | This paper proposes a model for combination of external and internal stimuli
for the action selection in an autonomous agent, based in an action selection
mechanism previously proposed by the authors. This combination model includes
additive and multiplicative elements, which allows to incorporate new
properties, whi... |
cs/0211041 | An Approach to Automatic Indexing of Scientific Publications in High
Energy Physics for Database SPIRES HEP | cs.IR cs.DL | We introduce an approach to automatic indexing of e-prints based on a
pattern-matching technique making extensive use of an Associative Patterns
Dictionary (APD), developed by us. Entries in the APD consist of natural
language phrases with the same semantic interpretation as a set of keywords
from a controlled vocabu... |
cs/0211042 | Database Repairs and Analytic Tableaux | cs.DB cs.LO | In this article, we characterize in terms of analytic tableaux the repairs of
inconsistent relational databases, that is databases that do not satisfy a
given set of integrity constraints. For this purpose we provide closing and
opening criteria for branches in tableaux that are built for database instances
and their... |
cs/0212004 | Minimal-Change Integrity Maintenance Using Tuple Deletions | cs.DB | We address the problem of minimal-change integrity maintenance in the context
of integrity constraints in relational databases. We assume that
integrity-restoration actions are limited to tuple deletions. We identify two
basic computational issues: repair checking (is a database instance a repair of
a given database?... |
cs/0212006 | Use of openMosix for parallel I/O balancing on storage in Linux cluster | cs.DC cs.DB | In this paper I present some experiences made in the matter of I/O for Linux
Clustering. In particular is illustrated the use of the package openMosix, a
balancer of workload for processes running in a cluster of nodes. I describe
some tests for balancing the load of I/O storage massive processes in a cluster
with fo... |
cs/0212008 | Principal Manifolds and Nonlinear Dimension Reduction via Local Tangent
Space Alignment | cs.LG cs.AI | Nonlinear manifold learning from unorganized data points is a very
challenging unsupervised learning and data visualization problem with a great
variety of applications. In this paper we present a new algorithm for manifold
learning and nonlinear dimension reduction. Based on a set of unorganized data
points sampled ... |
cs/0212010 | JohnnyVon: Self-Replicating Automata in Continuous Two-Dimensional Space | cs.NE cs.CE | JohnnyVon is an implementation of self-replicating automata in continuous
two-dimensional space. Two types of particles drift about in a virtual liquid.
The particles are automata with discrete internal states but continuous
external relationships. Their internal states are governed by finite state
machines but their... |
cs/0212011 | Mining the Web for Lexical Knowledge to Improve Keyphrase Extraction:
Learning from Labeled and Unlabeled Data | cs.LG cs.IR | Keyphrases are useful for a variety of purposes, including summarizing,
indexing, labeling, categorizing, clustering, highlighting, browsing, and
searching. The task of automatic keyphrase extraction is to select keyphrases
from within the text of a given document. Automatic keyphrase extraction makes
it feasible to ... |
cs/0212012 | Unsupervised Learning of Semantic Orientation from a
Hundred-Billion-Word Corpus | cs.LG cs.IR | The evaluative character of a word is called its semantic orientation. A
positive semantic orientation implies desirability (e.g., "honest", "intrepid")
and a negative semantic orientation implies undesirability (e.g., "disturbing",
"superfluous"). This paper introduces a simple algorithm for unsupervised
learning of... |
cs/0212013 | Learning to Extract Keyphrases from Text | cs.LG cs.IR | Many academic journals ask their authors to provide a list of about five to
fifteen key words, to appear on the first page of each article. Since these key
words are often phrases of two or more words, we prefer to call them
keyphrases. There is a surprisingly wide variety of tasks for which keyphrases
are useful, as... |
cs/0212014 | Extraction of Keyphrases from Text: Evaluation of Four Algorithms | cs.LG cs.IR | This report presents an empirical evaluation of four algorithms for
automatically extracting keywords and keyphrases from documents. The four
algorithms are compared using five different collections of documents. For each
document, we have a target set of keyphrases, which were generated by hand. The
target keyphrase... |
cs/0212015 | Answering Subcognitive Turing Test Questions: A Reply to French | cs.CL | Robert French has argued that a disembodied computer is incapable of passing
a Turing Test that includes subcognitive questions. Subcognitive questions are
designed to probe the network of cultural and perceptual associations that
humans naturally develop as we live, embodied and embedded in the world. In
this paper,... |
cs/0212017 | Classes of Spatiotemporal Objects and Their Closure Properties | cs.DB | We present a data model for spatio-temporal databases. In this model
spatio-temporal data is represented as a finite union of objects described by
means of a spatial reference object, a temporal object and a geometric
transformation function that determines the change or movement of the reference
object in time.
We... |
cs/0212018 | Real numbers having ultimately periodic representations in abstract
numeration systems | cs.CC cs.CL | Using a genealogically ordered infinite regular language, we know how to
represent an interval of R. Numbers having an ultimately periodic
representation play a special role in classical numeration systems. The aim of
this paper is to characterize the numbers having an ultimately periodic
representation in generalize... |
cs/0212019 | Thinking, Learning, and Autonomous Problem Solving | cs.NE | Ever increasing computational power will require methods for automatic
programming. We present an alternative to genetic programming, based on a
general model of thinking and learning. The advantage is that evolution takes
place in the space of constructs and can thus exploit the mathematical
structures of this space... |
cs/0212020 | Learning Algorithms for Keyphrase Extraction | cs.LG cs.CL cs.IR | Many academic journals ask their authors to provide a list of about five to
fifteen keywords, to appear on the first page of each article. Since these key
words are often phrases of two or more words, we prefer to call them
keyphrases. There is a wide variety of tasks for which keyphrases are useful,
as we discuss in... |
cs/0212021 | A Simple Model of Unbounded Evolutionary Versatility as a Largest-Scale
Trend in Organismal Evolution | cs.NE cs.CE q-bio.PE | The idea that there are any large-scale trends in the evolution of biological
organisms is highly controversial. It is commonly believed, for example, that
there is a large-scale trend in evolution towards increasing complexity, but
empirical and theoretical arguments undermine this belief. Natural selection
results ... |
cs/0212022 | Algorithms for Rapidly Dispersing Robot Swarms in Unknown Environments | cs.RO | We develop and analyze algorithms for dispersing a swarm of primitive robots
in an unknown environment, R. The primary objective is to minimize the
makespan, that is, the time to fill the entire region. An environment is
composed of pixels that form a connected subset of the integer grid.
There is at most one robot... |
cs/0212023 | How to Shift Bias: Lessons from the Baldwin Effect | cs.LG cs.NE | An inductive learning algorithm takes a set of data as input and generates a
hypothesis as output. A set of data is typically consistent with an infinite
number of hypotheses; therefore, there must be factors other than the data that
determine the output of the learning algorithm. In machine learning, these
other fac... |
cs/0212024 | Unsupervised Language Acquisition: Theory and Practice | cs.CL cs.LG | In this thesis I present various algorithms for the unsupervised machine
learning of aspects of natural languages using a variety of statistical models.
The scientific object of the work is to examine the validity of the so-called
Argument from the Poverty of the Stimulus advanced in favour of the proposition
that hu... |
cs/0212025 | Searching for Plannable Domains can Speed up Reinforcement Learning | cs.AI | Reinforcement learning (RL) involves sequential decision making in uncertain
environments. The aim of the decision-making agent is to maximize the benefit
of acting in its environment over an extended period of time. Finding an
optimal policy in RL may be very slow. To speed up learning, one often used
solution is th... |
cs/0212027 | Qualitative Study of a Robot Arm as a Hamiltonian System | cs.RO | A double pendulum subject to external torques is used as a model to study the
stability of a planar manipulator with two links and two rotational driven
joints. The hamiltonian equations of motion and the fixed points (stationary
solutions) in phase space are determined. Under suitable conditions, the
presence of con... |
cs/0212028 | Technical Note: Bias and the Quantification of Stability | cs.LG cs.CV | Research on bias in machine learning algorithms has generally been concerned
with the impact of bias on predictive accuracy. We believe that there are other
factors that should also play a role in the evaluation of bias. One such factor
is the stability of the algorithm; in other words, the repeatability of the
resul... |
cs/0212029 | A Theory of Cross-Validation Error | cs.LG cs.CV | This paper presents a theory of error in cross-validation testing of
algorithms for predicting real-valued attributes. The theory justifies the
claim that predicting real-valued attributes requires balancing the conflicting
demands of simplicity and accuracy. Furthermore, the theory indicates precisely
how these conf... |
cs/0212030 | Theoretical Analyses of Cross-Validation Error and Voting in
Instance-Based Learning | cs.LG cs.CV | This paper begins with a general theory of error in cross-validation testing
of algorithms for supervised learning from examples. It is assumed that the
examples are described by attribute-value pairs, where the values are symbolic.
Cross-validation requires a set of training examples and a set of testing
examples. T... |
cs/0212031 | Contextual Normalization Applied to Aircraft Gas Turbine Engine
Diagnosis | cs.LG cs.CE cs.CV | Diagnosing faults in aircraft gas turbine engines is a complex problem. It
involves several tasks, including rapid and accurate interpretation of patterns
in engine sensor data. We have investigated contextual normalization for the
development of a software tool to help engine repair technicians with
interpretation o... |
cs/0212032 | Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised
Classification of Reviews | cs.LG cs.CL cs.IR | This paper presents a simple unsupervised learning algorithm for classifying
reviews as recommended (thumbs up) or not recommended (thumbs down). The
classification of a review is predicted by the average semantic orientation of
the phrases in the review that contain adjectives or adverbs. A phrase has a
positive sem... |
cs/0212033 | Mining the Web for Synonyms: PMI-IR versus LSA on TOEFL | cs.LG cs.CL cs.IR | This paper presents a simple unsupervised learning algorithm for recognizing
synonyms, based on statistical data acquired by querying a Web search engine.
The algorithm, called PMI-IR, uses Pointwise Mutual Information (PMI) and
Information Retrieval (IR) to measure the similarity of pairs of words. PMI-IR
is empiric... |
cs/0212034 | Types of Cost in Inductive Concept Learning | cs.LG cs.CV | Inductive concept learning is the task of learning to assign cases to a
discrete set of classes. In real-world applications of concept learning, there
are many different types of cost involved. The majority of the machine learning
literature ignores all types of cost (unless accuracy is interpreted as a type
of cost ... |
cs/0212035 | Exploiting Context When Learning to Classify | cs.LG cs.CV | This paper addresses the problem of classifying observations when features
are context-sensitive, specifically when the testing set involves a context
that is different from the training set. The paper begins with a precise
definition of the problem, then general strategies are presented for enhancing
the performance... |
cs/0212036 | Myths and Legends of the Baldwin Effect | cs.LG cs.NE | This position paper argues that the Baldwin effect is widely misunderstood by
the evolutionary computation community. The misunderstandings appear to fall
into two general categories. Firstly, it is commonly believed that the Baldwin
effect is concerned with the synergy that results when there is an evolving
populati... |
cs/0212037 | The Management of Context-Sensitive Features: A Review of Strategies | cs.LG cs.CV | In this paper, we review five heuristic strategies for handling
context-sensitive features in supervised machine learning from examples. We
discuss two methods for recovering lost (implicit) contextual information. We
mention some evidence that hybrid strategies can have a synergetic effect. We
then show how the work... |
cs/0212038 | The Identification of Context-Sensitive Features: A Formal Definition of
Context for Concept Learning | cs.LG cs.CV | A large body of research in machine learning is concerned with supervised
learning from examples. The examples are typically represented as vectors in a
multi-dimensional feature space (also known as attribute-value descriptions). A
teacher partitions a set of training examples into a finite number of classes.
The ta... |
cs/0212039 | Low Size-Complexity Inductive Logic Programming: The East-West Challenge
Considered as a Problem in Cost-Sensitive Classification | cs.LG cs.NE | The Inductive Logic Programming community has considered proof-complexity and
model-complexity, but, until recently, size-complexity has received little
attention. Recently a challenge was issued "to the international computing
community" to discover low size-complexity Prolog programs for classifying
trains. The cha... |
cs/0212040 | Data Engineering for the Analysis of Semiconductor Manufacturing Data | cs.LG cs.CE cs.CV | We have analyzed manufacturing data from several different semiconductor
manufacturing plants, using decision tree induction software called Q-YIELD.
The software generates rules for predicting when a given product should be
rejected. The rules are intended to help the process engineers improve the
yield of the produ... |
cs/0212041 | Robust Classification with Context-Sensitive Features | cs.LG cs.CV | This paper addresses the problem of classifying observations when features
are context-sensitive, especially when the testing set involves a context that
is different from the training set. The paper begins with a precise definition
of the problem, then general strategies are presented for enhancing the
performance o... |
cs/0212042 | Increasing Evolvability Considered as a Large-Scale Trend in Evolution | cs.NE cs.CE q-bio.PE | Evolvability is the capacity to evolve. This paper introduces a simple
computational model of evolvability and demonstrates that, under certain
conditions, evolvability can increase indefinitely, even when there is no
direct selection for evolvability. The model shows that increasing evolvability
implies an accelerat... |
cs/0212045 | Local Community Identification through User Access Patterns | cs.IR cs.HC | Community identification algorithms have been used to enhance the quality of
the services perceived by its users. Although algorithms for community have a
widespread use in the Web, their application to portals or specific subsets of
the Web has not been much studied. In this paper, we propose a technique for
local c... |
cs/0212049 | An Ehrenfeucht-Fraisse Game Approach to Collapse Results in Database
Theory | cs.LO cs.DB | We present a new Ehrenfeucht-Fraisse game approach to collapse results in
database theory and we show that, in principle, this approach suffices to prove
every natural generic collapse result. Following this approach we can deal with
certain infinite databases where previous, highly involved methods fail. We
prove th... |
cs/0212051 | ExploitingWeb Service Semantics: Taxonomies vs. Ontologies | cs.DB | Comprehensive semantic descriptions of Web services are essential to exploit
them in their full potential, that is, discovering them dynamically, and
enabling automated service negotiation, composition and monitoring. The
semantic mechanisms currently available in service registries which are based
on taxonomies fail... |
cs/0212052 | Improving the Functionality of UDDI Registries through Web Service
Semantics | cs.DB | In this paper we describe a framework for exploiting the semantics of Web
services through UDDI registries. As a part of this framework, we extend the
DAML-S upper ontology to describe the functionality we find essential for
e-businesses. This functionality includes relating the services with electronic
catalogs, des... |
cs/0212053 | Merging Locally Correct Knowledge Bases: A Preliminary Report | cs.AI cs.LO | Belief integration methods are often aimed at deriving a single and
consistent knowledge base that retains as much as possible of the knowledge
bases to integrate. The rationale behind this approach is the minimal change
principle: the result of the integration process should differ as less as
possible from the knowl... |
cs/0301001 | Least squares fitting of circles and lines | cs.CV | We study theoretical and computational aspects of the least squares fit (LSF)
of circles and circular arcs. First we discuss the existence and uniqueness of
LSF and various parametrization schemes. Then we evaluate several popular
circle fitting algorithms and propose a new one that surpasses the existing
methods in ... |
cs/0301006 | Temporal plannability by variance of the episode length | cs.AI | Optimization of decision problems in stochastic environments is usually
concerned with maximizing the probability of achieving the goal and minimizing
the expected episode length. For interacting agents in time-critical
applications, learning of the possibility of scheduling of subtasks (events) or
the full task is a... |
cs/0301007 | Kalman filter control in the reinforcement learning framework | cs.LG cs.AI | There is a growing interest in using Kalman-filter models in brain modelling.
In turn, it is of considerable importance to make Kalman-filters amenable for
reinforcement learning. In the usual formulation of optimal control it is
computed off-line by solving a backward recursion. In this technical note we
show that s... |
cs/0301008 | Formal Concept Analysis and Resolution in Algebraic Domains | cs.LO cs.AI | We relate two formerly independent areas: Formal concept analysis and logic
of domains. We will establish a correspondene between contextual attribute
logic on formal contexts resp. concept lattices and a clausal logic on coherent
algebraic cpos. We show how to identify the notion of formal concept in the
domain theo... |
cs/0301009 | A Script Language for Data Integration in Database | cs.DB | A Script Language in this paper is designed to transform the original data
into the target data by the computing formula. The Script Language can be
translated into the corresponding SQL Language, and the computation is finally
implemented by the first type of dynamic SQL. The Script Language has the
operations of in... |
cs/0301010 | Comparisons and Computation of Well-founded Semantics for Disjunctive
Logic Programs | cs.AI | Much work has been done on extending the well-founded semantics to general
disjunctive logic programs and various approaches have been proposed. However,
these semantics are different from each other and no consensus is reached about
which semantics is the most intended. In this paper we look at disjunctive
well-foun... |
cs/0301014 | Convergence and Loss Bounds for Bayesian Sequence Prediction | cs.LG cs.AI math.PR | The probability of observing $x_t$ at time $t$, given past observations
$x_1...x_{t-1}$ can be computed with Bayes' rule if the true generating
distribution $\mu$ of the sequences $x_1x_2x_3...$ is known. If $\mu$ is
unknown, but known to belong to a class $M$ one can base ones prediction on the
Bayes mix $\xi$ defin... |
cs/0301017 | Completeness and Decidability Properties for Functional Dependencies in
XML | cs.DB | XML is of great importance in information storage and retrieval because of
its recent emergence as a standard for data representation and interchange on
the Internet. However XML provides little semantic content and as a result
several papers have addressed the topic of how to improve the semantic
expressiveness of X... |
cs/0301018 | Novel Runtime Systems Support for Adaptive Compositional Modeling on the
Grid | cs.CE cs.DC | Grid infrastructures and computing environments have progressed significantly
in the past few years. The vision of truly seamless Grid usage relies on
runtime systems support that is cognizant of the operational issues underlying
grid computations and, at the same time, is flexible enough to accommodate
diverse appli... |
cs/0301023 | A semantic framework for preference handling in answer set programming | cs.AI | We provide a semantic framework for preference handling in answer set
programming. To this end, we introduce preference preserving consequence
operators. The resulting fixpoint characterizations provide us with a uniform
semantic framework for characterizing preference handling in existing
approaches. Although our ap... |
cs/0302001 | Many Hard Examples in Exact Phase Transitions with Application to
Generating Hard Satisfiable Instances | cs.CC cond-mat.stat-mech cs.AI cs.DM | This paper first analyzes the resolution complexity of two random CSP models
(i.e. Model RB/RD) for which we can establish the existence of phase
transitions and identify the threshold points exactly. By encoding CSPs into
CNF formulas, it is proved that almost all instances of Model RB/RD have no
tree-like resolutio... |
cs/0302002 | Optimizing GoTools' Search Heuristics using Genetic Algorithms | cs.NE | GoTools is a program which solves life & death problems in the game of Go.
This paper describes experiments using a Genetic Algorithm to optimize
heuristic weights used by GoTools' tree-search. The complete set of heuristic
weights is composed of different subgroups, each of which can be optimized with
a suitable fit... |
cs/0302004 | Unique Pattern Matching in Strings | cs.PL cs.DB | Regular expression patterns are a key feature of document processing
languages like Perl and XDuce. It is in this context that the first and longest
match policies have been proposed to disambiguate the pattern matching process.
We formally define a matching semantics with these policies and show that the
generally a... |
cs/0302012 | The New AI: General & Sound & Relevant for Physics | cs.AI cs.LG quant-ph | Most traditional artificial intelligence (AI) systems of the past 50 years
are either very limited, or based on heuristics, or both. The new millennium,
however, has brought substantial progress in the field of theoretically optimal
and practically feasible algorithms for prediction, search, inductive inference
based... |
cs/0302014 | An Algorithm for Aligning Sentences in Bilingual Corpora Using Lexical
Information | cs.CL | In this paper we describe an algorithm for aligning sentences with their
translations in a bilingual corpus using lexical information of the languages.
Existing efficient algorithms ignore word identities and consider only the
sentence lengths (Brown, 1991; Gale and Church, 1993). For a sentence in the
source languag... |
cs/0302015 | Unsupervised Learning in a Framework of Information Compression by
Multiple Alignment, Unification and Search | cs.AI cs.LG | This paper describes a novel approach to unsupervised learning that has been
developed within a framework of "information compression by multiple alignment,
unification and search" (ICMAUS), designed to integrate learning with other AI
functions such as parsing and production of language, fuzzy pattern
recognition, p... |
cs/0302021 | Building an Open Language Archives Community on the OAI Foundation | cs.CL cs.DL | The Open Language Archives Community (OLAC) is an international partnership
of institutions and individuals who are creating a worldwide virtual library of
language resources. The Dublin Core (DC) Element Set and the OAI Protocol have
provided a solid foundation for the OLAC framework. However, we need more
precision... |
cs/0302023 | Segmentation, Indexing, and Visualization of Extended Instructional
Videos | cs.IR cs.CV | We present a new method for segmenting, and a new user interface for indexing
and visualizing, the semantic content of extended instructional videos. Given a
series of key frames from the video, we generate a condensed view of the data
by clustering frames according to media type and visual similarities. Using
variou... |
cs/0302024 | Analysis and Interface for Instructional Video | cs.IR cs.CV | We present a new method for segmenting, and a new user interface for indexing
and visualizing, the semantic content of extended instructional videos. Using
various visual filters, key frames are first assigned a media type (board,
class, computer, illustration, podium, and sheet). Key frames of media type
board and s... |
cs/0302029 | Defeasible Logic Programming: An Argumentative Approach | cs.AI | The work reported here introduces Defeasible Logic Programming (DeLP), a
formalism that combines results of Logic Programming and Defeasible
Argumentation. DeLP provides the possibility of representing information in the
form of weak rules in a declarative manner, and a defeasible argumentation
inference mechanism fo... |
cs/0302032 | Empirical Methods for Compound Splitting | cs.CL | Compounded words are a challenge for NLP applications such as machine
translation (MT). We introduce methods to learn splitting rules from
monolingual and parallel corpora. We evaluate them against a gold standard and
measure their impact on performance of statistical MT systems. Results show
accuracy of 99.1% and pe... |
cs/0302034 | Interest Rate Model Calibration Using Semidefinite Programming | cs.CE | We show that, for the purpose of pricing Swaptions, the Swap rate and the
corresponding Forward rates can be considered lognormal under a single
martingale measure. Swaptions can then be priced as options on a basket of
lognormal assets and an approximation formula is derived for such options. This
formula is centere... |
cs/0302035 | Risk-Management Methods for the Libor Market Model Using Semidefinite
Programming | cs.CE | When interest rate dynamics are described by the Libor Market Model as in
BGM97, we show how some essential risk-management results can be obtained from
the dual of the calibration program. In particular, if the objetive is to
maximize another swaption's price, we show that the optimal dual variables
describe a hedgi... |
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