text stringlengths 27 153 | label stringlengths 27 153 | id int64 0 40k |
|---|---|---|
for possible illustrate the briefly I At will systems. model end a cognitive general | At the end I will briefly illustrate a possible general model for cognitive systems. | 9,200 |
interest. of regions segmentation locate to we image an split mean By | By segmentation we mean split an image to locate regions of interest. | 9,201 |
training a and an classes Here, we partition image basis. according define discriminate to | Here, we discriminate and define an image partition classes according to a training basis. | 9,202 |
of training consists This urban basis classes: aquatic, vegetation and three pattern regions. | This training basis consists of three pattern classes: aquatic, urban and vegetation regions. | 9,203 |
been gestures mouse have performed. Thus various recognizing events the | Thus recognizing the gestures various mouse events have been performed. | 9,204 |
We multiscale then to optimal method distance tangent of the the solution. convergence the study | We then study the convergence of the multiscale tangent distance method to the optimal solution. | 9,205 |
distance of in performance method We the examine applications. tangent classification finally image the | We finally examine the performance of the tangent distance method in image classification applications. | 9,206 |
expectation-maximization also We solution. (EM) (point) for a MAP consider | We also consider expectation-maximization (EM) for a MAP (point) solution. | 9,207 |
The service. of process the by businessprocesses web web pages customizing composite by using | The process of customizing businessprocesses by composite the web pages by using web service. | 9,208 |
to DNA is transfer genome the host of Lateral Wolbachia common. | Lateral transfer of Wolbachia DNA to the host genome is common. | 9,209 |
sequence. with definitively were co-assembled fragments nematode-derived Many | Many fragments were co-assembled with definitively nematode-derived sequence. | 9,210 |
expression the found genes. evidence We of limited Wolbachia-derived of | We found limited evidence of expression of the Wolbachia-derived genes. | 9,211 |
recommendation a describe completely scale fashion. large automated visual for We system | We describe a completely automated large scale visual recommendation system for fashion. | 9,212 |
two methods importance on new We Monte based sampling. sequential Carlo propose | We propose two new Monte Carlo methods based on sequential importance sampling. | 9,213 |
computation. Parallel (PVM) Virtual use to Machine We up speed the | We use Parallel Virtual Machine (PVM) to speed up the computation. | 9,214 |
hallucinations speech absence perceptions Purpose: stimulation. in (AVHs) of verbal a external Auditory are the | Purpose: Auditory verbal hallucinations (AVHs) are speech perceptions in the absence of a external stimulation. | 9,215 |
is a on predictive control The which account based self-monitoring in model, is implemented. verbal | The account is based on a predictive control model, in which verbal self-monitoring is implemented. | 9,216 |
during activity articulation) (without Lip muscle covert was and rest. AVHs Methods: recorded | Methods: Lip muscle activity was recorded during covert AVHs (without articulation) and rest. | 9,217 |
electromyography patients. eleven schizophrenia used (EMG) was on Surface | Surface electromyography (EMG) was used on eleven schizophrenia patients. | 9,218 |
This how AVHs understanding better occur. help will | This will help better understanding how AVHs occur. | 9,219 |
and sequence. from exhibit Cells phenotypes different often the DNA same stable | Cells often exhibit different and stable phenotypes from the same DNA sequence. | 9,220 |
epigenetic of for regulation. our implications deep These have understanding results | These results have deep implications for our understanding of epigenetic regulation. | 9,221 |
an this paper, we modes in a present In histogram. algorithm automatically detect to meaningful | In this paper, we present an algorithm to automatically detect meaningful modes in a histogram. | 9,222 |
is based in scale-space proposed local representation. behavior of on method minima the The a | The proposed method is based on the behavior of local minima in a scale-space representation. | 9,223 |
parameters. fast, require and does easy not to is The algorithm any implement, | The algorithm is easy to implement, fast, and does not require any parameters. | 9,224 |
details offer note we on to practice. this this implement algorithm how in efficiently In | In this note we offer details on how to efficiently implement this algorithm in practice. | 9,225 |
an for from We interactive algorithm learning present policy demonstration. Confidence-Based Autonomy (CBA), | We present Confidence-Based Autonomy (CBA), an interactive algorithm for policy learning from demonstration. | 9,226 |
its in simulated compared and complex are individual and domain. CBA a components evaluated driving | CBA and its individual components are compared and evaluated in a complex simulated driving domain. | 9,227 |
extensions number the refinements also of are to introduced. and A basic algorithm | A number of refinements and extensions to the basic algorithm are also introduced. | 9,228 |
including It scheduling, resource allocation, applied bioinformatics, been has etc. various problems, to | It has been applied to various problems, including resource allocation, bioinformatics, scheduling, etc. | 9,229 |
domains. very these to solve problems However, techniques not with suited are well large | However, these techniques are not well suited to solve problems with very large domains. | 9,230 |
complexity. improved arc soft asymptotic to BAC consistency, and Compared space significantly time provides | Compared to soft arc consistency, BAC provides significantly improved time and space asymptotic complexity. | 9,231 |
some well of results. as empirical evaluation the as We an complexity approach worst-case provide | We provide an empirical evaluation of the approach as well as some worst-case complexity results. | 9,232 |
results macros. This several presents for on based tractability planning new paper | This paper presents several new tractability results for planning based on macros. | 9,233 |
work of consider spatio-temporal In this videos. we behavior detecting the problem anomalous in | In this work we consider the problem of detecting anomalous spatio-temporal behavior in videos. | 9,234 |
reduction approach and is sparse estimate models. Our the parameter to using covariance | Our approach is to estimate the covariance using parameter reduction and sparse models. | 9,235 |
algorithms problem. We our to learning relevant propose | We propose learning algorithms relevant to our problem. | 9,236 |
that SP of shown solutions. estimates over covers clusters marginals that was It represent | It was shown that SP estimates marginals over covers that represent clusters of solutions. | 9,237 |
generalizes SP. naturally interpretation This cover the of | This naturally generalizes the cover interpretation of SP. | 9,238 |
on weighted RSP Max-SAT random solvers also Max-SAT instances. state-of-the-art weighted outperforms | RSP also outperforms state-of-the-art weighted Max-SAT solvers on random weighted Max-SAT instances. | 9,239 |
of our its demonstrate variations. and method all accuracy Experimental new results the | Experimental results demonstrate the accuracy of our new method and all its variations. | 9,240 |
consistency CP-nets. dominance We in computational investigate testing and the complexity of | We investigate the computational complexity of testing dominance and consistency in CP-nets. | 9,241 |
negative often and arguments. positive is matter a a and listing decision of Making comparing | Making a decision is often a matter of listing and comparing positive and negative arguments. | 9,242 |
Prospect is Cumulative Theory. is in That done, example, for what | That is what is done, for example, in Cumulative Prospect Theory. | 9,243 |
terms, decision well other qualitative is bipolar. In as the as process | In other terms, the decision process is qualitative as well as bipolar. | 9,244 |
proposed. rules former More that decisive refine the are also | More decisive rules that refine the former are also proposed. | 9,245 |
modelling call includes which responsible the incompleteness process. process for we incompleteness, the This the | This includes modelling the process responsible for the incompleteness, which we call the incompleteness process. | 9,246 |
allow behaviour process We be partly to the unknown. | We allow the process behaviour to be partly unknown. | 9,247 |
known common hard. Multiagent be and to and planning are problems computationally coordination | Multiagent planning and coordination problems are common and known to be computationally hard. | 9,248 |
be wide programs. two-agent bilinear range formulated that as problems We a of show can | We show that a wide range of two-agent problems can be formulated as bilinear programs. | 9,249 |
the A evolutionary among species. tree shows relationships phylogenetic | A phylogenetic tree shows the evolutionary relationships among species. | 9,250 |
Internal represent correspond and the leaf nodes events tree to speciation of species. nodes | Internal nodes of the tree represent speciation events and leaf nodes correspond to species. | 9,251 |
rooted This inspires programming a for encoding trees. constraint | This inspires a constraint programming encoding for rooted trees. | 9,252 |
allows constraint-based an construction this We efficient that show supertree to the problem. solution | We show that this allows an efficient constraint-based solution to the supertree construction problem. | 9,253 |
of the simple of model model with a Soft goals classical extend preferences. planning | Soft goals extend the classical model of planning with a simple model of preferences. | 9,254 |
in has complexity the situations. operators resulting than approach other some much characteristics better Hence | Hence the resulting approach has much better complexity characteristics than other operators in some situations. | 9,255 |
obtain yields operator. revision, compositional the most natural that the under We Satoh definition, revision | We obtain that compositional revision, under the most natural definition, yields the Satoh revision operator. | 9,256 |
magnitude variation was as donors. donors with unrelated in in greater matched This related compared | This variation was greater in magnitude in unrelated donors as compared with matched related donors. | 9,257 |
piece-wise we prior. general First, using a constant methodology a use Bayesian Dirichlet | First, we use a piece-wise constant Bayesian methodology using a general Dirichlet prior. | 9,258 |
analysis. correlation with We linear these also compare | We also compare these with linear correlation analysis. | 9,259 |
this framework algorithm for We configuration problem. describe automatic an | We describe an automatic framework for this algorithm configuration problem. | 9,260 |
procedures, algorithm achieved and improvements. using consistent substantial our performance Nevertheless, automated configuration we | Nevertheless, using our automated algorithm configuration procedures, we achieved substantial and consistent performance improvements. | 9,261 |
the analysis paper model. new for introduced co-sparse recently algorithm learning addresses a This | This paper addresses a new learning algorithm for the recently introduced co-sparse analysis model. | 9,262 |
the to training, we technique called operators. a bi-level analysis For introduce learn optimization | For training, we introduce a technique called bi-level optimization to learn the analysis operators. | 9,263 |
to framework implement. a and intuitive easy develops is approach to understand Our that | Our approach develops a framework that is intuitive to understand and easy to implement. | 9,264 |
in reasoning. problem Inference in with important probabilistic applications numerous Nets Bayes is (BAYES) an | Inference in Bayes Nets (BAYES) is an important problem with numerous applications in probabilistic reasoning. | 9,265 |
sum-of-products members these class (SUMPROD) problems, of and problems. the Both others, are of | Both these problems, and others, are members of the class of sum-of-products (SUMPROD) problems. | 9,266 |
is for optimization A search algorithm problems solving constraint distributed new presented. (DisCOPs) | A new search algorithm for solving distributed constraint optimization problems (DisCOPs) is presented. | 9,267 |
variables assign compute sequentially assignments partial on Agents asynchronously. bounds and | Agents assign variables sequentially and compute bounds on partial assignments asynchronously. | 9,268 |
based bounds on the is partial asynchronous assignments. of computation The propagation | The asynchronous bounds computation is based on the propagation of partial assignments. | 9,269 |
described is in its The and detail algorithm proven. correctness | The algorithm is described in detail and its correctness proven. | 9,270 |
presented fully a resulting form. batch variational iterative automated first are The in schemes | The resulting fully automated variational schemes are first presented in a batch iterative form. | 9,271 |
AI several technique has the become for recent advances, Thanks applications. underlying to Planning | Thanks to recent advances, AI Planning has become the underlying technique for several applications. | 9,272 |
current planning The tools. belief support update limited for in severely is | The support for belief update is severely limited in current planning tools. | 9,273 |
DEC-POMDPs. algorithm paper an contribution solving iteration main optimal of The policy this for is | The main contribution of this paper is an optimal policy iteration algorithm for solving DEC-POMDPs. | 9,274 |
to algorithm represent The policies. stochastic uses controllers finite-state | The algorithm uses stochastic finite-state controllers to represent policies. | 9,275 |
domains. We observable for identifying algorithms in deterministic-actions dynamic present partially exact and effects preconditions | We present exact algorithms for identifying deterministic-actions effects and preconditions in dynamic partially observable domains. | 9,276 |
Such real common in scenarios applications. are world | Such scenarios are common in real world applications. | 9,277 |
and assumptions Our from models. action observations traditional partial work about departs | Our work departs from traditional assumptions about partial observations and action models. | 9,278 |
modified such domains. algorithms for We for tractable yield the problem | We yield tractable algorithms for the modified problem for such domains. | 9,279 |
exactly. identify tractability experiments verify guarantees, Our models theoretical action that we the and show | Our experiments verify the theoretical tractability guarantees, and show that we identify action models exactly. | 9,280 |
use already Several adventure-game playing planning, and applications these exploration, in autonomous results. | Several applications in planning, autonomous exploration, and adventure-game playing already use these results. | 9,281 |
diagnosis. also probabilistic They are for and reinforcement observable learning, partially promising settings, | They are also promising for probabilistic settings, partially observable reinforcement learning, and diagnosis. | 9,282 |
several to decision tasks real-world expensive choose among require us Many observations. making | Many real-world decision making tasks require us to choose among several expensive observations. | 9,283 |
It heuristic-guided observations. selecting been practice general has to for procedures use | It has been general practice to use heuristic-guided procedures for selecting observations. | 9,284 |
label optimally example, Models hidden (HMMs). Hidden allow our Markov For variables to algorithms in | For example, our algorithms allow to optimally label hidden variables in Hidden Markov Models (HMMs). | 9,285 |
is for even polytrees. value optimizing of that prove $NP^{PP}$-hard We information the | We prove that the optimizing value of information is $NP^{PP}$-hard even for polytrees. | 9,286 |
of two the compiling model. We algorithms for a graphical provide AOMDD | We provide two algorithms for compiling the AOMDD of a graphical model. | 9,287 |
potential AOMDDs. We demonstrates the that provide evaluation an experimental of | We provide an experimental evaluation that demonstrates the potential of AOMDDs. | 9,288 |
paper, distance implement plant a researched were this system. In to several foliage retrieval measures | In this paper, several distance measures were researched to implement a foliage plant retrieval system. | 9,289 |
and chart future We experimental results work. provide | We provide experimental results and chart future work. | 9,290 |
dimensionality techniques these problems. scale impractical large the on Nevertheless, curse makes of | Nevertheless, the curse of dimensionality makes these techniques impractical on large scale problems. | 9,291 |
focus of consisting cycle. on of one single the Here permutations we variables | Here we focus on permutations of the variables consisting of one single cycle. | 9,292 |
them as a analyze We function classes and these of cube the quantify dimensionality. | We analyze these classes and quantify them as a function of the cube dimensionality. | 9,293 |
Distributed agent-coordination constraint problems optimization problems. a popular and of are way solving (DCOP) formulating | Distributed constraint optimization (DCOP) problems are a popular way of formulating and solving agent-coordination problems. | 9,294 |
It often algorithms. desirable DCOP with to solve and asynchronous problems memory-bounded is | It is often desirable to solve DCOP problems with memory-bounded and asynchronous algorithms. | 9,295 |
of the DisCSP. subproblems search algorithm partitions into the different The | The algorithm partitions the search into different subproblems of the DisCSP. | 9,296 |
algorithm, version Asynchronous resulting completeness. of the its Complete The ensures Overlay Partial (CompAPO), | The resulting version of the algorithm, Complete Asynchronous Partial Overlay (CompAPO), ensures its completeness. | 9,297 |
Formal for of proofs soundness and CompAPO are the given. completeness | Formal proofs for the soundness and completeness of CompAPO are given. | 9,298 |
of algorithm, the and discussed, CompOptAPO, an is optimization Additionally, evaluated. presented, version | Additionally, an optimization version of the algorithm, CompOptAPO, is presented, discussed, and evaluated. | 9,299 |
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