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We Decision first-order policies (MDPs) large select with representations. compact for Processes Markov
We select policies for large Markov Decision Processes (MDPs) with compact first-order representations.
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using a taxonomic language. policies represented decision concept lists, Our as are ensembles of
Our policies are represented as ensembles of decision lists, using a taxonomic concept language.
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work application of the this to problem. reinforcement-learning We the relational discuss also
We also discuss the application of this work to the relational reinforcement-learning problem.
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zero For collective a rescue terminates cooperative in growth rate, catastrophe.
For zero rescue rate, cooperative growth terminates in a collective catastrophe.
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e.g. a signal, and spatial motion, global
global motion, and a spatial signal, e.g.
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modeled signal well is sparse often as some being domain. The spatial in
The spatial signal is often well modeled as being sparse in some domain.
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new of First, Bayesianism a given. foundation is
First, a new foundation of Bayesianism is given.
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NP-SPEC a NP language for declarative problems specifying in is in way. a
NP-SPEC is a language for specifying problems in NP in a declarative way.
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comprise arthropods. Pycnogonids, spiders, lineage sea or a of primitive
Pycnogonids, or sea spiders, comprise a primitive lineage of arthropods.
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evolution. such, reveal hold As into arthropod insights potential they to
As such, they hold potential to reveal insights into arthropod evolution.
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juvenile the stage. the from molt emerge and Larvae hydroid simultaneously into
Larvae emerge from the hydroid and simultaneously molt into the juvenile stage.
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preceding the mature there of Over eight the are stages post-embryonic course adult. development
Over the course of post-embryonic development there are eight stages preceding the mature adult.
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appendages, chelifores, some anteriormost the All structures, except transformation. degree for undergo of the
All structures, except for the anteriormost appendages, the chelifores, undergo some degree of transformation.
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and remain the hatching mobile are present over prior of course to Chelifores development.
Chelifores are present prior to hatching and remain mobile over the course of development.
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collaborative a systems. We principled and present efficient for multiagent planning dynamical algorithm
We present a principled and efficient planning algorithm for collaborative multiagent dynamical systems.
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connected subsystem The a hierarchy. are through subsystems
The subsystems are connected through a subsystem hierarchy.
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can which applied the step models intractable. be Hence to exactupdate is for it
Hence it can be applied to models for which the exactupdate step is intractable.
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Our for approach to successful. that results must chosen be appropriately be these this show
Our results show that these must be chosen appropriately for this approach to be successful.
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natural This settings. is in arguably many representation
This representation is arguably natural in many settings.
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efficient. CP-semantics queries very the that strong and of Furthermore, ensures computation dominance is optimization
Furthermore, the strong CP-semantics ensures that computation of optimization and dominance queries is very efficient.
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decision demonstrate in value also representation this We the making. of
We also demonstrate the value of this representation in decision making.
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for We confidence sampling networks. in algorithms two inference present probabilistic Bayesian
We present two sampling algorithms for probabilistic confidence inference in Bayesian networks.
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evidence. An of evaluation even unlikely excellent proposed for empirical performance, shows very the algorithms
An empirical evaluation of the proposed algorithms shows excellent performance, even for very unlikely evidence.
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We consider severalexperts. aggregating of task beliefs of the
We consider the task of aggregating beliefs of severalexperts.
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probabilitydistributions. beliefs We assume these as represented that are
We assume that these beliefs are represented as probabilitydistributions.
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distribution aggregate Naturally, be thecombined would sets. the sample learned theideal one from
Naturally, theideal aggregate distribution would be the one learned from thecombined sample sets.
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Our well experiments show in practice. algorithmperforms that preliminary this
Our preliminary experiments show that this algorithmperforms well in practice.
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. on Mechanical to Reply Dependence Properties' 'Length Comment Scale DNA of
Reply to Comment on 'Length Scale Dependence of DNA Mechanical Properties' .
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this to phenomenon." quantify manuscript The is this purpose "incommensurability of
The purpose of this manuscript is to quantify this "incommensurability phenomenon."
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formed cell. from complex embryonic organism starting single a a is development, During
During embryonic development, a complex organism is formed from a single starting cell.
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each clustered quantitative temporal based profiles. TFs species We expression on for their further
We further clustered TFs for each species based on their quantitative temporal expression profiles.
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trends TF development in similar expression vertebrate showed This very and species. in insect
This showed very similar TF expression trends in development in vertebrate and insect species.
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fighting for provides insights Understanding new this treatments for with cancer. developing process
Understanding this process provides insights for developing new treatments for fighting with cancer.
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with plausible incomplete reasoning article deals spatial from large-scale This properties. knowledge about
This article deals with plausible reasoning from incomplete knowledge about large-scale spatial properties.
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consisting observations,is set availableinformation, neighbour The of to points. a extrapolated of pointwise
The availableinformation, consisting of a set of pointwise observations,is extrapolated to neighbour points.
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An numerical the evolutionary stable ab-initio of density-dependent, presented. dispersal strategy is study
An ab-initio numerical study of the density-dependent, evolutionary stable dispersal strategy is presented.
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scaling A to the laws data. are emerge few from seen general
A few general scaling laws are seen to emerge from the data.
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mixture (TrAp) developed algorithm problem. solving this for efficient have We an
We have developed an efficient algorithm (TrAp) for solving this mixture problem.
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the karyotypes using somatic the of and We tumor hypermutation datasets. method applicability demonstrate
We demonstrate the applicability of the method using tumor karyotypes and somatic hypermutation datasets.
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In problem in CLGs. of explore this the paper inference we
In this paper we explore the problem of inference in CLGs.
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in harder CLGs can that significantly than We inference in Bayes Nets. inference show be
We show that inference in CLGs can be significantly harder than inference in Bayes Nets.
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off work restart cut employed Previous have values. fixed strategies on
Previous work on restart strategies have employed fixed cut off values.
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and analyzed class Classes number size. were edges according of to
Classes were analyzed according to number of edges and class size.
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Gaussian edges, By shape. the number classes of approaches distribution of a
By edges, the distribution of number of classes approaches a Gaussian shape.
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The generating undirected algorithm for graphs. orderly includes also program of variation a new
The program also includes a new variation of orderly algorithm for generating undirected graphs.
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Although intractable, POMDPs formulation are solution. our tractable typically admits
Although POMDPs are typically intractable, our formulation admits tractable solution.
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inference enhanced proposed networks. has algorithm for these CLG No been exact
No exact inference algorithm has been proposed for these enhanced CLG networks.
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Lauritzen's algorithm to algorithm. comparable to its implement complexity in often simple Our and is
Our algorithm is simple to implement and often comparable in its complexity to Lauritzen's algorithm.
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We show previous that empirically higher approximate achieves algorithms. than it accuracy substantially
We show empirically that it achieves substantially higher accuracy than previous approximate algorithms.
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against is management accuracy. objective balance The tractability hypothesis of to
The objective of hypothesis management is to balance tractability against accuracy.
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Our literature. is related compared tracking work and in the approach to fusion
Our approach is compared to related work in the tracking and fusion literature.
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description an logics. DL-Lite family of important is
DL-Lite is an important family of description logics.
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belief evaluating complex querie probabilities network. a over of boolean
evaluating probabilities of complex boolean querie over a belief network.
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probabilistic on Preliminary evaluation effect the empirical constraint demonstrate of propagation computation.
Preliminary empirical evaluation demonstrate the effect of constraint propagation on probabilistic computation.
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is similarity definition issue the A of user in between key this preferences. approach
A key issue in this approach is the definition of similarity between user preferences.
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is {em the case of decision certainty}. This under making for
This is for the case of decision making under {em certainty}.
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belief approximation a to propose new value-directed for We POMDPs. approach state
We propose a new approach to value-directed belief state approximation for POMDPs.
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function computing concurrentoptions. This over allows for us the property value SMDPalgorithms use to
This property allows us to use SMDPalgorithms for computing the value function over concurrentoptions.
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on We clustering propose components a spectral local based principal (PCA). method analysis
We propose a spectral clustering method based on local principal components analysis (PCA).
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algorithms norm subdifferential. derived form are nonparametric a justified and using the nuclear Backfitting of
Backfitting algorithms are derived and justified using a nonparametric form of the nuclear norm subdifferential.
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gene methods data. are illustrated expression The on
The methods are illustrated on gene expression data.
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inference (BNs). networks propose approximate inBayesian recognition using for networks We
We propose using recognition networks for approximate inference inBayesian networks (BNs).
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input vector is to The evidential MLP thestates nodes. of of a the the
The input to the MLP is a vector of thestates of the evidential nodes.
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networks both and Recognition performwell observation using biases. correct incorrect
Recognition networks performwell using both correct and incorrect observation biases.
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systems. central in role Uncertainty spoken a plays dialogue
Uncertainty plays a central role in spoken dialogue systems.
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model process used to Some Markov are dialogue manager. like stochastic the decision (MDP) models
Some stochastic models like Markov decision process (MDP) are used to model the dialogue manager.
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uncertainty MDP-based increases. user's about when intention system degrades a fast
MDP-based system degrades fast when uncertainty about a user's intention increases.
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on model (POMDP). observable decision dialogue a partially propose Markov We the process based novel
We propose a novel dialogue model based on the partially observable Markov decision process (POMDP).
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grid methods two in point We selection algorithms. grid-based approximation also propose for
We also propose two methods for grid point selection in grid-based approximation algorithms.
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handles users real-time. from two-handed efficient multiple multi-threaded implementation input in The
The efficient multi-threaded implementation handles two-handed input from multiple users in real-time.
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forgetting variable by dilation. belief paper merging builds and This relationship between a first using
This paper first builds a relationship between belief merging and variable forgetting by using dilation.
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Variable applied to is forgetting operation. belief capture merging
Variable forgetting is applied to capture belief merging operation.
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inheritance present probabilistic We programming logic with overriding. under
We present probabilistic logic programming under inheritance with overriding.
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default recent to reasoning This conditional probabilistic approaches is using with constraints. done by
This is done by using recent approaches to probabilistic default reasoning with conditional constraints.
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properties the of entailment new We relations. analyze the semantic
We analyze the semantic properties of the new entailment relations.
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of is from The quantum transition. point investigated of macromolecule change biological conformational the
The conformational change of biological macromolecule is investigated from the point of quantum transition.
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theory A protein quantum on is folding proposed.
A quantum theory on protein folding is proposed.
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the are from conformational states defined. of Simultaneously, the well local multi-minima property torsion potential
Simultaneously, from the multi-minima property of torsion potential the local conformational states are well defined.
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folding protein rate the deduced. Then, formulas for general are
Then, the general formulas for protein folding rate are deduced.
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to We technique multi-layer clustering present the networks. feedforward applied deep neural learning
We present the clustering learning technique applied to multi-layer feedforward deep neural networks.
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to for technique paper this promote is systems. goal The robotic the vision of general-purpose
The goal of this paper is to promote the technique for general-purpose robotic vision systems.
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We in datasets datasets. report image static use and object tracking its
We report its use in static image datasets and object tracking datasets.
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followed structure This two strands. of disruption is in by
This is followed by disruption of structure in two strands.
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on results MNIST architecture The resulting state-of-the-art the classification achieves benchmark.
The resulting architecture achieves state-of-the-art results on the MNIST classification benchmark.
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Expectation for (EP) inference. framework provides a Propagation approximate
Expectation Propagation (EP) provides a framework for approximate inference.
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EP the Through to expansion, order. see first we correct that is
Through the expansion, we see that EP is correct to first order.
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be By complexity corrections higher the considering increasing of can orders, approximation. to applied polynomial
By considering higher orders, corrections of increasing polynomial complexity can be applied to the approximation.
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the provide they of assessment Furthermore, error. approximation a polynomial-time
Furthermore, they provide a polynomial-time assessment of the approximation error.
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EP We provide both the exactness theoretical on solution. the of and also practical insights
We also provide both theoretical and practical insights on the exactness of the EP solution.
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Since the not and are are provide experts, crowds necessarily rather erroneous. they labels noisy
Since crowds are not necessarily experts, the labels they provide are rather noisy and erroneous.
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high-quality Although is leads mechanism not cost-effective. it labels, actually to the
Although the mechanism leads to high-quality labels, it is not actually cost-effective.
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to models inference be make will surveyed. algorithms on Afterwards, these
Afterwards, algorithms to make inference on these models will be surveyed.
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of the estimators proposed properties Moreover, are semiparametric asymptotic provided.
Moreover, asymptotic properties of the proposed semiparametric estimators are provided.
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Their practical theoretical previously relations discussed. and combination are
Their theoretical relations and practical combination are previously discussed.
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descriptors. as descriptors, WSS While wavelet basis uses sub-bands treats pixel-value PSS
While PSS uses pixel-value descriptors, WSS treats wavelet sub-bands as basis descriptors.
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results results other compare in making. with our recent decision qualitative We
We compare our results with other recent results in qualitative decision making.
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work of This segmentation with indoor inputs. multi-class addresses RGB-D scenes
This work addresses multi-class segmentation of indoor scenes with RGB-D inputs.
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deals Bayesian paper solution the of representation asymmetric This with problems. and decision
This paper deals with the representation and solution of asymmetric Bayesian decision problems.
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an for asymmetric algorithm solving diagrams. influence give We
We give an algorithm for solving asymmetric influence diagrams.
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and evolution. important organismic and fitness, between are links Molecular phenotypes functions, information genomic
Molecular phenotypes are important links between genomic information and organismic functions, fitness, and evolution.
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