wanyu/IteraTeR_v2 huggingface dataset:
Original:  The tradeoff is that it is more prone to be trapped in local maxima than the evolutionary algorithms in the case of mildly rugged landscapes .
Revised:  The tradeoff is that it is more prone to be trapped in local maxima than the evolutionary algorithms .
Edit intent: coherence
Original: We study the performance of non-adaptive schedul-ing policies in computing systems with multiple servers.
Revised: We study the performance of non-adaptive scheduling policies in computing systems with multiple servers.
Edit intent: fluency
Original:  Computejobs are mostly regular, with modest service requirements.
Revised:  Compute jobs are mostly regular, with modest service requirements.
Edit intent: fluency
Original:  However, there are sporadic data intensive jobs, whose expectedservice time is much higher than that of the regular jobs.
Revised:  However, there are sporadic data intensive jobs, whose expected service time is much higher than that of the regular jobs.
Edit intent: fluency
Original:  We believe that these performance indicators aregood predictors of the relative performance of the policies in thequeuing system, which is supported by simulations results.
Revised:  We believe that these performance indicators are good predictors of the relative performance of the policies in thequeuing system, which is supported by simulations results.
Edit intent: fluency
Original:  We believe that these performance indicators aregood predictors of the relative performance of the policies in thequeuing system, which is supported by simulations results.
Revised:  We believe that these performance indicators aregood predictors of the relative performance of the policies in the queuing system, which is supported by simulations results.
Edit intent: fluency
Original:  e.g., a poly(\log^d (T)) bound for the online d-dimensional Tus\'nady 's problem.
Revised:  e.g., a poly(\log^d (T)) bound for the online d-dimensional Tusn\'ady 's problem.
Edit intent: fluency
Original: In this article, we propose a covariance based method for combining impartial data sets in the genotype to phenotype spectrum.
Revised: In this article, we propose a covariance based method for combining partial data sets in the genotype to phenotype spectrum.
Edit intent: clarity
Original:  Those new metrics attribute a larger value to keeping a connection with the network periphery instead.
Revised:  These new metrics attribute a larger value to keeping a connection with the network periphery instead.
Edit intent: fluency
Original:  Those new metrics attribute a larger value to keeping a connection with the network periphery instead.
Revised:  Those new metrics attribute a higher score to nodes keeping a connection with the network periphery instead.
Edit intent: clarity
Original:  In contrast to established metrics, which identify central nodes based on their brokerage power, the number and weight of their connections, and the ability to quickly reach all other nodes, we introduce five new measures of Distinctiveness Centrality.
Revised:  As an addition to established metrics, which identify central nodes based on their brokerage power, the number and weight of their connections, and the ability to quickly reach all other nodes, we introduce five new measures of Distinctiveness Centrality.
Edit intent: clarity
Original:  Then we describe the generation of new candidate solutions and propose an operator that recombines the whole population to generate variants that preserve normal statistics.
Revised:  We describe the generation of new candidate solutions and propose an operator that recombines the whole population to generate variants that preserve normal statistics.
Edit intent: coherence
Original:  Then we describe the generation of new candidate solutions and propose an operator that recombines the whole population to generate variants that preserve normal statistics.
Revised:  Then we describe the generation of new phenotypes and introduce an operator that recombines the whole population to generate variants that preserve normal statistics.
Edit intent: clarity
Original:  QGA is extremely simple in implementation with no matrix inversion or factorization, does not require storing a covariance matrix, is trivial to parallelize, and may form the basis of more robust algorithms .
Revised:  QGA is extremely simple in implementation with no matrix inversion or factorization, does not require storing a covariance matrix, and may form the basis of more robust algorithms .
Edit intent: clarity
Original:  The more general problem of covering a set of N segments (not necessarily disjoint) by min-area disjoint  polygons can also be solved in near linear time   .
Revised:  The more general problem of covering a set of N segments (not necessarily disjoint) by min-area disjoint polygons can also be computed in near linear time .
Edit intent: clarity
Original:  This belief is largely based on an early result showing that the join of two uniform samples is not an independent sample of the original join  and that it leads to quadratically fewer output tuples  .
Revised:  This belief is largely based on an early result showing that the join of two uniform samples is not an independent sample of the original join , and that it leads to quadratically fewer output tuples .
Edit intent: fluency
Original:  So , the main challenge is about collecting relevant evidences from different layer to assist the link prediction task on a target layer .
Revised:  Here , the main challenge is about collecting relevant evidences from different layer to assist the link prediction task on a target layer .
Edit intent: fluency
Original:  So , the main challenge is about collecting relevant evidences from different layer to assist the link prediction task on a target layer .
Revised:  So , the main challenge is about collecting relevant evidence from different layers to assist the link prediction task on a target layer .
Edit intent: fluency
Original:  So , the main challenge is about collecting relevant evidences from different layer to assist the link prediction task on a target layer .
Revised:  So , the main challenge is about collecting relevant evidences from different layer to assist the link prediction task .
Edit intent: clarity
Original:  It is known that co-membership in communities increases the chance of connectivity between nodes.
Revised:  It is known that co-membership in communities increases the likelihood of connectivity between nodes.
Edit intent: clarity
Original:  Here, we discuss that co-membership in the communities of auxiliary layers that have similar community structure ( significant inter-layer community overlap ) with the target layer does the same.
Revised:  We discuss that co-membership in the communities of auxiliary layers that have similar community structure ( significant inter-layer community overlap ) with the target layer does the same.
Edit intent: coherence
Original:  Here, we discuss that co-membership in the communities of auxiliary layers that have similar community structure ( significant inter-layer community overlap ) with the target layer does the same.
Revised:  Here, we discuss that co-membership in the communities of the similar layers augments the chance of connectivity. The layers are considered similar if they show significant inter-layer community overlap ) with the target layer does the same.
Edit intent: clarity
Original:  The proposed ML-BNMTF  as a link prediction method in multiplex networks, is devised based on these observations and comparison against baseline methods supports the findings .
Revised:  The proposed ML-BNMTF , as a link prediction method in multiplex networks, is devised based on these observations and comparison against baseline methods supports the findings .
Edit intent: fluency
Original: In this article, Momentum Iterative Hessian Sketch (M-IHS) techniques, a group of solvers for large scale  linear Least Squares (LS) problems, are proposed and analyzed in detail.
Revised:  Momentum Iterative Hessian Sketch (M-IHS) techniques, a group of solvers for large scale linear Least Squares (LS) problems, are proposed and analyzed in detail.
Edit intent: coherence
Original:  the M-IHS variants are capable of avoiding all matrix decompositions and inversions, which is one of the main advantages over the alternative solvers such as the Blendenpik and the LSRN. Similar to the Chebyshev Semi-iterations , the M-IHS variants do not use any inner products and eliminate the corresponding synchronizations steps in hierarchical or distributed memory systems, yet the M-IHS converges faster than the Chebyshev Semi-iteration based solvers  .
Revised:  the proposed techniques are capable of avoiding all matrix decompositions and inversions, which is one of the main advantages over the alternative solvers such as the Blendenpik and the LSRN. Similar to the Chebyshev Semi-iterations , the M-IHS variants do not use any inner products and eliminate the corresponding synchronizations steps in hierarchical or distributed memory systems, yet the M-IHS converges faster than the Chebyshev Semi-iteration based solvers .
Edit intent: clarity
Original:  the M-IHS variants are capable of avoiding all matrix decompositions and inversions, which is one of the main advantages over the alternative solvers such as the Blendenpik and the LSRN. Similar to the Chebyshev Semi-iterations , the M-IHS variants do not use any inner products and eliminate the corresponding synchronizations steps in hierarchical or distributed memory systems, yet the M-IHS converges faster than the Chebyshev Semi-iteration based solvers  .
Revised:  the M-IHS variants are capable of avoiding all matrix decompositions and inversions, which is one of the main advantages over the alternative solvers such as the Blendenpik and the LSRN. Similar to the Chebyshev semi-iterations , the M-IHS variants do not use any inner products and eliminate the corresponding synchronizations steps in hierarchical or distributed memory systems, yet the M-IHS converges faster than the Chebyshev Semi-iteration based solvers .
Edit intent: fluency
Original:  the M-IHS variants are capable of avoiding all matrix decompositions and inversions, which is one of the main advantages over the alternative solvers such as the Blendenpik and the LSRN. Similar to the Chebyshev Semi-iterations , the M-IHS variants do not use any inner products and eliminate the corresponding synchronizations steps in hierarchical or distributed memory systems, yet the M-IHS converges faster than the Chebyshev Semi-iteration based solvers  .
Revised:  the M-IHS variants are capable of avoiding all matrix decompositions and inversions, which is one of the main advantages over the alternative solvers such as the Blendenpik and the LSRN. Similar to the Chebyshev Semi-iterations , the M-IHS variants do not use any inner products and eliminate the corresponding synchronization steps in hierarchical or distributed memory systems, yet the M-IHS converges faster than the Chebyshev Semi-iteration based solvers .
Edit intent: fluency
Original:  The rate region for the function computation problem in general topologies is an open problem, and has  been considered under certain restrictive assumptions (e.g. tree networks, linear functions, etc.).
Revised:  The rate region for the function computation problem in general topologies is an open problem, and has only been considered under certain restrictive assumptions (e.g. tree networks, linear functions, etc.).
Edit intent: clarity
Original:  To understand the limits of computation, we introduce the notion of entropic surjectivity as a measure to determine how surjective the function is  . Exploiting Little's law for stationary systems, we later provide a connection between this  notion and the proportion of flow (which we call computation processing factor ) that requires communications.
Revised:  To understand the limits of computation, we introduce the notion of entropic surjectivity as a measure to determine how sparse the function is . Exploiting Little's law for stationary systems, we later provide a connection between this notion and the proportion of flow (which we call computation processing factor ) that requires communications.
Edit intent: clarity
Original:  To understand the limits of computation, we introduce the notion of entropic surjectivity as a measure to determine how surjective the function is  . Exploiting Little's law for stationary systems, we later provide a connection between this  notion and the proportion of flow (which we call computation processing factor ) that requires communications.
Revised:  To understand the limits of computation, we introduce the notion of entropic surjectivity as a measure to determine how surjective the function is and to understand the limits of computation . Exploiting Little's law for stationary systems, we later provide a connection between this notion and the proportion of flow (which we call computation processing factor ) that requires communications.
Edit intent: coherence
Original:  To understand the limits of computation, we introduce the notion of entropic surjectivity as a measure to determine how surjective the function is  . Exploiting Little's law for stationary systems, we later provide a connection between this  notion and the proportion of flow (which we call computation processing factor ) that requires communications.
Revised:  To understand the limits of computation, we introduce the notion of entropic surjectivity as a measure to determine how surjective the function is . Exploiting Little's law for stationary systems, we provide a connection between this notion and the proportion of flow (which we call computation processing factor ) that requires communications.
Edit intent: coherence
Original:  To understand the limits of computation, we introduce the notion of entropic surjectivity as a measure to determine how surjective the function is  . Exploiting Little's law for stationary systems, we later provide a connection between this  notion and the proportion of flow (which we call computation processing factor ) that requires communications.
Revised:  To understand the limits of computation, we introduce the notion of entropic surjectivity as a measure to determine how surjective the function is . Exploiting Little's law for stationary systems, we later provide a connection between this new notion and the proportion of flow (which we call computation processing factor ) that requires communications.
Edit intent: clarity
Original:  To understand the limits of computation, we introduce the notion of entropic surjectivity as a measure to determine how surjective the function is  . Exploiting Little's law for stationary systems, we later provide a connection between this  notion and the proportion of flow (which we call computation processing factor ) that requires communications.
Revised:  To understand the limits of computation, we introduce the notion of entropic surjectivity as a measure to determine how surjective the function is . Exploiting Little's law for stationary systems, we later provide a connection between this notion and the computation processing factor ) that requires communications.
Edit intent: clarity
Original:  This connection gives us an understanding of how much a node (in isolation) should compute (or compress) in order to communicate the desired function within the network .
Revised:  This connection gives us an understanding of how much a node (in isolation) should compute to communicate the desired function within the network .
Edit intent: clarity
Original:  Our analysis does not put any assumptions on the network topologyand characterizes the functions only via their entropic surjectivity, and provides insight into how to distribute computation depending on the entropic surjectivity of the computation task .
Revised:  Our analysis does not put any assumptions on the topology. Our analysis characterizes the functions only via their entropic surjectivity, and provides insight into how to distribute computation depending on the entropic surjectivity of the computation task .
Edit intent: clarity
Original:  However, due to power and storage constraints, sampling frequencies are low, often no faster than one frame per second, and sometimes are irregular due to the use of a motion trigger.
Revised:  Due to power and storage constraints, sampling frequencies are low, often no faster than one frame per second, and sometimes are irregular due to the use of a motion trigger.
Edit intent: coherence
Original:  We show that our model leads to performance gains over strong baselines in all settings .
Revised:  We show that our model leads to performance gains over strong baselines .
Edit intent: clarity
Original:  Here, we present a widely applicable and interpretable probabilistic machine learning method for nonparametric longitudinal data analysis using additive Gaussian process regression .
Revised:  Here, we present a widely applicable and interpretable method for nonparametric longitudinal data analysis using additive Gaussian process regression .
Edit intent: clarity
Original:  Here, we present a widely applicable and interpretable probabilistic machine learning method for nonparametric longitudinal data analysis using additive Gaussian process regression .
Revised:  Here, we present a widely applicable and interpretable probabilistic machine learning method for nonparametric analysis of longitudinal data using additive Gaussian process regression .
Edit intent: fluency
Original:  Here, we present a widely applicable and interpretable probabilistic machine learning method for nonparametric longitudinal data analysis using additive Gaussian process regression .
Revised:  Here, we present a widely applicable and interpretable probabilistic machine learning method for nonparametric longitudinal data analysis using additive Gaussian processes .
Edit intent: clarity
Original:  In this paper , we present an efficient parallel direct algorithm  for the compact high-order approximation of the 3D Helmholtz equation ]  . The developed method is based on a combination of the separation of variables technique and a Fast Fourier Transform (FFT) type method.
Revised:  In this paper , we present an efficient parallel direct algorithm for the compact high-order approximation of the three-dimensional Helmholtz equations ] . The developed method is based on a combination of the separation of variables technique and a Fast Fourier Transform (FFT) type method.
Edit intent: fluency
Original: We considered ] a generalization of the presented algorithm to the solution of  linear systems obtained from approximation on the compact 27-point 3D stencils on the rectangular grids with similar  stencil coefficients.
Revised: We considered ] a generalization of the presented algorithm to the solution of linear systems obtained from approximation on the compact 27-point three-dimensional stencils on the rectangular grids with similar stencil coefficients.
Edit intent: clarity
Original:   ] As an example of the diversity of applications  , the direct parallel implementation of a compact fourth-order approximation scheme for a convection-diffusion equation is considered.
Revised:  ]. As an example of the diversity of applications , the direct parallel implementation of a compact fourth-order approximation scheme for a convection-diffusion equation is considered.
Edit intent: fluency
Original: This paper is concerned with a problem of radio access network (RAN) slicing in a unmanned aerial vehicle (UAV) network for enhanced mobile broadband (eMBB) service provision.
Revised: Unmanned aerial vehicle (UAV) network for enhanced mobile broadband (eMBB) service provision.
Edit intent: coherence
Original: This paper is concerned with the network slicing problem for enhanced mobile broadband (eMBB) service in a multi-UAV-aided network . Different from most of the existing network slicing approaches, we investigate  non-orthogonal network slicing implementation joint with network resource allocation for eMBB service in this paper.
Revised: This paper is concerned with the resource allocation in a multi-UAV-aided network for providing enhanced mobile broadband (eMBB) service in a multi-UAV-aided network . Different from most of the existing network slicing approaches, we investigate non-orthogonal network slicing implementation joint with network resource allocation for eMBB service in this paper.
Edit intent: clarity
Original: This paper is concerned with the network slicing problem for enhanced mobile broadband (eMBB) service in a multi-UAV-aided network . Different from most of the existing network slicing approaches, we investigate  non-orthogonal network slicing implementation joint with network resource allocation for eMBB service in this paper.
Revised: This paper is concerned with the network slicing problem for enhanced mobile broadband (eMBB) service in a multi-UAV-aided network . Different from most of the existing network resource allocation approaches, we investigate non-orthogonal network slicing implementation joint with network resource allocation for eMBB service in this paper.
Edit intent: fluency
Original:  Specifically, our objective is to maximize the system energy efficiency while balancing the fairness of service among user equipments (UEs) and the fairness of power consumption among UAVs under the constraints on eMBB UEs ' quality of service, UAVs' network capacity and power consumption as well .
Revised:  Specifically, our objective is to maximize the network energy efficiency under the constraints on eMBB UEs ' quality of service, UAVs' network capacity and power consumption as well .
Edit intent: clarity
Original:  Specifically, our objective is to maximize the system energy efficiency while balancing the fairness of service among user equipments (UEs) and the fairness of power consumption among UAVs under the constraints on eMBB UEs ' quality of service, UAVs' network capacity and power consumption as well .
Revised:  Specifically, our objective is to maximize the system energy efficiency while balancing the fairness of service among user equipments (UEs) and the fairness of power consumption among UAVs under the constraints on user equipments ' quality of service, UAVs' network capacity and power consumption as well .
Edit intent: clarity
Original:  Specifically, our objective is to maximize the system energy efficiency while balancing the fairness of service among user equipments (UEs) and the fairness of power consumption among UAVs under the constraints on eMBB UEs ' quality of service, UAVs' network capacity and power consumption as well .
Revised:  Specifically, our objective is to maximize the system energy efficiency while balancing the fairness of service among user equipments (UEs) and the fairness of power consumption among UAVs under the constraints on eMBB UEs ' quality of service, UAVs' network capacity and power consumption .
Edit intent: coherence
Original:  Besides, we solve the slice request acceptance problem by designing a two-stage optimization method and tackle the non-convexity of the resource allocation problem by exploiting a successive convex approximation approach . Simulation results show that our proposed framework can achieve the highest energy efficiency compared with other benchmark algorithms .
Revised:  Besides, we solve the slice request acceptance problem by designing a two-stage approximation strategy to handle the non-linearity of the subchannel allocation subproblem and exploit a successive convex approximation approach . Simulation results show that our proposed framework can achieve the highest energy efficiency compared with other benchmark algorithms .
Edit intent: clarity
Original:  We formulate the energy efficiency maximization problem as a  mixed-integer non-convex programming problem.
Revised:  We formulate the energy efficiency maximization problem as a challenging mixed-integer non-convex programming problem.
Edit intent: clarity