wanyu/IteraTeR_v2 huggingface dataset:
Original:  The k-center problem finds k points as centers among P, such that the maximum distance of any point of P to their closest centers (r) is minimized.
Revised:  The k-center problem finds k points as centers among P, such that the maximum distance of any point of P to their closest centers (r) is minimized.
Edit intent: fluency
Original: Next-generation wireless networks (NGWN) have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services.
Revised: Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services.
Edit intent: clarity
Original:  Machine learning  algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making.
Revised:  Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making.
Edit intent: clarity
Original:  Hence, in this article, we review the thirty-year history of machine learning by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning , respectively .
Revised:  Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning , respectively .
Edit intent: clarity
Original:  Hence, in this article, we review the thirty-year history of machine learning by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning , respectively .
Revised:  Hence, in this article, we review the thirty-year history of machine learning by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning .
Edit intent: coherence
Original:  This article aims for assisting the readers in clarifying the motivation and methodology of the various machine learning algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.
Revised:  This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.
Edit intent: clarity
Original: In recent years several compressed indexes based on variants of the Borrows-Wheeler transformation have been introduced.
Revised: In recent years several compressed indexes based on variants of the Burrows-Wheeler transformation have been introduced.
Edit intent: fluency
Original:  For a polynomial lying in the interior of the SAGE cone, we prove that the decision algorithm terminates within a number of arithmetic operations, which is polynomial in the degree and number of terms of the input, and singly exponential in the number of variables .
Revised:  For a polynomial lying in the interior of the SAGE cone, we prove that the decision algorithm terminates within a number of arithmetic operations, which is polynomial in the number of terms of the input, and singly exponential in the number of variables .
Edit intent: clarity
Original:  The discontinuities dictate the spacial discretization, which leads to a stochastic grid.
Revised:  The discontinuities dictate the spatial discretization, which leads to a stochastic grid.
Edit intent: fluency
Original:  Specifically, a scenario with dependent advection and diffusion coefficients that are modeled as sums of continuous random fields and discontinuous jump components are considered.
Revised:  Specifically, a scenario with coupled advection- and diffusion coefficients that are modeled as sums of continuous random fields and discontinuous jump components are considered.
Edit intent: clarity
Original:  Existing solutions either use \Omega(n) space or use word RAM bit tricks (i.e. do not work on a pointer machine ) . Our result is the first solution on a pointer machine that achieves worst-case o(n) space.
Revised:  Existing solutions either use \Omega(n) space or use word RAM bit tricks (i.e. do not work on a pointer machine . Our result is the first solution on a pointer machine that achieves worst-case o(n) space.
Edit intent: fluency
Original:  These include an optimal data structure for random access to a grammar-compressed string and an optimal data structure for a variant of the level ancestor problem.
Revised:  These include an optimal data structures for random access to a grammar-compressed string and an optimal data structure for a variant of the level ancestor problem.
Edit intent: fluency
Original: Objective: This paper proposes a stable volume integral equation (VIE) solver based on polarization/magnetization currents  , for the accurate and efficient computation of the electromagnetic scattering from highly inhomogeneous and high contrast objects.
Revised: A stable volume integral equation (VIE) solver based on polarization/magnetization currents , for the accurate and efficient computation of the electromagnetic scattering from highly inhomogeneous and high contrast objects.
Edit intent: coherence
Original: Objective: This paper proposes a stable volume integral equation (VIE) solver based on polarization/magnetization currents  , for the accurate and efficient computation of the electromagnetic scattering from highly inhomogeneous and high contrast objects.
Revised: Objective: This paper proposes a stable volume integral equation (VIE) solver based on polarization/magnetization currents is presented , for the accurate and efficient computation of the electromagnetic scattering from highly inhomogeneous and high contrast objects.
Edit intent: clarity
Original:  Methods: We employ the Galerkin Method of Moments to discretize the formulation with discontinuous piecewise linear basis functions on uniform voxelized grids, allowing for the acceleration of the associated matrix-vector products in an iterative solver, with the help of FFT.
Revised:  We employ the Galerkin Method of Moments to discretize the formulation with discontinuous piecewise linear basis functions on uniform voxelized grids, allowing for the acceleration of the associated matrix-vector products in an iterative solver, with the help of FFT.
Edit intent: coherence
Original:  Results: Numerical experiments are conducted to study the accuracy and convergence properties of the proposed framework .
Revised:  Numerical results illustrate the superior accuracy and more stable convergence properties of the proposed framework .
Edit intent: clarity
Original:  Their results are compared against standard low order (piecewise constant) discretization schemes , a more conventional VIE formulation based on electric flux densities , and a commercial software package that employs the finite difference time domain method.
Revised:  Their results are compared against standard low order (piecewise constant) discretization schemes and a more conventional VIE formulation based on electric flux densities , and a commercial software package that employs the finite difference time domain method.
Edit intent: coherence
Original:  Significance: The developed solver can be applied to accurately analyze complex geometries, including realistic human body models, typically used in modeling the interactions between electromagnetic waves and biological tissue , that arise in magnetic resonance scanners .
Revised:  Significance: The developed solver can be applied to accurately analyze complex geometries, including realistic human body models, typically used in modeling the interactions between electromagnetic waves and biological tissue .
Edit intent: coherence
Original: A kernel-independent treecode (KITC) is presented for fast summation of pairwise particle interactions.
Revised: A kernel-independent treecode (KITC) is presented for fast summation of particle interactions.
Edit intent: clarity
Original:  In general, treecodes replace the particle-particle interactions by particle-cluster interactions, and here we utilize barycentric Lagrange interpolation at Chebyshev points to compute well-separated particle-cluster interactions.
Revised:  The method employs barycentric Lagrange interpolation at Chebyshev points to compute well-separated particle-cluster interactions.
Edit intent: clarity
Original:  In general, treecodes replace the particle-particle interactions by particle-cluster interactions, and here we utilize barycentric Lagrange interpolation at Chebyshev points to compute well-separated particle-cluster interactions.
Revised:  In general, treecodes replace the particle-particle interactions by particle-cluster interactions, and here we utilize barycentric Lagrange interpolation at Chebyshev points to approximate well-separated particle-cluster interactions.
Edit intent: clarity
Original:  The scheme requires only kernel evaluations and is suitable for non-oscillatory kernels  .
Revised:  The scheme requires only kernel evaluations , is suitable for non-oscillatory kernels .
Edit intent: coherence
Original:  The algorithm is demonstrated in serial and parallel simulations for systems of regularized Stokeslets and rotlets in 3D, and numerical results show the treecode performance in terms of error, CPU time, and memory overhead .
Revised:  The algorithm is demonstrated for systems of regularized Stokeslets and rotlets in 3D, and numerical results show the treecode performance in terms of error, CPU time, and memory overhead .
Edit intent: clarity
Original:  The algorithm is demonstrated in serial and parallel simulations for systems of regularized Stokeslets and rotlets in 3D, and numerical results show the treecode performance in terms of error, CPU time, and memory overhead .
Revised:  The algorithm is demonstrated in serial and parallel simulations for systems of regularized Stokeslets and rotlets in 3D, and numerical results show the treecode performance in terms of error, CPU time, and memory consumption .
Edit intent: clarity
Original:  The KITC is a relatively simple algorithm with low memory overhead , and this enables a straightforward efficient parallelization.
Revised:  The KITC is a relatively simple algorithm with low memory consumption , and this enables a straightforward efficient parallelization.
Edit intent: clarity
Original:  By leveraging insights from the multi-way matching and spectral graph clustering literatures , CLEAR provides cycle consistent and accurate solutions in a computationally efficient manner.
Revised:  By leveraging insights from the multi-way matching and spectral graph clustering literature , CLEAR provides cycle consistent and accurate solutions in a computationally efficient manner.
Edit intent: fluency
Original: A new reference design is introduced for Holographic Coherent Diffraction Imaging .
Revised: A new reference design is introduced for holographic coherent diffraction imaging .
Edit intent: fluency
Original:  This consists of two reference portions - being "block" and "pinhole" shaped regions -  adjacent to the imaging specimen.
Revised:  This consists in two references - being "block" and "pinhole" shaped regions - adjacent to the imaging specimen.
Edit intent: clarity
Original:  This consists of two reference portions - being "block" and "pinhole" shaped regions -  adjacent to the imaging specimen.
Revised:  This consists of two reference portions - "block" and "pinhole" shaped regions - adjacent to the imaging specimen.
Edit intent: clarity
Original:  This consists of two reference portions - being "block" and "pinhole" shaped regions -  adjacent to the imaging specimen.
Revised:  This consists of two reference portions - being "block" and "pinhole" shaped regions - placed adjacent to the imaging specimen.
Edit intent: clarity
Original:  Numerical experiments on simulated data also shows the dual-reference scheme achieving a smaller recovery error than the leading single-reference schemes.
Revised:  Numerical experiments on simulated data also shows the dual-reference scheme achieves a smaller recovery error than the leading single-reference schemes.
Edit intent: fluency
Original:  Numerical experiments on simulated data also shows the dual-reference scheme achieving a smaller recovery error than the leading single-reference schemes.
Revised:  Numerical experiments on simulated data also shows the dual-reference scheme achieving a smaller recovery error than leading single-reference schemes.
Edit intent: fluency
Original:  The algorithm has O(N) time and O(1) memory complexities if the given array of N numbers is sorted.
Revised:  The algorithm has O(N) time and O(1) memory complexity if the given array of N numbers is sorted.
Edit intent: fluency
Original:  While it is often applied in the literal sense, a common interpretation sees the one-fifth success rule as a family of success-based updated rules that are determined by an update strength F and a success rate s . We analyze in this work how the performance of the (1+1) Evolutionary Algorithm (EA) on LeadingOnes depends on these two hyper-parameters.
Revised:  While it is often applied in the literal sense, a common interpretation sees the one-fifth success rule as a family of success-based updated rules that are determined by an update strength F and a success rate . We analyze in this work how the performance of the (1+1) Evolutionary Algorithm (EA) on LeadingOnes depends on these two hyper-parameters.
Edit intent: fluency
Original:  While it is often applied in the literal sense, a common interpretation sees the one-fifth success rule as a family of success-based updated rules that are determined by an update strength F and a success rate s . We analyze in this work how the performance of the (1+1) Evolutionary Algorithm (EA) on LeadingOnes depends on these two hyper-parameters.
Revised:  While it is often applied in the literal sense, a common interpretation sees the one-fifth success rule as a family of success-based updated rules that are determined by an update strength F and a success rate s . We analyze in this work how the performance of the (1+1) Evolutionary Algorithm on LeadingOnes depends on these two hyper-parameters.
Edit intent: clarity
Original:  We also prove that the running time obtained by this parameter setting is asymptotically optimal among all dynamic choices of the mutation rate for the (1+1) EA, up to lower order error terms .
Revised:  We also prove that the running time obtained by this parameter setting is , apart from lower order terms, the same that is achieved with the best fitness-dependent mutation rate .
Edit intent: clarity
Original:  We show that such lattices exist in arbitrarily large dimensions and discuss some examples arising from complete graphs, product graphs, as well as some other notable examples of graphs.
Revised:  We show that such lattices exist in arbitrarily large dimensions and demonstrate examples arising from complete graphs, product graphs, as well as some other notable examples of graphs.
Edit intent: clarity
Original:  We show that such lattices exist in arbitrarily large dimensions and discuss some examples arising from complete graphs, product graphs, as well as some other notable examples of graphs.
Revised:  We show that such lattices exist in arbitrarily large dimensions and discuss some examples arising from some notable families of graphs.
Edit intent: clarity
Original:  After appropriate weight pretraining, the networks  dynamically adapt to learn new tasks and thereafter continue to achieve them without further teacher feedback.
Revised:  After appropriate weight pretraining, the networks quickly and dynamically adapt to learn new tasks and thereafter continue to achieve them without further teacher feedback.
Edit intent: clarity
Original: Importance: Artificial Intelligence (AI) is necessary to address the large and growing deficit in retina and healthcare access globally.
Revised:  Artificial Intelligence (AI) is necessary to address the large and growing deficit in retina and healthcare access globally.
Edit intent: coherence
Original:  Mobile AI diagnostic platforms running in the Cloud may effectively and efficiently distribute such AI capability.
Revised:  And mobile AI diagnostic platforms running in the Cloud may effectively and efficiently distribute such AI capability.
Edit intent: clarity
Original:  Objective: To evaluate the feasibility of Cloud-based mobile artificial intelligence for detection of retinal disease.
Revised:  Here we sought to evaluate the feasibility of Cloud-based mobile artificial intelligence for detection of retinal disease.
Edit intent: clarity
Original:  Design: A multicenter retrospective image analysis was conducted in which board-certified ophthalmologists with fellowship training in retina evaluated OCT images of the macula.
Revised:  A multicenter retrospective image analysis was conducted in which board-certified ophthalmologists with fellowship training in retina evaluated OCT images of the macula.
Edit intent: coherence
Original:  Exclusion criteria included poor quality scans, ambiguous or overly subtle features, macula holes, retinoschisis, and dense epiretinal membranes.
Revised:  Exclusion criteria included poor scan quality, ambiguous features, macula holes, retinoschisis, and dense epiretinal membranes.
Edit intent: clarity
Original:  Main outcome and Measures: Accuracy in the form of sensitivity and specificity of the AI mobile app compared against assessments of board-certified retina specialists .
Revised:  Accuracy in the form of sensitivity and specificity of the AI mobile app compared against assessments of board-certified retina specialists .
Edit intent: coherence
Original:  The effectiveness of our theoretical result is numerically illustrated by simulations on empirical human and animal social networks.
Revised:  The effectiveness of our result by numerical simulations on empirically observed human and animal social networks.
Edit intent: clarity
Original: In this paper we develop an adaptive step size control for the numerical tracking of implicitly defined paths in the context of polynomial homotopy continuation methods.
Revised: This article develops a new predictor-corrector algorithm for numerical path tracking in the context of polynomial homotopy continuation methods.
Edit intent: clarity
Original:  Here, we investigate whether evolutionary dynamics interacts with the spatial structure of a prey-predator community in which both species show limited mobility and predators perceptual ranges are subject to natural selection.
Revised:  Here, we investigate whether an evolutionary dynamics may interact with the spatial structure of a prey-predator community in which both species show limited mobility and predators perceptual ranges are subject to natural selection.
Edit intent: clarity
Original:  Here, we investigate whether evolutionary dynamics interacts with the spatial structure of a prey-predator community in which both species show limited mobility and predators perceptual ranges are subject to natural selection.
Revised:  Here, we investigate whether evolutionary dynamics interacts with the spatial structure of a prey-predator community in which both species show limited mobility and predator perceptual ranges are subject to natural selection.
Edit intent: fluency
Original: Recent vibrational energy exchange experiments on a protein have been explained employing the relation, not new in itself,between protein and fractal structure.
Revised: Recent experimental findings on a protein have been explained employing the relation, not new in itself,between protein and fractal structure.
Edit intent: clarity
Original:  Within the actor-critic MARL, we introduce multiple cooperative critics from two levels of the hierarchy and propose a hierarchical critic-based multi-agent reinforcement learning algorithm.
Revised:  Within the actor-critic MARL, we introduce multiple cooperative critics from two levels of the hierarchy and propose a hierarchical critic-based MARL algorithm.
Edit intent: clarity
Original:  The agent not only receives low-level details but also consider coordination from high levels that receiving global information to increase operation skills .
Revised:  The agent not only receives low-level details but also considers coordination from high levels that receiving global information to increase operation skills .
Edit intent: fluency
Original:  The agent not only receives low-level details but also consider coordination from high levels that receiving global information to increase operation skills .
Revised:  The agent not only receives low-level details but also consider coordination from high levels to obtain global information for increasing operational performance .
Edit intent: clarity
Original:  Here, we define multiple cooperative critics in the top-bottom hierarchy, called the Hierarchical Critics Assignment (HCA) framework.
Revised:  Here, we define multiple cooperative critics in a top-down hierarchy, called the Hierarchical Critics Assignment (HCA) framework.
Edit intent: fluency
Original:  Here, we define multiple cooperative critics in the top-bottom hierarchy, called the Hierarchical Critics Assignment (HCA) framework.
Revised:  Here, we define multiple cooperative critics in the top-bottom hierarchy, called the Hierarchical Critic Assignment (HCA) framework.
Edit intent: fluency
Original:  Our experiment, a two-player tennis competition task  in the Unity environment, tested  HCA multi-agent framework based on  Asynchronous Advantage Actor-Critic (A3C) with Proximal Policy Optimization (PPO) algorithm.
Revised:  Our experiment, a two-player tennis competition task performed in the Unity environment, tested HCA multi-agent framework based on Asynchronous Advantage Actor-Critic (A3C) with Proximal Policy Optimization (PPO) algorithm.
Edit intent: clarity
Original:  Our experiment, a two-player tennis competition task  in the Unity environment, tested  HCA multi-agent framework based on  Asynchronous Advantage Actor-Critic (A3C) with Proximal Policy Optimization (PPO) algorithm.
Revised:  Our experiment, a two-player tennis competition task in the Unity environment, tested the HCA multi-agent framework based on Asynchronous Advantage Actor-Critic (A3C) with Proximal Policy Optimization (PPO) algorithm.
Edit intent: fluency
Original:  Our experiment, a two-player tennis competition task  in the Unity environment, tested  HCA multi-agent framework based on  Asynchronous Advantage Actor-Critic (A3C) with Proximal Policy Optimization (PPO) algorithm.
Revised:  Our experiment, a two-player tennis competition task in the Unity environment, tested HCA multi-agent framework based on the Asynchronous Advantage Actor-Critic (A3C) with Proximal Policy Optimization (PPO) algorithm.
Edit intent: fluency
Original:  The results showed that the HCA- framework outperforms the non-hierarchical critics baseline method for MARL tasks.
Revised:  The results showed that the HCA framework outperforms the non-hierarchical critics baseline method for MARL tasks.
Edit intent: fluency
Original:  The results showed that the HCA- framework outperforms the non-hierarchical critics baseline method for MARL tasks.
Revised:  The results showed that the HCA- framework outperforms the non-hierarchical critic baseline method on MARL tasks.
Edit intent: fluency
Original: In this paper , we investigate the use of global information to speed up the learning process and increase the cumulative rewards of multi-agent reinforcement learning (MARL) tasks.
Revised: In this study , we investigate the use of global information to speed up the learning process and increase the cumulative rewards of multi-agent reinforcement learning (MARL) tasks.
Edit intent: clarity