wanyu/IteraTeR_v2 huggingface dataset:
Original:  We extensively evaluate our method on thousands of symbolic regression tasks and desired expressions to show that it significantly outperforms baseline algorithms and exhibits discovery of novel expressions outside of the training set.
Revised:  We extensively evaluate our method on thousands of target expressions showing the efficacy of our system compared to exiting methods for finding unknown functions outside of the training set.
Edit intent: clarity
Original:  We further establish that the scheme is half-order accurate for HJBQVIs with Lipschitz coefficients, and first-order accurate for equations with more regular coefficients.
Revised:  We further establish that the schemes are half-order accurate for HJBQVIs with Lipschitz coefficients, and first-order accurate for equations with more regular coefficients.
Edit intent: fluency
Original:  This paper presents a particle swarm optimization (PSO) based cooperative coevolutionary algorithm for the predator robots, called CCPSO-R, where real and virtual robots coexist for the first time in an evolutionary algorithm (EA).
Revised:  This paper presents a particle swarm optimization (PSO) based cooperative coevolutionary algorithm for the (predator) robots, called CCPSO-R, where real and virtual robots coexist for the first time in an evolutionary algorithm (EA).
Edit intent: fluency
Original:  This paper presents a particle swarm optimization (PSO) based cooperative coevolutionary algorithm for the predator robots, called CCPSO-R, where real and virtual robots coexist for the first time in an evolutionary algorithm (EA).
Revised:  This paper presents a particle swarm optimization (PSO) based cooperative coevolutionary algorithm for the predator robots, called CCPSO-R, where real and virtual robots coexist in an evolutionary algorithm (EA).
Edit intent: clarity
Original:  Virtual robots sample and explore the vicinity of the corresponding real robot and act as their action spaces, while the real robots consist of the real predators swarm who actually pursue the prey robot without fixed behavior rules under the immediate guidance of the fitness function, which is designed in a modular manner with very limited domain knowledges .
Revised:  Virtual robots sample and explore the vicinity of the corresponding real robots and act as their action spaces, while the real robots consist of the real predators swarm who actually pursue the prey robot without fixed behavior rules under the immediate guidance of the fitness function, which is designed in a modular manner with very limited domain knowledges .
Edit intent: fluency
Original:  Virtual robots sample and explore the vicinity of the corresponding real robot and act as their action spaces, while the real robots consist of the real predators swarm who actually pursue the prey robot without fixed behavior rules under the immediate guidance of the fitness function, which is designed in a modular manner with very limited domain knowledges .
Revised:  Virtual robots sample and explore the vicinity of the corresponding real robot and act as their action spaces, while the real robots consist of the real predators who actually pursue the prey robot without fixed behavior rules under the immediate guidance of the fitness function, which is designed in a modular manner with very limited domain knowledges .
Edit intent: fluency
Original:  Virtual robots sample and explore the vicinity of the corresponding real robot and act as their action spaces, while the real robots consist of the real predators swarm who actually pursue the prey robot without fixed behavior rules under the immediate guidance of the fitness function, which is designed in a modular manner with very limited domain knowledges .
Revised:  Virtual robots sample and explore the vicinity of the corresponding real robot and act as their action spaces, while the real robots consist of the real predators swarm who actually pursue the prey robot without fixed behavior rules under the immediate guidance of the fitness function, which is designed in a modular manner with very limited domain knowledge .
Edit intent: fluency
Original:  Experiments are conducted on a scalable predator robots swarm with 4 types of preys, the statistical results of which show the reliability, generality, and scalability of the proposed CCPSO-R.  Finally, the codes of this paper are public availabe at: URL
Revised:  Experiments are conducted on a scalable swarm of predator robots with 4 types of preys, the statistical results of which show the reliability, generality, and scalability of the proposed CCPSO-R. Finally, the codes of this paper are public availabe at: URL
Edit intent: fluency
Original:  Experiments are conducted on a scalable predator robots swarm with 4 types of preys, the statistical results of which show the reliability, generality, and scalability of the proposed CCPSO-R.  Finally, the codes of this paper are public availabe at: URL
Revised:  Experiments are conducted on a scalable predator robots swarm with 4 types of preys, the results of which show the reliability, generality, and scalability of the proposed CCPSO-R. Finally, the codes of this paper are public availabe at: URL
Edit intent: clarity
Original:  Experiments are conducted on a scalable predator robots swarm with 4 types of preys, the statistical results of which show the reliability, generality, and scalability of the proposed CCPSO-R.  Finally, the codes of this paper are public availabe at: URL
Revised:  Experiments are conducted on a scalable predator robots swarm with 4 types of preys, the statistical results of which show the reliability, generality, and scalability of the proposed CCPSO-R. Finally, the codes of this paper are public available at: URL
Edit intent: fluency
Original:  Here two physical RC systems based on a single magnetic skyrmion memristor (MSM) and 24 spin-torque nano-oscillators (STNOs) were proposed and modelled to process image classification task and nonlinear dynamic system prediction, respectively.
Revised:  Here two physical RC systems based on a single magnetic skyrmion memristor (MSM) and 24 spin-torque nano-oscillators (STNOs) were proposed and modeled to process image classification task and nonlinear dynamic system prediction, respectively.
Edit intent: fluency
Original:  Based on our micromagnetic simulation results on the nonlinear responses of MSM and STNO with current pulses stimulation,  handwritten digits recognition task domesticates that a RC system using one single MSM has the outstanding performance on image classification.
Revised:  Based on our micromagnetic simulation results on the nonlinear responses of MSM and STNO with current pulses stimulation, the handwritten digits recognition task domesticates that a RC system using one single MSM has the outstanding performance on image classification.
Edit intent: clarity
Original:  Based on our micromagnetic simulation results on the nonlinear responses of MSM and STNO with current pulses stimulation,  handwritten digits recognition task domesticates that a RC system using one single MSM has the outstanding performance on image classification.
Revised:  Based on our micromagnetic simulation results on the nonlinear responses of MSM and STNO with current pulses stimulation, handwritten digits recognition task domesticates that an RC system using one single MSM has the outstanding performance on image classification.
Edit intent: fluency
Original:  In addition, the complex unknown nonlinear dynamic problems can also be well solved by a physical RC system consisted of 24 STNOs confirmed in  second-order nonlinear dynamic system and NARMA10 tasks.
Revised:  In addition, the complex unknown nonlinear dynamic problems can also be well solved by a physical RC system consisted of 24 STNOs confirmed in a second-order nonlinear dynamic system and NARMA10 tasks.
Edit intent: fluency
Original: Seismic data processing algorithms greatly benefit , or even require regularly sampled and reliable data.
Revised: Seismic data processing algorithms greatly benefit from regularly sampled and reliable data.
Edit intent: coherence
Original:  Therefore, interpolation and denoising play a fundamental role as  starting steps of most seismic data processing pipelines.
Revised:  Therefore, interpolation and denoising play a fundamental role as one of the starting steps of most seismic data processing pipelines.
Edit intent: clarity
Original:  Inspired by the great contributions achieved in image processing and computer vision, we investigate a particular architecture of convolutional neural network known as U-net, which implements a convolutional autoencoder able to describe the complex features of clean and regularly sampled data for reconstructing the corrupted ones.
Revised:  Inspired by the great contributions achieved in image processing and computer vision, we investigate a particular architecture of convolutional neural network referred to as U-net, which implements a convolutional autoencoder able to describe the complex features of clean and regularly sampled data for reconstructing the corrupted ones.
Edit intent: coherence
Original:  In training phase we exploit part of the data for tailoring the network to the specific tasks of interpolation, denoising and joint denoising/interpolation, while during the system deployment we are able to retrieve the remaining corrupted shot gathers in a computationally efficient procedure.
Revised:  In training phase we exploit part of the data for tailoring the network to the specific tasks of interpolation, denoising and joint denoising/interpolation, while during the system deployment we are able to recover the remaining corrupted shot gathers in a computationally efficient procedure.
Edit intent: fluency
Original:  In our experimental campaign, we consider a plurality of data corruptions  , including different noise models and missing traces' distributions.
Revised:  We consider a plurality of data corruptions , including different noise models and missing traces' distributions.
Edit intent: clarity
Original:  Moreover, we compare the proposed denoising and interpolation technique to a recent state-of-the-art method .
Revised:  Moreover, we compare the proposed denoising and interpolation .
Edit intent: clarity
Original:  For this reason, techniques such as spectrum sharing and dynamic spectrum access  will soon become essential components of the IoT wireless communication process.
Revised:  For this reason, techniques such as spectrum sharing , dynamic spectrum access will soon become essential components of the IoT wireless communication process.
Edit intent: fluency
Original:  The reason behind machine learning's popularity is that it provides a general framework to solve very complex problems where a model of the phenomenon being learned is too complex to derive or too dynamic to be summarized in mathematical terms.
Edit intent: coherence
Original:  First, we present extensive background notions on machine learning techniques.
Revised:  First, we present extensive background notions of machine learning techniques.
Edit intent: fluency
Original:  Finally, we provide a series of research challenges associated with the applications of machine learning techniques for IoT wireless communications .
Revised:  Additionally, before concluding, we also provide a brief discussion of the application of machine learning techniques for IoT wireless communications .
Edit intent: clarity
Original:  The operator, which we call the \kappa-operator, allows to learn a safe policy in a model-based fashion without actually observing the SRE.
Revised:  The operator, which we call the \kappa-operator, allows to learn a robust policy in a model-based fashion without actually observing the SRE.
Edit intent: clarity
Original:  Using the JKO scheme, along with the Benamou-Brenier dynamical characterization of the Wasserstein distance , we reduce computing the solution of these evolutionary PDEs to solving a sequence of fully discrete minimization problems, with strictly convex objective function and linear constraint.
Revised:  Using the JKO scheme, along with the Benamou-Brenier dynamical characterization of the Wasserstein distance to reduce computing the solution of these evolutionary PDEs to solving a sequence of fully discrete minimization problems, with strictly convex objective function and linear constraint.
Edit intent: fluency
Original:  Using the JKO scheme, along with the Benamou-Brenier dynamical characterization of the Wasserstein distance , we reduce computing the solution of these evolutionary PDEs to solving a sequence of fully discrete minimization problems, with strictly convex objective function and linear constraint.
Revised:  Using the JKO scheme, along with the Benamou-Brenier dynamical characterization of the Wasserstein distance , we reduce computing the solution of the discrete time equations to solving fully discrete minimization problems, with strictly convex objective function and linear constraint.
Edit intent: clarity
Original:  We compute the minimizer of these fully discrete problems by applying a recent , provably convergent primal dual splitting scheme for three operators \mbox{ Yan17 . By leveraging the PDE' s underlying variational structure, our method overcomes traditional stability issues arising from the strong nonlinearity and degeneracy, and it is also naturally positivity preserving and entropy decreasing.
Revised:  We compute the minimizer of these fully discrete problems by applying a recent , provably convergent primal dual splitting scheme for three operators \mbox{ Yan17 . By leveraging the PDEs' underlying variational structure, our method overcomes traditional stability issues arising from the strong nonlinearity and degeneracy, and it is also naturally positivity preserving and entropy decreasing.
Edit intent: fluency
Original:  We prove that minimizers of the fully discrete problem converge to minimizers of the continuum JKO problem as the  discretization is refined , and in the process, we recover convergence results for existing numerical methods for computing Wasserstein geodesics \mbox{ PPO14 conclude with simulations of nonlinear PDEs and Wasserstein geodesics in one and two dimensions that illustrate the key properties of our numerical method.
Revised:  We prove that minimizers of the fully discrete problem converge to minimizers of the continuum JKO problem as the discretization is refined . We conclude with simulations of nonlinear PDEs and Wasserstein geodesics in one and two dimensions that illustrate the key properties of our numerical method.
Edit intent: coherence
Original:  For diseases with low values of the basic reproductive ratio, R_0,  the value of p turns out to have a decisive influence on the existence or not of a major outbreak.
Revised:  For diseases with low values of the basic reproductive ratio, R_0, we found that the value of p turns out to have a decisive influence on the existence or not of a major outbreak.
Edit intent: coherence
Original:  For diseases with low values of the basic reproductive ratio, R_0,  the value of p turns out to have a decisive influence on the existence or not of a major outbreak.
Revised:  For diseases with low values of the basic reproductive ratio, R_0, the value of p has a decisive influence on the existence or not of a major outbreak.
Edit intent: clarity
Original:  A deterministic approximation of the stochastic model , developed by the authors in previous work , is considered.
Revised:  A deterministic approximation of the stochastic model developed in previous work , is considered.
Edit intent: clarity
Original:  The existence of a threshold value of p for exponential epidemic spread is checked in this deterministic context .
Revised:  The existence of a threshold value of p for exponential epidemic spread .
Edit intent: clarity
Original:  An analytical expression, that defines a function of the quotient between the transmission and recovery rates, is obtained to approximate this threshold.
Revised:  An analytical expression, which defines a function of the quotient between the transmission and recovery rates, is obtained to approximate this threshold.
Edit intent: fluency
Original:  An analytical expression, that defines a function of the quotient between the transmission and recovery rates, is obtained to approximate this threshold.
Revised:  An analytical expression, that defines a function of the quotient between the transmission and recovery rates, is proposed to approximate this threshold.
Edit intent: clarity
Original:  Different analyses based on intensive stochastic simulations show that this expression is also a good estimate for a similar threshold value of p in the stochastic model.
Revised:  Different analyses based on intensive stochastic simulations and found that this expression is also a good estimate for a similar threshold value of p in the stochastic model.
Edit intent: clarity
Original:  We first used a deterministic approximation of the stochastic model developed in previous work and checked the existence of a threshold value of p for exponential epidemic spread.
Revised:  We first used a deterministic approximation of the stochastic model and checked the existence of a threshold value of p for exponential epidemic spread.
Edit intent: clarity
Original:  An analytical expression, which defines a function of the quotient  between the transmission and recovery rates, is proposed to approximate this threshold.
Revised:  An analytical expression, which defines a function of the quotient between the transmission and recovery rates, is obtained to approximate this threshold.
Edit intent: clarity
Original:  We then performed different analyses based on intensive stochastic simulations and found that this expression is also a good estimate for a similar threshold value of p  in the stochastic model.
Revised:  We then performed different analyses based on intensive stochastic simulations and found that this expression is also a good estimate for a similar threshold value of p obtained in the stochastic model.
Edit intent: clarity
Original:  Though a number of methods have been developed in the past decades, it is still quite challenging to design quality guaranteed algorithms with low complexities for the problems .
Revised:  Though a number of methods have been developed in the past decades, it is still quite challenging to design quality guaranteed algorithm with low complexity for this problem .
Edit intent: fluency
Original:  Based on some novel observations, we show that this greedy strategy actually can handle k-center /median/means clustering with outliers efficiently, in terms of qualities and complexities .
Revised:  Based on some novel observations, we show that this greedy strategy actually can handle k-center clustering with outliers efficiently, in terms of qualities and complexities .
Edit intent: clarity
Original:  With the goal of establishing a standard of evaluating TSDB systems, we present the IoTDB-Benchmark framework, specifically designed for TSDB and IoT application scenarios.
Revised:  With the goal of establishing a standard of evaluating TSDB systems, we present the IoTDB-Benchmark framework, specifically designed for TSDB and IoT application scenarios.
Edit intent: fluency
Original: With the wide application of time series databases ( TSDB ) in big data fields like cluster monitoring and industrial IoT, there have been developed a number of TSDBs for time series data management.
Revised: With the wide application of time series databases ( TSDBs ) in big data fields like cluster monitoring and industrial IoT, there have been developed a number of TSDBs for time series data management.
Edit intent: fluency
Original: Models of threshold driven contagion successfully explain the cascading spread of information, behaviour, systematic risks and epidemics on social, financial and biological networks.
Revised: Models of threshold driven contagion explain the cascading spread of information, behaviour, systematic risks and epidemics on social, financial and biological networks.
Edit intent: clarity
Original: Models of threshold driven contagion successfully explain the cascading spread of information, behaviour, systematic risks and epidemics on social, financial and biological networks.
Revised: Models of threshold driven contagion successfully explain the cascading spread of information, behavior, systemic risk, and epidemics on social, financial and biological networks.
Edit intent: fluency
Original:  Contradicting real observations, on single-layer networks with sufficiently high connectivity such models predict no global cascades .
Revised:  At odds with empirical observation, these models predict that single-layer networks with sufficiently high connectivity such models predict no global cascades .
Edit intent: clarity
Original:  We investigate threshold driven contagion on weight heterogeneous multiplex networks and show that they  remain susceptible to global cascades at any level of connectivity ;
Revised:  We investigate threshold driven contagion on weight heterogeneous multiplex networks and show that they can remain susceptible to global cascades at any level of connectivity ;
Edit intent: clarity
Original:  We investigate threshold driven contagion on weight heterogeneous multiplex networks and show that they  remain susceptible to global cascades at any level of connectivity ;
Revised:  We investigate threshold driven contagion on weight heterogeneous multiplex networks and show that they remain susceptible to global cascades at any level of connectivity ,
Edit intent: fluency
Original:  Our results provide a missing theoretical explanation for the observation of large scale contagion in highly connected but heterogeneous networks.
Revised:  Our results provide a novel theoretical explanation for the observation of large scale contagion in highly connected but heterogeneous networks.
Edit intent: clarity
Original: We have witnessed an exponential growth in commercial data services, which has lead to the big data's era .
Revised: We have witnessed an exponential growth in commercial data services, which has lead to the 'big data era' .
Edit intent: fluency
Original:  The main benefits of the proposed framework are that by relying on big data which reflects  the real requirements of users, we can refine the motivation, problem formulations , and methodology of powerful machine learning algorithms in the context of wireless networks.
Revised:  The main benefits of the proposed framework are that by relying on big data which reflects the users, we can refine the motivation, problem formulations , and methodology of powerful machine learning algorithms in the context of wireless networks.
Edit intent: clarity
Original:  The main benefits of the proposed framework are that by relying on big data which reflects  the real requirements of users, we can refine the motivation, problem formulations , and methodology of powerful machine learning algorithms in the context of wireless networks.
Revised:  The main benefits of the proposed framework are that by relying on big data which reflects the real requirements of users, we can refine the motivation, problem formulations and methodology of powerful machine learning algorithms in the context of wireless networks.
Edit intent: fluency
Original:  To characterize the efficiency of the proposed framework, a pair of practical case studies are provided : 1) To predict the positioning of drone-mounted areal base stations (BSs) deployments according to specific tele-traffic requirements  . 2) To predict the content caching requirements of BSs according to the users' preferences  .
Revised:  In order to characterize the efficiency of the proposed framework, a pair of practical case studies are provided : 1) To predict the positioning of drone-mounted areal base stations (BSs) deployments according to specific tele-traffic requirements . 2) To predict the content caching requirements of BSs according to the users' preferences .
Edit intent: coherence