wanyu/IteraTeR_v2 huggingface dataset:
Original:  Furthermore , the winning tickets we find above that size learn faster than the original network and exhibit higher test accuracy.
Revised:  Above this size , the winning tickets we find above that size learn faster than the original network and exhibit higher test accuracy.
Edit intent: coherence
Original:  Furthermore , the winning tickets we find above that size learn faster than the original network and exhibit higher test accuracy.
Revised:  Furthermore , the winning tickets that we find learn faster than the original network and exhibit higher test accuracy.
Edit intent: clarity
Original:  Furthermore , the winning tickets we find above that size learn faster than the original network and exhibit higher test accuracy.
Revised:  Furthermore , the winning tickets we find above that size learn faster than the original network and reach higher test accuracy.
Edit intent: clarity
Original: Confronted with the challenge of high performance for applications and the restriction of hardware resources for field-programmable gate arrays (FPGAs), partial dynamic re- configuration (PDR) technology is anticipated to accelerate the reconfiguration process and alleviate the device shortage.
Revised: Confronted with the challenge of high performance for applications and the restriction of hardware resources for field-programmable gate arrays (FPGAs), partial dynamic reconfiguration (PDR) technology is anticipated to accelerate the reconfiguration process and alleviate the device shortage.
Edit intent: clarity
Original:  The partitions, schedule, and floorplan of the tasks are represented by the partitioned sequence triple P- ST (PS,QS,RS), where (PS,QS) is a hybrid nested sequence pair (HNSP) for representing the spatial and temporal partitions, as well as the floorplan, and RS is the partitioned dynamic configu- ration order of the tasks.
Revised:  The partitions, schedule, and floorplan of the tasks are represented by the partitioned sequence triple P-ST (PS,QS,RS), where (PS,QS) is a hybrid nested sequence pair (HNSP) for representing the spatial and temporal partitions, as well as the floorplan, and RS is the partitioned dynamic configu- ration order of the tasks.
Edit intent: fluency
Original:  The partitions, schedule, and floorplan of the tasks are represented by the partitioned sequence triple P- ST (PS,QS,RS), where (PS,QS) is a hybrid nested sequence pair (HNSP) for representing the spatial and temporal partitions, as well as the floorplan, and RS is the partitioned dynamic configu- ration order of the tasks.
Revised:  The partitions, schedule, and floorplan of the tasks are represented by the partitioned sequence triple P- ST (PS,QS,RS), where (PS,QS) is a hybrid nested sequence pair (HNSP) for representing the spatial and temporal partitions, as well as the floorplan, and RS is the partitioned dynamic configuration order of the tasks.
Edit intent: fluency
Original:  The floorplanning and scheduling of task modules can be computed from the partitioned sequence triple P- ST in O(n^2) time.
Revised:  The floorplanning and scheduling of task modules can be computed from the partitioned sequence triple P-ST in O(n^2) time.
Edit intent: fluency
Original:  To integrate the exploration of the scheduling and floorplanning design space, we use a simulated annealing- based search engine and elaborate a perturbation method, where a randomly chosen task module is removed from the partition sequence triple and then inserted back into a proper position selected from all the (n+1)^3 possible combinations of partitions, schedule and floorplan.
Revised:  To integrate the exploration of the scheduling and floorplanning design space, we use a simulated annealing-based search engine and elaborate a perturbation method, where a randomly chosen task module is removed from the partition sequence triple and then inserted back into a proper position selected from all the (n+1)^3 possible combinations of partitions, schedule and floorplan.
Edit intent: fluency
Original:  Cloud computing offers a solution to problems of this kind, by supporting the dynamic allocation and release of resources according to need .
Revised:  Cloud computing offers a solution to problems of this kind, by supporting the dynamic allocation and release of resources .
Edit intent: clarity
Original:  We find  that dynamic cache instantiation has the potential to provide substantial cost reductions in some cases, but that this potential is strongly dependent on the object popularity skew .
Revised:  We find that dynamic cache instantiation can provide substantial cost reductions in some cases, but that this potential is strongly dependent on the object popularity skew .
Edit intent: clarity
Original:  We find  that dynamic cache instantiation has the potential to provide substantial cost reductions in some cases, but that this potential is strongly dependent on the object popularity skew .
Revised:  We find that dynamic cache instantiation has the potential to provide substantial cost reductions , that potential reductions strongly dependent on the object popularity skew .
Edit intent: clarity
Original: A block graph is a graph in which every block is a complete graph (clique) .
Revised: A block graph is a graph in which every block is a complete graph .
Edit intent: coherence
Original:  Characterizing nonsingular block graphs, other than trees, is an interesting open problem  .
Revised:  An interesting open problem .
Edit intent: coherence
Original:  In this article, we give some classes of nonsingular and singular block graphs and related conjectures.
Revised:  In this article, we present some classes of nonsingular and singular block graphs and related conjectures.
Edit intent: coherence
Original:  We generalize this model so as to allow zero or partial contact between cells in an open system .
Revised:  We generalize this model so as to allow zero or partial contact between cells .
Edit intent: clarity
Original:  Notably, our approach covers the case where one peer does not have classes, or a noisy record of classes.
Revised:  Notably, our approach covers the case where one peer does not have classes, or a noisy record of classes.
Edit intent: fluency
Original:  In contrast, we find that the nervous system is tuned to temporal properties of mechanosensory signals, like its integral and derivative, that extend over many seconds.
Revised:  In contrast, we find that the behavioral response is tuned to temporal properties of mechanosensory signals, like its integral and derivative, that extend over many seconds.
Edit intent: clarity
Original:  A generalised exponential Euler method, named here as the Mittag-Leffler Euler integrator, is used for the temporal discretization . Spatial discretization by the spectral Galerkin method is then performed.
Revised:  A generalised exponential Euler method, named here as the Mittag-Leffler Euler integrator, is used for the temporal discretization , while the spatial discretization is performed by the spectral Galerkin method is then performed.
Edit intent: coherence
Original:  Multiple spatial dimension is allowed when the noise is of trace class .  Numerical experiments are presented to validate the theory  .
Revised:  Multiple spatial dimension is allowed when the noise is of trace class . Numerical experiments that validate the theory .
Edit intent: clarity
Original:  Multiple spatial dimension is allowed when the noise is of trace class .  Numerical experiments are presented to validate the theory  .
Revised:  Multiple spatial dimension is allowed when the noise is of trace class . Numerical experiments are presented to validate the theory are presented .
Edit intent: clarity
Original:  We describe recent work involving such networks confined to a finite region of space , considering effects due to the geometry (convex,non-convex, and fractal), node distribution, distance-dependent link probability, mobility, directivity and interference.
Revised:  We describe recent work involving such networks , considering effects due to the geometry (convex,non-convex, and fractal), node distribution, distance-dependent link probability, mobility, directivity and interference.
Edit intent: clarity
Original:  The problems of finding the minimum size of a k-dominating, resp. total k-dominating set, in a given graph, are referred to as k-domination, resp. total k-domination.
Revised:  The problems of finding the minimum size of a k-dominating, respectively total k-dominating set, in a given graph, are referred to as k-domination, resp. total k-domination.
Edit intent: clarity
Original:  The problems of finding the minimum size of a k-dominating, resp. total k-dominating set, in a given graph, are referred to as k-domination, resp. total k-domination.
Revised:  The problems of finding the minimum size of a k-dominating, resp. total k-dominating set, in a given graph, are referred to as k-domination, respectively total k-domination.
Edit intent: clarity
Original:  On the other hand, it follows from recent work by Kang et al.  (2017) that these two families of problems are solvable in time O(|V(G)|^{6k+4}) in the class of interval graphs.
Revised:  On the other hand, it follows from recent work of Kang et al. (2017) that these two families of problems are solvable in time O(|V(G)|^{6k+4}) in the class of interval graphs.
Edit intent: fluency
Original:  On the other hand, it follows from recent work by Kang et al.  (2017) that these two families of problems are solvable in time O(|V(G)|^{6k+4}) in the class of interval graphs.
Revised:  On the other hand, it follows from recent work by Kang et al. ~ (2017) that these two families of problems are solvable in time O(|V(G)|^{6k+4}) in the class of interval graphs.
Edit intent: fluency
Original:  In this work, we develop faster algorithms for k-domination and total k-domination in the class of proper interval graphs .
Revised:  We develop faster algorithms for k-domination and total k-domination in the class of proper interval graphs .
Edit intent: clarity
Original:  The algorithms run in time O(|V(G)|^{3k}) for each fixed k%DIFDELCMD < \ge %%% 1 and are also applicable to the weighted case.
Revised:  The algorithms run in time O(|V(G)|^{3k}) %DIFDELCMD < \ge %%% 1 and are also applicable to the weighted case.
Edit intent: clarity
Original:  The algorithms run in time O(|V(G)|^{3k}) for each fixed k%DIFDELCMD < \ge %%% 1 and are also applicable to the weighted case.
Revised:  The algorithms run in time O(|V(G)|^{3k}) for each fixed k%DIFDELCMD < \ge %%% . The algorithms are also applicable to the weighted case.
Edit intent: coherence
Original: The sinoatrial-node (SAN) is a complex heterogeneous network that generates a stable rhythm in healthy hearts, yet a general mechanistic explanation for when and how these networks remain stable is lacking.
Revised: The sinoatrial-node (SAN) is a complex heterogeneous tissue that generates a stable rhythm in healthy hearts, yet a general mechanistic explanation for when and how these networks remain stable is lacking.
Edit intent: clarity
Original: The sinoatrial-node (SAN) is a complex heterogeneous network that generates a stable rhythm in healthy hearts, yet a general mechanistic explanation for when and how these networks remain stable is lacking.
Revised: The sinoatrial-node (SAN) is a complex heterogeneous network that generates a stable rhythm in healthy hearts, yet a general mechanistic explanation for when and how this tissue remains stable is lacking.
Edit intent: clarity
Original:  Although computational and theoretical analyses could elucidate this phenomena, such methods have rarely been used in realistic (large-dimensional) gap-junction coupled heterogeneous pacemaker cell models.
Revised:  Although computational and theoretical analyses could elucidate these phenomena, such methods have rarely been used in realistic (large-dimensional) gap-junction coupled heterogeneous pacemaker cell models.
Edit intent: fluency
Original:  Moreover, the phase reduced models accurately predicts key properties of the tissue electrical dynamics, including wave frequencies when synchronization occurs, and wave propagation direction in a variety of network models.
Revised:  Moreover, the phase reduced models accurately predict key properties of the tissue electrical dynamics, including wave frequencies when synchronization occurs, and wave propagation direction in a variety of network models.
Edit intent: fluency
Original:   Thus, we demonstrate that phase reduced oscillator models applied to realistic pacemaker networks provide novel insights into the spatial-temporal dynamics of cardiac pacemaker activity.
Revised:  Thus, we demonstrate that phase reduced oscillator models applied to realistic pacemaker tissue is a useful tool for investigating the spatial-temporal dynamics of cardiac pacemaker activity.
Edit intent: clarity
Original:  Although computational and theoretical analyses could elucidate these phenomena, such methods have rarely been used in realistic (large-dimensional) gap-junction coupled heterogeneous pacemaker cell models.
Revised:  Although computational and theoretical analyses could elucidate these phenomena, such methods have rarely been used in realistic (large-dimensional) gap-junction coupled heterogeneous pacemaker tissue models.
Edit intent: clarity
Original:  In this study, we adapt a recent model of pacemaker cells (Severi et al. , 2012), incorporating biophysical representations of ion channel and intracellular calcium dynamics, to capture physiological features of a heterogeneous population of pacemaker cells ;
Revised:  In this study, we adapt a recent model of pacemaker cells (Severi et al. 2012), incorporating biophysical representations of ion channel and intracellular calcium dynamics, to capture physiological features of a heterogeneous population of pacemaker cells ;
Edit intent: fluency
Original:  In this study, we adapt a recent model of pacemaker cells (Severi et al. , 2012), incorporating biophysical representations of ion channel and intracellular calcium dynamics, to capture physiological features of a heterogeneous population of pacemaker cells ;
Revised:  In this study, we adapt a recent model of pacemaker cells (Severi et al. , 2012), incorporating biophysical representations of ion channel and intracellular calcium dynamics, to capture physiological features of a heterogeneous population of pacemaker cells ,
Edit intent: fluency
Original:  Combined with results of Borodin, Kostochka and Toft (Discrete Mathematics, 2000), Yang and Yuan (Discrete Mathematics, 2006) and Wu, Yuan and Zhao (\emph{Journal of Mathematical Study}, 1996), it also completely settles the complexity of deciding whether a graph with bounded maximum degree can be partitioned into two subgraphs of prescribed degeneracy.
Revised:  Combined with results of Borodin, Kostochka and Toft (Discrete Mathematics, 2000), Yang and Yuan (Discrete Mathematics, 2006) and Wu, Yuan and Zhao (\emph{Journal of Mathematical Study}, 1996), it also settles the complexity of deciding whether a graph with bounded maximum degree can be partitioned into two subgraphs of prescribed degeneracy.
Edit intent: clarity
Original:  We study the population dynamics of spreading cells, investigating the characteristic processes involved in cell response to the substrate.
Revised:  Here we study the population dynamics of spreading cells, investigating the characteristic processes involved in cell response to the substrate.
Edit intent: style
Original:  We discuss how this local information can be used to gain various insights about the clusters including varying relative cluster densities and indication of local strength in different regions of a cluster .
Revised:  We discuss how this local information can be used to gain various insights about the clusters including varying relative cluster densities and local cluster strength in different regions of a cluster .
Edit intent: clarity
Original:  The efficacy of EAP/SHAPE is shown by applying it to various synthetic and real world benchmark datasets.
Revised:  The efficacy of EAP/SHAPE is shown by applying it to various synthetic and real world datasets.
Edit intent: clarity
Original: We consider the analysis of spectral clustering algorithms for community detection under a  stochastic block model (SBM). A general spectral clustering algorithm consists of three steps: (1) regularization of an appropriate adjacency or Laplacian matrix (2) a form of spectral truncation and (3) a k-means type algorithm in the reduced spectral domain.
Revised: We consider spectral clustering algorithms for community detection under a stochastic block model (SBM). A general spectral clustering algorithm consists of three steps: (1) regularization of an appropriate adjacency or Laplacian matrix (2) a form of spectral truncation and (3) a k-means type algorithm in the reduced spectral domain.
Edit intent: clarity
Original: We consider the analysis of spectral clustering algorithms for community detection under a  stochastic block model (SBM). A general spectral clustering algorithm consists of three steps: (1) regularization of an appropriate adjacency or Laplacian matrix (2) a form of spectral truncation and (3) a k-means type algorithm in the reduced spectral domain.
Revised: We consider the analysis of spectral clustering algorithms for community detection under a stochastic block model (SBM). A modern spectral clustering algorithm consists of three steps: (1) regularization of an appropriate adjacency or Laplacian matrix (2) a form of spectral truncation and (3) a k-means type algorithm in the reduced spectral domain.
Edit intent: clarity
Original:  We show how the variations in the spectral truncation step reflects in the consistency results under a general SBM.
Revised:  We show how the variations in the spectral truncation step and show how this variation changes the nature of the misclassification rate in a general SBM.
Edit intent: clarity
Original: Given a first order autonomous algebraic ordinary differential equation, we present a method to compute all formal series solutions .
Revised: Given a first-order autonomous algebraic ordinary differential equation, we present a method to compute all formal series solutions .
Edit intent: fluency
Original:  Furthermore, when the ground field is the field of the complex numbers,  the computed formal power series solutions are indeed convergent in suitable neighborhoods.
Revised:  Furthermore, when the ground field is the field of the complex numbers, we prove that the computed formal power series solutions are indeed convergent in suitable neighborhoods.
Edit intent: clarity
Original:  Furthermore, when the ground field is the field of the complex numbers,  the computed formal power series solutions are indeed convergent in suitable neighborhoods.
Revised:  Furthermore, when the ground field is the field of the complex numbers, the computed formal power series solutions are all convergent in suitable neighborhoods.
Edit intent: clarity
Original:  Here, we propose an inference procedure for this goal based on the kinetic Ising model.
Revised:  Here, we propose a systematic procedure for pre- and post-processing generic point process data in an objective manner, to handle data in the framework of a binary simple statistical model, the Ising or generalized McCulloch--Pitts model.
Edit intent: clarity
Original:  Applications to data from artificial andin vitro neuronal networks show that the proposed procedure performs fairly well when identifying relevant couplings, including the discrimination of their signs, with low computational cost.
Revised:  Applications to data from artificial and neuronal networks show that the proposed procedure performs fairly well when identifying relevant couplings, including the discrimination of their signs, with low computational cost.
Edit intent: clarity
Original:  Applications to data from artificial andin vitro neuronal networks show that the proposed procedure performs fairly well when identifying relevant couplings, including the discrimination of their signs, with low computational cost.
Revised:  Applications to data from artificial andin vitro neuronal networks show that the proposed procedure identifies the presence/absence of synaptic couplings fairly well including their signs, with low computational cost.
Edit intent: clarity
Original: Contrast enhancement(CE) forensics has always been attracted widely attention on image forensic community.
Revised: Contrast enhancement(CE) forensics has always been of concern to image forensics community.
Edit intent: clarity
Original:  It can provide an effective rule for recovering image history and identifying and locating tampered images.
Revised:  It can provide an effective rule for recovering image history and identifying tampered images.
Edit intent: clarity
Original:  Although , a number of algorithms have been proposed, the robustness of CE forensics technique for common pre/post processings is not satisfactory.
Revised:  Although a number of algorithms have been proposed, the robustness of CE forensics technique for common pre/post processings is not satisfactory.
Edit intent: fluency
Original:  Although , a number of algorithms have been proposed, the robustness of CE forensics technique for common pre/post processings is not satisfactory.
Revised:  Although , a number of algorithms have been proposed, the robustness of CE forensics techniques for common pre/post processings is not satisfactory.
Edit intent: fluency
Original:  To deal with it , in this letter , we first take the theoretical analysis for the robustness and stability of feature space in pixel and histogram domain .
Revised:  To deal with it , in this letter we first present a theoretical analysis of the robustness and stability of feature space in pixel and histogram domain .
Edit intent: clarity
Original:  To deal with it , in this letter , we first take the theoretical analysis for the robustness and stability of feature space in pixel and histogram domain .
Revised:  To deal with it , in this letter , we first take the theoretical analysis for the robustness and stability of feature space in pixel and histogram domains .
Edit intent: fluency
Original:  Then, two kinds of end-to-end methods based on convolutional neural networks : P-CNN, H-CNN , are proposed to achieve robust CE forensics when JPEG compression and  histogram-based anti-forensics attack is applied as an pre/post processing, respectively.
Revised:  Then, two kinds of end-to-end methods based on convolutional neural networks ( P-CNN, H-CNN , are proposed to achieve robust CE forensics when JPEG compression and histogram-based anti-forensics attack is applied as an pre/post processing, respectively.
Edit intent: fluency
Original:  Then, two kinds of end-to-end methods based on convolutional neural networks : P-CNN, H-CNN , are proposed to achieve robust CE forensics when JPEG compression and  histogram-based anti-forensics attack is applied as an pre/post processing, respectively.
Revised:  Then, two kinds of end-to-end methods based on convolutional neural networks : P-CNN, H-CNN ) are proposed to achieve robust CE forensics when JPEG compression and histogram-based anti-forensics attack is applied as an pre/post processing, respectively.
Edit intent: fluency
Original:  Then, two kinds of end-to-end methods based on convolutional neural networks : P-CNN, H-CNN , are proposed to achieve robust CE forensics when JPEG compression and  histogram-based anti-forensics attack is applied as an pre/post processing, respectively.
Revised:  Then, two kinds of end-to-end methods based on convolutional neural networks : P-CNN, H-CNN , are proposed to achieve robust CE forensics when JPEG compression and the histogram-based anti-forensics attack is applied as an pre/post processing, respectively.
Edit intent: fluency