wanyu/IteraTeR_v2 huggingface dataset:
Original:  We investigated the behavior of these Bayesian alternatives to mutual information (in exact and asymptotic forms)  on simulated and real data.
Revised:  We investigated the behavior of these Bayesian alternatives (in exact and asymptotic forms) on simulated and real data.
Edit intent: clarity
Original: The row (resp. column) rank profile of a matrix describes the stair-case shape of its row (resp. column) echelon form.
Revised: The row (resp. column) rank profile of a matrix describes the staircase shape of its row (resp. column) echelon form.
Edit intent: fluency
Original:  In an ISSAC'13 paper, we proposed a recursive Gaussian elimination that can compute simulta-neously the row and column rank profiles of a matrix as well as those of all of its leading sub-matrices, in the same time as state of the art Gaussian elimination algorithms.
Revised:  In an ISSAC'13 paper, we proposed a recursive Gaussian elimination that can compute simultaneously the row and column rank profiles of a matrix as well as those of all of its leading sub-matrices, in the same time as state of the art Gaussian elimination algorithms.
Edit intent: fluency
Original:  Therefore, we propose the definition of a new matrix invariant, the rank profile matrix, summa-rizing all information on the row and column rank profiles of all the leading sub-matrices.
Revised:  Therefore, we propose the definition of a new matrix invariant, the rank profile matrix, summarizing all information on the row and column rank profiles of all the leading sub-matrices.
Edit intent: fluency
Original:  We also explore the conditions for a Gaussian elimination algorithm to compute all or part of this invariant, through the correspond-ing PLUQ decomposition.
Revised:  We also explore the conditions for a Gaussian elimination algorithm to compute all or part of this invariant, through the corresponding PLUQ decomposition.
Edit intent: fluency
Original:  As a consequence, we show that the classical iterative CUP decomposition algorithm can actually be adapted to com-pute the rank profile matrix.
Revised:  As a consequence, we show that the classical iterative CUP decomposition algorithm can actually be adapted to compute the rank profile matrix.
Edit intent: fluency
Original:  For computing predictions, however, deterministic hypotheses are used asymmetrically as functions.
Revised:  For computing predictions, however, deterministic hypotheses can be abstracted as functions.
Edit intent: clarity
Original:  We build upon Simon's notion of structural equations in order to  extract the (so-called) causal ordering embedded in a hypothesis structure (set of mathematical equations).
Revised:  We build upon Simon's notion of structural equations in order to efficiently extract the (so-called) causal ordering embedded in a hypothesis structure (set of mathematical equations).
Edit intent: clarity
Original:  We build upon Simon's notion of structural equations in order to  extract the (so-called) causal ordering embedded in a hypothesis structure (set of mathematical equations).
Revised:  We build upon Simon's notion of structural equations in order to extract the (so-called) causal ordering between variables, implicit in a hypothesis structure (set of mathematical equations).
Edit intent: clarity
Original:  We show how to process the hypothesis causal structure effectively through original algorithms for encoding it into a set of functional dependencies (fd's) and then perform causal reasoning in terms of acyclic pseudo-transitive reasoning over fd's.
Revised:  We show how to process the hypothesis predictive structure effectively through original algorithms for encoding it into a set of functional dependencies (fd's) and then perform causal reasoning in terms of acyclic pseudo-transitive reasoning over fd's.
Edit intent: clarity
Original:  We show how to process the hypothesis causal structure effectively through original algorithms for encoding it into a set of functional dependencies (fd's) and then perform causal reasoning in terms of acyclic pseudo-transitive reasoning over fd's.
Revised:  We show how to process the hypothesis causal structure effectively through original algorithms for encoding it into a set of functional dependencies (fd's) and then performing causal reasoning in terms of acyclic pseudo-transitive reasoning over fd's.
Edit intent: fluency
Original:  Like Graphical Models , such a probabilistic database should be normalized so that the uncertainty arisen from competing hypotheses is decomposed into factors and can be recovered with its joint probability distribution by a lossless join.
Revised:  Like Graphical Models , such a probabilistic database should be normalized so that the uncertainty arisen from competing hypotheses is decomposed into factors and propagated properly onto predictive data by recovering its joint probability distribution by a lossless join.
Edit intent: clarity
Original:  Like Graphical Models , such a probabilistic database should be normalized so that the uncertainty arisen from competing hypotheses is decomposed into factors and can be recovered with its joint probability distribution by a lossless join.
Revised:  Like Graphical Models , such a probabilistic database should be normalized so that the uncertainty arisen from competing hypotheses is decomposed into factors and can be recovered with its joint probability distribution through a lossless join.
Edit intent: clarity
Original:  This is motivated in our thesis as a design-theoretic principle for data-driven hypothesis management and predictive analytics.
Revised:  That is motivated as a design-theoretic principle for data-driven hypothesis management and predictive analytics.
Edit intent: clarity
Original:  The challenge is known for  long time, and the subject has been intensively studied.
Revised:  The challenge is known for a long time, and the subject has been intensively studied.
Edit intent: fluency
Original:  To achieve our progress we exploit the correlation between the computations with matrices and polynomials, randomized matrix computations, and complex plane geometry, extend the techniques of the matrix sign iteration , and use the structure of the companion matrix of the input polynomial.
Revised:  In order to achieve our progress we exploit the correlation between the computations with matrices and polynomials, randomized matrix computations, and complex plane geometry, extend the techniques of the matrix sign iteration , and use the structure of the companion matrix of the input polynomial.
Edit intent: coherence
Original:  To achieve our progress we exploit the correlation between the computations with matrices and polynomials, randomized matrix computations, and complex plane geometry, extend the techniques of the matrix sign iteration , and use the structure of the companion matrix of the input polynomial.
Revised:  To achieve our progress we exploit the correlation between the computations with matrices and polynomials, randomized matrix computations, and complex plane geometry, extend the techniques of the matrix sign iterations , and use the structure of the companion matrix of the input polynomial.
Edit intent: fluency
Original:  They are, however, are quite involved and require a high precision of computing when the degree of the input polynomial is large, which causes numerical stability problems.
Revised:  They are, however, quite involved and require a high precision of computing when the degree of the input polynomial is large, which causes numerical stability problems.
Edit intent: fluency
Original:  We observe that these difficulties do not appear at the initial stage of the algorithms, and in our present paper we extend this stage , analyze it, and avoid the cited problems, still achieving the solution at a nearly optimal estimated complexity , provided that some mild initial isolation of the roots of the input polynomial is ensured.
Revised:  We observe that these difficulties do not appear at the initial stages of the algorithms, and in our present paper we extend this stage , analyze it, and avoid the cited problems, still achieving the solution at a nearly optimal estimated complexity , provided that some mild initial isolation of the roots of the input polynomial is ensured.
Edit intent: fluency
Original:  We observe that these difficulties do not appear at the initial stage of the algorithms, and in our present paper we extend this stage , analyze it, and avoid the cited problems, still achieving the solution at a nearly optimal estimated complexity , provided that some mild initial isolation of the roots of the input polynomial is ensured.
Revised:  We observe that these difficulties do not appear at the initial stage of the algorithms, and in our present paper we extend this stage , analyze it, and avoid the cited problems, still achieving the solution within a nearly optimal estimated complexity , provided that some mild initial isolation of the roots of the input polynomial is ensured.
Edit intent: clarity
Original:  We observe that these difficulties do not appear at the initial stage of the algorithms, and in our present paper we extend this stage , analyze it, and avoid the cited problems, still achieving the solution at a nearly optimal estimated complexity , provided that some mild initial isolation of the roots of the input polynomial is ensured.
Revised:  We observe that these difficulties do not appear at the initial stage of the algorithms, and in our present paper we extend this stage , analyze it, and avoid the cited problems, still achieving the solution at a nearly optimal complexity estimates , provided that some mild initial isolation of the roots of the input polynomial is ensured.
Edit intent: clarity
Original:  We observe that these difficulties do not appear at the initial stage of the algorithms, and in our present paper we extend this stage , analyze it, and avoid the cited problems, still achieving the solution at a nearly optimal estimated complexity , provided that some mild initial isolation of the roots of the input polynomial is ensured.
Revised:  We observe that these difficulties do not appear at the initial stage of the algorithms, and in our present paper we extend this stage , analyze it, and avoid the cited problems, still achieving the solution at a nearly optimal estimated complexity , provided that some mild initial isolation of the roots of the input polynomial has been ensured.
Edit intent: clarity
Original:  The resulting algorithms promise to be of  practical value for root-finding and can be extended to the problem of polynomial factorization, which has also interest on its own  .
Revised:  The resulting algorithms promise to be of some practical value for root-finding and can be extended to the problem of polynomial factorization, which has also interest on its own .
Edit intent: clarity
Original:  The resulting algorithms promise to be of  practical value for root-finding and can be extended to the problem of polynomial factorization, which has also interest on its own  .
Revised:  The resulting algorithms promise to be of practical value for root-finding and can be extended to the problem of polynomial factorization, which is of interest on its own .
Edit intent: clarity
Original:  They are, however, quite involved and require a high precision of computing when the degree of the input polynomialis large, which causes numerical stability problems  .
Revised:  They are, however, quite involved and require a high precision of computing that exceeds the degree of the input polynomialis large, which causes numerical stability problems .
Edit intent: clarity
Original:  They are, however, quite involved and require a high precision of computing when the degree of the input polynomialis large, which causes numerical stability problems  .
Revised:  They are, however, quite involved and require a high precision of computing when the degree of the polynomial. This causes numerical stability problems .
Edit intent: clarity
Original:  They are, however, quite involved and require a high precision of computing when the degree of the input polynomialis large, which causes numerical stability problems  .
Revised:  They are, however, quite involved and require a high precision of computing when the degree of the input polynomialis large, which causes numerical stability problems when the degree is large .
Edit intent: clarity
Original:  We observe that these difficulties do not appear at the initial stages of the algorithms, and in our present paper we extend one of these stages, analyze it, and avoid the cited problems, still achieving the solution within a nearly optimal complexity estimates, provided that some mild initial isolation of the roots of the input polynomial has been ensured.
Revised:  We observe , however, that such a difficulty disappears at the initial stages of the algorithms, and in our present paper we extend one of these stages, analyze it, and avoid the cited problems, still achieving the solution within a nearly optimal complexity estimates, provided that some mild initial isolation of the roots of the input polynomial has been ensured.
Edit intent: clarity
Original:  We observe that these difficulties do not appear at the initial stages of the algorithms, and in our present paper we extend one of these stages, analyze it, and avoid the cited problems, still achieving the solution within a nearly optimal complexity estimates, provided that some mild initial isolation of the roots of the input polynomial has been ensured.
Revised:  We observe that these difficulties do not appear at the initial stage of the algorithms, and in our present paper we extend one of these stages, analyze it, and avoid the cited problems, still achieving the solution within a nearly optimal complexity estimates, provided that some mild initial isolation of the roots of the input polynomial has been ensured.
Edit intent: fluency
Original:  We observe that these difficulties do not appear at the initial stages of the algorithms, and in our present paper we extend one of these stages, analyze it, and avoid the cited problems, still achieving the solution within a nearly optimal complexity estimates, provided that some mild initial isolation of the roots of the input polynomial has been ensured.
Revised:  We observe that these difficulties do not appear at the initial stages of the algorithms, and in our present paper we extend this stage to root-finding within a nearly optimal complexity estimates, provided that some mild initial isolation of the roots of the input polynomial has been ensured.
Edit intent: clarity
Original:  The resulting algorithms promise to be of some practical value for  root-finding and can be extended to the problem of polynomial factorization, which is of interest on its own right.
Revised:  The resulting algorithms promise to be of some practical value for polynomial root-finding and can be extended to the problem of polynomial factorization, which is of interest on its own right.
Edit intent: fluency
Original:  The resulting algorithms promise to be of some practical value for  root-finding and can be extended to the problem of polynomial factorization, which is of interest on its own right.
Revised:  The resulting algorithms promise to be of some practical value for root-finding and factorization, the latter task being of interest on its own right.
Edit intent: clarity
Original:  Generalizing results of De Fraysseix and Ossona de Mendez, and Felsner, we establish a correspondence between these labelings and orientations and characterize the set of orientations of a map that correspond to such a Schnyder wood .
Revised:  Generalizing results of De Fraysseix and Ossona de Mendez, and Felsner, we establish a correspondence between these labelings and orientations and characterize the set of orientations of a map that correspond to such a Schnyder labeling .
Edit intent: clarity
Original: Recent advances about the problem of transmission network expansion planning propose the use of robust optimization techniques  , as an alternative to stochastic mathematical programming methods, to make the problem tractable in realistic systems.
Revised: In recent advances in solving the problem of transmission network expansion planning propose the use of robust optimization techniques , as an alternative to stochastic mathematical programming methods, to make the problem tractable in realistic systems.
Edit intent: clarity
Original: Recent advances about the problem of transmission network expansion planning propose the use of robust optimization techniques  , as an alternative to stochastic mathematical programming methods, to make the problem tractable in realistic systems.
Revised: Recent advances about the problem of transmission network expansion planning , the use of robust optimization techniques , as an alternative to stochastic mathematical programming methods, to make the problem tractable in realistic systems.
Edit intent: coherence
Original:  They consider different sources of uncertainty  , mainly related to the capacity and availability of generation facilities and demands, and make use of adaptive robust optimization models.
Revised:  Different sources of uncertainty , mainly related to the capacity and availability of generation facilities and demands, and make use of adaptive robust optimization models.
Edit intent: clarity
Original:  They consider different sources of uncertainty  , mainly related to the capacity and availability of generation facilities and demands, and make use of adaptive robust optimization models.
Revised:  They consider different sources of uncertainty , mainly related to the capacity and availability of generation facilities and demand, and making use of adaptive robust optimization models.
Edit intent: fluency
Original:  The resulting formulations materialize on three-level mixed-integer optimization problems, which are solved using different strategies.
Revised:  The mathematical formulations for these models give rise to three-level mixed-integer optimization problems, which are solved using different strategies.
Edit intent: clarity
Original:  Although it is true that these robust methods are more efficient than their stochastic counterparts, it is also true that solution times for mixed-integer linear programming problems growth exponentially with respect to the size of the problem.
Revised:  Although it is true that these robust methods are more efficient than their stochastic counterparts, it is also correct that solution times for mixed-integer linear programming problems growth exponentially with respect to the size of the problem.
Edit intent: clarity
Original:  Although it is true that these robust methods are more efficient than their stochastic counterparts, it is also true that solution times for mixed-integer linear programming problems growth exponentially with respect to the size of the problem.
Revised:  Although it is true that these robust methods are more efficient than their stochastic counterparts, it is also true that solution times for mixed-integer linear programming problems increase exponentially with respect to the size of the problem.
Edit intent: clarity
Original:  This fact encourage researchers , practitioners and system operators to use computational efficient methods when solving this type of problems.
Revised:  Because of this , practitioners and system operators to use computational efficient methods when solving this type of problems.
Edit intent: coherence
Original:  This fact encourage researchers , practitioners and system operators to use computational efficient methods when solving this type of problems.
Revised:  This fact encourage researchers , practitioners and system operators need to use computationally efficient methods when solving this type of problems.
Edit intent: clarity
Original:  This paper addresses the issue of improving computational performance by taking different features from existing algorithms  .
Revised:  This paper addresses the issue of improving computational performance by taking different features from existing algorithms is addressed .
Edit intent: clarity
Original:  In particular, we replace the lower-level problem by its dual , and solve the resulting bi-level problem using a primal cutting plane algorithm within a decomposition scheme.
Revised:  In particular, we replace the lower-level problem with a dual one , and solve the resulting bi-level problem using a primal cutting plane algorithm within a decomposition scheme.
Edit intent: clarity
Original:  Using this alternative and simple approach, the computing time for solving transmission expansion planning problems reduces drastically.
Revised:  By using this alternative and simple approach, the computing time for solving transmission expansion planning problems reduces drastically.
Edit intent: fluency
Original:  Using this alternative and simple approach, the computing time for solving transmission expansion planning problems reduces drastically.
Revised:  Using this alternative and simple approach, the computing time for solving transmission expansion planning problems has been reduced drastically.
Edit intent: coherence
Original:  Numerical results on an illustrative example, the IEEE-24 and IEEE 118-bus test systems demonstrate that the algorithm is superior in terms of computational performance with respect to existing methods.
Revised:  Numerical results in an illustrative example, the IEEE-24 and IEEE 118-bus test systems demonstrate that the algorithm is superior in terms of computational performance with respect to existing methods.
Edit intent: clarity
Original: We generated short term forecasts for Guinea, Liberia, and Sierra Leone, beginning October 1, 2014, which we have since validated using subsequent data.
Revised: We generated short term forecasts for Guinea, Liberia, and Sierra Leone, which we then validated using subsequent data.
Edit intent: clarity
Original:  By estimating terms for surveillance and interventions , the best-fit models correctly forecasted the qualitative behavior for all three countries, both individually and for all countries combined.
Revised:  By estimating terms for surveillance and interventions , the best-fit models correctly forecasted EVD activity for all three countries, both individually and for all countries combined.
Edit intent: clarity
Original:  In particular, the models correctly forecasted the slow-down and stabilization in Liberia but continued exponential growth in Sierra Leone through October and November 2014.
Revised:  In particular, the models correctly forecasted the slow-down and stabilization in Liberia but continued exponential growth in Sierra Leone through November 2014.
Edit intent: clarity
Original: The 2014-2015 Ebola epidemic in West Africa is the largest ever recorded, with over 27,000 cases and 11,000 deaths as of June 2015.
Revised: The Ebola epidemic in West Africa is the largest ever recorded, with over 27,000 cases and 11,000 deaths as of June 2015.
Edit intent: clarity
Original:  The public health response was challenged by difficulties with disease surveillance (particularly in more remote regions) , which impacted subsequent analysis and decision-making regarding optimal interventions.
Revised:  The public health response was challenged by difficulties with disease surveillance , which impacted subsequent analysis and decision-making regarding optimal interventions.
Edit intent: clarity
Original:  A key feature of the model is that it includes a generalized correction term accounting for factors such as the reporting fraction and fraction of the population at risk (e.g. due to contact patterns, interventions, spatiotemporal spread, pre-existing immunity, asymptomatic cases, etc.).
Revised:  A key feature of the model is that it includes a generalized correction term accounting for factors such as the fraction of cases reported and fraction of the population at risk (e.g. due to contact patterns, interventions, spatiotemporal spread, pre-existing immunity, asymptomatic cases, etc.).
Edit intent: clarity