wanyu/IteraTeR_v2 huggingface dataset:
Original: Finding the dense regions of a graph and relations among them is a fundamental task in network analysis.
Revised: Finding the dense regions of a graph and relations among them is a fundamental problem in network analysis.
Edit intent: clarity
Original:  In this work , we generalize the iterative h-index computation for any nucleus decomposition and prove convergence bounds  .
Revised:  This work generalizes the iterative h-index computation for any nucleus decomposition and prove convergence bounds .
Edit intent: coherence
Original: A family of sharp target range strategies is presented for portfolio selection problems.
Revised: A novel investment strategy is presented for portfolio selection problems.
Edit intent: clarity
Original: A family of sharp target range strategies is presented for portfolio selection problems.
Revised: A family of sharp target range strategies is presented for portfolio choice problems.
Edit intent: fluency
Original:  This strategy favorably shapes the entire probability distribution of return, as it simultaneously seeks a high expected return, cuts off downside risk, and implicitly caps volatility, skewness and other higher moments of the return distribution .
Revised:  This strategy favorably shapes the entire probability distribution of return, as it simultaneously seeks a desired expected return, cuts off downside risk, and implicitly caps volatility, skewness and other higher moments of the return distribution .
Edit intent: clarity
Original:  This strategy favorably shapes the entire probability distribution of return, as it simultaneously seeks a high expected return, cuts off downside risk, and implicitly caps volatility, skewness and other higher moments of the return distribution .
Revised:  This strategy favorably shapes the entire probability distribution of return, as it simultaneously seeks a high expected return, cuts off downside risk, and implicitly caps volatility, skewness and other higher moments .
Edit intent: clarity
Original:  To illustrate the effectiveness of our new investment strategies , we study a multi-period portfolio selection problem with transaction cost, where the results are generated by the Least-Squares Monte-Carlo algorithm .
Revised:  To illustrate the effectiveness of our investment strategy , we study a multi-period portfolio selection problem with transaction cost, where the results are generated by the Least-Squares Monte-Carlo algorithm .
Edit intent: clarity
Original: A novel investment strategy is presented for portfolio choice problems.
Revised: In this paper, we propose a novel investment strategy is presented for portfolio choice problems.
Edit intent: coherence
Original:  Our proposed strategy maximizes the expected portfolio value within a target range, composed of a conservative lower target representing capital guarantee and a desired upper target representing  investment goal.
Revised:  Our proposed strategy maximizes the expected portfolio value bounded within a targeted range, composed of a conservative lower target representing capital guarantee and a desired upper target representing investment goal.
Edit intent: clarity
Original:  Our proposed strategy maximizes the expected portfolio value within a target range, composed of a conservative lower target representing capital guarantee and a desired upper target representing  investment goal.
Revised:  Our proposed strategy maximizes the expected portfolio value within a target range, composed of a conservative lower target representing a need for capital protection and a desired upper target representing investment goal.
Edit intent: clarity
Original:  Our proposed strategy maximizes the expected portfolio value within a target range, composed of a conservative lower target representing capital guarantee and a desired upper target representing  investment goal.
Revised:  Our proposed strategy maximizes the expected portfolio value within a target range, composed of a conservative lower target representing capital guarantee and a desired upper target representing an investment goal.
Edit intent: fluency
Original:  This strategy favorably shapes the entire probability distribution of return, as it simultaneously seeks a desired expected return, cuts off downside risk, and implicitly caps volatility , skewness and other higher moments.
Revised:  This strategy favorably shapes the entire probability distribution of return, as it simultaneously seeks a desired expected return, cuts off downside risk, and implicitly caps volatility and higher moments.
Edit intent: clarity
Original:  To illustrate the effectiveness of our investment strategy, we study a multi-period portfolio selection problem with transaction cost , and develop a decensored regression approach that improves the classical least squares Monte Carlo algorithm when dealing with truncated and discontinuous payoff functions.
Revised:  To illustrate the effectiveness of this investment strategy, we study a multi-period portfolio selection problem with transaction cost , and develop a decensored regression approach that improves the classical least squares Monte Carlo algorithm when dealing with truncated and discontinuous payoff functions.
Edit intent: fluency
Original:  To illustrate the effectiveness of our investment strategy, we study a multi-period portfolio selection problem with transaction cost , and develop a decensored regression approach that improves the classical least squares Monte Carlo algorithm when dealing with truncated and discontinuous payoff functions.
Revised:  To illustrate the effectiveness of our investment strategy, we study a multi-period portfolio optimization problem with transaction cost , and develop a decensored regression approach that improves the classical least squares Monte Carlo algorithm when dealing with truncated and discontinuous payoff functions.
Edit intent: clarity
Original:  To illustrate the effectiveness of our investment strategy, we study a multi-period portfolio selection problem with transaction cost , and develop a decensored regression approach that improves the classical least squares Monte Carlo algorithm when dealing with truncated and discontinuous payoff functions.
Revised:  To illustrate the effectiveness of our investment strategy, we study a multi-period portfolio selection problem with transaction costs , and develop a decensored regression approach that improves the classical least squares Monte Carlo algorithm when dealing with truncated and discontinuous payoff functions.
Edit intent: fluency
Original:  To illustrate the effectiveness of our investment strategy, we study a multi-period portfolio selection problem with transaction cost , and develop a decensored regression approach that improves the classical least squares Monte Carlo algorithm when dealing with truncated and discontinuous payoff functions.
Revised:  To illustrate the effectiveness of our investment strategy, we study a multi-period portfolio selection problem with transaction cost , and develop a two-stage regression approach that improves the classical least squares Monte Carlo algorithm when dealing with truncated and discontinuous payoff functions.
Edit intent: clarity
Original:  Our numerical tests show that the resulting distribution of portfolio wealth mimics the shape of the objective function, and that the presented strategy dominates the classical utility approachin terms of the mean-variance efficient frontier and the trade-off between return and downside risk .
Revised:  Our numerical tests show that the resulting distribution of portfolio wealth mimics the shape of the objective function, and that the presented strategy dominates the classical utility approachin terms of the mean-variance efficient frontier and the trade-off .
Edit intent: clarity
Original:  This strategy favorably shapes the entire probability distribution of return , as it simultaneously seeks a desired expected return, cuts off downside risk , and implicitly caps volatility and higher moments.
Revised:  This strategy favorably shapes the entire probability distribution of returns , as it simultaneously seeks a desired expected return, cuts off downside risk , and implicitly caps volatility and higher moments.
Edit intent: fluency
Original:  This strategy favorably shapes the entire probability distribution of return , as it simultaneously seeks a desired expected return, cuts off downside risk , and implicitly caps volatility and higher moments.
Revised:  This strategy favorably shapes the entire probability distribution of return , as it simultaneously seeks a desired expected return, cuts off downside risk and implicitly caps volatility and higher moments.
Edit intent: fluency
Original:  To illustrate the effectiveness of this investment strategy, we study a multi-period portfolio optimization problem with transaction costs , and develop a two-stage regression approach that improves the classical least squares Monte Carlo  algorithm when dealing with difficult payoffs  such as highly concave, abruptly changing or discontinuous functions.
Revised:  To illustrate the effectiveness of this investment strategy, we study a multiperiod portfolio optimization problem with transaction costs , and develop a two-stage regression approach that improves the classical least squares Monte Carlo algorithm when dealing with difficult payoffs such as highly concave, abruptly changing or discontinuous functions.
Edit intent: fluency
Original:  To illustrate the effectiveness of this investment strategy, we study a multi-period portfolio optimization problem with transaction costs , and develop a two-stage regression approach that improves the classical least squares Monte Carlo  algorithm when dealing with difficult payoffs  such as highly concave, abruptly changing or discontinuous functions.
Revised:  To illustrate the effectiveness of this investment strategy, we study a multi-period portfolio optimization problem with transaction costs and develop a two-stage regression approach that improves the classical least squares Monte Carlo algorithm when dealing with difficult payoffs such as highly concave, abruptly changing or discontinuous functions.
Edit intent: fluency
Original:  To illustrate the effectiveness of this investment strategy, we study a multi-period portfolio optimization problem with transaction costs , and develop a two-stage regression approach that improves the classical least squares Monte Carlo  algorithm when dealing with difficult payoffs  such as highly concave, abruptly changing or discontinuous functions.
Revised:  To illustrate the effectiveness of this investment strategy, we study a multi-period portfolio optimization problem with transaction costs , and develop a two-stage regression approach that improves the classical least squares Monte Carlo (LSMC) algorithm when dealing with difficult payoffs such as highly concave, abruptly changing or discontinuous functions.
Edit intent: clarity
Original:  To illustrate the effectiveness of this investment strategy, we study a multi-period portfolio optimization problem with transaction costs , and develop a two-stage regression approach that improves the classical least squares Monte Carlo  algorithm when dealing with difficult payoffs  such as highly concave, abruptly changing or discontinuous functions.
Revised:  To illustrate the effectiveness of this investment strategy, we study a multi-period portfolio optimization problem with transaction costs , and develop a two-stage regression approach that improves the classical least squares Monte Carlo algorithm when dealing with difficult payoffs , such as highly concave, abruptly changing or discontinuous functions.
Edit intent: fluency
Original:  Our numerical results show substantial improvements over the classical least squares Monte Carlo algorithm for both the constant relative risk aversion (CRRA) utility approach and the proposed skewed target range strategy (STRS).
Revised:  Our numerical results show substantial improvements over the classical least squares Monte Carlo algorithm for both the constant relative risk-aversion (CRRA) utility approach and the proposed skewed target range strategy (STRS).
Edit intent: fluency
Original:  Compared to the CRRA utility approach, the STRS achieves a similar mean-variance efficient frontier while delivering a better downside risk-return trade-off.
Revised:  When compared with the CRRA utility approach, the STRS achieves a similar mean-variance efficient frontier while delivering a better downside risk-return trade-off.
Edit intent: coherence
Original:  Extensive experiments conducted over three large-scale real datasets indicate the proposed approach outperforms state-of-art methods for item recommendation.
Revised:  Extensive experiments conducted over three large scale real datasets indicate the proposed approach outperforms state-of-art methods for item recommendation.
Edit intent: fluency
Original:  Extensive experiments conducted over three large-scale real datasets indicate the proposed approach outperforms state-of-art methods for item recommendation.
Revised:  Extensive experiments conducted over three large-scale real datasets indicate the proposed approach outperforms the compared methods for item recommendation.
Edit intent: clarity
Original:  The key common bottleneck in most stencil codes is data movement, and other research has shown that improving data locality through optimisations that schedule across loops do particularly well.
Revised:  The key common bottleneck in most stencil codes is data movement, and prior research has shown that improving data locality through optimisations that schedule across loops do particularly well.
Edit intent: clarity
Original: For a rumor spreading protocol, the spread time is defined as the first time that everyone learns the rumor .
Revised: For a rumour spreading protocol, the spread time is defined as the first time that everyone learns the rumor .
Edit intent: fluency
Original: For a rumor spreading protocol, the spread time is defined as the first time that everyone learns the rumor .
Revised: For a rumor spreading protocol, the spread time is defined as the first time that everyone learns the rumour .
Edit intent: fluency
Original:  We compare the synchronous push \&pull rumor spreading protocol with its asynchronous variant, and show that for any n-vertex graph and any starting vertex, the ratio between their expected spread times is bounded by O \left({n} \log n{\log^{2/3} n}} \right) ^{1/3 . This improves the O(\sqrt n) upper bound of Giakkoupis, Nazari, and Woelfel (in Proceedings of ACM Symposium on Principles of Distributed Computing, 2016).
Revised:  We compare the synchronous push pull rumour spreading protocol with its asynchronous variant, and show that for any n-vertex graph and any starting vertex, the ratio between their expected spread times is bounded by O \left({n} \log n{\log^{2/3} n}} \right) ^{1/3 . This improves the O(\sqrt n) upper bound of Giakkoupis, Nazari, and Woelfel (in Proceedings of ACM Symposium on Principles of Distributed Computing, 2016).
Edit intent: clarity
Original:  We compare the synchronous push \&pull rumor spreading protocol with its asynchronous variant, and show that for any n-vertex graph and any starting vertex, the ratio between their expected spread times is bounded by O \left({n} \log n{\log^{2/3} n}} \right) ^{1/3 . This improves the O(\sqrt n) upper bound of Giakkoupis, Nazari, and Woelfel (in Proceedings of ACM Symposium on Principles of Distributed Computing, 2016).
Revised:  We compare the synchronous push \&pull rumor spreading protocol with its asynchronous variant, and show that for any n-vertex graph and any starting vertex, the ratio between their expected spread times is bounded by O \left({n} \log n{\log^{2/3} n}} \right) . This improves the O(\sqrt n) upper bound of Giakkoupis, Nazari, and Woelfel (in Proceedings of ACM Symposium on Principles of Distributed Computing, 2016).
Edit intent: coherence
Original:  Our bound is tight up to a factor of O(\log ^{2/3 n), as illustrated by the string of diamonds graph  and n^{\beta} in expectation, then 0\leq\alpha \leq 1 and \alpha \leq \beta \leq 1{3} + 2{3} \alpha;
Revised:  Our bound is tight up to a factor of O(\log n), as illustrated by the string of diamonds graph and n^{\beta} in expectation, then 0\leq\alpha \leq 1 and \alpha \leq \beta \leq 1{3} + 2{3} \alpha;
Edit intent: clarity
Original: Most network studies rely on some observed network , that differs from the underlying network which is obfuscated by sampling errors.
Revised: Most network studies rely on an observed network that differs from the underlying network which is obfuscated by sampling errors.
Edit intent: clarity
Original: Most network studies rely on some observed network , that differs from the underlying network which is obfuscated by sampling errors.
Revised: Most network studies rely on some observed network , that differs from the underlying network which is obfuscated by measurement errors.
Edit intent: clarity
Original:  It is well known that such sampling errors impact network metrics, e.g.: centrality measures.
Revised:  It is well known that such errors can have a severe impact on the reliability of network metrics, e.g.: centrality measures.
Edit intent: clarity
Original:  In order to measure this sensitivity of centrality measures with respect to sampling errors we study the probability, that given two randomly chosen nodes, the more central one in the observed network is also more central in the underlying network.
Revised:  We introduce a metric for the reliability of centrality measures with respect to sampling errors we study the probability, that given two randomly chosen nodes, the more central one in the observed network is also more central in the underlying network.
Edit intent: clarity
Original:  In order to measure this sensitivity of centrality measures with respect to sampling errors we study the probability, that given two randomly chosen nodes, the more central one in the observed network is also more central in the underlying network.
Revised:  In order to measure this sensitivity of centrality measures -- called sensitivity. Given two randomly chosen nodes, the more central one in the observed network is also more central in the underlying network.
Edit intent: clarity
Original:  As this concept relies on the underlying network which is generally not accessible, we present first thoughts on how to approximate this sensitivity, given (i) the observed network and (ii) some assumptions on the underlying error-mechanism (e.g. : the percentage of missing edges or nodes)  .
Revised:  The sensitivity concept relies on the underlying network which is generally not accessible, we present first thoughts on how to approximate this sensitivity, given (i) the observed network and (ii) some assumptions on the underlying error-mechanism (e.g. : the percentage of missing edges or nodes) .
Edit intent: clarity
Original:  As this concept relies on the underlying network which is generally not accessible, we present first thoughts on how to approximate this sensitivity, given (i) the observed network and (ii) some assumptions on the underlying error-mechanism (e.g. : the percentage of missing edges or nodes)  .
Revised:  As this concept relies on the underlying network which is generally not accessible, we present first thoughts on how to approximate this sensitivity, given (i) the observed network and (ii) some assumptions on the underlying error-mechanism (e.g. , the percentage of missing edges or nodes) .
Edit intent: fluency
Original:  Our highly-tuned kernels in combination with the reduced communication requirements allow an improvement in time-to-solution over state-of-the-art simulators by more than an order of magnitude at every scale.
Revised:  Our highly-tuned kernels in combination with the reduced communication requirements allow an improvement in time-to-solution over state-of-the-art simulations by more than an order of magnitude at every scale.
Edit intent: fluency
Original: A fundamental explanandum of the hard problem of consciousness concerns the link between the physical and the phenomenal.
Revised: A suitable solution to the hard problem of consciousness concerns the link between the physical and the phenomenal.
Edit intent: clarity
Original: A fundamental explanandum of the hard problem of consciousness concerns the link between the physical and the phenomenal.
Revised: A fundamental explanandum of the hard problem of consciousness should explain the relation between the physical and the phenomenal.
Edit intent: clarity
Original:  That is to say, given that there are such things as physical processes and conscious experience, what is it about the particular physical processes  (e.g. certain neural processes)
Revised:  Given that there are such things as physical processes and conscious experience, what is it about the particular physical processes (e.g. certain neural processes)
Edit intent: coherence
Original:  That is to say, given that there are such things as physical processes and conscious experience, what is it about the particular physical processes  (e.g. certain neural processes)
Revised:  That is to say, given that there are such things as physical processes and conscious experience, what is it about the particular physical processes from which conscious experience arises (e.g. certain neural processes)
Edit intent: clarity
Original:  that entail instances of conscious experience that accounts for such entailment ? Building on the fundamental premises of property dualism,
Revised:  that accounts for such entailment ? Building on the fundamental premises of property dualism,
Edit intent: clarity
Original:  that entail instances of conscious experience that accounts for such entailment ? Building on the fundamental premises of property dualism,
Revised:  that entail instances of conscious experience that accounts for such phenomenon ? Building on the fundamental premises of property dualism,
Edit intent: clarity
Original:  this paper speculates that certain properties of the particular physical processes that entail instances of conscious experience may obey mathematical laws pursuant to which such properties have magnitudes that are numerically defined at most times (and are thus physical properties at such times ), but have magnitudes that are numerically undefined, or "irreducibly abstract," at other times (and can thus, it is argued, be inferred to be phenomenal properties at such times ).
Revised:  this paper argues that certain properties of the particular physical processes that entail instances of conscious experience may obey mathematical laws pursuant to which such properties have magnitudes that are numerically defined at most times (and are thus physical properties at such times ), but have magnitudes that are numerically undefined, or "irreducibly abstract," at other times (and can thus, it is argued, be inferred to be phenomenal properties at such times ).
Edit intent: clarity
Original:  this paper speculates that certain properties of the particular physical processes that entail instances of conscious experience may obey mathematical laws pursuant to which such properties have magnitudes that are numerically defined at most times (and are thus physical properties at such times ), but have magnitudes that are numerically undefined, or "irreducibly abstract," at other times (and can thus, it is argued, be inferred to be phenomenal properties at such times ).
Revised:  this paper speculates that certain properties of the particular physical processes from which conscious experience arises may obey mathematical laws pursuant to which such properties have magnitudes that are numerically defined at most times (and are thus physical properties at such times ), but have magnitudes that are numerically undefined, or "irreducibly abstract," at other times (and can thus, it is argued, be inferred to be phenomenal properties at such times ).
Edit intent: clarity