wanyu/IteraTeR_v2 huggingface dataset:
Original: Networking companies, especially the ones with the biggest market shares, tend to offer end to end solutions for their customers, with large discounts, that it would sound irrational to decline such offers, helping contractors make larger profits, leaving clients more fragile to future uncertainties, and rubbing the client from the leverage of optionality.
Revised: Networking companies, especially the ones with the biggest market shares, tend to offer end to end solutions for their customers, with large discounts, that it would sound irrational to decline such offers, helping contractors make larger profits, leaving clients more fragile to future uncertainties, and robbing the client from the leverage of optionality.
Edit intent: fluency
Original:  Based on a few observations, the method is learned and tailored to discriminate the various important plane regions a diagram is set into.
Revised:  Based on a few observations, the method is tailored to efficiently discriminate important plane regions a diagram is set into.
Edit intent: clarity
Original:  Relying on optimal measure quantisation results the method is tailored to efficiently discriminate important plane regions where meaningful differences arise.
Revised:  The algorithm is simple and efficiently discriminates important space regions where meaningful differences arise.
Edit intent: clarity
Original:  The proposed methodology comes with only high level tuning parameters such as the total measure encoding budget , and we provide a completely open access software.
Revised:  The proposed methodology comes with a single high level tuning parameters such as the total measure encoding budget , and we provide a completely open access software.
Edit intent: clarity
Original:  The proposed methodology comes with only high level tuning parameters such as the total measure encoding budget , and we provide a completely open access software.
Revised:  The proposed methodology comes with only high level tuning parameter: the total measure encoding budget , and we provide a completely open access software.
Edit intent: clarity
Original:  The proposed methodology comes with only high level tuning parameters such as the total measure encoding budget , and we provide a completely open access software.
Revised:  The proposed methodology comes with only high level tuning parameters such as the total measure encoding budget . We provide a completely open access software.
Edit intent: coherence
Original: This work presents a multilevel approach to large-scale topology optimization accounting for linearized buckling criteria.
Revised: This work presents a multilevel approach to large--scale topology optimization accounting for linearized buckling criteria.
Edit intent: fluency
Original:  Examples of 2D and 3D structures , discretized by up to some millions of degrees of freedom in Matlab, are presented to show the effectiveness of the proposed method.
Revised:  Examples of 2D and 3D structures discretized by up to some millions of degrees of freedom in Matlab, are presented to show the effectiveness of the proposed method.
Edit intent: fluency
Original:  Examples of 2D and 3D structures , discretized by up to some millions of degrees of freedom in Matlab, are presented to show the effectiveness of the proposed method.
Revised:  Examples of 2D and 3D structures , discretized by up to some millions of degrees of freedom are solved in Matlab to show the effectiveness of the proposed method.
Edit intent: clarity
Original:  Finally, a post-processing procedure is suggested in order to reinforce the optimized design against local buckling.
Revised:  Finally, a post--processing procedure is suggested in order to reinforce the optimized design against local buckling.
Edit intent: fluency
Original: Deep neural networks (DNNs) are known for extracting good representations from a large amount of data.
Revised: Deep neural networks (DNNs) are known for extracting useful information from large amounts of data.
Edit intent: clarity
Original:  However, the representations learned in DNNs are typically hard to interpret, especially the ones learned in dense layers.
Revised:  However, the representations learned in DNNs are typically hard to interpret, especially in dense layers.
Edit intent: clarity
Original:  One crucial issue  is that neurons within each layer of DNNs are conditionally independent with each other, which makes the co-training and analysis of neurons at higher modularity difficult.
Revised:  One crucial issue is that neurons in the same layer of DNNs are conditionally independent with each other, which makes the co-training and analysis of neurons at higher modularity difficult.
Edit intent: clarity
Original:  One crucial issue  is that neurons within each layer of DNNs are conditionally independent with each other, which makes the co-training and analysis of neurons at higher modularity difficult.
Revised:  One crucial issue is that neurons within each layer of DNNs are conditionally independent of each other, which makes the co-training and analysis of neurons at higher modularity difficult.
Edit intent: fluency
Original:  One crucial issue  is that neurons within each layer of DNNs are conditionally independent with each other, which makes the co-training and analysis of neurons at higher modularity difficult.
Revised:  One crucial issue is that neurons within each layer of DNNs are conditionally independent with each other, which makes co-training and analysis of neurons at higher modularity difficult.
Edit intent: fluency
Original:  One crucial issue  is that neurons within each layer of DNNs are conditionally independent with each other, which makes the co-training and analysis of neurons at higher modularity difficult.
Revised:  One crucial issue is that neurons within each layer of DNNs are conditionally independent with each other, which makes the co-training and emergence of higher modularity difficult.
Edit intent: clarity
Original:  In contrast , the dependency patterns of biological neurons in the human brain are largely different from those of DNNs. Neuronal assembly describes such neuron dependencies that could be found among a group of biological neurons as having strong internal synaptic interactions , potentially high semantical correlations that are deemed to facilitate the memorization process.
Revised:  In contrast to DNNs, biological neurons in the human brain are largely different from those of DNNs. Neuronal assembly describes such neuron dependencies that could be found among a group of biological neurons as having strong internal synaptic interactions , potentially high semantical correlations that are deemed to facilitate the memorization process.
Edit intent: clarity
Original:  Moreover, BEAN further results in sparse and structured connectivity and parameter sharing among neurons, which substantially improves the efficiency and generalizability of the model  .
Revised:  Moreover, our few-shot learning experiments demonstrate that BEAN could also enhance the generalizability of the model .
Edit intent: clarity
Original: In this paper we provide explicit upper and lower bounds on the L^2 n-widths, i.e., the best constants in L^2 approximation.
Revised: In this paper we provide explicit upper and lower bounds on certain L^2 n-widths, i.e., the best constants in L^2 approximation.
Edit intent: clarity
Original: In this paper we provide explicit upper and lower bounds on the L^2 n-widths, i.e., the best constants in L^2 approximation.
Revised: In this paper we provide explicit upper and lower bounds on the L^2 n-widths, i.e., best constants in L^2 approximation.
Edit intent: fluency
Original:  Recent years have witnessed the quick growth of a research field called differentiable programming, the aim of which is to express computational graphs more synthetically and modularly by resorting to actual programming languages endowed with flow control operators and higher-order combinators, such as map and fold.
Revised:  Recent years have witnessed the quick growth of a research field called differentiable programming, the aim of which is to express computational graphs more synthetically and modularly by resorting to actual programming languages endowed with control flow operators and higher-order combinators, such as map and fold.
Edit intent: fluency
Original:  In the past years new tools specifically designed to aid the measurement of behavior in laboratories have come to fruition.
Revised:  In the past years powerful tools specifically designed to aid the measurement of behavior in laboratories have come to fruition.
Edit intent: clarity
Original:  In the past years new tools specifically designed to aid the measurement of behavior in laboratories have come to fruition.
Revised:  In the past years new tools specifically designed to aid the measurement of behavior have come to fruition.
Edit intent: clarity
Original:  We envision that the fast-paced development of new deep learning tools will rapidly change the landscape of realizable real-world neuroscience experiments .
Revised:  We envision that the fast-paced development of new deep learning tools will rapidly change the landscape of realizable real-world neuroscience .
Edit intent: clarity
Original:  DCG strikes a flexible trade-off between representational capacity and generalization by factorizing the joint value function of all agents according to a coordination graph into payoffs between pairs of agents.
Revised:  DCG strikes a flexible trade-off between representational capacity and generalization by factoring the joint value function of all agents according to a coordination graph into payoffs between pairs of agents.
Edit intent: fluency
Original:  Payoff functions are approximated with deep neural networks and parameter sharing improves generalization over the state-action space .
Revised:  Payoff functions are approximated with deep neural networks that employ parameter sharing and low-rank approximations to significantly improve sample efficiency .
Edit intent: clarity
Original:  We show that DCG can solve challenging predator-prey tasks that are vulnerable to the relative overgeneralization pathology and in which all other known value factorization approaches fail .
Revised:  We show that DCG can solve predator-prey tasks that are vulnerable to the relative overgeneralization pathology and in which all other known value factorization approaches fail .
Edit intent: clarity
Original:  We show that DCG can solve challenging predator-prey tasks that are vulnerable to the relative overgeneralization pathology and in which all other known value factorization approaches fail .
Revised:  We show that DCG can solve challenging predator-prey tasks that highlight the relative overgeneralization pathology and in which all other known value factorization approaches fail .
Edit intent: clarity
Original:  The key finding is that if the measurements are polluted with Gaussian noise, then the error due to the noise grows at most linearly with the standard deviation with high probability under certain conditions.
Revised:  The key finding is that if the measurements are polluted with Gaussian noise, then the error due to noise grows at most linearly with the standard deviation with high probability under certain conditions.
Edit intent: fluency
Original:  The analysis gives insights on how to make the Loewner approach robust against noise via linear transformations and judicious selections of measurements.
Revised:  The analysis gives insights into making the Loewner approach robust against noise via linear transformations and judicious selections of measurements.
Edit intent: fluency
Original: When building a global brand of any kind---a political actor, clothing style, or belief system---developing widespread awareness is a primary goal.
Revised: When building a global brand of any kind -- a political actor, clothing style, or belief system---developing widespread awareness is a primary goal.
Edit intent: fluency
Original: When building a global brand of any kind---a political actor, clothing style, or belief system---developing widespread awareness is a primary goal.
Revised: When building a global brand of any kind---a political actor, clothing style, or belief system -- developing widespread awareness is a primary goal.
Edit intent: fluency
Original:  Short of knowing any of the stories or products of a brand, being talked about in whatever fashion---raw fame---is , as Oscar Wilde would have it, better than not being talked about at all.
Revised:  Short of knowing any of the stories or products of a brand, being talked about in whatever fashion -- raw fame -- is , as Oscar Wilde would have it, better than not being talked about at all.
Edit intent: fluency
Original:  Here, we measure, examine, and contrast the day-to-day raw fame dynamics on Twitter for U.S. Presidents and major U.S. Presidential candidates from 2008 to 2019 : Barack Obama, John McCain, Mitt Romney, Hillary Clinton, and Donald Trump .
Revised:  Here, we measure, examine, and contrast the day-to-day raw fame dynamics on Twitter for US Presidents and major U.S. Presidential candidates from 2008 to 2019 : Barack Obama, John McCain, Mitt Romney, Hillary Clinton, and Donald Trump .
Edit intent: fluency
Original:  Here, we measure, examine, and contrast the day-to-day raw fame dynamics on Twitter for U.S. Presidents and major U.S. Presidential candidates from 2008 to 2019 : Barack Obama, John McCain, Mitt Romney, Hillary Clinton, and Donald Trump .
Revised:  Here, we measure, examine, and contrast the day-to-day raw fame dynamics on Twitter for U.S. Presidents and major US Presidential candidates from 2008 to 2019 : Barack Obama, John McCain, Mitt Romney, Hillary Clinton, and Donald Trump .
Edit intent: fluency
Original:  Finally, we track how  one other entity has more sustained ultrafame than `trump' on Twitter: The Korean pop boy band BTS.
Revised:  Finally, we track how only one other entity has more sustained ultrafame than `trump' on Twitter: The Korean pop boy band BTS.
Edit intent: fluency
Original:  Finally, we track how  one other entity has more sustained ultrafame than `trump' on Twitter: The Korean pop boy band BTS.
Revised:  Finally, we track how one other entity has more sustained ultrafame than `trump' on Twitter: The K-pop (Korean pop) band BTS.
Edit intent: clarity
Original: We study the complexity of approximating the multimarginal optimal transport ( OT) problem , a generalization of the classical optimal transport distance, considered here between m discrete probability distributions supported each on n support points.
Revised: We study the complexity of approximating the multimarginal optimal transport ( MOT) distance , a generalization of the classical optimal transport distance, considered here between m discrete probability distributions supported each on n support points.
Edit intent: clarity
Original:  This implies that many of the combinatorial algorithmsdeveloped for classical OT are not applicable to multimarginal OT, and therefore the standard interior-point algorithm bounds result in an intractable complexity bound of%DIFDELCMD < \mathcal{O}%%%  (n^{3m}).
Revised:  This implies that many of the combinatorial algorithmsdeveloped for classical OT are not applicable to multimarginal OT, and therefore the standard interior-point %DIFDELCMD < \mathcal{O}%%% (n^{3m}).
Edit intent: clarity
Original:  Second, we propose and analyze two simple algorithms for approximating the multimarginal OT problem.
Revised:  We then propose two simple and algorithms for approximating the multimarginal OT problem.
Edit intent: clarity
Original:  The first algorithm, which we refer to as multimarginal Sinkhorn, improves upon previous multimarginal generalizations of the celebrated  Sinkhorn algorithm.
Revised:  The first algorithm, which we refer to as multimarginal Sinkhorn Sinkhorn algorithm.
Edit intent: clarity
Original:  We show that it achieves a near-linear time complexity bound of %DIFDELCMD < \mathcal{O}%%% (m^3n^m / \varepsilon^2 ) for a tolerance \varepsilon \in (0, 1).
Revised:  We show that it achieves a complexity bound of %DIFDELCMD < \mathcal{O}%%% (m^3n^m / \varepsilon^2 ) for a tolerance \varepsilon \in (0, 1).
Edit intent: clarity
Original:  This \textit{  matches the best known complexity bound for the Sinkhorn algorithm when m = 2 for approximating the classical OT distance.
Revised:  This \textit{ matches the best known complexity bound for the Sinkhorn algorithm in the classical OT distance.
Edit intent: clarity
Original:  This \textit{  matches the best known complexity bound for the Sinkhorn algorithm when m = 2 for approximating the classical OT distance.
Revised:  This \textit{ matches the best known complexity bound for the Sinkhorn algorithm when m = 2 for approximating the classical OT setting when m = 2.
Edit intent: clarity
Original:  The second algorithm, which we refer to as multimarginal Randkhorn, accelerates the first algorithm by incorporating a randomized \textit{  estimate sequence and achieves a complexity bound of%DIFDELCMD < \widetilde{\mathcal{O}}%%% (m^{8/3 n^{m+1/3}/\varepsilon} \tilde{O}\varepsilon^{-4/3}} ).
Revised:  The second algorithm, which we refer to as \textit{ estimate sequence and achieves a complexity bound of%DIFDELCMD < \widetilde{\mathcal{O}}%%% (m^{8/3 n^{m+1/3}/\varepsilon} \tilde{O}\varepsilon^{-4/3}} ).
Edit intent: clarity
Original:  The second algorithm, which we refer to as multimarginal Randkhorn, accelerates the first algorithm by incorporating a randomized \textit{  estimate sequence and achieves a complexity bound of%DIFDELCMD < \widetilde{\mathcal{O}}%%% (m^{8/3 n^{m+1/3}/\varepsilon} \tilde{O}\varepsilon^{-4/3}} ).
Revised:  The second algorithm, which we refer to as multimarginal Randkhorn, accelerates the first algorithm by incorporating a randomized \textit{ estimate sequence and %DIFDELCMD < \widetilde{\mathcal{O}}%%% (m^{8/3 n^{m+1/3}/\varepsilon} \tilde{O}\varepsilon^{-4/3}} ).
Edit intent: clarity
Original:  The second algorithm, which we refer to as multimarginal Randkhorn, accelerates the first algorithm by incorporating a randomized \textit{  estimate sequence and achieves a complexity bound of%DIFDELCMD < \widetilde{\mathcal{O}}%%% (m^{8/3 n^{m+1/3}/\varepsilon} \tilde{O}\varepsilon^{-4/3}} ).
Revised:  The second algorithm, which we refer to as multimarginal Randkhorn, accelerates the first algorithm by incorporating a randomized \textit{ estimate sequence and achieves a complexity bound of%DIFDELCMD < \widetilde{\mathcal{O}}%%% (m^{8/3 n^{m+1/3}/\varepsilon} the complexity bound is\tilde{O}\varepsilon^{-4/3}} ).
Edit intent: coherence
Original:  This improves on the complexity bound of the first algorithm by 1/\varepsilon and matches the best known complexity bound for the Randkhorn algorithmwhen m=2 for approximating the classical OT distance }\hspace{0pt} in terms of n. Finally, we compare our new algorithms with the commercial LP solver }\textsc{  .
Revised:  This bound is better than that of the first algorithm by 1/\varepsilon and matches the best known complexity bound for the Randkhorn algorithmwhen m=2 for approximating the classical OT distance }\hspace{0pt} in terms of n. Finally, we compare our new algorithms with the commercial LP solver }\textsc{ .
Edit intent: clarity
Original:  This improves on the complexity bound of the first algorithm by 1/\varepsilon and matches the best known complexity bound for the Randkhorn algorithmwhen m=2 for approximating the classical OT distance }\hspace{0pt} in terms of n. Finally, we compare our new algorithms with the commercial LP solver }\textsc{  .
Revised:  This improves on the complexity bound of the first algorithm in terms of 1/\varepsilon and matches the best known complexity bound for the Randkhorn algorithmwhen m=2 for approximating the classical OT distance }\hspace{0pt} in terms of n. Finally, we compare our new algorithms with the commercial LP solver }\textsc{ .
Edit intent: clarity
Original:  Our experimental results showed that NGEMMoutperformed the state-of-art BLAS libraries such as MKL  by an average of 1.4x .
Revised:  We compared NGEMM's performance with the state-of-art BLAS libraries such as MKL by an average of 1.4x .
Edit intent: clarity
Original:  We have applied NGEMM to a number of production services in Microsoft 
Revised:  We have applied NGEMM to a number of production services in Microsoft .
Edit intent: fluency
Original:  While algorithms have been developed for solving (i.e., computing a game-theoretic solution concept such as Nash equilibrium) two-player zero-sum stochastic games, research on algorithms for non-zero-sum and multiplayer stochastic games is very limited.
Revised:  While algorithms have been developed for solving (i.e., computing a game-theoretic solution concept such as Nash equilibrium) two-player zero-sum stochastic games, research on algorithms for non-zero-sum and multiplayer stochastic games is limited.
Edit intent: clarity
Original: Useful models of loop kernel runtimes on out-of-order architectures require an analysis of the the in-core performance behavior of instructions and their dependencies.
Revised: Useful models of loop kernel runtimes on out-of-order architectures require an analysis of the in-core performance behavior of instructions and their dependencies.
Edit intent: fluency
Original:  The approach is shown to avoid high computational costs by using a compact training set and to provide a reduced-order model with guaranteed accuracy over the entire parameter domain.
Revised:  The approach is shown to avoid high computational costs by using a small training set and to provide a reduced-order model with guaranteed accuracy over the entire parameter domain.
Edit intent: clarity
Original: IEEE 802.11bd and 3GPP NR V2X represent the new specifications for the next generation of Vehicle-to-Vehicle (V2V) networks, which will foresee the integration of the millimeter wave band in vehicular operations to address the high data rates and low latencyrequirements of V2V communications .
Revised: IEEE 802.11bd and 3GPP NR V2X represent the new specifications for next generation vehicular networks, exploiting new communication technologies and new spectrum, such as the millimeter wave (mmWave) band, to improve throughput and reduce latency .
Edit intent: clarity
Original:  In this paper, we review the latest standard developments and present an overview of the mmWave-specific challenges that 802.11bd and NR V2X will have to address  .
Revised:  In this paper, we review the latest standard developments and the issues that 802.11bd and NR V2X will have to address .
Edit intent: clarity
Original:  To the best of our knowledge, our work is the first that considers a full-stack  end-to-end approach for the design of  V2V networks, discussing open issues that span from the physical to the higher layers, and reporting the results of an end-to-end performance evaluation that highlight the potentials of mmWaves for V2V communications.
Revised:  To the best of our knowledge, our work is the first that considers a full-stack , end-to-end approach for the design of V2V networks, discussing open issues that span from the physical to the higher layers, and reporting the results of an end-to-end performance evaluation that highlight the potentials of mmWaves for V2V communications.
Edit intent: fluency
Original:  To the best of our knowledge, our work is the first that considers a full-stack  end-to-end approach for the design of  V2V networks, discussing open issues that span from the physical to the higher layers, and reporting the results of an end-to-end performance evaluation that highlight the potentials of mmWaves for V2V communications.
Revised:  To the best of our knowledge, our work is the first that considers a full-stack end-to-end approach for the design of mmWave V2V networks, discussing open issues that span from the physical to the higher layers, and reporting the results of an end-to-end performance evaluation that highlight the potentials of mmWaves for V2V communications.
Edit intent: fluency