wanyu/IteraTeR_v2 huggingface dataset:
Original: {\em   Based on some novel insights in geometry, we prove that the complexities of these two problems can be significantly reduced through JL transform .
Revised: {\em Based on some novel insights from the geometry, we prove that the complexities of these two problems can be significantly reduced through JL transform .
Edit intent: clarity
Original: Distributed Constraint Optimization Problems (DCOPs) are an important framework that models coordinated decision-making problem in multi-agent systems with a set of discrete variables.
Revised: Distributed Constraint Optimization Problems (DCOPs) are an important framework for modeling coordinated decision-making problem in multi-agent systems with a set of discrete variables.
Edit intent: fluency
Original: Distributed Constraint Optimization Problems (DCOPs) are an important framework that models coordinated decision-making problem in multi-agent systems with a set of discrete variables.
Revised: Distributed Constraint Optimization Problems (DCOPs) are an important framework that models coordinated decision-making problems in multi-agent systems with a set of discrete variables.
Edit intent: fluency
Original:  Later work has extended this to model problems with a set of continuous variables  (F-DCOPs).
Revised:  Later works have extended DCOPs to model problems with a set of continuous variables (F-DCOPs).
Edit intent: clarity
Original:  In this paper, we combine both of these models into the Mixed Integer Functional DCOP (MIF-DCOP) model that can deal with problems regardless of its variables' type.
Revised:  In this paper, we combine both of these frameworks into the Mixed Integer Functional DCOP (MIF-DCOP) model that can deal with problems regardless of its variables' type.
Edit intent: clarity
Original:  In this paper, we combine both of these models into the Mixed Integer Functional DCOP (MIF-DCOP) model that can deal with problems regardless of its variables' type.
Revised:  In this paper, we combine both of these models into the Mixed Integer Functional DCOP (MIF-DCOP) framework that can deal with problems regardless of its variables' type.
Edit intent: clarity
Original:  In this paper, we combine both of these models into the Mixed Integer Functional DCOP (MIF-DCOP) model that can deal with problems regardless of its variables' type.
Revised:  In this paper, we combine both of these models into the Mixed Integer Functional DCOP (MIF-DCOP) model that can deal with problems regardless of their variables' type.
Edit intent: fluency
Original:  We then propose a novel algorithm , called Distributed Parallel Simulated Annealing (DPSA), where agents cooperatively learn the optimal parameter configuration for the algorithm while also solving the given problem using the learned knowledge.
Revised:  We then propose a novel algorithm - Distributed Parallel Simulated Annealing (DPSA), where agents cooperatively learn the optimal parameter configuration for the algorithm while also solving the given problem using the learned knowledge.
Edit intent: clarity
Original:  Finally, we empirically benchmark our approach in DCOP, F-DCOP  and MIF-DCOP settings and show that DPSA produces solutions of significantly better quality than the state-of-the-art non-exact algorithms in their corresponding setting .
Revised:  Finally, we empirically evaluate our approach in DCOP, F-DCOP and MIF-DCOP settings and show that DPSA produces solutions of significantly better quality than the state-of-the-art non-exact algorithms in their corresponding setting .
Edit intent: clarity
Original:  Finally, we empirically benchmark our approach in DCOP, F-DCOP  and MIF-DCOP settings and show that DPSA produces solutions of significantly better quality than the state-of-the-art non-exact algorithms in their corresponding setting .
Revised:  Finally, we empirically benchmark our approach in DCOP, F-DCOP , and MIF-DCOP settings and show that DPSA produces solutions of significantly better quality than the state-of-the-art non-exact algorithms in their corresponding setting .
Edit intent: fluency
Original:  Finally, we empirically benchmark our approach in DCOP, F-DCOP  and MIF-DCOP settings and show that DPSA produces solutions of significantly better quality than the state-of-the-art non-exact algorithms in their corresponding setting .
Revised:  Finally, we empirically benchmark our approach in DCOP, F-DCOP and MIF-DCOP settings and show that DPSA produces solutions of significantly better quality than the state-of-the-art non-exact algorithms in their corresponding settings .
Edit intent: fluency
Original: In the presence of large dimensional datasets that contain many irrelevant features(variables), dimensionality reduction algorithms have proven to be useful in removing features with low variance and combine features with high correlation .
Revised: A central problem in machine learning and pattern recognition is the process of recognizing the most important features .
Edit intent: coherence
Original:  In this paper, we propose a new feature selection method which uses singular value decomposition of a matrix and }]  the method of least squares to remove the irrelevant features and detect correlations between the remaining features .\tilde \mathbf{x}\mathbf{x} \tilde \mathbf{x}.
Revised:  In this paper, we provide a new feature selection method which uses singular value decomposition of a matrix and }] the method of least squares to remove the irrelevant features and detect correlations between the remaining features .\tilde \mathbf{x}\mathbf{x} \tilde \mathbf{x}.
Edit intent: clarity
Original:  In this paper, we propose a new feature selection method which uses singular value decomposition of a matrix and }]  the method of least squares to remove the irrelevant features and detect correlations between the remaining features .\tilde \mathbf{x}\mathbf{x} \tilde \mathbf{x}.
Revised:  In this paper, we propose a new feature selection method which uses singular value decomposition of a matrix and }] the method of least squares to remove the irrelevant features and detect correlations between the remaining features .\tilde \mathbf{x}\mathbf{x} \tilde A\mathbf{x}.
Edit intent: fluency
Original:  The results show that our method is favorable in various aspects compared to state-of-the-art feature selection methods.\e
Revised:  The results show that our method is favorable in several aspects compared to state-of-the-art feature selection methods.\e
Edit intent: fluency
Original:  The results show that our method is favorable in various aspects compared to state-of-the-art feature selection methods.\e
Revised:  The results show that our method is favorable in various aspects compared to each feature selection algorithm.\e
Edit intent: clarity
Original:  In this paper, we address this problem using two video streams as the input;
Revised:  In this paper, we address this problem using two video streams as input;
Edit intent: fluency
Original:  For alignment, we propose to use a set of pre-trained and trainable convolutional neural networks (CNNs) to compute the flows between the missing frame and the two existing frames of the main video by utilizing the content of the auxiliary video frames.
Revised:  For alignment, we propose to compute flows between the missing frame and the two existing frames of the main video by utilizing the content of the auxiliary video frames.
Edit intent: clarity
Original:  For alignment, we propose to use a set of pre-trained and trainable convolutional neural networks (CNNs) to compute the flows between the missing frame and the two existing frames of the main video by utilizing the content of the auxiliary video frames.
Revised:  For alignment, we propose to use a set of pre-trained and trainable convolutional neural networks (CNNs) to compute the flows between the missing frame and two existing frames of the main video by utilizing the content of the auxiliary video frames.
Edit intent: fluency
Original:  We then warp the existing frames using the flows to produce a set of aligned frames.
Edit intent: coherence
Original:  For appearance estimation, we propose to combine the aligned and auxiliary frames using a context and occlusion aware CNN . We train our model on a set of synthetically generated hybrid videos and show high-quality results on a wide range of test scenes.
Revised:  For appearance estimation, we propose to combine the aligned and auxiliary frames using a context and occlusion aware network . We train our model on a set of synthetically generated hybrid videos and show high-quality results on a wide range of test scenes.
Edit intent: clarity
Original:  For appearance estimation, we propose to combine the aligned and auxiliary frames using a context and occlusion aware CNN . We train our model on a set of synthetically generated hybrid videos and show high-quality results on a wide range of test scenes.
Revised:  For appearance estimation, we propose to combine the aligned and auxiliary frames using a context and occlusion aware CNN . We train our model on synthetically generated hybrid videos and show high-quality results on a wide range of test scenes.
Edit intent: clarity
Original:  For appearance estimation, we propose to combine the aligned and auxiliary frames using a context and occlusion aware CNN . We train our model on a set of synthetically generated hybrid videos and show high-quality results on a wide range of test scenes.
Revised:  For appearance estimation, we propose to combine the aligned and auxiliary frames using a context and occlusion aware CNN . We train our model on a set of synthetically generated hybrid videos and show high-quality results on a variety of test scenes.
Edit intent: clarity
Original:  We further demonstrate the practicalityof our approach by showing the performance of our system on two real dual camera setups with small baseline.
Revised:  To demonstrate practicality, we show the performance of our system on two real dual camera setups with small baseline.
Edit intent: clarity
Original: This paper presents the concept of an adaptive safe padding that forces Reinforcement Learning (RL) to synthesize optimal control policies while ensuring safety during the learning process.
Revised: This paper presents the concept of an adaptive safe padding that forces Reinforcement Learning (RL) to synthesise optimal control policies while ensuring safety during the learning process.
Edit intent: fluency
Original: A two-stage data-analysis method is proposed for total-reflection high-energy positron diffraction (TRHEPD) . TRHEPD is a novel experimental method for the determination of surface structure, which has been extensively developed at the Slow Positron Facility, Institute of Materials Structure Science, High Energy Accelerator Research Organization (KEK).
Revised: Total-reflection high-energy positron diffraction (TRHEPD) . TRHEPD is a novel experimental method for the determination of surface structure, which has been extensively developed at the Slow Positron Facility, Institute of Materials Structure Science, High Energy Accelerator Research Organization (KEK).
Edit intent: clarity
Original: A two-stage data-analysis method is proposed for total-reflection high-energy positron diffraction (TRHEPD) . TRHEPD is a novel experimental method for the determination of surface structure, which has been extensively developed at the Slow Positron Facility, Institute of Materials Structure Science, High Energy Accelerator Research Organization (KEK).
Revised: A two-stage data-analysis method is proposed for total-reflection high-energy positron diffraction (TRHEPD) is a novel experimental method for the determination of surface structure, which has been extensively developed at the Slow Positron Facility, Institute of Materials Structure Science, High Energy Accelerator Research Organization (KEK).
Edit intent: fluency
Original:  The numerical problem is solved on a supercomputer .
Revised:  The numerical problem is solved on a supercomputer 
Edit intent: fluency
Original: The existence and uniqueness of weak solutions of dynamical low-rank evolution  for parabolic partial differential equations in two spatial dimensions is shown, covering also non-diagonal diffusion in the elliptic part.
Revised: The existence and uniqueness of weak solutions to dynamical low-rank evolution for parabolic partial differential equations in two spatial dimensions is shown, covering also non-diagonal diffusion in the elliptic part.
Edit intent: fluency
Original: The existence and uniqueness of weak solutions of dynamical low-rank evolution  for parabolic partial differential equations in two spatial dimensions is shown, covering also non-diagonal diffusion in the elliptic part.
Revised: The existence and uniqueness of weak solutions of dynamical low-rank evolution problems for parabolic partial differential equations in two spatial dimensions is shown, covering also non-diagonal diffusion in the elliptic part.
Edit intent: clarity
Original:  In this paper, we propose a Collaborative Dual Attentive Autoencoder (CATA++) for recommending scientific articles.
Revised:  In this paper, we introduce a Collaborative Dual Attentive Autoencoder (CATA++) for recommending scientific articles.
Edit intent: clarity
Original:  We use attention mechanism to capture the most pertinent part of information in making more relevant recommendations.
Revised:  We employ the attention mechanism to capture the most pertinent part of information in making more relevant recommendations.
Edit intent: clarity
Original:  We use attention mechanism to capture the most pertinent part of information in making more relevant recommendations.
Revised:  We use attention mechanism to capture the most related parts of information in making more relevant recommendations.
Edit intent: clarity
Original:  We use attention mechanism to capture the most pertinent part of information in making more relevant recommendations.
Revised:  We use attention mechanism to capture the most pertinent part of information in order to make more relevant recommendations.
Edit intent: clarity
Original:  Comprehensive experiments on three real-world datasets have shown that our dual-way learning strategy has significantly improved the MF performance in comparison with other state-of-the-art MF-based models according to various experimental evaluations.
Revised:  Extensive experiments on three real-world datasets have shown that our dual-way learning strategy has significantly improved the MF performance in comparison with other state-of-the-art MF-based models according to various experimental evaluations.
Edit intent: clarity
Original:  Comprehensive experiments on three real-world datasets have shown that our dual-way learning strategy has significantly improved the MF performance in comparison with other state-of-the-art MF-based models according to various experimental evaluations.
Revised:  Comprehensive experiments on three real-world datasets have shown that our dual-way learning strategy has significantly improved the MF performance in comparison with other state-of-the-art MF-based models using various experimental evaluations.
Edit intent: clarity
Original: A number of prototypical optimization problems in multi-agent systems (e.g.  task allocation and network load-sharing) exhibit a highly local structure: that is, each agent's decision variables are only directly coupled to few other agent's variables through the objective function or the constraints.
Revised: A number of prototypical optimization problems in multi-agent systems (e.g. , task allocation and network load-sharing) exhibit a highly local structure: that is, each agent's decision variables are only directly coupled to few other agent's variables through the objective function or the constraints.
Edit intent: fluency
Original:  Here, we consider the problem under the assumption that A and B have low doubling dimension , which is common for high-dimensional data in real world.
Revised:  Here, we consider the problem under the assumption that A and B have low doubling dimensions , which is common for high-dimensional data in real world.
Edit intent: fluency
Original:  Inspired by the geometric method {\em net tree}, we propose a novel " data-dependent " algorithm to solve this problem efficiently.
Revised:  Inspired by the geometric method {\em net tree}, we propose a novel `` data-dependent " algorithm to solve this problem efficiently.
Edit intent: fluency
Original:  We also study the performance of our method on real datasets, and the experimental results suggest that our method can save a large amount of running time comparing with existing EMD algorithms.
Revised:  We also study the performance of our method on synthetic and real datasets. The experimental results suggest that our method can save a large amount of running time comparing with existing EMD algorithms.
Edit intent: clarity
Original: Electrical and chemical synapses shape the dynamics of neural networks and their functional roles in information processing has been an important question in neurobiology.
Revised: Electrical and chemical synapses shape the dynamics of neural networks and their functional roles in information processing has been a longstanding question in neurobiology.
Edit intent: clarity
Original: Electrical and chemical synapses shape the dynamics of neural networks and their functional roles in information processing has been a longstanding question in neurobiology.
Revised: Electrical and chemical synapses shape the dynamics of neural networks and their functional roles in information processing have been a longstanding question in neurobiology.
Edit intent: fluency
Original:  For each isolated layer, numerical computations indicate that weaker electrical and chemical synaptic couplings are better optimizers of self-induced stochastic resonance.
Revised:  For each isolated layer, computations indicate that weaker electrical and chemical synaptic couplings are better optimizers of self-induced stochastic resonance.
Edit intent: clarity
Original:  These results should guide experiments aimed at  confirming the mechanism of stochastic self-induced resonance in real biological neural networks.
Revised:  These results may guide experiments aimed at confirming the mechanism of stochastic self-induced resonance in real biological neural networks.
Edit intent: clarity
Original:  These results should guide experiments aimed at  confirming the mechanism of stochastic self-induced resonance in real biological neural networks.
Revised:  These results should guide experiments aimed at establishing or confirming the mechanism of stochastic self-induced resonance in real biological neural networks.
Edit intent: clarity
Original:  These results should guide experiments aimed at  confirming the mechanism of stochastic self-induced resonance in real biological neural networks.
Revised:  These results should guide experiments aimed at confirming the mechanism of self-induced resonance in real biological neural networks.
Edit intent: clarity
Original:  We assume  an initial state with non-trivial overlap with the ground state can be efficiently prepared, and the spectral gap between the ground energy and  first excited energy is bounded from below.
Revised:  We assume that an initial state with non-trivial overlap with the ground state can be efficiently prepared, and the spectral gap between the ground energy and first excited energy is bounded from below.
Edit intent: fluency
Original:  We assume  an initial state with non-trivial overlap with the ground state can be efficiently prepared, and the spectral gap between the ground energy and  first excited energy is bounded from below.
Revised:  We assume an initial state with non-trivial overlap with the ground state can be efficiently prepared, and the spectral gap between the ground energy and the first excited energy is bounded from below.
Edit intent: fluency
Original:  When such  upper bound is unknown , we propose a hybrid quantum-classical algorithm to estimate the ground energy, where the dependence of the number of queries to the initial state on  precision is exponentially improved compared to the current state-of-the-art algorithm proposed in [Ge et al. 2019].
Revised:  When such an upper bound is unknown , we propose a hybrid quantum-classical algorithm to estimate the ground energy, where the dependence of the number of queries to the initial state on precision is exponentially improved compared to the current state-of-the-art algorithm proposed in [Ge et al. 2019].
Edit intent: fluency
Original:  When such  upper bound is unknown , we propose a hybrid quantum-classical algorithm to estimate the ground energy, where the dependence of the number of queries to the initial state on  precision is exponentially improved compared to the current state-of-the-art algorithm proposed in [Ge et al. 2019].
Revised:  When such upper bound is not known , we propose a hybrid quantum-classical algorithm to estimate the ground energy, where the dependence of the number of queries to the initial state on precision is exponentially improved compared to the current state-of-the-art algorithm proposed in [Ge et al. 2019].
Edit intent: fluency
Original:  When such  upper bound is unknown , we propose a hybrid quantum-classical algorithm to estimate the ground energy, where the dependence of the number of queries to the initial state on  precision is exponentially improved compared to the current state-of-the-art algorithm proposed in [Ge et al. 2019].
Revised:  When such upper bound is unknown , we propose a hybrid quantum-classical algorithm to estimate the ground energy, where the dependence of the number of queries to the initial state on the desired precision is exponentially improved compared to the current state-of-the-art algorithm proposed in [Ge et al. 2019].
Edit intent: clarity
Original:  This estimated ground state energy is then combined with the first algorithm to prepare a ground state without knowing an upper bound of the ground energy.
Revised:  These two algorithms can then be combined to prepare a ground state without knowing an upper bound of the ground energy.
Edit intent: clarity
Original:  TextBrewer provides a simple and uniform workflow that enables quick setup of distillation experiments with highly flexible configurations.
Revised:  TextBrewer provides a simple and uniform workflow that enables quick setting up of distillation experiments with highly flexible configurations.
Edit intent: fluency
Original:  With simple configuration , we achieve results that are comparable with or even higher than the state-of-the-art performance .
Revised:  With simple configurations , we achieve results that are comparable with or even higher than the state-of-the-art performance .
Edit intent: fluency
Original:  In this paper, we build RCC, the first unified and comprehensive RDMA-enabled distributed transaction processing framework supporting six  concurrency control protocols using either two-sided or one-sided primitives.
Revised:  In this paper, we develop RCC, the first unified and comprehensive RDMA-enabled distributed transaction processing framework supporting six concurrency control protocols using either two-sided or one-sided primitives.
Edit intent: clarity
Original: The need for recognition of numerical (decimal, floating-point) constants in terms of elementary functions  emerges in many areas of experimental mathematics, numerical analysis, computer algebra systems, model building,  approximation and data compression.
Revised: The need for recognition /approximation of functions in terms of elementary functions emerges in many areas of experimental mathematics, numerical analysis, computer algebra systems, model building, approximation and data compression.
Edit intent: clarity