wanyu/IteraTeR_full_sent huggingface dataset:
Original:  The answer to this question is crucial in guiding the design of future systems and providing access to high-performance resources to a broadened community. Here we present a multi-level approach to identifying the performance gap between HPC and cloud computing and to isolate several variables that contribute to this gap by dividing our experiments into (i) hardware and system microbenchmarks and (ii) user applications.
Revised:  The answer to this question is crucial in guiding the design of future systems and providing access to high-performance computing. We present a multi-level approach to identifying the performance gap between HPC and cloud computing and to isolate several variables that contribute to this gap by dividing our experiments into (i) hardware and system microbenchmarks and (ii) user applications.
Edit intent: clarity
Original:  Here we present a multi-level approach to identifying the performance gap between HPC and cloud computing and to isolate several variables that contribute to this gap by dividing our experiments into (i) hardware and system microbenchmarks and (ii) user applications.
Revised:  Here we present a multi-level approach to investigate the performance gap between HPC and cloud computing and to isolate several variables that contribute to this gap by dividing our experiments into (i) hardware and system microbenchmarks and (ii) user applications.
Edit intent: clarity
Original:  Here we present a multi-level approach to identifying the performance gap between HPC and cloud computing and to isolate several variables that contribute to this gap by dividing our experiments into (i) hardware and system microbenchmarks and (ii) user applications.
Revised:  Here we present a multi-level approach to identifying the performance gap between HPC and cloud computing , isolating different variables that contribute to this gap by dividing our experiments into (i) hardware and system microbenchmarks and (ii) user applications.
Edit intent: clarity
Original:  Here we present a multi-level approach to identifying the performance gap between HPC and cloud computing and to isolate several variables that contribute to this gap by dividing our experiments into (i) hardware and system microbenchmarks and (ii) user applications.
Revised:  Here we present a multi-level approach to identifying the performance gap between HPC and cloud computing and to isolate several variables that contribute to this gap . Our experiments are divided into (i) hardware and system microbenchmarks and (ii) user applications.
Edit intent: coherence
Original:  Here we present a multi-level approach to identifying the performance gap between HPC and cloud computing and to isolate several variables that contribute to this gap by dividing our experiments into (i) hardware and system microbenchmarks and (ii) user applications. Our results show that today's high-end cloud computing can deliver HPC-like performance - at least at modest scales - not only for computationally intensive applications , but also for memory- and communication-intensive applications , thanks to the high-speed memory systems and interconnects and dedicated batch scheduling now available on some cloud platforms.
Revised:  Here we present a multi-level approach to identifying the performance gap between HPC and cloud computing and to isolate several variables that contribute to this gap by dividing our experiments into (i) hardware and system microbenchmarks and (ii) user application proxies. The results show that today's high-end cloud computing can deliver HPC-like performance - at least at modest scales - not only for computationally intensive applications , but also for memory- and communication-intensive applications , thanks to the high-speed memory systems and interconnects and dedicated batch scheduling now available on some cloud platforms.
Edit intent: clarity
Original:  Our results show that today's high-end cloud computing can deliver HPC-like performance - at least at modest scales - not only for computationally intensive applications , but also for memory- and communication-intensive applications , thanks to the high-speed memory systems and interconnects and dedicated batch scheduling now available on some cloud platforms.
Revised:  Our results show that today's high-end cloud computing can deliver HPC-competitive performance not only for computationally intensive applications , but also for memory- and communication-intensive applications , thanks to the high-speed memory systems and interconnects and dedicated batch scheduling now available on some cloud platforms.
Edit intent: clarity
Original:  Our results show that today's high-end cloud computing can deliver HPC-like performance - at least at modest scales - not only for computationally intensive applications , but also for memory- and communication-intensive applications , thanks to the high-speed memory systems and interconnects and dedicated batch scheduling now available on some cloud platforms.
Revised:  Our results show that today's high-end cloud computing can deliver HPC-like performance - at least at modest scales - not only for computationally intensive applications but also for memory- and communication-intensive applications , thanks to the high-speed memory systems and interconnects and dedicated batch scheduling now available on some cloud platforms.
Edit intent: fluency
Original:  Our results show that today's high-end cloud computing can deliver HPC-like performance - at least at modest scales - not only for computationally intensive applications , but also for memory- and communication-intensive applications , thanks to the high-speed memory systems and interconnects and dedicated batch scheduling now available on some cloud platforms.
Revised:  Our results show that today's high-end cloud computing can deliver HPC-like performance - at least at modest scales - not only for computationally intensive applications , but also for memory- and communication-intensive applications - at least at modest scales - thanks to the high-speed memory systems and interconnects and dedicated batch scheduling now available on some cloud platforms.
Edit intent: fluency
Original:  These new integrators can be constructed at arbitrary orders of accuracy , have improved stability compared to existing polynomial based exponential linear multistep methods , and can offer significant computational savings compared to current state-of-the-art methods .
Revised:  These new integrators can be constructed at arbitrary orders of accuracy and have improved stability compared to existing polynomial based exponential linear multistep methods , and can offer significant computational savings compared to current state-of-the-art methods .
Edit intent: coherence
Original:  These new integrators can be constructed at arbitrary orders of accuracy , have improved stability compared to existing polynomial based exponential linear multistep methods , and can offer significant computational savings compared to current state-of-the-art methods .
Revised:  These new integrators can be constructed at arbitrary orders of accuracy , have improved stability compared to existing exponential linear multistep methods , and can offer significant computational savings compared to current state-of-the-art methods .
Edit intent: coherence
Original:  These new integrators can be constructed at arbitrary orders of accuracy , have improved stability compared to existing polynomial based exponential linear multistep methods , and can offer significant computational savings compared to current state-of-the-art methods .
Revised:  These new integrators can be constructed at arbitrary orders of accuracy , have improved stability compared to existing polynomial based exponential linear multistep methods . Moreover, if the ODE right-hand side evaluations can be parallelized efficiently, then high-order EPBMs are significantly more efficient at obtaining highly accurate solutions than exponential linear multistep methods and exponential spectral deferred correction methods of equivalent order .
Edit intent: meaning-changed
Original:  Our results are alarming: even on the state-of-the-art systems trained with massive parallel data (tens of millions), the attacks are still successful (over 50\% success rate) under surprisingly low poisoning rates (e.g., 0.006\%).
Revised:  Our results are alarming: even on the state-of-the-art systems trained with massive parallel data (tens of millions), the attacks are still successful (over 50\% success rate) under surprisingly low poisoning budgets (e.g., 0.006\%).
Edit intent: clarity
Original: We present a novel way to perform image registration , which is not limited to a specific kind, between image pairs with very large deformation , while preserving Quasiconformal property without tedious manual landmark labeling that conventional mathematical registration methods require. Alongside the practical function of our algorithm, one just-as-important underlying message is that the integration between typical CNN and existing Mathematical model is successful as will be pointed out by our paper, meaning that machine learning and mathematical model could coexist, cover for each other and significantly improve registration result. This paper will demonstrate an unprecedented idea of making use of both robustness of CNNs and rigorousness of mathematical model to obtain meaningful registration maps between 2D images under the aforementioned strict constraints for the sake of well-posedness .
Revised: Image registration has been widely studied over the past several decades, with numerous applications in science, engineering and medicine. Most of the conventional mathematical models for large deformation image registration rely on prescribed landmarks, which usually require tedious manual labeling and are prone to error. In recent years, there has been a surge of interest in the use of machine learning for image registration. However, most learning-based methods cannot ensure the bijectivity of the registration, which makes it difficult to establish a 1-1 correspondence between the images. In this paper, we develop a novel method for large deformation image registration by a fusion of convolutional neural network (CNN) and quasiconformal theory. More specifically, we propose a new fidelity term for incorporating the CNN features in our quasiconformal energy minimization model, which enables us to obtain meaningful registration maps between 2D images under the aforementioned strict constraints for the sake of well-posedness .
Edit intent: meaning-changed
Original:  This paper will demonstrate an unprecedented idea of making use of both robustness of CNNs and rigorousness of mathematical model to obtain meaningful registration maps between 2D images under the aforementioned strict constraints for the sake of well-posedness .
Revised:  This paper will demonstrate an unprecedented idea of making use of both robustness of CNNs and rigorousness of mathematical model to obtain meaningful registration results without prescribing any landmarks. Moreover, unlike other learning-based methods, the bijectivity of our method is guaranteed by quasiconformal theory. Experimental results are presented to demonstrate the effectiveness of the proposed method. More broadly, our work sheds light on how rigorous mathematical theories and practical machine learning approaches can be integrated for developing computational methods with improved performance .
Edit intent: meaning-changed
Original:  More specifically, we propose a new fidelity term for incorporating the CNN features in our quasiconformal energy minimization model, which enables us to obtain meaningful registration results without prescribing any landmarks.
Revised:  More specifically, we propose a quasiconformal energy model with a novel fidelity term that incorporates the features extracted using a pre-trained CNN, thereby allowing us to obtain meaningful registration results without prescribing any landmarks.
Edit intent: clarity
Original: We establish a rigorous duality theory for a finite horizon problem of optimal consumption in the presence of an income stream that can terminate randomly at an exponentially distributed time, independent of the asset prices.
Revised: We establish a rigorous duality theory , under No Unbounded Profit with Bounded Risk, for an infinite horizon problem of optimal consumption in the presence of an income stream that can terminate randomly at an exponentially distributed time, independent of the asset prices.
Edit intent: meaning-changed
Original:  We thus close a duality gap encountered by Vellekoop and Davis in an infinite horizon version of this problem . Nearly all the classical tenets of duality theory are found to hold, with the notable exception that the marginal utility of initial wealth at zero is finite.
Revised:  We thus close a duality gap encountered by Vellekoop and Davis in an infinite horizon version of this problem in a Black-Scholes market. Many of the classical tenets of duality theory are found to hold, with the notable exception that the marginal utility of initial wealth at zero is finite.
Edit intent: meaning-changed
Original:  The intuition is that the agent will receive some income , no matter how early it terminates, so is not infinitely penalised for having zero initial capital. We then solve the problem numerically, with an additional terminal wealth objective, using deep learning. We transform the problem with randomly terminating income into one that no longer depends on the jump component but has an additional inter-temporal wealth objective. We then numerically solve the second order backward stochastic differential equations (2BSDEs), in both the primal and dual dimensions, to find the optimal control and tight lower and upper bounds for the value function .
Revised:  We use as dual variables a class of supermartingale deflators such that deflated wealth plus cumulative deflated consumption in excess of income is a supermartingale. We show that the space of discounted local martingale deflators is dense in our dual domain, so that the dual problem can also be expressed as an infimum over the discounted local martingale deflators. We characterise the optimal wealth process, showing that optimal deflated wealth is a potential decaying to zero, while deflated wealth plus cumulative deflated consumption over income is a uniformly integrable martingale at the optimum. We apply the analysis to the Vellekoop and Davis example and give a numerical solution .
Edit intent: meaning-changed
Original:  Manipulation Primitives, such as `` Move down until contact '', `` Slide along x while maintaining contact with the surface '' , have enough complexity to keep the search tree shallow, yet are generic enough to generalize across a wide range of assembly tasks.
Revised:  Manipulation Primitives, such as " Move down until contact '', `` Slide along x while maintaining contact with the surface '' , have enough complexity to keep the search tree shallow, yet are generic enough to generalize across a wide range of assembly tasks.
Edit intent: fluency
Original:  Manipulation Primitives, such as `` Move down until contact '', `` Slide along x while maintaining contact with the surface '' , have enough complexity to keep the search tree shallow, yet are generic enough to generalize across a wide range of assembly tasks.
Revised:  Manipulation Primitives, such as `` Move down until contact ", " Slide along x while maintaining contact with the surface '' , have enough complexity to keep the search tree shallow, yet are generic enough to generalize across a wide range of assembly tasks.
Edit intent: fluency
Original:  Manipulation Primitives, such as `` Move down until contact '', `` Slide along x while maintaining contact with the surface '' , have enough complexity to keep the search tree shallow, yet are generic enough to generalize across a wide range of assembly tasks.
Revised:  Manipulation Primitives, such as `` Move down until contact '', `` Slide along x while maintaining contact with the surface " , have enough complexity to keep the search tree shallow, yet are generic enough to generalize across a wide range of assembly tasks.
Edit intent: fluency
Original:  Direct sim2real transfer (without retraining in real) achieves excellent success rates on challenging assembly tasks, such as round peg insertion with 100 micron clearance or square peg insertion with large hole position/orientation estimation errors.
Revised:  Direct sim2real transfer (without retraining in real) achieves excellent success rates on challenging assembly tasks, such as round peg insertion with 0.04 mm clearance or square peg insertion with large hole position/orientation estimation errors.
Edit intent: meaning-changed
Original:  Unfairness is common for some clients and they may always be regarded as outliers, so we also consider the fairness problem, and give randomized algorithms that embody lottery models, so that for each client j with its submitted parameter e_j%DIFDELCMD < \geq0%%% , the expected number of connections for it is at least e_j.
Revised:  In order to address the fairness concern, we also consider the fairness problem, and give randomized algorithms that embody lottery models, so that for each client j with its submitted parameter e_j%DIFDELCMD < \geq0%%% , the expected number of connections for it is at least e_j.
Edit intent: coherence
Original:  Unfairness is common for some clients and they may always be regarded as outliers, so we also consider the fairness problem, and give randomized algorithms that embody lottery models, so that for each client j with its submitted parameter e_j%DIFDELCMD < \geq0%%% , the expected number of connections for it is at least e_j.
Revised:  Unfairness is common for some clients and they may always be regarded as outliers, so we also consider variants of the aforementioned problems, namely fair robust fault-tolerant center problems. In these problems, each client j with its submitted parameter e_j%DIFDELCMD < \geq0%%% , the expected number of connections for it is at least e_j.
Edit intent: meaning-changed
Original:  Unfairness is common for some clients and they may always be regarded as outliers, so we also consider the fairness problem, and give randomized algorithms that embody lottery models, so that for each client j with its submitted parameter e_j%DIFDELCMD < \geq0%%% , the expected number of connections for it is at least e_j.
Revised:  Unfairness is common for some clients and they may always be regarded as outliers, so we also consider the fairness problem, and give randomized algorithms that embody lottery models, so that for each client j %DIFDELCMD < \geq0%%% , the expected number of connections for it is at least e_j.
Edit intent: coherence
Original:  Unfairness is common for some clients and they may always be regarded as outliers, so we also consider the fairness problem, and give randomized algorithms that embody lottery models, so that for each client j with its submitted parameter e_j%DIFDELCMD < \geq0%%% , the expected number of connections for it is at least e_j.
Revised:  Unfairness is common for some clients and they may always be regarded as outliers, so we also consider the fairness problem, and give randomized algorithms that embody lottery models, so that for each client j with its submitted parameter e_j%DIFDELCMD < \geq0%%% has a value e_j, and we need to stochastically open a set of facilities such that the expected number of connections for it is at least e_j.
Edit intent: meaning-changed
Original:  Unfairness is common for some clients and they may always be regarded as outliers, so we also consider the fairness problem, and give randomized algorithms that embody lottery models, so that for each client j with its submitted parameter e_j%DIFDELCMD < \geq0%%% , the expected number of connections for it is at least e_j.
Revised:  Unfairness is common for some clients and they may always be regarded as outliers, so we also consider the fairness problem, and give randomized algorithms that embody lottery models, so that for each client j with its submitted parameter e_j%DIFDELCMD < \geq0%%% , the expected number of facilities that are assigned to j is at least e_j.
Edit intent: clarity
Original: We study a family of clustering problems that require fault-tolerant solutions that are also robust with the presence of outliers.
Revised: In many fundamental combinatorial optimization problems, a feasible solution induces some real cost vectors as an intermediate result, and the optimization objective is a certain function of the vectors. For example, in the problem of makespan minimization on unrelated parallel machines, a feasible job assignment induces a vector containing the sizes of assigned jobs for each machine, and the goal is to minimize the L_\infty norm of L_1 norms of the vectors. Another example is fault-tolerant solutions that are also robust with the presence of outliers.
Edit intent: meaning-changed
Original: We study a family of clustering problems that require fault-tolerant solutions that are also robust with the presence of outliers. We consider robust fault-tolerant k-center, matroid center and knapsack center, and develop pure or multi-criteria approximation algorithms for them.
Revised: We study a family of clustering problems that require fault-tolerant k-center, matroid center and knapsack center, and develop pure or multi-criteria approximation algorithms for them.
Edit intent: clarity
Original:  We consider robust fault-tolerant k-center, matroid center and knapsack center, and develop pure or multi-criteria approximation algorithms for them. In order to address the fairness concern, we also consider variants of the aforementioned problems, namely fair robust fault-tolerant center problems.
Revised:  We consider robust fault-tolerant k-center, where each client is connected to multiple open facilities, thus having a vector of distances to these facilities, and the goal is to minimize the L_\infty norm of L_\infty norms of these vectors. In this paper, we study the maximum of norm problem. Given an arbitrary symmetric monotone norm f, the objective is defined as the maximum (L_\infty norm) of f-norm values of the induced cost vectors. This versatile formulation captures a wide variety of problems, including makespan minimization, fault-tolerant center problems.
Edit intent: meaning-changed
Original:  In order to address the fairness concern, we also consider variants of the aforementioned problems, namely fair robust fault-tolerant center problems. In these problems, each client j has a value e_j, and we need to stochastically open a set of facilities such that the expected number of facilities that are assigned to j is at least e_j. We develop a pure approximation for fair robust fault-tolerant k-center and multi-criteria approximation algorithms for the knapsack and matroid variations .
Revised:  In order to address the fairness concern, we also consider variants of the aforementioned problems, namely fair robust fault-tolerant k-center and multi-criteria approximation algorithms for the knapsack and matroid variations .
Edit intent: coherence
Original:  We develop a pure approximation for fair robust fault-tolerant k-center and multi-criteria approximation algorithms for the knapsack and matroid variations .
Revised:  We develop a pure approximation for fair robust fault-tolerant k-center and many others. We give concrete results for load balancing on unrelated parallel machines and clustering problems, including constant-factor approximation algorithms when f belongs with a certain rich family of norms, and O(\log n)-approximations when f is general and satisfies some mild assumptions. We also consider the aforementioned problems in a generalized fairness setting. As a concrete example, the insight is to prevent a scheduling algorithm from assigning too many jobs consistently on any machine in a job-recurring scenario, and causing the machine's controller to fail. Our algorithm needs to stochastically output a feasible solution minimizing the objective function, and satisfy the given marginal fairness constraints .
Edit intent: meaning-changed