wanyu/IteraTeR_v2 huggingface dataset:
Original:  Specifically , we show that if n requests are assigned to n serversbased on the proposed coded scheme , the maximum load of servers will be \Theta(1), while in the nearest replica strategy the maximum load is \Theta(\log n) . More surprisingly, this coded scheme will have the same communication cost performance as the nearest replica strategy, asymptotically.
Revised:  Specifically , we show that if n requests arrive randomly at n servers, the proposed scheme results in the maximum load of servers will be \Theta(1), while in the nearest replica strategy the maximum load is \Theta(\log n) . More surprisingly, this coded scheme will have the same communication cost performance as the nearest replica strategy, asymptotically.
Edit intent: clarity
Original: Deep convolutional neural networks follow roughly the architecture of biological visual systems , and have shown a performance comparable to human observers in object recognition tasks.
Revised: Deep convolutional neural networks follow roughly the architecture of biological visual systems and have shown a performance comparable to human observers in object recognition tasks.
Edit intent: fluency
Original:  It appears that there is no  difference between searches for simple features that pop out in experiments with humans, and for feature configurations that exhibit strict capacity limitations in human vision.
Revised:  It appears that there is no clear difference between searches for simple features that pop out in experiments with humans, and for feature configurations that exhibit strict capacity limitations in human vision.
Edit intent: clarity
Original:  Both types of stimuli reveal moderate capacity limitations in the neural network tested here.
Revised:  Both types of stimuli reveal moderate capacity limitations in the neural networks tested here.
Edit intent: fluency
Original:  However, nodal elements fail in the H-formulation modelling of electromagnetic fields along interfaces between regions with high contrast medium properties , thus N\'ed\'elec elements (of arbitrary order) are preferred .
Revised:  However, nodal elements fail in the H-formulation for modelling electromagnetic fields along interfaces between regions with high contrast medium properties , thus N\'ed\'elec elements (of arbitrary order) are preferred .
Edit intent: clarity
Original:  The composition of a customized , robust,  nonlinear solver completes the exposition of the developed tools to tackle the problem.
Revised:  The composition of a tailored , robust, nonlinear solver completes the exposition of the developed tools to tackle the problem.
Edit intent: clarity
Original:  A set of detailed numerical experiments in 2D/3D shows the availability of the finite element approximation to model the phenomena, including a validation against experimental data .
Revised:  First, a comparison against experimental data is performed to show the availability of the finite element approximation to model the phenomena, including a validation against experimental data .
Edit intent: clarity
Original:  Extending previous work for finite automata over commutative groups, we prove that the context-free language \mathtt{L_1^*= \{a^n b^n : n\geq 1\}^* }  can not be recognized by any rational monoid automaton over a finitely generated permutable monoid.
Revised:  Extending previous work for finite automata over commutative groups, we demonstrate a context-free language \mathtt{L_1^*= \{a^n b^n : n\geq 1\}^* } can not be recognized by any rational monoid automaton over a finitely generated permutable monoid.
Edit intent: clarity
Original:  Extending previous work for finite automata over commutative groups, we prove that the context-free language \mathtt{L_1^*= \{a^n b^n : n\geq 1\}^* }  can not be recognized by any rational monoid automaton over a finitely generated permutable monoid.
Revised:  Extending previous work for finite automata over commutative groups, we prove that the context-free language \mathtt{L_1^*= \{a^n b^n : n\geq 1\}^* } that can not be recognized by any rational monoid automaton over a finitely generated permutable monoid.
Edit intent: fluency
Original: Neural networks are an increasingly attractive algorithm for natural language processing and pattern recognition applications .
Revised: Neural networks are an increasingly attractive algorithm for natural language processing and pattern recognition .
Edit intent: clarity
Original:  Deep networks with >50M parameters  made possible by modern GPU clusters operating at <50 pJ per op and more recently, production accelerators capable of <5pJ per operation at the board level.
Revised:  Deep networks with >50M parameters are made possible by modern GPU clusters operating at <50 pJ per op and more recently, production accelerators capable of <5pJ per operation at the board level.
Edit intent: coherence
Original:  Using an analog resistive memory (ReRAM) crossbar to perform key matrix operations in an accelerator is an attractive option that is gaining significant interest .
Revised:  Using an analog resistive memory (ReRAM) crossbar to perform key matrix operations in an accelerator is an attractive option .
Edit intent: clarity
Original: As the effort to scale up existing quantum hardware proceeds, the necessity of effective methods to schedule quantum gates and minimize the number of operations becomes more compelling.
Revised: As the effort to scale up existing quantum hardware proceeds, it becomes necessary to schedule quantum gates and minimize the number of operations becomes more compelling.
Edit intent: clarity
Original: As the effort to scale up existing quantum hardware proceeds, the necessity of effective methods to schedule quantum gates and minimize the number of operations becomes more compelling.
Revised: As the effort to scale up existing quantum hardware proceeds, the necessity of effective methods to schedule quantum gates in a way that minimizes the number of operations becomes more compelling.
Edit intent: clarity
Original:  Three are the constraints that have to be taken into account: The order or dependency of the quantum gates in the specific algorithm, the fact that any qubit may be involved in at most one gate at a time, and the restriction that two-qubit gates are implementable only between connected qubits.
Revised:  Three are the constraints that have to be satisfied: the order or dependency of the quantum gates in the specific algorithm, the fact that any qubit may be involved in at most one gate at a time, and the restriction that two-qubit gates are implementable only between connected qubits.
Edit intent: clarity
Original:  The last aspect implies that the compilation depends not only on the algorithm, but also on hardware properties like its connectivity.
Revised:  The last aspect implies that the compilation depends not only on the algorithm, but also on hardware properties like connectivity.
Edit intent: clarity
Original:  Here we suggest a two-step approach in which logical gates are initially scheduled neglecting the limited connectivity , while routing operations are added at a later step and their number is empirically minimized.
Revised:  Here we suggest a two-step approach in which logical gates are initially scheduled neglecting connectivity considerations , while routing operations are added at a later step and their number is empirically minimized.
Edit intent: clarity
Original:  As a practical application, we schedule the Quantum Approximate Optimization Algorithm in a linear geometry and quantify the reduction in the number of gates and circuit depth by increasing the efficacy of the scheduling strategies.
Revised:  As a practical application, we schedule the Quantum Approximate Optimization Algorithm in a linear geometry and quantify the reduction in the number of gates and circuit depth that results from increasing the efficacy of the scheduling strategies.
Edit intent: clarity
Original:  All this allowed us to implement an 18-layer ResNet for 224%DIFDELCMD < \times224 %%%  images classification, achieving 57.5 %DIFDELCMD < \\%%% %DIF < top-1 accuracy.
Revised:  All this allowed us to implement an 18-layer ResNet for %DIFDELCMD < \times224 %%% images classification, achieving 57.5 %DIFDELCMD < \\%%% %DIF < top-1 accuracy.
Edit intent: clarity
Original:  Our implementation of ResNet-18 consumes 5\times less power and is 4\times slower for ImageNet, when compared to the same NN on the latest Nvidia GPUs.
Revised:  Our implementation of ResNet-18 consumes 5x less power and is 4\times slower for ImageNet, when compared to the same NN on the latest Nvidia GPUs.
Edit intent: clarity
Original:  Our implementation of ResNet-18 consumes 5\times less power and is 4\times slower for ImageNet, when compared to the same NN on the latest Nvidia GPUs.
Revised:  Our implementation of ResNet-18 consumes 5\times less power and is 4x slower for ImageNet, when compared to the same NN on the latest Nvidia GPUs.
Edit intent: fluency
Original:  Smaller NNs, that fit a single FPGA, are running faster then on GPUs on small ( 32%DIFDELCMD < \times32%%%  ) inputs, while consuming up to 20\times less energy and power.
Revised:  Smaller NNs, that fit a single FPGA, are running faster then on GPUs on small ( %DIFDELCMD < \times32%%% ) inputs, while consuming up to 20\times less energy and power.
Edit intent: clarity
Original:  Smaller NNs, that fit a single FPGA, are running faster then on GPUs on small ( 32%DIFDELCMD < \times32%%%  ) inputs, while consuming up to 20\times less energy and power.
Revised:  Smaller NNs, that fit a single FPGA, are running faster then on GPUs on small ( 32%DIFDELCMD < \times32%%% ) inputs, while consuming up to 20x less energy and power.
Edit intent: fluency
Original: Dimensionality reduction is critical in analyzing increasingly high-volume, high-dimensional time series.
Revised: Dimensionality reduction is a critical step in analytics pipelines for high-volume, high-dimensional time series.
Edit intent: clarity
Original:  In this paper, we revisit a now-classic study of time series dimensionality reduction operators and find that for a given quality constraint, Principal Component Analysis (PCA) uncovers representations that are over 2x smaller than those obtained via alternative techniques favored in the literature.
Revised:  Principal Component Analysis (PCA) uncovers representations that are over 2x smaller than those obtained via alternative techniques favored in the literature.
Edit intent: coherence
Original:  By progressively samplingits input, computing a candidate basis for transformation, and terminating once it finds a sufficiently high quality basis in a reasonable running time, DROP provides speedups of up to 50x over PCA via SVD and 33x in end-to-end high-dimensional analytics pipelines .
Revised:  By progressively samplingits input, computing a candidate basis for transformation, and terminating once it finds a sufficiently high quality basis in a reasonable running time, DROP provides speedups of up to 50x over PCA via SVD and 33x in end-to-end workflows .
Edit intent: clarity
Original:  We demonstrate how accounting for downstream analytics operations during dimensionality reduction via PCA allows stochastic methods to efficiently operate over very small (e.g., 1\%) subsamples of input data, thus reducing computational overhead and end-to-end runtime.
Revised:  We demonstrate how accounting for downstream analytics operations during DR via PCA allows stochastic methods to efficiently operate over very small (e.g., 1\%) subsamples of input data, thus reducing computational overhead and end-to-end runtime.
Edit intent: clarity
Original:  We demonstrate how accounting for downstream analytics operations during dimensionality reduction via PCA allows stochastic methods to efficiently operate over very small (e.g., 1\%) subsamples of input data, thus reducing computational overhead and end-to-end runtime.
Revised:  We demonstrate how accounting for downstream analytics operations during dimensionality reduction via PCA allows stochastic methods to efficiently terminate after operating over small (e.g., 1\%) subsamples of input data, thus reducing computational overhead and end-to-end runtime.
Edit intent: clarity
Original:  By combining techniques spanning progressive sampling, approximate query processing, and cost-based optimization, our proposed dimensionality reduction optimizer enables end-to-end speedups of up to 13.9 times over classic SVD-based PCA techniques, and achieves parity with and can exceed conventional approaches like FFT and PAA by up to 3 times in end-to-end workflows .
Revised:  By combining techniques spanning progressive sampling, approximate query processing, and cost-based optimization, our proposed dimensionality reduction optimizer enables end-to-end speedups of up to 13.9 times over classic SVD-based PCA techniques, and exceeds conventional approaches like FFT and PAA by up to 3 times in end-to-end workflows .
Edit intent: clarity
Original:  By combining techniques spanning progressive sampling, approximate query processing, and cost-based optimization, our proposed dimensionality reduction optimizer enables end-to-end speedups of up to 13.9 times over classic SVD-based PCA techniques, and achieves parity with and can exceed conventional approaches like FFT and PAA by up to 3 times in end-to-end workflows .
Revised:  By combining techniques spanning progressive sampling, approximate query processing, and cost-based optimization, our proposed dimensionality reduction optimizer enables end-to-end speedups of up to 13.9 times over classic SVD-based PCA techniques, and achieves parity with and can exceed conventional approaches like FFT and PAA by up to 3 times in end-to-end workloads .
Edit intent: clarity
Original: We consider the problem of distributedly estimating Gaussian random fields in multi-agent frameworks.
Revised: We consider the problem of distributedly estimating Gaussian processes in multi-agent frameworks.
Edit intent: clarity
Original:  Each sensor collects few measurements and aims to collaboratively reconstruct a common estimate based on all data.
Revised:  Each agent collects few measurements and aims to collaboratively reconstruct a common estimate based on all data.
Edit intent: clarity
Original:  Agents are assumed to have limited computational and communication capabilities and to gather M noisy measurements in total on input locations independently drawn from a known common probability density.
Revised:  Agents are assumed with limited computational and communication capabilities and to gather M noisy measurements in total on input locations independently drawn from a known common probability density.
Edit intent: fluency
Original:  Differently, we propose two suboptimal approaches using the first E orthonormal eigenfunctions obtained from the KL expansion of the chosen kernel, where typically E \ll M.
Revised:  Differently, we propose two suboptimal approaches using the first E orthonormal eigenfunctions obtained from the expansion of the chosen kernel, where typically E \ll M.
Edit intent: clarity
Original:  The benefit is twofold: first, the computation and communication complexities scale with E and not with M . Second, computing the required sufficient statistics can be performed via standard average consensus algorithms.
Revised:  The benefits are that the computation and communication complexities scale with E and not with M . Second, computing the required sufficient statistics can be performed via standard average consensus algorithms.
Edit intent: coherence
Original:  The benefit is twofold: first, the computation and communication complexities scale with E and not with M . Second, computing the required sufficient statistics can be performed via standard average consensus algorithms.
Revised:  The benefit is twofold: first, the computation and communication complexities scale with E and not with M , and computing the required sufficient statistics can be performed via standard average consensus algorithms.
Edit intent: coherence
Original:  The benefit is twofold: first, the computation and communication complexities scale with E and not with M . Second, computing the required sufficient statistics can be performed via standard average consensus algorithms.
Revised:  The benefit is twofold: first, the computation and communication complexities scale with E and not with M . Second, computing the required statistics can be performed via standard average consensus algorithms.
Edit intent: clarity
Original:  We obtain probabilistic non-asymptotic bounds for both approaches, useful to determine a priori the desired level of estimation accuracy .
Revised:  We obtain probabilistic non-asymptotic bounds that determine a priori the desired level of estimation accuracy .
Edit intent: clarity
Original:  Furthermore, we also derive new distributed strategies to tune the regularization parameter which rely on the Stein's unbiased risk estimate (SURE) paradigm and can again be implemented via standard average consensusalgorithms .
Revised:  Furthermore, we also derive new distributed strategies relying on Stein's unbiased risk estimate (SURE) paradigm and can again be implemented via standard average consensusalgorithms .
Edit intent: coherence
Original:  Furthermore, we also derive new distributed strategies to tune the regularization parameter which rely on the Stein's unbiased risk estimate (SURE) paradigm and can again be implemented via standard average consensusalgorithms .
Revised:  Furthermore, we also derive new distributed strategies to tune the regularization parameter which rely on the Stein's unbiased risk estimate (SURE) paradigm and can again be implemented via average consensus .
Edit intent: clarity
Original: With the ever increasing size of  web, relevant information extraction on the Internet with a query formed by a few keywords has become a big challenge.
Revised: With the ever increasing size of the web, relevant information extraction on the Internet with a query formed by a few keywords has become a big challenge.
Edit intent: fluency
Original:  To overcome this, query expansion (QE) plays a crucial role in improving  the Internet searches, where the user's initial query is reformulated to a new query by adding new meaningful terms with similar significance.
Revised:  Query Expansion (QE) plays a crucial role in improving the Internet searches, where the user's initial query is reformulated to a new query by adding new meaningful terms with similar significance.
Edit intent: coherence
Original:  To overcome this, query expansion (QE) plays a crucial role in improving  the Internet searches, where the user's initial query is reformulated to a new query by adding new meaningful terms with similar significance.
Revised:  To overcome this, query expansion (QE) plays a crucial role in improving searches on the Internet. Here, the Internet searches, where the user's initial query is reformulated to a new query by adding new meaningful terms with similar significance.
Edit intent: clarity
Original:  To overcome this, query expansion (QE) plays a crucial role in improving  the Internet searches, where the user's initial query is reformulated to a new query by adding new meaningful terms with similar significance.
Revised:  To overcome this, query expansion (QE) plays a crucial role in improving the user's initial query is reformulated to a new query by adding new meaningful terms with similar significance.
Edit intent: coherence
Original:  To overcome this, query expansion (QE) plays a crucial role in improving  the Internet searches, where the user's initial query is reformulated to a new query by adding new meaningful terms with similar significance.
Revised:  To overcome this, query expansion (QE) plays a crucial role in improving the Internet searches, where the user's initial query is reformulated by adding additional meaningful terms with similar significance.
Edit intent: clarity
Original:  It has also become very influential in the field of personalized social document, Question Answering over Linked Data (QALD), and, Text Retrieval Conference (TREC) and REAL sets .
Revised:  It has become very influential in the field of personalized social document, Question Answering over Linked Data (QALD), and, Text Retrieval Conference (TREC) and REAL sets .
Edit intent: clarity
Original:  This paper surveys QE techniques in IR from 1960 to 2017 with respect to core techniques, data sources used, weighting and ranking methodologies, user participation and applications (of QE techniques) -- bringing out similarities and differences.
Revised:  This paper surveys QE techniques in IR from 1960 to 2017 with respect to core techniques, data sources used, weighting and ranking methodologies, user participation and applications -- bringing out similarities and differences.
Edit intent: clarity
Original:  We show that the Frechet mean is comparable to other summary methods,  despite its stickiness property, and that the Frechet variance is faster and more precise than commonly used variance measures.
Revised:  We show that the Frechet mean is comparable to other summary methods, and, despite its stickiness property, and that the Frechet variance is faster and more precise than commonly used variance measures.
Edit intent: coherence
Original:  These mean and variance measures are more theoretically justified, and more robust, than previous estimates of this type, and can be estimated reasonably efficiently .
Revised:  These mean and variance are more theoretically justified, and more robust, than previous estimates of this type, and can be estimated reasonably efficiently .
Edit intent: clarity
Original: The Internet of Mobile Things (IoMT) requires support for a data lifecycle process ranging from sorting, cleaning and monitoring data streams to more complex tasks such as querying, aggregation, and analytics.
Revised: The Internet of Mobile Things (IoMT) requires support for a data life cycle process ranging from sorting, cleaning and monitoring data streams to more complex tasks such as querying, aggregation, and analytics.
Edit intent: fluency
Original:  Current solutions for stream data management in IoMT have been focused on partial aspects of a data lifecycle process, with special emphasis on sensor networks.
Revised:  Current solutions for stream data management in IoMT have been focused on partial aspects of a data life cycle process, with special emphasis on sensor networks.
Edit intent: fluency
Original:  This paper aims to address this problem by developing an offline and real-time data lifecycle process that incorporates a layered, data-flow centric, and an edge/ cloud computing approach that is needed for handling heterogeneous, streaming and geographicallydispersed IoMT data streams .
Revised:  This paper aims to address this problem by developing streaming data life cycle process that incorporates a layered, data-flow centric, and an edge/ cloud computing approach that is needed for handling heterogeneous, streaming and geographicallydispersed IoMT data streams .
Edit intent: clarity
Original:  This paper aims to address this problem by developing an offline and real-time data lifecycle process that incorporates a layered, data-flow centric, and an edge/ cloud computing approach that is needed for handling heterogeneous, streaming and geographicallydispersed IoMT data streams .
Revised:  This paper aims to address this problem by developing an offline and real-time data lifecycle process that incorporates an edge/ cloud computing approach that is needed for handling heterogeneous, streaming and geographicallydispersed IoMT data streams .
Edit intent: coherence
Original:  This paper aims to address this problem by developing an offline and real-time data lifecycle process that incorporates a layered, data-flow centric, and an edge/ cloud computing approach that is needed for handling heterogeneous, streaming and geographicallydispersed IoMT data streams .
Revised:  This paper aims to address this problem by developing an offline and real-time data lifecycle process that incorporates a layered, data-flow centric, and an edge/ fog/cloud architecture that is needed for handling heterogeneous, streaming and geographicallydispersed IoMT data streams .
Edit intent: clarity