wanyu/IteraTeR_v2 huggingface dataset:
Original:  In addition , we adapt or use existing algorithms/ models of variable selection, regression, or conformal inference to acquire new clinical findings  with the AEGIS study data.
Revised:  In addition , we adapt or use existing models of variable selection, regression, or conformal inference to acquire new clinical findings with the AEGIS study data.
Edit intent: clarity
Original:  In addition , we adapt or use existing algorithms/ models of variable selection, regression, or conformal inference to acquire new clinical findings  with the AEGIS study data.
Revised:  In addition , we adapt or use existing algorithms/ models of variable selection, regression, and conformal inference to acquire new clinical findings with the AEGIS study data.
Edit intent: fluency
Original:  In addition , we adapt or use existing algorithms/ models of variable selection, regression, or conformal inference to acquire new clinical findings  with the AEGIS study data.
Revised:  In addition , we adapt or use existing algorithms/ models of variable selection, regression, or conformal inference to obtain new clinical findings with the AEGIS study data.
Edit intent: fluency
Original:  In addition , we adapt or use existing algorithms/ models of variable selection, regression, or conformal inference to acquire new clinical findings  with the AEGIS study data.
Revised:  In addition , we adapt or use existing algorithms/ models of variable selection, regression, or conformal inference to acquire new clinical findings with the AEGIS data.
Edit intent: clarity
Original:  The fitted models allow : i) to identify new factors associated with long-term glucose changes ;
Revised:  The fitted models allow : i) We identify new factors associated with long-term glucose changes ;
Edit intent: coherence
Original:  The fitted models allow : i) to identify new factors associated with long-term glucose changes ;
Revised:  The fitted models allow : i) to identify new factors associated with long-term glucose evolution ;
Edit intent: clarity
Original:  By not being tied to any real data, random graph models are inadequate in many practical contexts , including areas of research, such as computational epidemiology, which are recently high on the agenda.
Revised:  By not being tied to any real data, random graph models are inadequate in many practical contexts -- including areas of research, such as computational epidemiology, which are recently high on the agenda.
Edit intent: fluency
Original:  The aim of our work is to fill the gap between these two approaches by defining a parametric data-driven model for urban social networks -- implemented and released as open source software.
Revised:  To fill the gap between these two approaches by defining a parametric data-driven model for urban social networks -- implemented and released as open source software.
Edit intent: clarity
Original:  The aim of our work is to fill the gap between these two approaches by defining a parametric data-driven model for urban social networks -- implemented and released as open source software.
Revised:  The aim of our work is to fill the gap between these two approaches , we present a data-driven model for urban social networks -- implemented and released as open source software.
Edit intent: clarity
Original:  The aim of our work is to fill the gap between these two approaches by defining a parametric data-driven model for urban social networks -- implemented and released as open source software.
Revised:  The aim of our work is to fill the gap between these two approaches by defining a parametric data-driven model for urban social networks , implemented and released as open source software.
Edit intent: fluency
Original:  The factors governing the structure of the obtained network, such as the dependency of friendship upon distance and age composition , are thoroughly studied through extensive simulations focused on three Italian cities of different size.
Revised:  The factors governing the structure of the obtained network, under different configurations , are thoroughly studied through extensive simulations focused on three Italian cities of different size.
Edit intent: clarity
Original:  Instead of working with partial differential equations, the new method works with an integral formulation that involves the semigroup of the differential operator.
Revised:  Instead of working with partial differential equations, the new method works with an integral formulation based on the semigroup of the differential operator.
Edit intent: clarity
Original:  Empirically, we demonstrate  that PiRank significantly improves over existing approaches on publicly available internet-scale learning-to-rank benchmarks.
Revised:  Empirically, we demonstrate that PiRank significantly improves over comparable approaches on publicly available internet-scale learning-to-rank benchmarks.
Edit intent: clarity
Original:  This paperintroduces a preliminary study to develop a neurohaptic-based BCI system for a variety of scenarios using actual touch and touch imagery paradigms.
Revised:  This paperintroduces a preliminary study for a variety of scenarios using actual touch and touch imagery paradigms.
Edit intent: clarity
Original:  Seven subjects participated in our experiment and evaluated classification performances using the basic machine learning algorithm and convolutional neural network-based deep learning approaches.
Revised:  Seven subjects were recruited for the experiment and evaluated classification performances using the basic machine learning algorithm and convolutional neural network-based deep learning approaches.
Edit intent: clarity
Original:  Seven subjects participated in our experiment and evaluated classification performances using the basic machine learning algorithm and convolutional neural network-based deep learning approaches.
Revised:  Seven subjects participated in our experiment and evaluated classification performances using machine learning and deep learning approaches.
Edit intent: clarity
Original:  Hence, we could confirm the feasibility of decoding actual touch and touch imagery on EEG signals for performing versatile and practical neurohaptic BCI .
Revised:  Hence, we could confirm the feasibility of decoding actual touch and touch imagery on EEG signals to develop practical neurohaptics .
Edit intent: clarity
Original: We study  fair allocation of undesirable indivisible items (or chores) and make three contributions : First, we show that determining the existence of an envy-free allocation is NP-complete even when agents have binary additive valuations.
Revised: We study the fair allocation of undesirable indivisible items (or chores) and make three contributions : First, we show that determining the existence of an envy-free allocation is NP-complete even when agents have binary additive valuations.
Edit intent: fluency
Original: We study  fair allocation of undesirable indivisible items (or chores) and make three contributions : First, we show that determining the existence of an envy-free allocation is NP-complete even when agents have binary additive valuations.
Revised: We study fair allocation of undesirable indivisible items (or chores) and make three contributions . First, we show that determining the existence of an envy-free allocation is NP-complete even when agents have binary additive valuations.
Edit intent: fluency
Original:  Second, we provide a polynomial-time algorithm for computing an allocation that satisfies envy-freeness up to one chore (EF1) under monotone valuations, correcting a existing proof of the same claim in the literature.
Revised:  Second, we provide a polynomial-time algorithm for computing an allocation that satisfies envy-freeness up to one chore (EF1) , correcting an existing proof in the literature.
Edit intent: clarity
Original:  Our third and most important result applies to a mixed resources model consisting of indivisible chores and a divisible, desirable heterogenous resource (metaphorically, a cake).
Revised:  Our third result applies to a mixed resources model consisting of indivisible chores and a divisible, desirable heterogenous resource (metaphorically, a cake).
Edit intent: clarity
Original:  Our third and most important result applies to a mixed resources model consisting of indivisible chores and a divisible, desirable heterogenous resource (metaphorically, a cake).
Revised:  Our third and most important result applies to a mixed resources model consisting of indivisible items and a divisible, desirable heterogenous resource (metaphorically, a cake).
Edit intent: clarity
Original:  Our third and most important result applies to a mixed resources model consisting of indivisible chores and a divisible, desirable heterogenous resource (metaphorically, a cake).
Revised:  Our third and most important result applies to a mixed resources model consisting of indivisible chores and a divisible, undesirable heterogeneous resource (i.e., a bad cake).
Edit intent: clarity
Original:  We show that there always exists an allocation that satisfies envy-freeness for mixed resources (EFM) in this setting, complementing an analogous recent result of Bei et al. ( AAAI 2020).
Revised:  We show that there always exists an allocation that satisfies envy-freeness for mixed resources (EFM) in this setting, complementing a recent result of Bei et al. ( AAAI 2020).
Edit intent: clarity
Original:  We also show a similar result in the flipped setting consisting of indivisible goods and a divisible "bad" cake.
Revised:  We also show a similar result in the flipped setting consisting of indivisible goods and divisible cake.
Edit intent: clarity
Original: This work studies a real-time environment monitoring scenario in the Industrial Internet of Things (IIoT) , where wireless sensors proactively collect environmental data and transmit it to the controller.
Revised: This work studies a real-time environment monitoring scenario in the industrial Internet of things , where wireless sensors proactively collect environmental data and transmit it to the controller.
Edit intent: clarity
Original:  Latest studies suggest that the pre-training benefits from gigantic model capacity.
Revised:  Latest studies suggest that pre-training benefits from gigantic model capacity.
Edit intent: fluency
Original:  We are hereby curious and ask: after pre-training, does a pre-trained model indeed have to stay large for its universal downstream transferability?
Revised:  We are hereby curious and ask: after pre-training, does a pre-trained model indeed have to stay large for its downstream transferability?
Edit intent: clarity
Original:  In this paper, we examine the supervised and self-supervised pre-trained models through the lens of  lottery ticket hypothesis (LTH).
Revised:  In this paper, we examine supervised and self-supervised pre-trained models through the lens of lottery ticket hypothesis (LTH).
Edit intent: fluency
Original:  In this paper, we examine the supervised and self-supervised pre-trained models through the lens of  lottery ticket hypothesis (LTH).
Revised:  In this paper, we examine the supervised and self-supervised pre-trained models through the lens of the lottery ticket hypothesis (LTH).
Edit intent: fluency
Original:  LTH identifies highly sparse matching subnetworks that can be trained in isolation from (nearly) scratch , to reach the full models' performance.
Revised:  LTH identifies highly sparse matching subnetworks that can be trained in isolation from (nearly) scratch yet still reach the full models' performance.
Edit intent: clarity
Original:  We extend the scope of LTH to questioning whether matching subnetworks still exist in the pre-training models, that enjoy the same downstream transfer performance.
Revised:  We extend the scope of LTH and question whether matching subnetworks still exist in the pre-training models, that enjoy the same downstream transfer performance.
Edit intent: coherence
Original:  We extend the scope of LTH to questioning whether matching subnetworks still exist in the pre-training models, that enjoy the same downstream transfer performance.
Revised:  We extend the scope of LTH to questioning whether matching subnetworks still exist in pre-trained computer vision models, that enjoy the same downstream transfer performance.
Edit intent: clarity
Original:  Our extensive experiments convey an overall positive message: from all pre-trained weights obtained by ImageNet classification, simCLR  and MoCo, we are consistently able to locate such matching subnetworks at 59.04\% to 96.48\% sparsity that transfer universally to multiple downstream tasks, whose performance see no degradation compared to using full pre-trained weights.
Revised:  Our extensive experiments convey an overall positive message: from all pre-trained weights obtained by ImageNet classification, simCLR , and MoCo, we are consistently able to locate such matching subnetworks at 59.04\% to 96.48\% sparsity that transfer universally to multiple downstream tasks, whose performance see no degradation compared to using full pre-trained weights.
Edit intent: fluency
Original:  In particular, we demonstrate that the star graph continuously transitions between amplifying and suppressing natural selection as migration rate asymmetry is varied.
Revised:  In particular, we demonstrate that the star graph transitions from amplifying to suppressing natural selection as migration rate asymmetry is varied.
Edit intent: clarity
Original:  Our results are universal in the sense that they do not hinge on a modeling choice of microscopic dynamics or update rules.
Revised:  The results from our model are universal in the sense that they do not hinge on a modeling choice of microscopic dynamics or update rules.
Edit intent: clarity
Original:  We find that the free layers at low dimensions fluctuate to randomize the resistance of the MTJ in an approximately bias-independent manner.
Revised:  We find that the free layers with low diameters fluctuate to randomize the resistance of the MTJ in an approximately bias-independent manner.
Edit intent: clarity
Original: Epilepsy is recognised as a dynamic disease, where seizures and their features change over time.
Revised: Epilepsy is recognised as a dynamic disease, where susceptibility to seizures and seizure characteristics change over time.
Edit intent: clarity
Original:  We find that all patients show an approximately circadian fluctuation in their EEG band power, but also many other fluctuations on patient-specific timescales.
Revised:  We find that all subjects show not only an approximately-circadian fluctuation in their EEG band power, but also many other fluctuations on patient-specific timescales.
Edit intent: clarity
Original:  We find that all patients show an approximately circadian fluctuation in their EEG band power, but also many other fluctuations on patient-specific timescales.
Revised:  We find that all patients show an approximately circadian fluctuation in their EEG band power, but also many other fluctuations on subject-specific timescales.
Edit intent: clarity
Original:  Importantly, we find that a combination of fluctuations on different timescales can explain the changes in seizure evolution in most patients above chance-level.
Revised:  Importantly, we find that a combination of fluctuations on different timescales can explain changes in seizure evolution in most patients above chance-level.
Edit intent: fluency
Original: Epilepsy is recognised as a dynamic disease, where susceptibility to seizures and seizure characteristics  change over time.
Revised: Epilepsy is recognised as a dynamic disease, where both seizure susceptibility and seizure characteristics change over time.
Edit intent: clarity
Original:  Specifically, we recently found variable seizure dynamics within individual patients.
Revised:  Specifically, we recently quantified the variable electrographic spatio-temporal seizure evolutions that exist within individual patients.
Edit intent: clarity
Original:  Additionally, the variability appeared to follow subject-specific circadian or longer timescale modulations.
Revised:  This variability appears to follow subject-specific circadian or longer timescale modulations.
Edit intent: coherence
Original:  Additionally, the variability appeared to follow subject-specific circadian or longer timescale modulations.
Revised:  Additionally, the variability appeared to follow subject-specific circadian , or longer, timescale modulations.
Edit intent: fluency
Original:  However, whether signatures of these modulations over different timescales can be captured on continuous (interictal) EEG remains unclear .
Revised:  However, whether signatures of these modulations over different timescales .
Edit intent: clarity
Original:  In this work, we analyse continuous interictal intracranial electroencephalographic (iEEG) recordings from video-telemetry units and find fluctuations in iEEG band power over different timescales ranging from minutes up to twelve days.
Revised:  In this work, we analyse continuous intracranial electroencephalographic (iEEG) recordings from video-telemetry units and find fluctuations in iEEG band power over different timescales ranging from minutes up to twelve days.
Edit intent: clarity
Original:  In this work, we analyse continuous interictal intracranial electroencephalographic (iEEG) recordings from video-telemetry units and find fluctuations in iEEG band power over different timescales ranging from minutes up to twelve days.
Revised:  In this work, we analyse continuous interictal intracranial electroencephalographic (iEEG) recordings from video-telemetry units and find fluctuations in iEEG band power over timescales ranging from minutes up to twelve days.
Edit intent: clarity
Original:  We find that all subjects show not only an approximately-circadian fluctuation in their EEG band power, but also many other fluctuations on subject-specific timescales.
Revised:  We find that all subjects show a circadian fluctuation in their EEG band power, but also many other fluctuations on subject-specific timescales.
Edit intent: clarity
Original:  We find that all subjects show not only an approximately-circadian fluctuation in their EEG band power, but also many other fluctuations on subject-specific timescales.
Revised:  We find that all subjects show not only an approximately-circadian fluctuation in their iEEG band power. We additionally find other fluctuations of similar magnitude on subject-specific timescales.
Edit intent: clarity
Original:  Importantly, we find that a combination of  fluctuations on different timescales can explain changes in seizure network evolution in a regression model in most subjects above chance level.
Revised:  Importantly, we find that a combination of these fluctuations on different timescales can explain changes in seizure network evolution in a regression model in most subjects above chance level.
Edit intent: clarity
Original:  Importantly, we find that a combination of  fluctuations on different timescales can explain changes in seizure network evolution in a regression model in most subjects above chance level.
Revised:  Importantly, we find that a combination of fluctuations on different timescales can explain changes in seizure evolutions in most subjects above chance level.
Edit intent: clarity
Original:  Understanding seizure modulating factors enables development of novel treatment strategies that  minimise the seizure spread, duration, or severity and therefore  clinical impact of seizures.
Revised:  Understanding seizure modulating factors enables development of novel treatment strategies that could minimise the seizure spread, duration, or severity and therefore clinical impact of seizures.
Edit intent: clarity
Original:  Understanding seizure modulating factors enables development of novel treatment strategies that  minimise the seizure spread, duration, or severity and therefore  clinical impact of seizures.
Revised:  Understanding seizure modulating factors enables development of novel treatment strategies that minimise the seizure spread, duration, or severity and therefore the clinical impact of seizures.
Edit intent: fluency
Original:  Due to the massive, speedy, unpredictable features of network flows, sketches are widely implemented in measurement nodes to  record the frequency or estimate the cardinality of flows approximately .
Revised:  Due to the massive, speedy, unpredictable features of network flows, sketches are widely implemented in measurement nodes to approximately record the frequency or estimate the cardinality of flows approximately .
Edit intent: fluency
Original:  Due to the massive, speedy, unpredictable features of network flows, sketches are widely implemented in measurement nodes to  record the frequency or estimate the cardinality of flows approximately .
Revised:  Due to the massive, speedy, unpredictable features of network flows, sketches are widely implemented in measurement nodes to record the frequency or estimate the cardinality of flows .
Edit intent: coherence
Original:  At their cores, sketches usually maintain one or multiple counter array(s), and relies on hash functions to select the counter(s) for each flow.
Revised:  At their cores, sketches usually maintain one or multiple counter array(s), and rely on hash functions to select the counter(s) for each flow.
Edit intent: fluency
Original:  Currently, tremendous redesigns and optimizations have been proposed to further improve the sketches for better network measurement performance.
Revised:  Currently, tremendous redesigns and optimizations have been proposed to improve the sketches for better network measurement performance.
Edit intent: clarity
Original:  However, the existing reviews or surveys mainly focus on one particular aspect of measurement tasks.
Revised:  However, existing reviews or surveys mainly focus on one particular aspect of measurement tasks.
Edit intent: fluency
Original:  Researchers and engineers in the network measurement community desire an all-in-one survey which covers the whole processing pipeline of sketch-based network measurement.
Revised:  Researchers and engineers in the network measurement community desire an all-in-one survey that covers the entire processing pipeline of sketch-based network measurement.
Edit intent: fluency
Original:  To this end, we present the first comprehensive survey in this area.
Revised:  To this end, we present the first comprehensive survey of this area.
Edit intent: clarity
Original:  To summary the existing efforts, we conduct an in-depth study of the existing literature, covering more than 80 sketch designs and optimization strategies.
Revised:  To summarize the existing efforts, we conduct an in-depth study of the existing literature, covering more than 80 sketch designs and optimization strategies.
Edit intent: fluency
Original:  To summary the existing efforts, we conduct an in-depth study of the existing literature, covering more than 80 sketch designs and optimization strategies.
Revised:  To summary the existing efforts, we carry out an in-depth study of the existing literature, covering more than 80 sketch designs and optimization strategies.
Edit intent: clarity
Original: In this papper , a deep reinforcement learning (DRL)-based approach to the Lyapunov optimization is considered to minimize the time-average penalty while maintaining queue stability.
Revised: In this paper , a deep reinforcement learning (DRL)-based approach to the Lyapunov optimization is considered to minimize the time-average penalty while maintaining queue stability.
Edit intent: fluency
Original:  however, most models still suffer from finding a balance between model size, model complexity , and model performance  .
Revised:  however, most models still suffer from finding a balance between model size, model complexity and model performance .
Edit intent: fluency
Original:  In this paper, we propose the group communication with context codec(GC3) design to decrease both model size and complexity without sacrificing the model performance.
Revised:  In this paper, we propose two simple modules, group communication and context codec, that can be easily applied to a wide range of architectures to jointly decrease the model size and complexity without sacrificing the model performance.
Edit intent: clarity