wanyu/IteraTeR_v2 huggingface dataset:
Original:  We slightly improve this bound by constructing a Boolean function of degree d with 3\cdot 2^{d-1}-2 relevant variables.
Revised:  We slightly improve the lower bound by constructing a Boolean function of degree d with 3\cdot 2^{d-1}-2 relevant variables.
Edit intent: clarity
Original:  This construction was independently observed by Avishay Tal, but has not appeared in a publication before Tal 17 .
Revised:  This construction was independently observed by Tal 17 .
Edit intent: coherence
Original: Deep neural networks are among the most influential architectures of deep learning algorithms, being deployed in many mobile intelligent applications.
Revised: Deep learning models are being deployed in many mobile intelligent applications.
Edit intent: clarity
Original:  End-side services, such as intelligent personal assistants (IPAs) , autonomous cars, and smart home services often employ either simple local models  or complex remote models on the cloud.
Revised:  End-side services, such as intelligent personal assistants , autonomous cars, and smart home services often employ either simple local models or complex remote models on the cloud.
Edit intent: clarity
Original:  We provide optimization formulations at layer granularity for forward and backward propagation in DNNs, which can adapt to mobile battery limitations and cloud server load constraints and quality of service.
Revised:  We provide optimization formulations at layer granularity for forward- and backward-propagations in DNNs, which can adapt to mobile battery limitations and cloud server load constraints and quality of service.
Edit intent: fluency
Original:  JointDNN achieves up to 18X and 32X reductions on the latency and mobile energy consumption of querying DNNs  , respectively.
Revised:  JointDNN achieves up to 18 and 32 times reductions on the latency and mobile energy consumption of querying DNNs , respectively.
Edit intent: clarity
Original:  JointDNN achieves up to 18X and 32X reductions on the latency and mobile energy consumption of querying DNNs  , respectively.
Revised:  JointDNN achieves up to 18X and 32X reductions on the latency and mobile energy consumption of querying DNNs compared to the status-quo approaches , respectively.
Edit intent: clarity
Original:  It is an active area of research.
Revised:  This is an active area of research.
Edit intent: fluency
Original:  Recently, Pallavoor, Raskhodnikova and Varma (ITCS'17) proposed an \varepsilon-tester for monotonicity of a function f\colon [n]\to[r] , whose complexity depends on the size of the range as O(\log r{\varepsilon prove a nearly matching lower bound of \Omega(\log r{\log \log r}) for adaptive two-sided testers.
Revised:  In this paper we study query complexity of \epsilon-testing monotonicity of a function f\colon [n]\to[r] , whose complexity depends on the size of the range as O(\log r{\varepsilon prove a nearly matching lower bound of \Omega(\log r{\log \log r}) for adaptive two-sided testers.
Edit intent: clarity
Original:  Recently, Pallavoor, Raskhodnikova and Varma (ITCS'17) proposed an \varepsilon-tester for monotonicity of a function f\colon [n]\to[r] , whose complexity depends on the size of the range as O(\log r{\varepsilon prove a nearly matching lower bound of \Omega(\log r{\log \log r}) for adaptive two-sided testers.
Revised:  Recently, Pallavoor, Raskhodnikova and Varma (ITCS'17) proposed an \varepsilon-tester for monotonicity of a function f\colon [n]\to[r] . All our lower bounds are for adaptive two-sided testers. * We prove a nearly matching lower bound of \Omega(\log r{\log \log r}) for adaptive two-sided testers.
Edit intent: clarity
Original:  Finally, } we give an alternative proof of the \Omega( \varepsilon ^{-1}d\log n - \varepsilon^{-1\log\varepsilon} \log\epsilon} ^{-1}) lower bound for testing monotonicity on the hypergrid [n]^d due to Chackrabarty and Seshadhri (RANDOM'13).
Revised:  Finally, } we give an alternative proof of the \Omega( \epsilon ^{-1}d\log n - \varepsilon^{-1\log\varepsilon} \log\epsilon} ^{-1}) lower bound for testing monotonicity on the hypergrid [n]^d due to Chackrabarty and Seshadhri (RANDOM'13).
Edit intent: fluency
Original:  Finally, } we give an alternative proof of the \Omega( \varepsilon ^{-1}d\log n - \varepsilon^{-1\log\varepsilon} \log\epsilon} ^{-1}) lower bound for testing monotonicity on the hypergrid [n]^d due to Chackrabarty and Seshadhri (RANDOM'13).
Revised:  Finally, } we give an alternative proof of the \Omega( \varepsilon ^{-1}d\log n - \log\varepsilon} \log\epsilon} ^{-1}) lower bound for testing monotonicity on the hypergrid [n]^d due to Chackrabarty and Seshadhri (RANDOM'13).
Edit intent: clarity
Original:  Finally, } we give an alternative proof of the \Omega( \varepsilon ^{-1}d\log n - \varepsilon^{-1\log\varepsilon} \log\epsilon} ^{-1}) lower bound for testing monotonicity on the hypergrid [n]^d due to Chackrabarty and Seshadhri (RANDOM'13).
Revised:  Finally, } we give an alternative proof of the \Omega( \varepsilon ^{-1}d\log n - \varepsilon^{-1\log\varepsilon} \epsilon^{-1\log\epsilon} ^{-1}) lower bound for testing monotonicity on the hypergrid [n]^d due to Chackrabarty and Seshadhri (RANDOM'13).
Edit intent: fluency
Original:  Finally, } we give an alternative proof of the \Omega( \varepsilon ^{-1}d\log n - \varepsilon^{-1\log\varepsilon} \log\epsilon} ^{-1}) lower bound for testing monotonicity on the hypergrid [n]^d due to Chackrabarty and Seshadhri (RANDOM'13).
Revised:  Finally, } we give an alternative proof of the \Omega( \varepsilon ^{-1}d\log n - \varepsilon^{-1\log\varepsilon} \log\epsilon} ^{-1}) lower bound for testing monotonicity on the hypergrid [n]^d due to Chakrabarty and Seshadhri (RANDOM'13).
Edit intent: fluency
Original:  The indicators N_TOP50, N_TOP25, and N_TOP10 can be used to identify those CRswhich belong to the 50\%, 25\%, or 10\% most frequently cited publications (CRs) over many citing publication years.
Revised:  The indicators N_TOP50, N_TOP25, and N_TOP10 can be used to identify those CRs which belong to the 50\%, 25\%, or 10\% most frequently cited publications (CRs) over many citing publication years.
Edit intent: fluency
Original:  We compare three parameter estimation methods for the weak variance-alpha-gamma process, method of moments, maximum likelihood estimation (MLE) and digital moment estimation (DME).
Revised:  We compare three calibration methods for the weak variance-alpha-gamma process, method of moments, maximum likelihood estimation (MLE) and digital moment estimation (DME).
Edit intent: clarity
Original:  We found that subjects were more willing to use technologies to enhance or repair other people than themselves, and especially to  repair functions more "core" to authentic identity in others.
Revised:  We found that subjects were more willing to use technologies to repair other people than themselves, and especially to repair functions more "core" to authentic identity in others.
Edit intent: clarity
Original:  We found that subjects were more willing to use technologies to enhance or repair other people than themselves, and especially to  repair functions more "core" to authentic identity in others.
Revised:  We found that subjects were more willing to use technologies to enhance or repair other people than themselves, and especially to enhance or repair functions more "core" to authentic identity in others.
Edit intent: fluency
Original:  Subjects' ratings of  moral acceptability of  uses was related to their reported willingness to use brain stimulation.
Revised:  Subjects' ratings of the moral acceptability of uses was related to their reported willingness to use brain stimulation.
Edit intent: fluency
Original: Probabilistic spin logic (PSL)  based on networks of binary stochastic neurons (or p-bits)  has been shown to provide a viable framework for many functionalities including Ising computing, Bayesian inference, invertible Boolean logic and image recognition.
Revised: Probabilistic spin logic (PSL) , based on networks of binary stochastic neurons (or p-bits) has been shown to provide a viable framework for many functionalities including Ising computing, Bayesian inference, invertible Boolean logic and image recognition.
Edit intent: fluency
Original: Probabilistic spin logic (PSL)  based on networks of binary stochastic neurons (or p-bits)  has been shown to provide a viable framework for many functionalities including Ising computing, Bayesian inference, invertible Boolean logic and image recognition.
Revised: Probabilistic spin logic (PSL) based on networks of binary stochastic neurons (or p-bits) , has been shown to provide a viable framework for many functionalities including Ising computing, Bayesian inference, invertible Boolean logic and image recognition.
Edit intent: fluency
Original:  While %DIFDELCMD < {\em %DIFDELCMD < %%% Neymanallocation provides a solution that minimizes the variance of an estimate using this sample, it works under the assumption that each stratum is abundant, i.e. has a large number of data points to choose from.
Revised:  While %DIFDELCMD < {\em %DIFDELCMD < %%% Neyman's allocation provides a solution that minimizes the variance of an estimate using this sample, it works under the assumption that each stratum is abundant, i.e. has a large number of data points to choose from.
Edit intent: fluency
Original:  We show a lower bound, that any streaming algorithm for SRS must have (in the worst case) a variance that is \Omega(r) factor away from the optimal, where r is the number of strata.
Revised:  We show a lower bound, that any streaming algorithm for SRS must have (in the worst case) a variance that is \Omega(r) away from the optimal, where r is the number of strata.
Edit intent: clarity
Original:  Our results from experiments on real and synthetic data show that that %DIFDELCMD < \voila %DIFDELCMD < %%%  can have significantly smaller variance than Neyman allocation (%DIFDELCMD < \voila%%%  's variances are a factor of 1.4x-3000x smaller than that of Neyman allocation, with the same setting).
Revised:  Our results from experiments on real and synthetic data show that that %DIFDELCMD < \voila %DIFDELCMD < %%% can have significantly smaller variance than Neyman %DIFDELCMD < \voila%%% 's variances are a factor of 1.4x-3000x smaller than that of Neyman allocation, with the same setting).
Edit intent: fluency
Original:  While Neyman 's allocation provides a solution that minimizes the variance of an estimate using this sample, it works under the assumption that each stratum is abundant, i.e.  has a large number of data points to choose from.
Revised:  While Neyman allocation provides a solution that minimizes the variance of an estimate using this sample, it works under the assumption that each stratum is abundant, i.e. has a large number of data points to choose from.
Edit intent: clarity
Original:  While Neyman 's allocation provides a solution that minimizes the variance of an estimate using this sample, it works under the assumption that each stratum is abundant, i.e.  has a large number of data points to choose from.
Revised:  While Neyman 's allocation provides a solution that minimizes the variance of an estimate using this sample, it works under the assumption that each stratum is abundant, i.e. , has a large number of data points to choose from.
Edit intent: fluency
Original:  We show a lower bound, that any streaming algorithm for SRS must have (in the worst case) a variance that is \Omega (r)  away from the optimal, where r is the number of strata.
Revised:  We show a lower bound, that any streaming algorithm for SRS must have (in the worst case) a variance that is \Omega (r) away from the optimal, where r is the number of strata.
Edit intent: fluency
Original:  Our results from experiments on real and synthetic data show that that VOILA can have significantly smaller variance than Neyman's allocation (VOILA's variances are a factor of 1.4 x-3000x smaller than that of Neyman allocation, with the same setting) .
Revised:  Our results from experiments on real and synthetic data show that VOILA can have significantly smaller variance than Neyman's allocation (VOILA's variances are a factor of 1.4 x-3000x smaller than that of Neyman allocation, with the same setting) .
Edit intent: fluency
Original:  Our results from experiments on real and synthetic data show that that VOILA can have significantly smaller variance than Neyman's allocation (VOILA's variances are a factor of 1.4 x-3000x smaller than that of Neyman allocation, with the same setting) .
Revised:  Our results from experiments on real and synthetic data show that that VOILA can have significantly ( 1.4 x-3000x smaller than that of Neyman allocation, with the same setting) .
Edit intent: clarity
Original:  The streaming algorithm S-VOIlA results in a variance that is typically close to VOILA, which was given the entire input beforehand.
Revised:  The streaming algorithm S-VOILA results in a variance that is typically close to VOILA, which was given the entire input beforehand.
Edit intent: fluency
Original:  By bringing together stochastic learning and computeralgebra in a novel way, we combine noisy observations with precise algebraic computations.
Revised:  By bringing together stochastic learning and computer algebra in a novel way, we combine noisy observations with precise algebraic computations.
Edit intent: fluency
Original: The past decades witness FLOPS (Floating-point Operations per Second) , as an important computation-centric performance metric , guides computer architecture evolution, bridges hardware and software co-design, and provides quantitative performance number for system optimization .
Revised: The past decades witness FLOPS (Floating-point Operations per Second) , as an important computation-centric performance metric .
Edit intent: clarity
Original:  To address the above issue, we propose a new computation-centric metric BOPS (Basic OPerations per Second) .
Revised:  To address the above issue, we propose a new computation-centric metric BOPs (Basic OPerations per Second) .
Edit intent: fluency
Original:  In our definition, Basic Operations include all of arithmetic, logical, comparing  and array addressing operations for integer and floating point.
Revised:  In our definition, Basic Operations include all of arithmetic, logical, comparing , and array addressing operations for integer and floating point.
Edit intent: fluency
Original:  To that end, we present a dwarf-based measuring tool to evaluate DC computer systems in terms of our new metrics .
Revised:  To that end, we present a dwarf-based measuring tool to evaluate DC computer systems .
Edit intent: clarity
Original:  On the basis of BOPS, also we propose a new roofline performance model for DC computing .
Revised:  On the basis of BOPS, we propose a new roofline performance model for DC computing .
Edit intent: coherence
Original:  On the basis of BOPS, also we propose a new roofline performance model for DC computing .
Revised:  On the basis of BOPS, also we propose a new Roofline performance model for DC computing .
Edit intent: fluency
Original:  These observations imply that FLOPS is inappropriate for evaluating DC computer systems.
Revised:  These observations imply that FLOPS (Floating-point Operations per Second) is inappropriate to evaluate DC computing systems.
Edit intent: clarity
Original:  To address the above issue, we propose BOPS (Basic OPerations per Second), which is the average number of BOPs (Basic OPerations) completed per second , as a new computation-centric metric.
Revised:  To address the above issue, we propose BOPS (Basic Operations Per Second), which is the average number of BOPs (Basic OPerations) completed per second , as a new computation-centric metric.
Edit intent: fluency
Original:  BOPs include the integer and floating point computations of arithmetic, logical, comparing and array addressing.
Revised:  BOPs include the integer and floating point computation operations of arithmetic, logical, comparing and array addressing.
Edit intent: clarity
Original:  BOPs include the integer and floating point computations of arithmetic, logical, comparing and array addressing.
Revised:  BOPs include the integer and floating point computations of arithmetic, comparing and array addressing.
Edit intent: clarity
Original:  The bias between the BOPS gap and the average user-perceived performance gap is no more than 11\%, and the BOPS efficiency of the Sort workload achieves 32\% .
Revised:  The bias between the BOPS gap and the average user-perceived performance gap is no more than 10\%. Second, the Sort workload can achieve 32\% .
Edit intent: clarity
Original:  Various entropy-based measures such as functional and spectral entropy have been proposed in brain network analysis.
Revised:  Various entropy-based measures such as functional and spectral entropies have been proposed in brain network analysis.
Edit intent: fluency
Original:  However, they are less widely used than traditional graph theoretic measures such as global and local efficiencies because  they are not well-defined on a graph or difficult to interpret its biological meaning.
Revised:  However, they are less widely used than traditional graph theoretic measures such as global and local efficiencies because either they are not well-defined on a graph or difficult to interpret its biological meaning.
Edit intent: coherence
Original:  It measures the exponential growth rate of the number of graph paths , based on the assumption that information flows through a graph forever.
Revised:  It measures the exponential growth rate of the number of paths in a graph, which is a relevant measure if information flows through a graph forever.
Edit intent: clarity
Original:  It measures the exponential growth rate of the number of graph paths , based on the assumption that information flows through a graph forever.
Revised:  It measures the exponential growth rate of the number of graph paths , based on the assumption that information flows through the graph forever.
Edit intent: fluency
Original:  We model the information propagation on a brain graph by the generalized Markov system associated to a new edge transition matrix.
Revised:  We model the information propagation on a graph by the generalized Markov system associated to a new edge transition matrix.
Edit intent: clarity
Original:  Moreover, its stationary distribution shows the information capacity of edge and the direction of information flow on a brain graph.
Revised:  Moreover, its stationary distribution shows the information capacity of edges and the direction of information flow on a brain graph.
Edit intent: fluency
Original:  In the clinical application, the volume entropy of brain graphs was significantly related to healthy normal aging from 20s to 60s.
Revised:  In brain imaging data application, the volume entropy of brain graphs was significantly related to healthy normal aging from 20s to 60s.
Edit intent: clarity
Original:  We compare their behavior to a random set of Twitter users, finding interesting differences in terms of the content they disseminate, the evolution of their account, as well as their general behavior and use of the Twitterplatform .
Revised:  We compare their behavior to a random set of Twitter users, finding interesting differences in terms of the content they disseminate, the evolution of their account, as well as their general behavior and use of Twitter .
Edit intent: clarity
Original:  Then, using a statistical model known as Hawkes Processes, we quantify the influence that these accounts had on the dissemination of news on social platforms such as Twitter, Reddit, and 4chan.
Revised:  Then, using Hawkes Processes, we quantify the influence that these accounts had on the dissemination of news on social platforms such as Twitter, Reddit, and 4chan.
Edit intent: clarity
Original:  Then, using a statistical model known as Hawkes Processes, we quantify the influence that these accounts had on the dissemination of news on social platforms such as Twitter, Reddit, and 4chan.
Revised:  Then, using a statistical model known as Hawkes Processes, we quantify the influence that trolls had on the dissemination of news on social platforms such as Twitter, Reddit, and 4chan.
Edit intent: clarity
Original:  Then, using a statistical model known as Hawkes Processes, we quantify the influence that these accounts had on the dissemination of news on social platforms such as Twitter, Reddit, and 4chan.
Revised:  Then, using a statistical model known as Hawkes Processes, we quantify the influence that these accounts had on the dissemination of news on social platforms like Twitter, Reddit, and 4chan.
Edit intent: fluency
Original:  Overall, our findings indicate that Russian troll accounts managed to stay active for long periods of time and to reach a substantial number of Twitter users with their messages .
Revised:  Overall, our findings indicate that Russian trolls managed to stay active for long periods of time and to reach a substantial number of Twitter users with their messages .
Edit intent: clarity
Original:  Overall, our findings indicate that Russian troll accounts managed to stay active for long periods of time and to reach a substantial number of Twitter users with their messages .
Revised:  Overall, our findings indicate that Russian troll accounts managed to stay active for long periods of time and to reach a substantial number of Twitter users with their tweets .
Edit intent: clarity
Original:  Given a black-box system with unknown dynamics and a linear temporal logic specification, the proposed algorithm is able to obtain an abstraction of the system with an arbitrarily small error and an arbitrarily large probability.
Revised:  Given a black-box system with unknown dynamics and a linear temporal logic specification, the proposed algorithm is able to obtain an abstraction of the system with an arbitrarily small error and a bounded probability.
Edit intent: clarity
Original:  Intriguingly, in mammalsthe receptors are replaced regularly  and the receptor distribution changes in response to olfactory experience.
Revised:  In mammals, the receptor neurons are replaced regularly and the receptor distribution changes in response to olfactory experience.
Edit intent: clarity
Original:  Intriguingly, in mammalsthe receptors are replaced regularly  and the receptor distribution changes in response to olfactory experience.
Revised:  Intriguingly, in mammalsthe receptors are replaced regularly , and the receptor distribution changes in response to olfactory experience.
Edit intent: fluency
Original:  Our model suggests that the receptor distribution is tuned to maximize the amount of information about the olfactory environment , in accordance with the efficient coding hypothesis.
Revised:  Our model suggests that the receptor distribution is tuned to efficiently encode information about the olfactory environment , in accordance with the efficient coding hypothesis.
Edit intent: clarity
Original:  We show that simple dynamical rules for neural birth and death processes converge to the predicted optimum .
Revised:  We show that simple dynamical rules for neural birth and death processes .
Edit intent: clarity
Original:  In mammals, the receptor neurons are replaced regularly, and the receptor distribution changes in response to olfactory experience.
Revised:  In mammals, the receptor neurons are replaced regularly, receptor abundances should continuously adapt to odor statistics. Indeed, experiments have found such changes in response to olfactory experience.
Edit intent: clarity
Original:  The observed changes are mysteriously context-dependent, with increased exposure to odorants leading variously to increased, decreased or unchanged abundance of activated receptors.
Revised:  These changes are mysteriously context-dependent, with increased exposure to odorants leading variously to increased, decreased or unchanged abundance of activated receptors.
Edit intent: clarity