wanyu/IteraTeR_v2 huggingface dataset:
Original:   We introduce Incremental Sequence Learning, a simple incremental approach to sequence learning.
Revised:  While the potential of incremental or curriculum learning to enhance learning is known, indiscriminate application of the principle does not necessarily lead to improvement, and it is essential therefore to know which forms of incremental or curriculum learning have a positive effect. This research contributes to that aim by comparing three instantiations of incremental or curriculum learning. We introduce Incremental Sequence Learning, a simple incremental approach to sequence learning.
Edit intent: coherence
Original:  To evaluate Incremental Sequence Learning and comparison methods, we introduce and make available a novel sequence learning task and data set: predicting and classifying MNIST pen stroke sequences , where the familiar handwritten digit images have been transformed to pen stroke sequences representing the skeletons of the digits .
Revised:  We introduce and make available a novel sequence learning task and data set: predicting and classifying MNIST pen stroke sequences , where the familiar handwritten digit images have been transformed to pen stroke sequences representing the skeletons of the digits .
Edit intent: coherence
Original:  To evaluate Incremental Sequence Learning and comparison methods, we introduce and make available a novel sequence learning task and data set: predicting and classifying MNIST pen stroke sequences , where the familiar handwritten digit images have been transformed to pen stroke sequences representing the skeletons of the digits .
Revised:  To evaluate Incremental Sequence Learning and comparison methods, we introduce and make available a novel sequence learning task and data set: predicting and classifying MNIST pen stroke sequences .
Edit intent: coherence
Original:  it displays lower variance and achieves sustained progress after all three comparison method have stopped improving  .
Revised:  it displays lower variance and achieves sustained progress after all three comparison methods have stopped improving .
Edit intent: fluency
Original: In this paper we present a simple unifying approach to prove several statements about intersecting and cross-intersecting families, including the Erd \H{o theorem, the Hilton-Milner theorem, a theorem due to Frankl concerning the size of intersecting families with bounded maximal degree, and versions of results on the sum of sizes of non-empty cross-intersecting families due to Frankl and Tokushige.
Revised: In this paper we present a simple unifying approach to prove several statements about intersecting and cross-intersecting families, including the Erd \H{o theorem, the Hilton--Milner theorem, a theorem due to Frankl concerning the size of intersecting families with bounded maximal degree, and versions of results on the sum of sizes of non-empty cross-intersecting families due to Frankl and Tokushige.
Edit intent: fluency
Original:  These graphs are quite often used in extremal set theory problems, however, the approach we develop proves to be particularly fruitful.
Revised:  These graphs are quite often used in Extremal Set Theory problems, however, the approach we develop proves to be particularly fruitful.
Edit intent: fluency
Original: In a previous article, an algorithm for discovering therapeutic targets in Boolean networks modeling disease mechanisms was introduced.
Revised: In a previous article, an algorithm for identifying therapeutic targets in Boolean networks modeling disease mechanisms was introduced.
Edit intent: clarity
Original: In a previous article, an algorithm for discovering therapeutic targets in Boolean networks modeling disease mechanisms was introduced.
Revised: In a previous article, an algorithm for discovering therapeutic targets in Boolean networks modeling pathological mechanisms was introduced.
Edit intent: clarity
Original:  In the present article, the updates made on this algorithm, named kali, are described.
Revised:  In the present article, the improvements made on this algorithm, named kali, are described.
Edit intent: clarity
Original:  However, like any computational tool, kali can predict but can not replace human expertise: it is an aid for coping with the complexity of biological systems  .
Revised:  However, like any computational tool, kali can predict but can not replace human expertise: it is a supporting tool for coping with the complexity of biological systems .
Edit intent: clarity
Original:  This case study is a published logic-based model of bladder tumorigenesis from which kali returns consistent results.
Revised:  The case study is a published logic-based model of bladder tumorigenesis from which kali returns consistent results.
Edit intent: fluency
Original:  Cardiovascular diseases (CVD) represent a major health issue in patients with schizophrenia and bipolar disorder (BD) . While many studies have shown increased CVD risks in schizophrenia and BD, the underlying mechanisms remain unclear.
Revised: Background: Cardiovascular diseases (CVD) represent a major health issue in patients with schizophrenia and bipolar disorder (BD) . While many studies have shown increased CVD risks in schizophrenia and BD, the underlying mechanisms remain unclear.
Edit intent: coherence
Original:  Cardiovascular diseases (CVD) represent a major health issue in patients with schizophrenia and bipolar disorder (BD) . While many studies have shown increased CVD risks in schizophrenia and BD, the underlying mechanisms remain unclear.
Revised:  Cardiovascular diseases (CVD) represent a major health issue in patients with schizophrenia and bipolar disorder (BD) , but the underlying mechanisms remain unclear.
Edit intent: coherence
Original:  Psychiatric medications such as anti-psychotics and various mood stabilizers are associated with metabolic syndrome and CVD.
Revised:  Psychiatric medications are associated with metabolic syndrome and CVD.
Edit intent: clarity
Original:   Using a polygenic risk score (PRS) approach, we investigated the associations of schizophrenia and BD with a comprehensive panel of cardiometabolic traits.
Revised:  Methods: Using a polygenic risk score (PRS) approach, we investigated the associations of schizophrenia and BD with a comprehensive panel of cardiometabolic traits.
Edit intent: fluency
Original:   Using a polygenic risk score (PRS) approach, we investigated the associations of schizophrenia and BD with a comprehensive panel of cardiometabolic traits.
Revised:  Using a polygenic risk score (PRS) approach, we investigated the associations of schizophrenia and BD with a panel of 13 cardiometabolic traits.
Edit intent: clarity
Original:  We found strong evidence of genetic predisposition to glucose metabolism abnormalities, type 2 diabetes and coronary artery disease in both schizophrenia and BD patients .
Revised:  We found strong evidence of genetic predisposition to glucose metabolism abnormalities, type 2 diabetes and coronary artery disease in both schizophrenia and BD .
Edit intent: clarity
Original:  Methods: Using a polygenic risk score (PRS) approach, we investigated the associations of schizophrenia and BD with a panel of 13 cardiometabolic traits.
Revised:  Methods: Using a polygenic risk score (PRS) approach, we investigated the associations of schizophrenia and BD with a panel of cardiometabolic traits.
Edit intent: clarity
Original:  On the other hand, we observed an inverse relationship between PRS of body mass index (BMI) and both schizophrenia and BD.
Revised:  On the other hand, we observed an inverse relationship between PRS of body mass index (BMI) with both schizophrenia and BD.
Edit intent: fluency
Original:  However, schizophrenia was associated with higher PRS of waist-hip ratio, especially after controlling for BMI.
Edit intent: coherence
Original:  Conclusions : Taken together, these results suggested shared genetic bases among cardiometabolic traits with schizophrenia and BD.
Revised:  Discussions : Taken together, these results suggested shared genetic bases among cardiometabolic traits with schizophrenia and BD.
Edit intent: clarity
Original: Background: Cardiovascular diseases (CVD) represent a major health issue in patients with schizophrenia and bipolar disorder (BD), but the  underlying mechanisms remain unclear.
Revised:  Cardiovascular diseases (CVD) represent a major health issue in patients with schizophrenia and bipolar disorder (BD), but the underlying mechanisms remain unclear.
Edit intent: coherence
Original: Random feature maps, such as random Fourier features,  have recently emerged as a powerful technique for speeding up and scaling the training of kernel-based methods  such as kernel ridge regression  .
Revised: Random feature maps, such as random Fourier features, which have recently emerged as a powerful technique for speeding up and scaling the training of kernel-based methods such as kernel ridge regression .
Edit intent: coherence
Original: Random feature maps, such as random Fourier features,  have recently emerged as a powerful technique for speeding up and scaling the training of kernel-based methods  such as kernel ridge regression  .
Revised: Random feature maps, such as random Fourier features, have recently emerged as a powerful technique for speeding up and scaling the training of kernel-based methods , such as kernel ridge regression .
Edit intent: fluency
Original:  We provide theoretical conditions on when this yields an effective preconditioner , and empirically evaluate our method and show it is highly effective for datasets of up to one million training examples.
Revised:  We provide theoretical conditions on when this yields an effective preconditioner . We empirically evaluate our method and show it is highly effective for datasets of up to one million training examples.
Edit intent: coherence
Original:  Here we study sketching methods for regularized variants of linear regression, low rank approximations , and canonical correlation analysis.
Revised:  Here we study sketching methods for regularized variants of linear regression, low rank approximation , and canonical correlation analysis.
Edit intent: fluency
Original: Deep learning frameworks have achieved overwhelming superiority in many fields of pattern recognition in recent years .
Revised: Deep learning frameworks have recently achieved superior performance in many pattern recognition problems .
Edit intent: clarity
Original:  However, the application of deep learning frameworks in image steganalysis is still in its initial stage.
Revised:  However, adoption of deep learning frameworks in image steganalysis is still in its initial stage.
Edit intent: clarity
Original:  However, the application of deep learning frameworks in image steganalysis is still in its initial stage.
Revised:  However, the application of deep learning in image steganalysis is still in its initial stage.
Edit intent: clarity
Original:  In this paper we firstly proved that the convolution phase and the quantization & truncation phase  are not learnable for deep neural networks.
Revised:  In this paper we firstly proved that the convolution phase and the quantization & truncation phase are not learnable in deep convolutional neural networks.
Edit intent: clarity
Original:  Then on the basis of the theoretical analysis, we proposed a new hybrid deep-learning framework for JPEG steganalysis, which is made up of two hybrid parts .
Revised:  Based on theoretical analysis, we proposed a new hybrid deep-learning framework for JPEG steganalysis, which is made up of two hybrid parts .
Edit intent: coherence
Original:  Then on the basis of the theoretical analysis, we proposed a new hybrid deep-learning framework for JPEG steganalysis, which is made up of two hybrid parts .
Revised:  Then on the basis of the theoretical analysis, our proposed framework involves two main stages .
Edit intent: clarity
Original:  The first part is hand-crafted .
Revised:  The first stage is hand-crafted .
Edit intent: clarity
Original:  The second part is a compound deep neural network containing three CNN subnets in which the model parameters are learnable during the training procedure.
Revised:  The second stage is a compound deep neural network containing three CNN subnets in which the model parameters are learnable during the training procedure.
Edit intent: clarity
Original:  The second part is a compound deep neural network containing three CNN subnets in which the model parameters are learnable during the training procedure.
Revised:  The second part is a compound deep neural network containing three deep subnets in which the model parameters are learnable during the training procedure.
Edit intent: clarity
Original:  The second part is a compound deep neural network containing three CNN subnets in which the model parameters are learnable during the training procedure.
Revised:  The second part is a compound deep neural network containing three CNN subnets in which the model parameters are learned in the training procedure.
Edit intent: clarity
Original:   We have conducted extensive experiments on  large-scale dataset extracted from ImageNet.
Revised:  We have conducted extensive experiments on a large-scale dataset extracted from ImageNet.
Edit intent: fluency
Original:  Primary dataset used in our experiments contains one million images, while our largest dataset contains ten million images.
Revised:  The primary dataset used in our experiments contains one million images, while our largest dataset contains ten million images.
Edit intent: fluency
Original:  The large-scale experiments show that our proposed framework outperforms all other steganalytic models( hand-crafted or deep-learning based) in the literature.
Revised:  The large-scale experiments show that the proposed framework outperforms all other steganalytic models( hand-crafted or deep-learning based) in the literature.
Edit intent: clarity
Original:  Furthermore, the experimental results revealed that our proposed framework possesses some great features, including well attacking-target transfer ability and insensitive to altered JPEG block artifact .
Revised:  Furthermore, we demonstrate that our framework is insensitive to JPEG blocking artifact alterations and the learned model can be easily transferred to a different attacking target. Both of these properties are of critical importance in practical applications. According to our best knowledge, This is the first report of deep learning in image steganalysis validated with large-scale test data .
Edit intent: coherence
Original:  We prove that the convolution phase and the quantization truncation phase of the rich models are not learnable in deep convolutional neural networks.
Revised:  truncation phase of the rich models are not learnable in deep convolutional neural networks.
Edit intent: coherence
Original:  Our experiments show that the proposed framework outperforms all other state-of-the-art steganalytic models either hand-crafted or learned using deep networks in the literature .
Revised:  Our experiments show that the integration of quantization and truncation into deep-learning steganalyzers do boost the detection performance by a clear margin .
Edit intent: clarity
Original:  Furthermore, we demonstrate that our framework is insensitive to JPEG blocking artifact alterations  and the learned model can be easily transferred to a different attacking target .
Revised:  Furthermore, we demonstrate that our framework is insensitive to JPEG blocking artifact alterations , and the learned model can be easily transferred to a different attacking target .
Edit intent: fluency
Original: The memristor has been regarded as a promising candidate of basic cell for the next-generation computation system . Compared to the traditional MOSFET device, the memristor is much more efficient in energy and area.
Revised: The memristor is promising to be the basic cell of next-generation computation system . Compared to the traditional MOSFET device, the memristor is much more efficient in energy and area.
Edit intent: clarity
Original: The memristor has been regarded as a promising candidate of basic cell for the next-generation computation system . Compared to the traditional MOSFET device, the memristor is much more efficient in energy and area.
Revised: The memristor has been regarded as a promising candidate of basic cell for the next-generation computation systems . Compared to the traditional MOSFET device, the memristor is much more efficient in energy and area.
Edit intent: fluency
Original: The memristor has been regarded as a promising candidate of basic cell for the next-generation computation system . Compared to the traditional MOSFET device, the memristor is much more efficient in energy and area.
Revised: The memristor has been regarded as a promising candidate of basic cell for the next-generation computation system . Compared to the traditional MOSFET device, the memristor is efficient over energy and area.
Edit intent: clarity
Original:  But the biggest obstacle for the memristorto replace the CMOS device is its precision, up till now, the highest precision acquired is 8-bits which can not reach the requirements of most numerical computation.
Revised:  But one of the biggest challenges faced with researchers is how to program a memristor's resistance precisely. Recently, an algorithm designed to save 8 valid bits in each memristor is proposed, but this is still not sufficient for precise computation.
Edit intent: coherence
Original:  In this paper, we propose a memristor crossbar-based computing system to conduct pretty high precision computation .
Revised:  In this paper, we propose a crossbar-based computing system to conduct pretty high precision computation .
Edit intent: clarity
Original:  The computation of each group can be calculated by memristor crossbar based structure . Analog-to-Digital Converters (ADCs) are  used to extract these valid most significant bits  .
Revised:  The computation of each group can be calculated by memristor crossbar based structure . Analog-to-Digital Converters (ADCs) are then used to extract these valid most significant bits .
Edit intent: coherence
Original:  The computation of each group can be calculated by memristor crossbar based structure . Analog-to-Digital Converters (ADCs) are  used to extract these valid most significant bits  .
Revised:  The computation of each group can be calculated by memristor crossbar based structure . Analog-to-Digital Converters (ADCs) are used to extract the valid bits, which are the most significant bits .
Edit intent: coherence
Original:  The computation of each group can be calculated by memristor crossbar based structure . Analog-to-Digital Converters (ADCs) are  used to extract these valid most significant bits  .
Revised:  The computation of each group can be calculated by memristor crossbar based structure . Analog-to-Digital Converters (ADCs) are used to extract these valid most significant bits of outputs .
Edit intent: clarity
Original: We address the question if a point inside a domain bounded by a simple closed arc spline is circularly visible from a specified arc from the boundary.
Revised: We address the question of whether a point inside a domain bounded by a simple closed arc spline is circularly visible from a specified arc from the boundary.
Edit intent: fluency
Original:  In particular, we present an easy to check criterion that implies that a point is not visible from a specified boundary arc.
Revised:  In particular, we present an easy-to-check criterion that implies that a point is not visible from a specified boundary arc.
Edit intent: fluency
Original:  In particular , we show a {\em super-polynomial gap} between the (information-theoretic) sample complexity and the  complexity of {\em any} Statistical Query algorithm for these problems .
Revised:  In particular , we show a {\em super-polynomial gap} between the (information-theoretic) sample complexity and the computational complexity of {\em any} Statistical Query algorithm for these problems .
Edit intent: clarity
Original:  In particular , we show a {\em super-polynomial gap} between the (information-theoretic) sample complexity and the  complexity of {\em any} Statistical Query algorithm for these problems .
Revised:  In particular , we show a {\em super-polynomial gap} between the (information-theoretic) sample complexity and the complexity of {\em any} Statistical Query algorithm for the problem .
Edit intent: clarity
Original:  Our SQ lower bound for Problem (1) implies that -- as far as SQ algorithms are concerned -- the computational complexity of learning GMMs is inherently exponential%DIFDELCMD < {\em %%% in the dimension of the latent space -- even though there is no such information-theoretic barrier .
Revised:  Our SQ lower bound for Problem (1) %DIFDELCMD < {\em %%% in the dimension of the latent space -- even though there is no such information-theoretic barrier .
Edit intent: clarity
Original:  Both our SQ lower bounds are attained via a unified moment-matching technique that may be useful in other contexts .
Revised:  Both our SQ lower bounds are attained via a unified moment-matching technique that is useful in other contexts .
Edit intent: clarity
Original:  Our lower bound technique also has implications for related inference problems, specifically for the problem of robust {\em  {\em testing {\em  } of an unknown mean Gaussian.
Revised:  Our lower bound technique also has implications for related inference problems, specifically for the problem of robust {\em {\em testing {\em } an unknown mean Gaussian.
Edit intent: clarity
Original:  Here we show an information-theoretic lower bound which separates the sample{\em   complexity of the robust testing problem from its{\em   non-robust variant.
Revised:  Here we show an information-theoretic sample lower bound that scales{\em complexity of the robust testing problem from its{\em non-robust variant.
Edit intent: clarity
Original:  Here we show an information-theoretic lower bound which separates the sample{\em   complexity of the robust testing problem from its{\em   non-robust variant.
Revised:  Here we show an information-theoretic lower bound which separates the sample{\em complexity of the corresponding robust{\em non-robust variant.
Edit intent: clarity
Original:  Here we show an information-theoretic lower bound which separates the sample{\em   complexity of the robust testing problem from its{\em   non-robust variant.
Revised:  Here we show an information-theoretic lower bound which separates the sample{\em complexity of the robust testing problem from its{\em learning non-robust variant.
Edit intent: fluency
Original: Researchers in the field of computational physics , chemistry, and materials science are regularly posed with the challenge of managing large and heterogeneous data spaces.
Revised: Researchers in the field of materials science , chemistry, and materials science are regularly posed with the challenge of managing large and heterogeneous data spaces.
Edit intent: clarity
Original: Researchers in the field of computational physics , chemistry, and materials science are regularly posed with the challenge of managing large and heterogeneous data spaces.
Revised: Researchers in the field of computational physics , chemistry, and computational physics are regularly posed with the challenge of managing large and heterogeneous data spaces.
Edit intent: clarity
Original:  The amount of data increases in lockstep with computational efficiency multiplied by the amount of available computational resources, which shifts the bottleneck within the scientific process from data acquisition to data post-processing and analysis.
Revised:  The amount of data increases in lockstep with computational efficiency multiplied by the amount of available computational resources, which shifts the bottleneck in the scientific process from data acquisition to data post-processing and analysis.
Edit intent: clarity