wanyu/IteraTeR_full_sent huggingface dataset:
Original: We study an offline multi-action policy learningalgorithm based on doubly robust estimators from causal inference settings, using argmax linear policy function classes. For general policy classes, we establish the connection of the regret bound with a generalization of the VC dimension in higher dimensions and specialize this to prove optimal regret bounds for the argmax linear function class{\epsilon})) iteration complexity, where each iteration consists of an SDP feasibility problem and a Newton update using the Nesterov-Todd direction, respectively} .
Revised: Diagonal preconditioning has been a staple technique in optimization and machine learning. It often reduces the condition number of the design or Hessian matrix it is applied to, thereby speeding up convergence. However, rigorous analyses of how well various diagonal preconditioning procedures improve the condition number of the preconditioned matrix and how that translates into improvements in optimization are rare. In this paper, we first provide an analysis of a popular diagonal preconditioning technique based on column standard deviation and its effect on the condition number using random matrix theory. Then we identify a class of design matrices whose condition numbers can be reduced significantly by this procedure. We then study the regret bound with a generalization of the VC dimension in higher dimensions and specialize this to prove optimal regret bounds for the argmax linear function class{\epsilon})) iteration complexity, where each iteration consists of an SDP feasibility problem and a Newton update using the Nesterov-Todd direction, respectively} .
Edit intent: meaning-changed
Original:  For general policy classes, we establish the connection of the regret bound with a generalization of the VC dimension in higher dimensions and specialize this to prove optimal regret bounds for the argmax linear function class{\epsilon})) iteration complexity, where each iteration consists of an SDP feasibility problem and a Newton update using the Nesterov-Todd direction, respectively} .
Revised:  For general policy classes, we establish the connection of the problem of optimal diagonal preconditioning to improve the condition number of any full-rank matrix and provide a bisection algorithm and a potential reduction algorithm with O(\log(\frac{1{\epsilon})) iteration complexity, where each iteration consists of an SDP feasibility problem and a Newton update using the Nesterov-Todd direction, respectively} .
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Original:  We also study various optimization approaches to solving the non-smooth non-convex problem associated with the argmax linear class, including convex relaxation, softmax relaxation, and Bayesian optimization. We find that Bayesian optimization with the Gradient-based Adaptive Stochastic Search (GASS)algorithm consistently outperforms convex relaxation in terms of policy value, and is much faster compared to softmax relaxation.
Edit intent: coherence
Original:  Finally, we apply the algorithms to simulated and warfarin dataset. On the warfarin dataset the offline algorithm trained using only a subset of features achieves state-of-the-art accuracy .
Revised:  Finally, we extend the optimal diagonal preconditioning algorithm to an adaptive setting and compare its empirical performance at reducing the condition number and speeding up convergence for regression and classification problems with that of another adaptive preconditioning technique, namely batch normalization, that is essential in training machine learning models .
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Original:  We find that COVID-19 has a strong infectious force if left unchecked, with a doubling time of under 3 days. However it is not particularly virulent. Our methods may be of generalinterest .
Revised:  Our methods reveal significant asymptomatic (hidden) infection, a lag of about 10 days, and we quantitatively confirm that the infectious force is strong with about a 0.14\% transition from mild to serious infection. Our methods are efficient, robust and general, being agnostic to the specific virus and applicable to different populations or cohorts .
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Original:  Computationally, graph burning is hard. It has already been proved that burning of path forests, spider graphs, and trees with maximum degree three are NP-Complete.
Revised:  Optimal burning of general graphs is NP-Hard. There is a 3-approximation algorithm to burn general graphs where as better approximation factors are there for many sub classes. Here we study burning of grids; provide a lower bound for burning arbitrary grids and a 2-approximation algorithm for burning square grids. On the other hand, burning path forests, spider graphs, and trees with maximum degree three are NP-Complete.
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Original: Historians split recent times into three industrial revolutions: mechanization (steam power), technical (electric power and mass production), and digital (computing and microelectronics). The world of NDEhas a parallel: tools to sharpen human senses, wave application to view inside the components, and digital processing and automation. As the industry goes through the fourth revolution powered by interconnections and enhanced digitalization, NDE is also on a new horizon : NDE 4.0 with information transparency, technical assistance, autonomous, and decentralized decisions.
Revised: Cyber technologies are offering new horizons for quality control in manufacturing and safety assurance in-service of physical assets. The line between non-destructive evaluation (NDE) and Industry 4.0 is getting blurred since both are sensory data-driven domains. This multidisciplinary approach has led to the emergence of a new capability : NDE 4.0 with information transparency, technical assistance, autonomous, and decentralized decisions.
Edit intent: coherence
Original:  As the industry goes through the fourth revolution powered by interconnections and enhanced digitalization, NDE is also on a new horizon : NDE 4.0 with information transparency, technical assistance, autonomous, and decentralized decisions. Technologies such as IIoT, AR, AI, 5G, and blockchains are opening up new inspection and safety assurance possibilities in every industrial sector. To establish a proper foundation for technical research on this emerging subject, it is important to first research the perception of stakeholders , misconceptions around NDE, the value proposition of NDE 4.0 , the challenges and opportunities, and even outline a process to pursue it.
Revised:  As the industry goes through the fourth revolution powered by interconnections and enhanced digitalization, NDE is also on a new horizon : NDE 4.0 . The NDT community is coming together once again to define the purpose, chart the process, and address the adoption of emerging technologies. In this paper, the authors have taken a design thinking approach to spotlight proper objectives for research on this emerging subject, it is important to first research the perception of stakeholders , misconceptions around NDE, the value proposition of NDE 4.0 , the challenges and opportunities, and even outline a process to pursue it.
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Original:  To establish a proper foundation for technical research on this emerging subject, it is important to first research the perception of stakeholders , misconceptions around NDE, the value proposition of NDE 4.0 , the challenges and opportunities, and even outline a process to pursue it.
Revised:  To establish a proper foundation for technical research on this subject. It begins with qualitative research on twenty different perceptions of stakeholders and misconceptions around the current state of NDE. The interpretation is used to define ten value propositions or use cases under "NDE for Industry 4.0 , the challenges and opportunities, and even outline a process to pursue it.
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Original:  To establish a proper foundation for technical research on this emerging subject, it is important to first research the perception of stakeholders , misconceptions around NDE, the value proposition of NDE 4.0 , the challenges and opportunities, and even outline a process to pursue it. This paper presents a critical view of current thinking and major use cases for NDE 4.0 - both Industry 4.0 for NDE and NDE 4.0 for Industry;
Revised:  To establish a proper foundation for technical research on this emerging subject, it is important to first research the perception of stakeholders , misconceptions around NDE, the value proposition of NDE 4.0 " and " Industry 4.0 for NDE and NDE 4.0 for Industry;
Edit intent: coherence
Original:  This paper presents a critical view of current thinking and major use cases for NDE 4.0 - both Industry 4.0 for NDE and NDE 4.0 for Industry; all leading up to a safer, cheaper, faster, and reliable inspection eco-system.
Revised:  This paper presents a critical view of current thinking and major use cases for NDE 4.0 - both Industry 4.0 for NDE and NDE 4.0 for NDE" leading up to a safer, cheaper, faster, and reliable inspection eco-system.
Edit intent: coherence
Original:  all leading up to a safer, cheaper, faster, and reliable inspection eco-system. It also dwells upon challenges such as skills relevance, adoption, and leadership in the cyber-physical world.
Revised:  all leading up to the clarity of purpose for NDE 4.0, enhanced safety and economic value for stakeholders. To pursue this worthy cause, the paper delves into some of the top adoption challenges, and proposes a journey of managed innovation, conscious skills development, and a new form of leadership required to succeed in the cyber-physical world.
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Original:  In some settings, this provides an alternative spectral algorithm to achieve constant factor approximation for  survivable network design  , and partially answers a question of Bansal about survivable network design with concentration property.
Revised:  In some settings, this provides an alternative spectral algorithm to achieve constant factor approximation for the classical survivable network design , and partially answers a question of Bansal about survivable network design with concentration property.
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Original: A principal component analysis of the TCGA data for 15 cancer localizations leads to the following results: The effective dimensionality of the region spanned by normal tissues and tumors in the gene expression state space is around 10 (out of a huge initial space with more than 60000 genes). Gene expression profiles uniquely distinguish between normal and cancer states. For any given tissue, the cancer state is a kind of attractor in the gene expression state space with at least 2500 highly differentially-expressed genes and a power-like tail in the expression distribution function.
Revised: A principal component analysis of the TCGA data for 15 cancer localizations unveils the following qualitative facts about tumors: 1) The state of a tissue in gene expression space may be described by a few variables. In particular, there is a single variable describing the progression from a normal tissue to a tumor. 2) Each cancer localization is characterized by a gene expression profile, in which genes have specific weights in the definition of the cancer state. There are no less than 2500 highly differentially-expressed genes and a power-like tail in the expression distribution function.
Edit intent: clarity
Original:  For any given tissue, the cancer state is a kind of attractor in the gene expression state space with at least 2500 highly differentially-expressed genes and a power-like tail in the expression distribution function.
Revised:  For any given tissue, the cancer state is a kind of attractor in the gene expression state space with at least 2500 differentially-expressed genes and a power-like tail in the expression distribution function.
Edit intent: clarity
Original:  For any given tissue, the cancer state is a kind of attractor in the gene expression state space with at least 2500 highly differentially-expressed genes and a power-like tail in the expression distribution function.
Revised:  For any given tissue, the cancer state is a kind of attractor in the gene expression state space with at least 2500 highly differentially-expressed genes , which lead to power-like tail in the expression distribution function.
Edit intent: coherence
Original:  For any given tissue, the cancer state is a kind of attractor in the gene expression state space with at least 2500 highly differentially-expressed genes and a power-like tail in the expression distribution function.
Revised:  For any given tissue, the cancer state is a kind of attractor in the gene expression state space with at least 2500 highly differentially-expressed genes and a power-like tails in the expression distribution function.
Edit intent: fluency
Original:  For any given tissue, the cancer state is a kind of attractor in the gene expression state space with at least 2500 highly differentially-expressed genes and a power-like tail in the expression distribution function. With regard to this 4 \% quantile of genes, pairs of localizations share between 314 and 1889 genescharacterizing the tumor state.
Revised:  For any given tissue, the cancer state is a kind of attractor in the gene expression state space with at least 2500 highly differentially-expressed genes and a power-like tail in the expression distribution functions. 3) Tumors in different localizations share hundreds or even thousands of differentially expressed genes. There are 6 genes common to the 15 studied tumor localizations. 4 \% quantile of genes, pairs of localizations share between 314 and 1889 genescharacterizing the tumor state.
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Original:  With regard to this 4 \% quantile of genes, pairs of localizations share between 314 and 1889 genescharacterizing the tumor state. The gene expression landscape shows distances between pairs of tumor localizations which inversely correlate with the number of shared genes. The most significantly altered top pathway in the cancer state is related to the "Extracellular URLanization" .
Revised:  With regard to this 4 \% quantile of genes, pairs of localizations share between 314 and 1889 genescharacterizing the tumor region is a kind of attractor. Tumors in advanced stages converge to this region independently of patient age or genetic variability. 5) There is a landscape of cancer in gene expression space with an approximate border separating normal tissues from tumors .
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Original:  At the time of writing  , the number of fatalities in Italy is expected to be 6000, and the crisis ends before April 15  , 2020.
Revised:  At the time of writing , the number of fatalities in Italy is expected to be 6000, and the crisis ends before April 15 , 2020. In this new version, we discuss what changed in the two weeks which passed since then. The trend changed drastically on March 17, 2020, when the Italian health system reached its capacity limit. Without this limit, probably 3500 more people would have died. Instead, due to the limitations, 17.000 people are expected to die now, which is a five-fold increase. The predicted end of the crisis now shifted to May 8 , 2020.
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Original: Researching the conditions for the emergence of life -- not necessarily as it is, but as it could be -- is one of the main goals of Artificial Life. Answering this question requires a model that can first explain the emergence of evolvable units , namely, structures that (1) preserve themselves in time (2) self-reproduce and (3) can tolerate a certain amount of variation when reproducing.
Revised: Researching the conditions for the emergence of evolvable units must display emerging structures that (1) preserve themselves in time (2) self-reproduce and (3) can tolerate a certain amount of variation when reproducing.
Edit intent: clarity
Original:  Answering this question requires a model that can first explain the emergence of evolvable units , namely, structures that (1) preserve themselves in time (2) self-reproduce and (3) can tolerate a certain amount of variation when reproducing.
Revised:  Answering this question requires a model that can first explain the emergence of evolvable units , namely, structures that (1) preserve themselves in time (2) self-reproduce and (3) tolerate a certain amount of variation when reproducing.
Edit intent: coherence
Original:  These patterns involve autopoietic structures that maintain URLanisation, recursive ones that grow in linear chains or binary-branching trees, and most notably, patterns able to reproduce themselves, duplicating their number at each generation.
Revised:  These patterns include autopoietic structures that maintain URLanisation, recursive ones that grow in linear chains or binary-branching trees, and most notably, patterns able to reproduce themselves, duplicating their number at each generation.
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Original: In this article, taking into account distributed delay and multidimensional L\'evy disturbances, wepresent an exhaustive study on the dynamic of the Susceptible-Infected-Removed (SIR ) model .
Revised: Recently, emerging epidemics like COVID-19 and its variants require predictive mathematical models to implement suitable responses in order to limit their negative and profound impact on society. The SIR (Susceptible-InfectedRemoved) system is a straightforward mathematical formulation to model the dissemination of many infectious diseases. The present paper reports novel theoretical and analytical results for a perturbed version of an SIR model with Gamma-distributed delay. Notably, our epidemic model is represented by It\^o-L'evy stochastic differential equations in order to simulate sudden and unexpected external phenomena. By using some new and ameliorated mathematical approaches, we study the dynamic of the Susceptible-Infected-Removed (SIR ) model .
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Original: In this article, taking into account distributed delay and multidimensional L\'evy disturbances, wepresent an exhaustive study on the dynamic of the Susceptible-Infected-Removed (SIR ) model . We aim to ameliorate the mathematical tools to obtain the long-run characteristics of the perturbed delayed model.
Revised: In this article, taking into account distributed delay and multidimensional L\'evy disturbances, wepresent an exhaustive study on the long-run characteristics of the perturbed delayed model.
Edit intent: coherence
Original:  Numerical simulations on different L\'evy disturbances are carried out to verify the obtained theoretical results .
Revised:  One of the most interesting results is that the dynamics of the stochastic model are closely related to the intensities of white noises and L'evy jumps, which can give us a good insight into the evolution of the epidemic in some unexpected situations. Our work complements the results of some previous investigations and provides a new approach to predict and analyze the dynamic behavior of epidemics with distributed delay. For illustrative purposes, numerical examples are presented for checking the theoretical study
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Original:  We use the Adaptive Multi-Factor (AMF) model estimated by the Groupwise Interpretable Basis Selection (GIBS) algorithm to find the basis assets significantly related to each of the portfolios.
Revised:  We use the Adaptive Multi-Factor (AMF) model estimated by the Groupwise Interpretable Basis Selection (GIBS) algorithm to find those basis assets significantly related to each of the portfolios.
Edit intent: clarity
Original:  We use the Adaptive Multi-Factor (AMF) model estimated by the Groupwise Interpretable Basis Selection (GIBS) algorithm to find the basis assets significantly related to each of the portfolios. The AMF results show that the two portfolios load on very different factors, which indicates that the volatility is not an independent measure of risk, but are related to the basis assets and risk factorsin the related industries.
Revised:  We use the Adaptive Multi-Factor (AMF) model estimated by the Groupwise Interpretable Basis Selection (GIBS) algorithm to find the basis assets significantly related to low and high volatility portfolios. These two portfolios load on very different factors, which indicates that the volatility is not an independent measure of risk, but are related to the basis assets and risk factorsin the related industries.
Edit intent: clarity
Original:  The AMF results show that the two portfolios load on very different factors, which indicates that the volatility is not an independent measure of risk, but are related to the basis assets and risk factorsin the related industries.
Revised:  The AMF results show that the two portfolios load on very different factors, indicating that volatility is not an independent measure of risk, but are related to the basis assets and risk factorsin the related industries.
Edit intent: coherence
Original:  The AMF results show that the two portfolios load on very different factors, which indicates that the volatility is not an independent measure of risk, but are related to the basis assets and risk factorsin the related industries.
Revised:  The AMF results show that the two portfolios load on very different factors, which indicates that the volatility is not an independent risk, but are related to the basis assets and risk factorsin the related industries.
Edit intent: clarity
Original:  The AMF results show that the two portfolios load on very different factors, which indicates that the volatility is not an independent measure of risk, but are related to the basis assets and risk factorsin the related industries. It is the performance of the loaded factors that results in the low-volatility anomaly.
Revised:  The AMF results show that the two portfolios load on very different factors, which indicates that the volatility is not an independent measure of risk, but that it's related to existing risk factors.
Edit intent: clarity
Original:  The out-performance of the low-volatility portfolio may not because of its low-risk (which contradicts the risk-premium theory) , but because of the out-performance of the risk factorsthe low-volatility portfolio is loaded on. Also, we compare the AMF model with the traditional Fama-French 5-factor (FF5) model in various aspects, which shows the superior performance of the AMF model over FF5 in many perspectives .
Revised:  The out-performance of the low-volatility portfolio is due to the (equilibrium) performance of these loaded risk factors. The AMF model outperforms the Fama-French 5-factor (FF5) model in various aspects, which shows the superior performance of the AMF model over FF5 in many perspectives .
Edit intent: clarity
Original:  Our results suggest that the disease propagation is highly related to population migration from Hubei resembling a L\'{e}vy flight which is characteristic of human mobility . Our results also suggest that the disease spread in a city in China is characterized by two-stages process.
Revised:  Our results suggest that the disease propagation is highly related to population migration from Hubei resembling a L\'{e}vy flight which is characteristic of human mobility and thus could be controlled by efficient quarantines. Since quarantine is usually applied on a city level, more insight can be obtained in analyzing the epidemic in cities. Our results suggest that the disease spread in a city in China is characterized by two-stages process.
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Original:  At early times, at order of few days, the infection rate in the city is almost constant probably due to the lack of means to detect infected individuals before infection signs are observed and at later times it decays approximately exponentially due to quarantines.
Revised:  At early times, at order of few days, the infection rate in the city is close to constant probably due to the lack of means to detect infected individuals before infection signs are observed and at later times it decays approximately exponentially due to quarantines.
Edit intent: clarity