wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Treating carotenoid molecules as transmitters and chlorophylls as receivers, a throughput of about 1 Gbit/s is achievable with  bit error rate below 10-3 , average transmission delays about 20 ps, and energy consumption c.a. 2.0x10^-18 J per bit.
Revised:  Treating carotenoid molecules as transmitters and chlorophylls as receivers, a throughput of about 1 Gbit/s is achievable with bit error rate below 10-3 , average transmission delays about 20 ps, and energy consumption c.a. 2.0x10^-18 J / bit.
Edit intent: fluency
Original: We study a general version of the problem of online learning under binary feedback: there is a hidden function f : \mathcal{X \rightarrow Y in a certain hypothesis class H. A learner is given adversarially chosen inputs (contexts) x_t \in X and is asked to submit a guess y_t \in Y for the value f(x_t).
Revised:  \rightarrow Y in a certain hypothesis class H. A learner is given adversarially chosen inputs (contexts) x_t \in X and is asked to submit a guess y_t \in Y for the value f(x_t).
Edit intent: coherence
Original:  We provide a }  O(d ^2) regret bound where d is the covering dimension of the hypothesis class. The algorithms are based on a novel technique which we call Steiner potential since in the linear case it reduces to controlling the value of the Steiner polynomial of a convex region at various scales.
Revised:  We provide a } O(d \log \log T + d \log d) regret which matches the \Omega(d \log \log T) lower bound up to the d \log d additive factor. If we replace pricing loss by the symmetric loss, we obtain an algorithm with nearly optimal regret of O(d \log d) matching the \Omega(d) lower bound up to \log d. These algorithms are based on a novel technique which we call Steiner potential since in the linear case it reduces to controlling the value of the Steiner polynomial of a convex region at various scales.
Edit intent: meaning-changed
Original:  We also show that this new technique provides optimal regret (up to log factors) in the linear case (i. e. the original contextual search problem), improving the previously known bound of \rightarrow Y in a certain hypothesis class H. We provide a generic algorithm with } O(d ^4) to O(d \log d) .
Revised:  The Steiner polynomial is a degree d polynomial with intrinsic volumes as the coefficients. We also study a generalized version of contextual search where the hidden linear function over the Euclidean space is replaced by a hidden function f : \mathcal{X \rightarrow Y in a certain hypothesis class H. We provide a generic algorithm with } O(d ^4) to O(d \log d) .
Edit intent: meaning-changed
Original:  We also show that this new technique provides optimal regret (up to log factors) in the linear case (i. e. the original contextual search problem), improving the previously known bound of \rightarrow Y in a certain hypothesis class H. We provide a generic algorithm with } O(d ^4) to O(d \log d) . Finally, we extend these results to a \tilde{O} noisy feedback model, where each round our feedback is flipped with  fixed probability p < 1/2.
Revised:  We also show that this new technique provides optimal regret (up to log factors) in the linear case (i. e. the original contextual search problem), improving the previously known bound of \rightarrow Y in a certain hypothesis class H. We provide a generic algorithm with } O(d ^2) regret where d is the covering dimension of this class. This leads in particular to a \tilde{O} noisy feedback model, where each round our feedback is flipped with fixed probability p < 1/2.
Edit intent: meaning-changed
Original:  Finally, we extend these results to a \tilde{O} noisy feedback model, where each round our feedback is flipped with  fixed probability p < 1/2.
Revised:  Finally, we extend these results to a \tilde{O}(s^2) regret algorithm for linear contextual search if the linear function is guaranteed to be s-sparse. Finally we also extend our results to the noisy feedback model, where each round our feedback is flipped with fixed probability p < 1/2.
Edit intent: meaning-changed
Original:  Given consumption and healthcare spending plans, Epstein-Zin utilities are defined over an agent's random lifetime, partially controllable by the agent as healthcare reduces Gompertz' natural growthrate of mortality.
Revised:  Given consumption and healthcare spending plans, Epstein-Zin utilities are defined over an agent's random lifetime, partially controllable by the agent as healthcare reduces mortality growth. To the best of our knowledge, this is the first time Epstein-Zin utilities are formulated on a controllable random horizon, via an infinite-horizon backward stochastic differential equation with superlinear growth. A new comparison result is established for the uniqueness of associated utility value processes.
Edit intent: meaning-changed
Original:  Compared with classical Epstein-Zin utility maximization, the additional controlled mortality processcomplicates the uniqueness of Epstein-Zin utilities and verification arguments. A combination of probabilistic arguments and analysis of the HJB equation are required to resolve the challenges .
Revised:  The verification argument features a delicate containment of the growth of the controlled morality process, which is unique to our framework, relying on a combination of probabilistic arguments and analysis of the HJB equation are required to resolve the challenges .
Edit intent: clarity
Original:  To apply ARL, we turn the well-studied single-agent model of Avellaneda and Stoikov [2008] into a discrete-time zero-sum game between a market maker and adversary , a proxy for other market participants who would like to profit at the market maker's expense.
Revised:  To apply ARL, we turn the well-studied single-agent model of Avellaneda and Stoikov [2008] into a discrete-time zero-sum game between a market maker and adversary . The adversary acts as a proxy for other market participants who would like to profit at the market maker's expense.
Edit intent: meaning-changed
Original:  To apply ARL, we turn the well-studied single-agent model of Avellaneda and Stoikov [2008] into a discrete-time zero-sum game between a market maker and adversary , a proxy for other market participants who would like to profit at the market maker's expense.
Revised:  To apply ARL, we turn the well-studied single-agent model of Avellaneda and Stoikov [2008] into a discrete-time zero-sum game between a market maker and adversary , a proxy for other market participants that would like to profit at the market maker's expense.
Edit intent: fluency
Original:  We empirically compare two conventional single-agent RL agents with ARL, and show that our ARL approach leads to: 1) the emergence of naturally risk-averse behaviour without constraints or domain-specific penalties;
Revised:  We empirically compare two conventional single-agent RL agents with ARL, and show that our ARL approach leads to: 1) the emergence of risk-averse behaviour without constraints or domain-specific penalties;
Edit intent: clarity
Original:  This result is applied to the FitzHugh-Nagumo model for neuronal dynamics, and the effectiveness is confirmed by numerical simulations, where we properly take account of the change of the equilibrium point.
Revised:  This result is applied to the FitzHugh-Nagumo model for neuronal dynamics, and the effectiveness is confirmed by numerical simulations, where we properly care for the change of the equilibrium point.
Edit intent: clarity
Original: We study the problem of minimum enclosing parallelogram with outliers, which asks to find, for a given set of n planar points, a parallelogram with minimum area that encloses at least (n-t) points, where the remaining points are regarded as outliers.
Revised: We study the problem of minimum enclosing parallelogram with outliers, which asks to find, for a given set of n planar points, a parallelogram with minimum area that encloses at least (n-t) points, where the uncovered points are regarded as outliers.
Edit intent: clarity
Original:  We further propose an sampling algorithm with runtime O(n+poly(n, t, 1/\epsilon)), which with high probability finds a parallelogram covering at least (1-\epsilon)(n-t) and at most (n-t+1) points with area no more than the exact optimal value .
Revised:  We further propose an sampling algorithm with runtime O(n+poly(n, t, 1/\epsilon)), which with high probability finds a parallelogram covering at least (1-\epsilon)(n-t) and at most (n-t+1) points with at most the exact optimal value .
Edit intent: clarity
Original:  We further propose an sampling algorithm with runtime O(n+poly(n, t, 1/\epsilon)), which with high probability finds a parallelogram covering at least (1-\epsilon)(n-t) and at most (n-t+1) points with area no more than the exact optimal value .
Revised:  We further propose an sampling algorithm with runtime O(n+poly(n, t, 1/\epsilon)), which with high probability finds a parallelogram covering at least (1-\epsilon)(n-t) and at most (n-t+1) points with area no more than the exact optimal area .
Edit intent: clarity
Original: We study the problem of minimum enclosing parallelogram with outliers, which asks to find, for a given set of n planar points, a parallelogram with minimum area that encloses at least (n-t) points , where the uncovered points are regarded as outliers.
Revised: We study the problem of minimum enclosing rectangle with outliers, which asks to find, for a given set of n planar points, a parallelogram with minimum area that encloses at least (n-t) points , where the uncovered points are regarded as outliers.
Edit intent: clarity
Original: We study the problem of minimum enclosing parallelogram with outliers, which asks to find, for a given set of n planar points, a parallelogram with minimum area that encloses at least (n-t) points , where the uncovered points are regarded as outliers.
Revised: We study the problem of minimum enclosing parallelogram with outliers, which asks to find, for a given set of n planar points, a rectangle with minimum area that encloses at least (n-t) points , where the uncovered points are regarded as outliers.
Edit intent: clarity
Original: We study the problem of minimum enclosing parallelogram with outliers, which asks to find, for a given set of n planar points, a parallelogram with minimum area that encloses at least (n-t) points , where the uncovered points are regarded as outliers.
Revised: We study the problem of minimum enclosing parallelogram with outliers, which asks to find, for a given set of n planar points, a parallelogram with minimum area that encloses at least (n-t) points . The uncovered points are regarded as outliers.
Edit intent: coherence
Original:  We present an exact algorithm with O( k^{2 +  n^2\log n) runtime and O(kt^{2 , assuming that no three points lie on the same line.
Revised:  We present an exact algorithm with O( k^{2 + kt^2\log{n n^2\log n) runtime and O(kt^{2 , assuming that no three points lie on the same line.
Edit intent: meaning-changed
Original:  We further propose an sampling algorithm with runtime O(n+poly(n, t, 1/\epsilon)), which with high probability finds a parallelogram covering at least (1-\epsilon)(n-t ) and at most (n-t+1 ) points with at most the exact optimal area.
Revised:  We further propose a sampling algorithm with runtime O(n+poly(n, t, 1/\epsilon)), which with high probability finds a parallelogram covering at least (1-\epsilon)(n-t ) and at most (n-t+1 ) points with at most the exact optimal area.
Edit intent: fluency
Original:  We further propose an sampling algorithm with runtime O(n+poly(n, t, 1/\epsilon)), which with high probability finds a parallelogram covering at least (1-\epsilon)(n-t ) and at most (n-t+1 ) points with at most the exact optimal area.
Revised:  We further propose an sampling algorithm with runtime O(n+poly(n, t, 1/\epsilon)), which with high probability finds a rectangle covering at least (1-\epsilon)(n-t ) and at most (n-t+1 ) points with at most the exact optimal area.
Edit intent: meaning-changed
Original:  We further propose an sampling algorithm with runtime O(n+poly(n, t, 1/\epsilon)), which with high probability finds a parallelogram covering at least (1-\epsilon)(n-t ) and at most (n-t+1 ) points with at most the exact optimal area.
Revised:  We further propose an sampling algorithm with runtime O(n+poly(n, t, 1/\epsilon)), which with high probability finds a parallelogram covering at least (1-\epsilon)(n-t ) points with at most the exact optimal area.
Edit intent: meaning-changed
Original:  For the problems, we need to find either a strong optimal solution or a set of all possible weak solutions. A strong solution of the problem is a solution that is optimal for all possible values of the objective function's coefficients that belong to predefined intervals. A weak solution is a solution that is optimal for some of the possible values of the coefficients. We characterize the strong solutions for considered problems. We give a generalization of the greedy algorithm for the case of interval objective function.
Revised:  We give a generalization of the greedy algorithm for the case of interval objective function.
Edit intent: coherence
Original:  We give a generalization of the greedy algorithm for the case of interval objective function. For the discrete optimization problems that we consider, the algorithm gives a set of all possible greedy solutions and the set of all possible values of the objective function for the solutions.
Revised:  We give a generalization of the greedy algorithm for the problems. Using the algorithm, we obtain the set of all possible greedy solutions and the set of all possible values of the objective function for the solutions.
Edit intent: clarity
Original: In this paper  we propose a generalization of the Deep Galerking Method (DGM) of \mbox{%DIFAUXCMD dgm Path-Dependent Partial Differential Equations (PPDEs).
Revised: In this paper , we propose a generalization of the Deep Galerking Method (DGM) of \mbox{%DIFAUXCMD dgm Path-Dependent Partial Differential Equations (PPDEs).
Edit intent: fluency
Original:  These equations firstly appeared in the seminal work of \mbox{%DIFAUXCMD fito_dupire  , where the functional It\^o calculus was developed to deal with path-dependent financial derivatives contracts  ]  . The method, which we call Path-Dependent DGM (PDGM), consists of using a combination of feed-forward and Long Short-Term Memory architectures to model the solution of the PPDE.
Revised:  These equations firstly appeared in the seminal work of Dupire , where the functional It\^o calculus was developed to deal with path-dependent financial derivatives contracts ] . The method, which we call Path-Dependent DGM (PDGM), consists of using a combination of feed-forward and Long Short-Term Memory architectures to model the solution of the PPDE.
Edit intent: coherence
Original:  These equations firstly appeared in the seminal work of \mbox{%DIFAUXCMD fito_dupire  , where the functional It\^o calculus was developed to deal with path-dependent financial derivatives contracts  ]  . The method, which we call Path-Dependent DGM (PDGM), consists of using a combination of feed-forward and Long Short-Term Memory architectures to model the solution of the PPDE.
Revised:  These equations firstly appeared in the seminal work of \mbox{%DIFAUXCMD fito_dupire 2009 , where the functional It\^o calculus was developed to deal with path-dependent financial derivatives contracts ] . The method, which we call Path-Dependent DGM (PDGM), consists of using a combination of feed-forward and Long Short-Term Memory architectures to model the solution of the PPDE.
Edit intent: meaning-changed
Original:  These equations firstly appeared in the seminal work of \mbox{%DIFAUXCMD fito_dupire  , where the functional It\^o calculus was developed to deal with path-dependent financial derivatives contracts  ]  . The method, which we call Path-Dependent DGM (PDGM), consists of using a combination of feed-forward and Long Short-Term Memory architectures to model the solution of the PPDE.
Revised:  These equations firstly appeared in the seminal work of \mbox{%DIFAUXCMD fito_dupire , where the functional It\^o calculus was developed to deal with path-dependent financial derivatives contracts . More specificaly, we generalize the Deep Galerking Method (DGM) of Sirignano and Spiliopoulos ] . The method, which we call Path-Dependent DGM (PDGM), consists of using a combination of feed-forward and Long Short-Term Memory architectures to model the solution of the PPDE.
Edit intent: meaning-changed
Original:  These equations firstly appeared in the seminal work of \mbox{%DIFAUXCMD fito_dupire  , where the functional It\^o calculus was developed to deal with path-dependent financial derivatives contracts  ]  . The method, which we call Path-Dependent DGM (PDGM), consists of using a combination of feed-forward and Long Short-Term Memory architectures to model the solution of the PPDE.
Revised:  These equations firstly appeared in the seminal work of \mbox{%DIFAUXCMD fito_dupire , where the functional It\^o calculus was developed to deal with path-dependent financial derivatives contracts 2018] . The method, which we call Path-Dependent DGM (PDGM), consists of using a combination of feed-forward and Long Short-Term Memory architectures to model the solution of the PPDE.
Edit intent: fluency
Original:  These equations firstly appeared in the seminal work of \mbox{%DIFAUXCMD fito_dupire  , where the functional It\^o calculus was developed to deal with path-dependent financial derivatives contracts  ]  . The method, which we call Path-Dependent DGM (PDGM), consists of using a combination of feed-forward and Long Short-Term Memory architectures to model the solution of the PPDE.
Revised:  These equations firstly appeared in the seminal work of \mbox{%DIFAUXCMD fito_dupire , where the functional It\^o calculus was developed to deal with path-dependent financial derivatives contracts ] to deal with these equations . The method, which we call Path-Dependent DGM (PDGM), consists of using a combination of feed-forward and Long Short-Term Memory architectures to model the solution of the PPDE.
Edit intent: coherence
Original:  We focus on such example: exponential power distribution (EPD) \rho(x)\propto \exp(-|(x-\mu)/\sigma|^\kappa/\kappa)  family, which covers wide range of tail behavior like Gaussian (\kappa=2) or Laplace (\kappa=1) distribution.
Revised:  We focus on such example: \rho(x)\propto \exp(-|(x-\mu)/\sigma|^\kappa/\kappa) family, which covers wide range of tail behavior like Gaussian (\kappa=2) or Laplace (\kappa=1) distribution.
Edit intent: clarity
Original:  We focus on such example: exponential power distribution (EPD) \rho(x)\propto \exp(-|(x-\mu)/\sigma|^\kappa/\kappa)  family, which covers wide range of tail behavior like Gaussian (\kappa=2) or Laplace (\kappa=1) distribution.
Revised:  We focus on such example: exponential power distribution (EPD) \rho(x)\propto \exp(-|(x-\mu)/\sigma|^\kappa/\kappa) exponential power distribution (EPD) family, which covers wide range of tail behavior like Gaussian (\kappa=2) or Laplace (\kappa=1) distribution.
Edit intent: meaning-changed
Original:  It is tested on daily log-return series for DJIA companies, leading to essentially better log-likelihoods than standard (static) estimation, surprisingly with optimal \kappa tails types varying between companies.
Revised:  It is tested on daily log-return series for DJIA companies, leading to essentially better log-likelihoods than standard (static) estimation, with optimal \kappa tails types varying between companies.
Edit intent: coherence
Original: The notion that an independent central bank reduces a country's inflationis a controversial hypothesis. To date, it has not been possible to satisfactorily answer this question because the complex macroeconomic structure that gives rise to the data has not been adequately incorporated into statistical analyses.
Revised: The notion that an independent central bank (CBI) reduce inflation? Despite numerous articles suggesting it does, this question has not been possible to satisfactorily answer this question because the complex macroeconomic structure that gives rise to the data has not been adequately incorporated into statistical analyses.
Edit intent: meaning-changed
Original:  We develop a causal model that summarizes the economic process of inflation . Based on this causal model and recent data, we discuss and identify the assumptions under which the effect of central bank independence on inflation can be identified and estimated. Given these and alternative assumptions, we estimate this effect using modern doubly robust effect estimators, i. e. , longitudinal targeted maximum likelihood estimators.
Revised:  We develop a causal model that summarizes the economic process of inflation and estimate the effect of CBI on inflation with modern doubly robust effect estimators, i. e. , longitudinal targeted maximum likelihood estimators.
Edit intent: clarity
Original:  Given these and alternative assumptions, we estimate this effect using modern doubly robust effect estimators, i. e. , longitudinal targeted maximum likelihood estimators. The estimation procedure incorporates machine learning algorithms and is tailored to address the challenges associated with complex longitudinal macroeconomic data .
Revised:  Given these and alternative assumptions, we estimate this effect using modern doubly robust effect estimation techniques. We incorporate a large amount of variables in our directed acyclic graph and overcome endogeneity issues of previous studies. Our approach includes machine learning algorithms and is tailored to address the challenges associated with complex longitudinal macroeconomic data .
Edit intent: meaning-changed
Original:  We do not find strong support for the hypothesis that having an independent central bank for a long period of time necessarily lowers inflation. Simulation studies evaluate the sensitivity of the proposed methods in complex settings when certain assumptions are violated and highlight the importance of working with appropriate learning algorithms for estimation.
Revised:  We do not find strong support for the hypothesis that CBI causes lower inflation. If a country had legislated CBI for every year between 1998 and 2008, it would have had an average reduction in inflation of -0.63 (-2.33; 1.07) percentage points in 2010.
Edit intent: meaning-changed
Original: Does an independent central bank (CBI) reduce inflation ? Despite numerous articles suggesting it does, this question has not been satisfactorily answered because the complex macroeconomic structure that gives rise to the data has not been adequately incorporated into economic analyses.
Revised: The notion that an independent central bank (CBI) reduce inflation ? Despite numerous articles suggesting it does, this question has not been satisfactorily answered because the complex macroeconomic structure that gives rise to the data has not been adequately incorporated into economic analyses.
Edit intent: clarity
Original: Does an independent central bank (CBI) reduce inflation ? Despite numerous articles suggesting it does, this question has not been satisfactorily answered because the complex macroeconomic structure that gives rise to the data has not been adequately incorporated into economic analyses.
Revised: Does an independent central bank reduces a country's inflation is a controversial hypothesis. To date, it has not been satisfactorily answered because the complex macroeconomic structure that gives rise to the data has not been adequately incorporated into economic analyses.
Edit intent: meaning-changed
Original: Does an independent central bank (CBI) reduce inflation ? Despite numerous articles suggesting it does, this question has not been satisfactorily answered because the complex macroeconomic structure that gives rise to the data has not been adequately incorporated into economic analyses.
Revised: Does an independent central bank (CBI) reduce inflation ? Despite numerous articles suggesting it does, this question has not been possible to satisfactorily answer this question because the complex macroeconomic structure that gives rise to the data has not been adequately incorporated into economic analyses.
Edit intent: clarity