wanyu/IteraTeR_v2 huggingface dataset:
Original:  Motivated by the GWAS problem, in this paper we introduce the information theoretic problem of \emph{associated subsequence retrieval}, where a dataset of N (possibly high dimensional ) sequences of length G, and their corresponding observable  characteristics is given.
Revised:  Motivated by the GWAS problem, in this paper we introduce the information-theoretic problem of \emph{associated subsequence retrieval}, where a dataset of N (possibly high dimensional ) sequences of length G, and their corresponding observable characteristics is given.
Edit intent: fluency
Original:  Motivated by the GWAS problem, in this paper we introduce the information theoretic problem of \emph{associated subsequence retrieval}, where a dataset of N (possibly high dimensional ) sequences of length G, and their corresponding observable  characteristics is given.
Revised:  Motivated by the GWAS problem, in this paper we introduce the information theoretic problem of \emph{associated subsequence retrieval}, where a dataset of N (possibly high-dimensional ) sequences of length G, and their corresponding observable characteristics is given.
Edit intent: fluency
Original:  The observable characteristic is assumed to be binary, and it is related to only a specific subsequence of length L of the sequences, called \textit{associated subsequence}.
Revised:  The observable (binary) characteristic is only related to a specific unknown subsequence of length L of the sequences, called \textit{associated subsequence}.
Edit intent: clarity
Original:  For each sequence, if the associated subsequence of it belongs to some universal finite set, then it is more likely to display the observable characteristic (i.e., it is more likely that the observable characteristic is one).
Revised:  For each sequence, if the associated subsequence of it belongs to a universal finite set, then it is more likely to display the observable characteristic (i.e., it is more likely that the observable characteristic is one).
Edit intent: clarity
Original:  Our approach enables fast and accurate inference and efficient sample generation independent of the dimensionality of the integration domain.
Revised:  Our approach enables fast and accurate inference and efficient sample generation independently of the dimensionality of the integration domain.
Edit intent: fluency
Original:  We demonstrate the benefits of our approach for generating natural images and in two applications to light-transport simulation .
Revised:  We show its benefits on generating natural images and in two applications to light-transport simulation .
Edit intent: clarity
Original:  First, we show how to learn joint path-sampling densities in  primary sample space and how to importance sample multi-dimensional path prefixes thereof.
Revised:  First, we show how to learn joint path-sampling densities in the primary sample space and how to importance sample multi-dimensional path prefixes thereof.
Edit intent: fluency
Original:  First, we show how to learn joint path-sampling densities in  primary sample space and how to importance sample multi-dimensional path prefixes thereof.
Revised:  First, we show how to learn joint path-sampling densities in primary sample space and importance sampling of multi-dimensional path prefixes thereof.
Edit intent: fluency
Original:  Second, we use our technique to extract conditional directional densities driven by the triple product of the rendering equation , and leverage them for path guiding.
Revised:  Second, we use our technique to extract conditional directional densities driven by the triple product of the rendering equation and leverage them for path guiding.
Edit intent: fluency
Original:  In all applications, our approach yields on-par or higher performance  at equal sample count than competing techniques .
Revised:  In all applications, our approach yields on-par or higher performance than competing techniques at equal sample count than competing techniques .
Edit intent: fluency
Original:  In all applications, our approach yields on-par or higher performance  at equal sample count than competing techniques .
Revised:  In all applications, our approach yields on-par or higher performance at equal sample count .
Edit intent: clarity
Original:  In particular, for the problem of minimizing a non-smooth Lipschitz and strongly convex function with black-box oracle access we give information theoretic lower bounds that indicate that the number of adaptive rounds of any randomized algorithmexactly match the upper bounds of single-query-per-round (i. e. non-parallel) algorithms ]\to   ) rounds of adaptivity that has convergence rate that is better than those achievable with a one-query-per-round algorithm.
Revised:  In particular, for the problem of minimizing a non-smooth Lipschitz and strongly convex function with black-box oracle access we give information theoretic lower bounds that indicate that the number of adaptive rounds of any randomized algorithmexactly match the upper bounds of single-query-per-round (i. e. non-parallel) algorithms ]\to poly ) rounds of adaptivity that has convergence rate that is better than those achievable with a one-query-per-round algorithm.
Edit intent: fluency
Original: Device-to-device  communication underlaying a cellular infrastructure has been proposed as a means of taking advantage of physical proximity of communicating devices, increased resource utilisation and improving cellular coverage.
Revised: Device-to-device (D2D) communication underlaying a cellular infrastructure has been proposed as a means of taking advantage of physical proximity of communicating devices, increased resource utilisation and improving cellular coverage.
Edit intent: clarity
Original: Device-to-device  communication underlaying a cellular infrastructure has been proposed as a means of taking advantage of physical proximity of communicating devices, increased resource utilisation and improving cellular coverage.
Revised: Device-to-device communication underlaying a cellular infrastructure has been proposed as a means of taking advantage of physical proximity of communicating devices, increased resource utilization and improving cellular coverage.
Edit intent: fluency
Original:  In this work, the system model assumes bursty arrival of packets at the mobile devices and allows each device to act as a relay for other sources.
Revised:  In this work, the system model assumes bursty arrival of packets at the mobile devices and allows each user to act as a relay for other sources.
Edit intent: clarity
Original:  The rate stability of queues  in the network in a D2D scenario with limited interdependence is considered and the system rate region is characterised .
Revised:  The rate stability of queues of the users in the network in a D2D scenario with limited interdependence is considered and the system rate region is characterised .
Edit intent: clarity
Original:  The rate stability of queues  in the network in a D2D scenario with limited interdependence is considered and the system rate region is characterised .
Revised:  The rate stability of queues in the network with limited interdependence is considered and the system rate region is characterised .
Edit intent: clarity
Original:  The rate stability of queues  in the network in a D2D scenario with limited interdependence is considered and the system rate region is characterised .
Revised:  The rate stability of queues in the network in a D2D scenario with limited interdependence is considered and the system rate region of the network is characterized .
Edit intent: clarity
Original: This paper is part of a project on developing an algorithmic theory of brain networks, based on stochastic Spiking Neural Network (SNN)models.
Revised: This paper presents a formal, mathematical foundation for modeling and reasoning about the behavior of synchronous, stochastic Spiking Neural Network (SNN)models.
Edit intent: clarity
Original:  In our work so far, we have developed models and algorithms for the Winner-Take-All problem from computational neuroscience LMP17a , Mus18 , and problems of similarity detection and neural coding%DIFDELCMD < [%%% LMP17b .
Revised:  In our work so far, we have developed models and algorithms for the Winner-Take-All problem from computational neuroscience LMP17a , Mus18 %DIFDELCMD < [%%% LMP17b .
Edit intent: coherence
Original:  In our work so far, we have developed models and algorithms for the Winner-Take-All problem from computational neuroscience LMP17a , Mus18 , and problems of similarity detection and neural coding%DIFDELCMD < [%%% LMP17b .
Revised:  In our work so far, we have developed models and algorithms for the Winner-Take-All problem from computational neuroscience LMP17a , Mus18 , and problems of similarity detection and neural coding%DIFDELCMD < [%%% .
Edit intent: clarity
Original:  This version assumes that the neurons' only state is a Boolean , indicating whether the neuron is firing or not.
Revised:  This version assumes that the neurons' only state is a Boolean value indicating whether the neuron is firing or not.
Edit intent: clarity
Original:  We give basic results for hiding .
Revised:  We prove results describing how the external behavior of a network built using these operators is related to the external behavior of the component networks .
Edit intent: clarity
Original:  Finally, we give a formal definition of a problem to be solved by an SNN, and give basic results showing how  composition and hiding of networks affect the problems that they solve .
Revised:  Finally, we give a formal definition of a problem to be solved by an SNN, and give basic results showing how the composition and hiding of networks affect the problems that they solve .
Edit intent: fluency
Original:  Finally, we give a formal definition of a problem to be solved by an SNN, and give basic results showing how  composition and hiding of networks affect the problems that they solve .
Revised:  Finally, we give a formal definition of a problem to be solved by an SNN, and give basic results showing how composition and hiding operators affect the problems that they solve .
Edit intent: clarity
Original:  Finally, we give a formal definition of a problem to be solved by an SNN, and give basic results showing how  composition and hiding of networks affect the problems that they solve .
Revised:  Finally, we give a formal definition of a problem to be solved by an SNN, and give basic results showing how composition and hiding of networks affect the problems that are solved by the networks .
Edit intent: clarity
Original:  We illustrate our definitions with three examples: building a circuit out of gates, building an "Attention " network out of a " Winner-Take-All " network and a "Filter " network, and a toy example involving combining two networks in a cyclic fashion.
Revised:  We illustrate our definitions with three examples: building a circuit out of gates, building an "Attention " network out of a " Winner-Take-All network and a "Filter " network, and a toy example involving combining two networks in a cyclic fashion.
Edit intent: fluency
Original:  We illustrate our definitions with three examples: building a circuit out of gates, building an "Attention " network out of a " Winner-Take-All " network and a "Filter " network, and a toy example involving combining two networks in a cyclic fashion.
Revised:  We illustrate our definitions with three examples: building a circuit out of gates, building an "Attention " network out of a " Winner-Take-All " network and a Filter network, and a toy example involving combining two networks in a cyclic fashion.
Edit intent: fluency
Original: In this letter , we propose a block-chained federated learning (BlockFL) architecture , where mobile devices' local learning model updates are exchanged and verified by leveraging blockchain .
Revised: By leveraging blockchain, this letter proposes a blockchained federated learning (BlockFL) architecture , where mobile devices' local learning model updates are exchanged and verified by leveraging blockchain .
Edit intent: clarity
Original: In this letter , we propose a block-chained federated learning (BlockFL) architecture , where mobile devices' local learning model updates are exchanged and verified by leveraging blockchain .
Revised: In this letter , we propose a block-chained federated learning (BlockFL) architecture where local learning model updates are exchanged and verified by leveraging blockchain .
Edit intent: clarity
Original: In this letter , we propose a block-chained federated learning (BlockFL) architecture , where mobile devices' local learning model updates are exchanged and verified by leveraging blockchain .
Revised: In this letter , we propose a block-chained federated learning (BlockFL) architecture , where mobile devices' local learning model updates are exchanged and verified .
Edit intent: clarity
Original:  We investigate the end-to-end learning completion latency of BlockFL, thereby yielding the optimal block generation rate as well as important insights in terms of network scalability and robustness .
Revised:  We investigate the end-to-end latency model of BlockFL and characterize the optimal block generation rate as well as important insights in terms of network scalability and robustness .
Edit intent: clarity
Original:  It is a reversible preprocessing step that rearranges an n-letter string into runs of identical characters (by exploiting context regularities), resulting in highly compressible strings, and is the basis for the ubiquitous bzip  program.
Revised:  It is a reversible preprocessing step that rearranges an n-letter string into runs of identical characters (by exploiting context regularities), resulting in highly compressible strings, and is the basis for the ubiquitous bzip program.
Edit intent: fluency
Original:  It is a reversible preprocessing step that rearranges an n-letter string into runs of identical characters (by exploiting context regularities), resulting in highly compressible strings, and is the basis for the ubiquitous bzip  program.
Revised:  It is a reversible preprocessing step that rearranges an n-letter string into runs of identical characters (by exploiting context regularities), resulting in highly compressible strings, and is the basis of the bzip program.
Edit intent: clarity
Original:  It is a reversible preprocessing step that rearranges an n-letter string into runs of identical characters (by exploiting context regularities), resulting in highly compressible strings, and is the basis for the ubiquitous bzip  program.
Revised:  It is a reversible preprocessing step that rearranges an n-letter string into runs of identical characters (by exploiting context regularities), resulting in highly compressible strings, and is the basis for the ubiquitous bzip compression program.
Edit intent: clarity
Original:  We study the succinct data structure problem of locally decoding short substrings of a given text under its compressed BWT, i.e., with small  redundancy r over the Move-To-Front based (bzip) compression.
Revised:  We study the succinct data structure problem of locally decoding short substrings of a given text under its compressed BWT, i.e., with small redundancy r over the Move-To-Front (bzip) compression.
Edit intent: coherence
Original:  The celebrated BWT-based FM-index (FOCS '00), and other related literature, gravitate toward a tradeoff of r=\tilde{O}(n/\sqrt{t}) bits, when a single character is to be decoded in O(t) time.
Revised:  The celebrated BWT-based FM-index (FOCS '00), as well as other related literature, gravitate toward a tradeoff of r=\tilde{O}(n/\sqrt{t}) bits, when a single character is to be decoded in O(t) time.
Edit intent: fluency
Original:  The celebrated BWT-based FM-index (FOCS '00), and other related literature, gravitate toward a tradeoff of r=\tilde{O}(n/\sqrt{t}) bits, when a single character is to be decoded in O(t) time.
Revised:  The celebrated BWT-based FM-index (FOCS '00), and other related literature, yield a trade-off of r=\tilde{O}(n/\sqrt{t}) bits, when a single character is to be decoded in O(t) time.
Edit intent: clarity
Original:  The key component is a locally-decodable \emph{ Move-to-Front (MTF) code: with only O(1) extra bits per block of length n^{\Omega(1)}, the decoding time of a single character can be decreased from \Omega(n) to O(\lg n).
Revised:  The key component is a \emph{ Move-to-Front (MTF) code: with only O(1) extra bits per block of length n^{\Omega(1)}, the decoding time of a single character can be decreased from \Omega(n) to O(\lg n).
Edit intent: clarity
Original:  This enumeration is also solved via a succession rule, which however does not generalize the one for F_4.
Revised:  This enumeration is also solved via a succession rule, which however does not generalize the one for F_4.
Edit intent: fluency
Original:  The associated enumeration sequence, which we call of powered Catalan numbers , is quite intringuing , and further investigated.
Revised:  The associated enumeration sequence, which we call of powered Catalan numberspowered Catalan numbers , is quite intringuing , and further investigated.
Edit intent: fluency
Original:  The associated enumeration sequence, which we call of powered Catalan numbers , is quite intringuing , and further investigated.
Revised:  The associated enumeration sequence, which we call of powered Catalan numbers , is quite intriguing , and further investigated.
Edit intent: fluency
Original:  Among such families, we introduce the steady paths \emph{ , which are naturally associated with steady.
Revised:  Among such families, we introduce the \emph{ , which are naturally associated with steady.
Edit intent: clarity
Original:  They allow to brigde the gap between the two types of families enumerated by powered Catalan numbers: indeed, we provide a size-preserving bijection between steady paths and valley-marked Dyck paths (which are naturally associated to pCat).
Revised:  They allow us to bridge the gap between the two types of families enumerated by powered Catalan numbers: indeed, we provide a size-preserving bijection between steady paths and valley-marked Dyck paths (which are naturally associated to pCat).
Edit intent: fluency
Original:  They allow to brigde the gap between the two types of families enumerated by powered Catalan numbers: indeed, we provide a size-preserving bijection between steady paths and valley-marked Dyck paths (which are naturally associated to pCat).
Revised:  They allow to brigde the gap between the two types of families enumerated by powered Catalan numbers: indeed, we provide a size-preserving bijection between steady paths and valley-marked Dyck paths (which are naturally associated with pCat).
Edit intent: fluency
Original: In this paper, we introduce an embedding model, named CapsE, exploring a capsule network to model relationship triples \textit{(subject, relation, object) .
Revised: In this paper, we introduce an embedding model, named CapsE, exploring a capsule network to model relationship triples \textit{(subject, relation, object) .
Edit intent: fluency
Original:  The last capsule layer consists of only one capsule to produce a vector output .
Revised:  The last capsule layer consists of only one capsule to produce a continuous vector .
Edit intent: clarity
Original:  The length of this vector output is used to measure the plausibility  of the triple.
Revised:  The length of this vector is used to measure the plausibility of the triple.
Edit intent: clarity
Original:  The length of this vector output is used to measure the plausibility  of the triple.
Revised:  The length of this vector output is used to measure the plausibility score of the triple.
Edit intent: clarity
Original:  Our proposed CapsE obtains  state-of-the-art link prediction results for knowledge graph completion on two benchmark datasets : WN18RR and FB15k-237, and outperforms strong search personalization baselines on SEARCH17 dataset .
Revised:  Our proposed CapsE obtains better performance than previous state-of-the-art link prediction results for knowledge graph completion on two benchmark datasets : WN18RR and FB15k-237, and outperforms strong search personalization baselines on SEARCH17 dataset .
Edit intent: clarity
Original:  Our proposed CapsE obtains  state-of-the-art link prediction results for knowledge graph completion on two benchmark datasets : WN18RR and FB15k-237, and outperforms strong search personalization baselines on SEARCH17 dataset .
Revised:  Our proposed CapsE obtains state-of-the-art link prediction results for knowledge graph completion on two benchmark datasets WN18RR and FB15k-237, and outperforms strong search personalization baselines on SEARCH17 dataset .
Edit intent: fluency
Original:  Our proposed CapsE obtains  state-of-the-art link prediction results for knowledge graph completion on two benchmark datasets : WN18RR and FB15k-237, and outperforms strong search personalization baselines on SEARCH17 dataset .
Revised:  Our proposed CapsE obtains state-of-the-art link prediction results for knowledge graph completion on two benchmark datasets : WN18RR and FB15k-237, and outperforms strong search personalization baselines on SEARCH17 .
Edit intent: clarity
Original: Hashing techniques have been applied broadly in large-scale retrieval tasks due to their low storage requirements and high speed of processing.
Revised: Hashing techniques have been applied broadly in retrieval tasks due to their low storage requirements and high speed of processing.
Edit intent: clarity
Original:  The paperproposes a novel discrete hashing learning framework which jointly performs classifier learning and subspace learning for cross-modal retrieval.
Revised:  The paperproposes a novel discrete hashing learning framework that jointly performs classifier learning and subspace learning for cross-modal retrieval.
Edit intent: fluency
Original:  The aim of kernelization is to learn a common subspace where heterogeneous data can be fused.
Revised:  Kernelization aims to find a common subspace where heterogeneous data can be fused.
Edit intent: clarity
Original:  The aim of kernelization is to learn a common subspace where heterogeneous data can be fused.
Revised:  The aim of kernelization is to learn a common subspace where multi-view features can be fused.
Edit intent: clarity
Original:  The quantization process is designed to learn discriminative unified hashing codes.
Revised:  The quantization stage is designed to learn discriminative unified hashing codes.
Edit intent: clarity
Original:  The resulting first-order programs can be executed by conventional logic programming interpreters and benefit from other optimizations that might offer .
Revised:  The resulting first-order programs can be executed by conventional logic programming interpreters and benefit from other optimizations that might be available .
Edit intent: clarity
Original:  Specifically, by decreasing the DRAM row activation latency (  tRCD) below manufacturer-recommended specifications, we induce read errors, or activation failures, that exhibit true random behavior.
Revised:  Specifically, by decreasing the DRAM row activation latency ( tRCD) below manufacturer-recommended specifications, to induce read errors, or activation failures, that exhibit true random behavior.
Edit intent: clarity
Original:  We then aggregate the resulting data from multiple cells to obtain a TRNG capable of continuous high-throughput operation .
Revised:  We then aggregate the resulting data from multiple cells to obtain a TRNG capable of providing a high throughput of random numbers at low latency .
Edit intent: clarity
Original:  To demonstrate that our TRNG design is viable on commodity DRAM chips, we rigorously characterize the behavior of activation failures in 282 state-of-the-art LPDDR4 devices from across three major DRAM vendors and verify our observations using four additional DDR3 DRAM devices drawn from the same vendors .
Revised:  To demonstrate that our TRNG design is viable using commodity DRAM chips, we rigorously characterize the behavior of activation failures in 282 state-of-the-art LPDDR4 devices from across three major DRAM vendors and verify our observations using four additional DDR3 DRAM devices drawn from the same vendors .
Edit intent: fluency