wanyu/IteraTeR_v2 huggingface dataset:
Original:  Correspondingly, we aim at recovering a representation of the subspace , and perform event detection by running point-to-subspace distance query in \ell^\infty, for each incoming observation .
Revised:  Correspondingly, we aim at recovering a representation of the subspace , and perform event detection by running point-to-subspace distance queries on this subspace for incoming data .
Edit intent: clarity
Original: Monitoring of streamed data to detect abnormal behavior (variously known as event detection, anomaly detection, change detection, or outlier detection) underlies many applications of the Internet of Things.
Revised: Monitoring of streamed data to detect abnormal behaviour (variously known as event detection, anomaly detection, change detection, or outlier detection) underlies many applications of the Internet of Things.
Edit intent: fluency
Original:  Here, we propose a novel framework for event detection in high-dimensional data across a variety of sources, with asynchronous sampling  and missing data , to instantly predict abnormal behavior .
Revised:  There, one often collects data from a variety of sources, with asynchronous sampling and missing data , to instantly predict abnormal behavior .
Edit intent: clarity
Original:  Here, we propose a novel framework for event detection in high-dimensional data across a variety of sources, with asynchronous sampling  and missing data , to instantly predict abnormal behavior .
Revised:  Here, we propose a novel framework for event detection in high-dimensional data across a variety of sources, with asynchronous sampling , and missing data , to instantly predict abnormal behavior .
Edit intent: fluency
Original:  Here, we propose a novel framework for event detection in high-dimensional data across a variety of sources, with asynchronous sampling  and missing data , to instantly predict abnormal behavior .
Revised:  Here, we propose a novel framework for event detection in high-dimensional data across a variety of sources, with asynchronous sampling and missing data . In this setting, one can predict abnormal behavior .
Edit intent: coherence
Original:  Correspondingly, we aim to recover a representation of the subspace  and perform event detection by running point-to-subspace distance queries on this subspace for incoming data.
Revised:  Correspondingly, we aim to recover a representation of the subspace , and perform event detection by running point-to-subspace distance queries on this subspace for incoming data.
Edit intent: fluency
Original:  Correspondingly, we aim to recover a representation of the subspace  and perform event detection by running point-to-subspace distance queries on this subspace for incoming data.
Revised:  Correspondingly, we aim to recover a representation of the subspace and perform event detection by running point-to-subspace distance query for incoming data.
Edit intent: clarity
Original:  On-line, we compute the distance of incoming data to the low-rank "normal " subspace and update the subspace to keep it consistent with the seasonal changes present.
Revised:  On-line, we compute the distance of incoming data to the low-rank normal subspace and update the subspace to keep it consistent with the seasonal changes present.
Edit intent: fluency
Original:  For the distance computation, we present an algorithm with a one-sided error bounded by a function of the number of coordinates employed  .
Revised:  For the distance computation, we present an algorithm with a one-sided error as a function of the number of coordinates employed .
Edit intent: clarity
Original:  In this work, we are the first to consider employing deep neural networks toward tackling this problem.
Revised:  In this work, we are the first to employ deep neural networks toward tackling this problem.
Edit intent: clarity
Original:  To capture this intuition, we design a tree-to-tree neural network as an encoder-decoder architecture to translate a source tree into a target one.
Revised:  To capture this intuition, we design a tree-to-tree neural network to translate a source tree into a target one.
Edit intent: clarity
Original: Networks observed in the real world like social networks, collaboration networks etc., exhibit temporal dynamics, i.e. nodes and edges appear and/or disappear over time.
Revised: Networks observed in real world like social networks, collaboration networks etc., exhibit temporal dynamics, i.e. nodes and edges appear and/or disappear over time.
Edit intent: fluency
Original:  Experiments done on synthetic and real-world networks for the task of community detection and link prediction demonstrate the utility and effectiveness of our model as compared to other similar existing approaches .
Revised:  Experiments done on synthetic and real world networks for the task of community detection and link prediction demonstrate the utility and effectiveness of our model as compared to other similar existing approaches .
Edit intent: fluency
Original: We present a simple solver of the fractional Laplacian based on the hypersingular integral representation.
Revised: We present a simple solver for the fractional Laplacian based on the hypersingular integral representation.
Edit intent: clarity
Original: We present a simple solver for the fractional Laplacian based on the hypersingular integral representation  .
Revised: We present a simple discretization scheme for the hypersingular integral representation .
Edit intent: clarity
Original: Emerging wireless services such as augmented reality require next-generation wireless networks to support ultra-reliable and low-latency communication (URLLC)
Revised: Next-generation wireless networks must enable emerging technologies such as augmented reality require next-generation wireless networks to support ultra-reliable and low-latency communication (URLLC)
Edit intent: clarity
Original: Emerging wireless services such as augmented reality require next-generation wireless networks to support ultra-reliable and low-latency communication (URLLC)
Revised: Emerging wireless services such as augmented reality require next-generation wireless networks to support ultra-reliable low-latency communication (URLLC)
Edit intent: clarity
Original:  , while also guaranteeing high data rates . Existing wireless networks that solely rely on the scarce sub-6 GHz, microwave (\muW) frequency bands will be unable to meet the low-latency, high capacity requirements of future wireless services  . Meanwhile, operating at high-frequency millimeter wave (mmWave) bands is seen as an attractive solution, primarily due to the bandwidth availability and possibility of large-scale multi-antenna communication.
Revised:  . Existing wireless networks that solely rely on the scarce sub-6 GHz, microwave (\muW) frequency bands will be unable to meet the low-latency, high capacity requirements of future wireless services . Meanwhile, operating at high-frequency millimeter wave (mmWave) bands is seen as an attractive solution, primarily due to the bandwidth availability and possibility of large-scale multi-antenna communication.
Edit intent: coherence
Original:  , while also guaranteeing high data rates . Existing wireless networks that solely rely on the scarce sub-6 GHz, microwave (\muW) frequency bands will be unable to meet the low-latency, high capacity requirements of future wireless services  . Meanwhile, operating at high-frequency millimeter wave (mmWave) bands is seen as an attractive solution, primarily due to the bandwidth availability and possibility of large-scale multi-antenna communication.
Revised:  , while also guaranteeing high data rates . Existing wireless systems that solely rely on the scarce sub-6 GHz, microwave (\muW) frequency bands will be unable to meet the low-latency, high capacity requirements of future wireless services . Meanwhile, operating at high-frequency millimeter wave (mmWave) bands is seen as an attractive solution, primarily due to the bandwidth availability and possibility of large-scale multi-antenna communication.
Edit intent: clarity
Original:  , while also guaranteeing high data rates . Existing wireless networks that solely rely on the scarce sub-6 GHz, microwave (\muW) frequency bands will be unable to meet the low-latency, high capacity requirements of future wireless services  . Meanwhile, operating at high-frequency millimeter wave (mmWave) bands is seen as an attractive solution, primarily due to the bandwidth availability and possibility of large-scale multi-antenna communication.
Revised:  , while also guaranteeing high data rates . Existing wireless networks that solely rely on the scarce sub-6 GHz, microwave (\muW) frequency bands will be unable to meet such stringent and mixed service requirements for future wireless services . Meanwhile, operating at high-frequency millimeter wave (mmWave) bands is seen as an attractive solution, primarily due to the bandwidth availability and possibility of large-scale multi-antenna communication.
Edit intent: clarity
Original:  , while also guaranteeing high data rates . Existing wireless networks that solely rely on the scarce sub-6 GHz, microwave (\muW) frequency bands will be unable to meet the low-latency, high capacity requirements of future wireless services  . Meanwhile, operating at high-frequency millimeter wave (mmWave) bands is seen as an attractive solution, primarily due to the bandwidth availability and possibility of large-scale multi-antenna communication.
Revised:  , while also guaranteeing high data rates . Existing wireless networks that solely rely on the scarce sub-6 GHz, microwave (\muW) frequency bands will be unable to meet the low-latency, high capacity requirements of future wireless services due to spectrum scarcity . Meanwhile, operating at high-frequency millimeter wave (mmWave) bands is seen as an attractive solution, primarily due to the bandwidth availability and possibility of large-scale multi-antenna communication.
Edit intent: clarity
Original:  However, even though leveraging the large bandwidth at mmWave frequencies can potentially boost the wireless capacity and reduce the transmission delay for low-latency applications, mmWave communication is inherently unreliable due to its susceptibility to blockage, high path loss, and channel uncertainty.
Revised:  However, mmWave communication is inherently unreliable due to its susceptibility to blockage, high path loss, and channel uncertainty.
Edit intent: coherence
Original:  To this end, in this paper, the first comprehensive tutorial for integrated mmWave-%DIFDELCMD < \muW %%%  communications is introduced.
Revised:  To this end, in this paper, the first comprehensive tutorial for %DIFDELCMD < \muW %%% communications is introduced.
Edit intent: clarity
Original:  To achieve this goal, key solution concepts are developed that include new architectures for the radio interface, URLLC-aware frame structure and resource allocation methods along with learning techniques, as well as mobility management, to realize the potential of integrated mmWave-\muW communications.
Revised:  To achieve this goal, key solution concepts are discussed that include new architectures for the radio interface, URLLC-aware frame structure and resource allocation methods along with learning techniques, as well as mobility management, to realize the potential of integrated mmWave-\muW communications.
Edit intent: clarity
Original:  To achieve this goal, key solution concepts are developed that include new architectures for the radio interface, URLLC-aware frame structure and resource allocation methods along with learning techniques, as well as mobility management, to realize the potential of integrated mmWave-\muW communications.
Revised:  To achieve this goal, key solution concepts are developed that include new architectures for the radio interface, URLLC-aware frame structure and resource allocation methods along with mobility management, to realize the potential of integrated mmWave-\muW communications.
Edit intent: coherence
Original:  The opportunities and challenges of each proposed scheme are discussed and key results are presented \muW  .
Revised:  The opportunities and challenges of each proposed scheme are discussed and key results are presented \muW framework .
Edit intent: clarity
Original: In this paper, we give quantum algorithms for two fundamental computation problems: solving polynomial systems and optimization over finite fields  .
Revised: In this paper, we give quantum algorithms for two fundamental computation problems: solving polynomial systems over finite fields .
Edit intent: clarity
Original:  The quantum algorithms can solve these problems with any given  probability and have complexities polynomial in the size of the input  and the condition number of certain polynomial system related to the problem.
Revised:  The quantum algorithms can solve these problems with any given probability and have complexities polynomial in the size of the input and the condition number of certain matrices derived from the problem.
Edit intent: clarity
Original: In this letter , we investigate the problem of providing gigabit wireless access with reliable communication in 5G millimeter-Wave (mmWave) massive multiple-input multiple-output (MIMO) networks.
Revised: This letter investigates the problem of providing gigabit wireless access with reliable communication in 5G millimeter-Wave (mmWave) massive multiple-input multiple-output (MIMO) networks.
Edit intent: fluency
Original:  In contrast to the classical network design based on average metrics, we propose a distributed risk-sensitive reinforcement learning-based framework  to jointly optimize the beamwidth and transmit power, while taking into account the sensitivity of mmWave links due to blockage.
Revised:  In contrast to the classical network design based on average metrics, a distributed risk-sensitive reinforcement learning-based framework to jointly optimize the beamwidth and transmit power, while taking into account the sensitivity of mmWave links due to blockage.
Edit intent: coherence
Original:  In contrast to the classical network design based on average metrics, we propose a distributed risk-sensitive reinforcement learning-based framework  to jointly optimize the beamwidth and transmit power, while taking into account the sensitivity of mmWave links due to blockage.
Revised:  In contrast to the classical network design based on average metrics, we propose a distributed risk-sensitive reinforcement learning-based framework is proposed to jointly optimize the beamwidth and transmit power, while taking into account the sensitivity of mmWave links due to blockage.
Edit intent: clarity
Original:  Further, we lay out the different levels at which neural reuse can occur through a dynamical filtering of the brain-body-environment system's operation - structural network, autonomous dynamics, and transient dynamics.
Revised:  Further, we lay out the different levels at which neural reuse can occur through a dynamical filtering of the brain-body-environment system's operation : structural network, autonomous dynamics, and transient dynamics.
Edit intent: fluency
Original:  Notably, transient dynamics reuse can only be explained by studying the brain-body-environment system as a whole and not just the brain.
Revised:  Notably, transient dynamics reuse could only be explained by studying the brain-body-environment system as a whole and not just the brain.
Edit intent: fluency
Original:  Although mechanisms that underlie this ability are not well known , they are largely attributed to neuromodulation.
Revised:  Although mechanisms that underlie this ability are not well understood , they are largely attributed to neuromodulation.
Edit intent: clarity
Original:  Experiments demonstrate accurate estimates and improved prediction, even on high-dimensional datasets of natural images 
Revised:  Experiments demonstrate accurate estimates and improved prediction, even on high-dimensional datasets of natural images .
Edit intent: fluency
Original:  Motivated by medical diagnosis, where diseases (targets) , cause symptoms (observations), we focus on label shift, where the label marginal p(y) changes but the conditional p(x| y) does not.
Revised:  Motivated by medical diagnosis, where diseases (targets) cause symptoms (observations), we focus on label shift, where the label marginal p(y) changes but the conditional p(x| y) does not.
Edit intent: fluency
Original:  Specifically, we identify the structural identity of each node based on a high-order proximity of the network named Rooted PageRank, followed by a novel biased Skip-Gram Negative Sampling algorithm and a carefully designed objective function to encode local proximities and global structural identities of nodes simultaneously.
Edit intent: coherence
Original:  In this paper we propose GEMSEC  a graph embedding algorithm which learns a clustering of the nodes simultaneously with computing their features.
Revised:  In this paper we propose GEMSEC - a graph embedding algorithm which learns a clustering of the nodes simultaneously with computing their features.
Edit intent: fluency
Original: Network embedding procedures localize nodes of a graph in a low dimensional feature space, which enables machine learning on graph data .
Revised: Modern graph embedding procedures can efficiently process graphs with millions of nodes .
Edit intent: clarity
Original:  In this paper  we propose GEMSEC - a graph embedding algorithm which learns a clustering of the nodes simultaneously with the embedding.
Revised:  In this paper , we propose GEMSEC - a graph embedding algorithm which learns a clustering of the nodes simultaneously with the embedding.
Edit intent: fluency
Original:  In this paper  we propose GEMSEC - a graph embedding algorithm which learns a clustering of the nodes simultaneously with the embedding.
Revised:  In this paper we propose GEMSEC -- a graph embedding algorithm which learns a clustering of the nodes simultaneously with the embedding.
Edit intent: fluency
Original:  In experiments, the joint embedding and clustering is found to be extremely scalable, with computation costs linear in the size of the input .
Revised:  In experiments, the method is found to be extremely scalable, with computation costs linear in the size of the input .
Edit intent: clarity
Original:  In experiments, the joint embedding and clustering is found to be extremely scalable, with computation costs linear in the size of the input .
Revised:  In experiments, the joint embedding and clustering is found to be computationally efficient and robust to the choice of hyperparameters .
Edit intent: clarity
Original: Assume that we have an outer function f:\{0 , 1\}^n%DIFDELCMD < \to %%% \{0, 1\} and a gadget function g:A\times B%DIFDELCMD < \to%%% \{0, 1\} and we want to lower bound deterministic communication complexity of a composed function f\circ g^n, denoted here by D^{cc(f\circ g^n), in terms of deterministic query complexity of f, denoted here by D^{dt}(f).
Revised: Recently , 1\}^n%DIFDELCMD < \to %%% \{0, 1\} and a gadget function g:A\times B%DIFDELCMD < \to%%% \{0, 1\} and we want to lower bound deterministic communication complexity of a composed function f\circ g^n, denoted here by D^{cc(f\circ g^n), in terms of deterministic query complexity of f, denoted here by D^{dt}(f).
Edit intent: coherence
Original: Assume that we have an outer function f:\{0 , 1\}^n%DIFDELCMD < \to %%% \{0, 1\} and a gadget function g:A\times B%DIFDELCMD < \to%%% \{0, 1\} and we want to lower bound deterministic communication complexity of a composed function f\circ g^n, denoted here by D^{cc(f\circ g^n), in terms of deterministic query complexity of f, denoted here by D^{dt}(f).
Revised: Assume that we have an outer function f:\{0 , %DIFDELCMD < \to %%% \{0, 1\} and a gadget function g:A\times B%DIFDELCMD < \to%%% \{0, 1\} and we want to lower bound deterministic communication complexity of a composed function f\circ g^n, denoted here by D^{cc(f\circ g^n), in terms of deterministic query complexity of f, denoted here by D^{dt}(f).
Edit intent: coherence
Original:  The study of such questions, now usually called }Simulation Theorems , was initiated in the work of Raz and McKenzie (\mbox{ raz1997separation et al. (\mbox{ chattopadhyay2017simulation hitting distributions . Using this tool, they proved that D^{cc(f \circ g^n)
Revised:  The study of such questions, now usually called } , was initiated in the work of Raz and McKenzie (\mbox{ raz1997separation et al. (\mbox{ chattopadhyay2017simulation hitting distributions . Using this tool, they proved that D^{cc(f \circ g^n)
Edit intent: coherence
Original:  The study of such questions, now usually called }Simulation Theorems , was initiated in the work of Raz and McKenzie (\mbox{ raz1997separation et al. (\mbox{ chattopadhyay2017simulation hitting distributions . Using this tool, they proved that D^{cc(f \circ g^n)
Revised:  The study of such questions, now usually called }Simulation Theorems Chattopadhyay et al. (\mbox{ chattopadhyay2017simulation hitting distributions . Using this tool, they proved that D^{cc(f \circ g^n)
Edit intent: coherence
Original:  The study of such questions, now usually called }Simulation Theorems , was initiated in the work of Raz and McKenzie (\mbox{ raz1997separation et al. (\mbox{ chattopadhyay2017simulation hitting distributions . Using this tool, they proved that D^{cc(f \circ g^n)
Revised:  The study of such questions, now usually called }Simulation Theorems , was initiated in the work of Raz and McKenzie (\mbox{ raz1997separation et al. hitting distributions . Using this tool, they proved that D^{cc(f \circ g^n)
Edit intent: coherence
Original:  The study of such questions, now usually called }Simulation Theorems , was initiated in the work of Raz and McKenzie (\mbox{ raz1997separation et al. (\mbox{ chattopadhyay2017simulation hitting distributions . Using this tool, they proved that D^{cc(f \circ g^n)
Revised:  The study of such questions, now usually called }Simulation Theorems , was initiated in the work of Raz and McKenzie (\mbox{ raz1997separation et al. (\mbox{ chattopadhyay2017simulation . Using this tool, they proved that D^{cc(f \circ g^n)
Edit intent: coherence
Original:  The study of such questions, now usually called }Simulation Theorems , was initiated in the work of Raz and McKenzie (\mbox{ raz1997separation et al. (\mbox{ chattopadhyay2017simulation hitting distributions . Using this tool, they proved that D^{cc(f \circ g^n)
Revised:  The study of such questions, now usually called }Simulation Theorems , was initiated in the work of Raz and McKenzie (\mbox{ raz1997separation et al. (\mbox{ chattopadhyay2017simulation hitting distributions (f \circ g^n)
Edit intent: coherence
Original:  = \Omega}%DIFDELCMD < \left(%%% D^{dt(f) \cdot D^{cc}(g)}%DIFDELCMD < \right)%%% , where g is either Inner Productor  Gap Hamming Distance gadget on k bits, and f is any function depending on at most 2^{ck ]  ]  . In this work we use hitting distributions to show Simulation Theorem for a new gadget .
Revised:  = \Omega}%DIFDELCMD < \left(%%% D^{dt(f) \cdot D^{cc}(g)}%DIFDELCMD < \right)%%% , where g is either Inner Productor Gap Hamming Distance gadget on k bits, and f is any function depending on at most 2^{ck ] wu2017raz] . In this work we use hitting distributions to show Simulation Theorem for a new gadget .
Edit intent: fluency
Original:  = \Omega}%DIFDELCMD < \left(%%% D^{dt(f)
Revised:  = \Omega}%DIFDELCMD < \left(%%% (f)
Edit intent: fluency
Original:  ] . We also investigate hitting distributions for disjointness predicate on k-element subsets of \{1, 2, \ldots, n\ Thickness Lemma, a combinatorial statement from the proof of Simulation Theorems of G\"{o\"{o}s et al and Chattopadhyaay et al. , and show that this Lemma can not be improved}  .
Revised:  ]) . We also investigate hitting distributions for disjointness predicate on k-element subsets of \{1, 2, \ldots, n\ Thickness Lemma, a combinatorial statement from the proof of Simulation Theorems of G\"{o\"{o}s et al and Chattopadhyaay et al. , and show that this Lemma can not be improved} .
Edit intent: fluency