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1708.04728 | 2747590145 | Deploying deep neural networks on mobile devices is a challenging task. Current model compression methods such as matrix decomposition effectively reduce the deployed model size, but still cannot satisfy real-time processing requirement. This paper first discovers that the major obstacle is the excessive execution time... | Recently, SqueezeNet @cite_15 has became widely used for its much smaller memory cost and increased speed. However, the near-AlexNet accuracy is far below the state-of-the-art performance. Compared with these two newly networks, our approach has much better accuracy with more significant acceleration. @cite_30 showed t... | {
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"Most modern convolutional neural networks (CNNs) used for object recognition are built using the same principles: Alternating convolution and max-pooling layers followed by... |
1708.04863 | 2748458152 | Agreement plays a central role in distributed systems working on a common task. The increasing size of modern distributed systems makes them more susceptible to single component failures. Fault-tolerant distributed agreement protocols rely for the most part on leader-based atomic broadcast algorithms, such as Paxos. Su... | Atomic broadcast plays a central role in fault-tolerant distributed systems; for instance, it enables the implementation of both state machine replication @cite_19 @cite_21 and distributed agreement @cite_0 @cite_22 . As a result, the atomic broadcast problem sparked numerous proposals for algorithms @cite_13 . Many of... | {
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1708.04955 | 2774797382 | A decentralized online quantum cash system, called qBitcoin, is given. We design the system which has great benefits of quantization in the following sense. Firstly, quantum teleportation technology is used for coin transaction, which prevents from the owner of the coin keeping the original coin data even after sending... | The attempt to making a money system based on quantum mechanics has a long history. It is believed that Wiesner made a prototype in about 1970 (published in 1983) @cite_5 , in which quantum money that can be verified by a bank is given. In his scheme, quantum money was secure in the sense that it cannot be copied due t... | {
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1708.04871 | 2748038854 | We present SMAUG (Secure Mobile Authentication Using Gestures), a novel biometric assisted authentication algorithm for mobile devices that is solely based on data collected from multiple sensors that are usually installed on modern devices -- touch screen, gyroscope and accelerometer. As opposed to existing approaches... | With respect to gesture recognition for single-touch gestures, Rubine @cite_30 is the usual reference when comparing new single-touch algorithms. Another prominent example for single-touch and single-stroke gesture recognition is @cite_0 . The authors of @cite_36 present a very efficient follow-up work for single-touch... | {
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1708.04871 | 2748038854 | We present SMAUG (Secure Mobile Authentication Using Gestures), a novel biometric assisted authentication algorithm for mobile devices that is solely based on data collected from multiple sensors that are usually installed on modern devices -- touch screen, gyroscope and accelerometer. As opposed to existing approaches... | Continuous authentication means that the device constantly tracks and evaluates the inputs and movements of the user onto the device to authenticate the user. They generally suffer fom privacy loss in some kind. Algorithms can be found in @cite_20 @cite_25 @cite_10 . In @cite_31 , the authors present an attack on the g... | {
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1708.05071 | 2746521834 | In this paper, we propose to use deep 3-dimensional convolutional networks (3D CNNs) in order to address the challenge of modelling spectro-temporal dynamics for speech emotion recognition (SER). Compared to a hybrid of Convolutional Neural Network and Long-Short-Term-Memory (CNN-LSTM), our proposed 3D CNNs simultaneou... | The performance of SER using deep architectures can still be much improved, and an optimal feature set has not been found yet for SER. For example, in @cite_17 @cite_0 @cite_12 , high-level features obtained from off-the-shelf features outperformed conventional methods. However, representation learning using log-spectr... | {
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1708.05071 | 2746521834 | In this paper, we propose to use deep 3-dimensional convolutional networks (3D CNNs) in order to address the challenge of modelling spectro-temporal dynamics for speech emotion recognition (SER). Compared to a hybrid of Convolutional Neural Network and Long-Short-Term-Memory (CNN-LSTM), our proposed 3D CNNs simultaneou... | CNN-based methods using low-level features were proposed and outperformed off-the-shelf feature-based methods @cite_6 @cite_16 @cite_11 @cite_1 @cite_26 . @cite_6 @cite_16 @cite_11 2D feature maps were composed of spectrogram features with a fine resolution. However, these 2D CNNs cannot model temporal dependency direc... | {
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1708.05905 | 2749529790 | Internet of Things (IoT) systems have aroused enthusiasm and concerns. Enthusiasm comes from their utilities in people daily life, and concerns may be associated with privacy issues. By using two IoT systems as case-studies, we examine users' privacy beliefs, concerns and attitudes. We focus on four major dimensions: t... | From a legislation viewpoint, considering the laws in the United States of America, privacy can be defined as the right of an individual to be let alone'' @cite_6 . People, in turn, usually associate the word privacy with a diversity of meanings. Some people believe that privacy is the right to control what information... | {
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1708.05905 | 2749529790 | Internet of Things (IoT) systems have aroused enthusiasm and concerns. Enthusiasm comes from their utilities in people daily life, and concerns may be associated with privacy issues. By using two IoT systems as case-studies, we examine users' privacy beliefs, concerns and attitudes. We focus on four major dimensions: t... | In information and communications technology (ICT), the concept of privacy is usually associated to the degree of control over the flow of personal information @cite_15 . In this context, people associate privacy to something regarding to their level of control over the collection of personal information, and usage of ... | {
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1708.05905 | 2749529790 | Internet of Things (IoT) systems have aroused enthusiasm and concerns. Enthusiasm comes from their utilities in people daily life, and concerns may be associated with privacy issues. By using two IoT systems as case-studies, we examine users' privacy beliefs, concerns and attitudes. We focus on four major dimensions: t... | Concerns about privacy usually arise from unauthorized collection of personal data, unauthorized secondary use of the data, errors in personal data, and improper access to personal data @cite_22 . People concerns are indeed associated to possible consequences that these occurrences may have on their lives. Two relevant... | {
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"Information privacy has been called one of the most important ethical issues of the informa1 Alien Lee was the accepting senior for this paper. tion age. Public opinion polls show rising levels of concer about privacy among Americ... |
1708.05870 | 2748257817 | We address a fundamental question in wireless networks that, surprisingly, has not been studied before: what is the maximum density of concurrently active links that satisfy a certain outage constraint? We call this quantity the spatial outage capacity (SOC), give a rigorous definition, and analyze it for Poisson bipol... | For Poisson bipolar networks, the mean success probability @math is calculated in @cite_1 and @cite_12 . For ad hoc networks modeled by the Poisson point process (PPP), the link success probability @math is studied in @cite_9 , where the focus is on the mean local delay, i.e. , the @math st moment of @math in our notat... | {
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"We study a slotted version of the Aloha Medium Access (MAC) protocol in a Mobile Ad-hoc Network (MANET). Our model features transm... |
1708.05870 | 2748257817 | We address a fundamental question in wireless networks that, surprisingly, has not been studied before: what is the maximum density of concurrently active links that satisfy a certain outage constraint? We call this quantity the spatial outage capacity (SOC), give a rigorous definition, and analyze it for Poisson bipol... | A version of the TC based on the link success probability distribution is introduced in @cite_8 , but it does not consider a MAC scheme, , all nodes always transmit ( @math ). The choice of @math is important as it greatly affects the link success probability distribution as shown in Fig. . In this paper, we consider t... | {
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"In this paper we consider a network where the nodes locations are modeled by a realization of a Poisson point process and remains fixed or changes very slowly over time. Most of the literature focuses on the spatial average of the ... |
1708.05870 | 2748257817 | We address a fundamental question in wireless networks that, surprisingly, has not been studied before: what is the maximum density of concurrently active links that satisfy a certain outage constraint? We call this quantity the spatial outage capacity (SOC), give a rigorous definition, and analyze it for Poisson bipol... | The meta distribution @math for Poisson bipolar networks with ALOHA and cellular networks is calculated in @cite_10 , where a closed-form expression for the moments of @math is obtained, and an exact integral expression and simple bounds on @math are provided. A key result in @cite_10 is that, for constant transmitter ... | {
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1708.05768 | 2750396241 | We consider the analysis of high dimensional data given in the form of a matrix with columns consisting of observations and rows consisting of features. Often the data is such that the observations do not reside on a regular grid, and the given order of the features is arbitrary and does not convey a notion of locality... | This work is also related to the matrix factorization proposed by @cite_10 , where the graph Laplacians of both the features and the observation regularize the decomposition of a dataset into a low-rank matrix and a sparse matrix representing noise. Then the observations are clustered using k-means on the low-dimension... | {
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"Mining useful clusters from high dimensional data have received significant attention of the computer vision and pattern recognition community in the recent years. Linear and nonlinear dimensionality reduction has played an import... |
1708.05732 | 2746990488 | Inter-connected objects, either via public or private networks are the near future of modern societies. Such inter-connected objects are referred to as Internet-of-Things (IoT) and or Cyber-Physical Systems (CPS). One example of such a system is based on Unmanned Aerial Vehicles (UAVs). The fleet of such vehicles are p... | The swarm intelligence paradigm has been used to optimise and control single UAVs: In @cite_0 , single vehicle autonomous path planning by learning from small number of examples. | {
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"Autonomous navigation for large Unmanned Aerial Vehicles (UAVs) is fairly straight-forward, as expensive sensors and monitoring devices can be employed. In contrast, obstacle avoidance remains a challenging task for Micro Aerial Ve... |
1708.05732 | 2746990488 | Inter-connected objects, either via public or private networks are the near future of modern societies. Such inter-connected objects are referred to as Internet-of-Things (IoT) and or Cyber-Physical Systems (CPS). One example of such a system is based on Unmanned Aerial Vehicles (UAVs). The fleet of such vehicles are p... | In @cite_8 , three-dimensional path planning for a single drone using a bat inspired algorithm to determine suitable points in space and applying B-spline curves to improve smoothness of the path. | {
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"Abstract As a challenging high dimension optimization problem, three-dimensional path planning for Uninhabited Combat Air Vehicles (UCAV) mainly centralizes on optimizing the flight route with different types of constrains under co... |
1708.05732 | 2746990488 | Inter-connected objects, either via public or private networks are the near future of modern societies. Such inter-connected objects are referred to as Internet-of-Things (IoT) and or Cyber-Physical Systems (CPS). One example of such a system is based on Unmanned Aerial Vehicles (UAVs). The fleet of such vehicles are p... | In @cite_35 , authors introduced and validated a decentralised architecture for search and rescue missions in ground based robot groups of different sizes. Considered limited communication ability with a command centre and employs distributed communication. | {
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"Multi-robot systems (MRS) may be very useful on assisting humans in many distributed activities, especially for search and rescue (SaR) missions in hazardous scenarios. However, there is a lack of full distributed solutions, addre... |
1708.05732 | 2746990488 | Inter-connected objects, either via public or private networks are the near future of modern societies. Such inter-connected objects are referred to as Internet-of-Things (IoT) and or Cyber-Physical Systems (CPS). One example of such a system is based on Unmanned Aerial Vehicles (UAVs). The fleet of such vehicles are p... | In @cite_1 , the authors achieved area coverage for surveillance in a FoD using visual relative localisation for keeping formation autonomously. | {
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"An algorithm for autonomous deployment of groups of Micro Aerial Vehicles (MAVs) in the cooperative surveillance task is presented in this paper. The algorithm enables to find a proper distributions of all MAVs in surveillance loca... |
1708.05894 | 2745765770 | Sepsis is a poorly understood and potentially life-threatening complication that can occur as a result of infection. Early detection and treatment improves patient outcomes, and as such it poses an important challenge in medicine. In this work, we develop a flexible classifier that leverages streaming lab results, vita... | There are many previously published early warning scores for predicting clinical deterioration or other related outcomes. For instance, the NEWS score ( @cite_13 ) and MEWS score ( @cite_25 ) are two of the more common scores used to assess overall deterioration. The SIRS score for systemic inflammatory response syndro... | {
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1708.05688 | 2746260445 | One of the most crucial issues in data mining is to model human behaviour in order to provide personalisation, adaptation and recommendation. This usually involves implicit or explicit knowledge, either by observing user interactions, or by asking users directly. But these sources of information are always subject to t... | The central role of information systems led to a lot of research and produced a variety of techniques and approaches @cite_29 . Here, we focus especially on recommender systems which are comprehensively described in @cite_18 @cite_33 . For the comparative assessment, different metrics are used to determine the predicti... | {
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1708.05688 | 2746260445 | One of the most crucial issues in data mining is to model human behaviour in order to provide personalisation, adaptation and recommendation. This usually involves implicit or explicit knowledge, either by observing user interactions, or by asking users directly. But these sources of information are always subject to t... | Probabilistic modelling of human cognition processes is quite common to the field of computational neuroscience. In particular, aspects of human decision-making can be stated as problems of probabilistic inference @cite_7 (often referred to as Bayesian Brain'' paradigm). Besides external influential factors, the belief... | {
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1708.05543 | 2747753476 | In the era of autonomous driving, urban mapping represents a core step to let vehicles interact with the urban context. Successful mapping algorithms have been proposed in the last decade building the map leveraging on data from a single sensor. The focus of the system presented in this paper is twofold: the joint esti... | Mapping from laser sensors is a well studied research area in Robotics; in the early studies, the map has been estimated in 2 dimensions @cite_14 , while, in recent years, the prevalent approach is to estimate it in 3D thanks to advances in algorithms, processing and sensors. Mapping can be pursued together with robot ... | {
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1708.05543 | 2747753476 | In the era of autonomous driving, urban mapping represents a core step to let vehicles interact with the urban context. Successful mapping algorithms have been proposed in the last decade building the map leveraging on data from a single sensor. The focus of the system presented in this paper is twofold: the joint esti... | Some approaches estimate a 2.5D map of the environment by populating a grid on the ground plane with the corresponding cell heights @cite_24 . These maps are useful for robot navigation, but neglect most of the environment details. A more coherent representation of the scene is volumetric, i.e, the space is partitioned... | {
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1708.05543 | 2747753476 | In the era of autonomous driving, urban mapping represents a core step to let vehicles interact with the urban context. Successful mapping algorithms have been proposed in the last decade building the map leveraging on data from a single sensor. The focus of the system presented in this paper is twofold: the joint esti... | Voxel-based approaches usually produce unappealing reconstructions, due to the voxelization of the space, and they need a very high resolution to capture fine details of the scene, trading off their efficiency. In Computer Vision community, different volumetric representations have been explored, in particular many alg... | {
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1708.05543 | 2747753476 | In the era of autonomous driving, urban mapping represents a core step to let vehicles interact with the urban context. Successful mapping algorithms have been proposed in the last decade building the map leveraging on data from a single sensor. The focus of the system presented in this paper is twofold: the joint esti... | Among image-based dense photoconsistent algorithms, the mesh-based algorithm @cite_4 @cite_1 have been proven to estimate very accurate models and to be scalable in large-scale environments. They bootstrap form an initial mesh with a volumetric method such as @cite_22 or @cite_0 and they refine it by minimizing a photo... | {
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1708.05543 | 2747753476 | In the era of autonomous driving, urban mapping represents a core step to let vehicles interact with the urban context. Successful mapping algorithms have been proposed in the last decade building the map leveraging on data from a single sensor. The focus of the system presented in this paper is twofold: the joint esti... | In our paper, in order to filter out moving objects from the lidar data and the images, we need to explicitly detect them. A laser-based moving objects detection algorithm has been proposed by Petrovskaya and Thrun @cite_35 to detect a moving vehicles using model-based vehicle fitting algorithm; the method performs wel... | {
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1708.05582 | 2749333275 | This paper presents models for detecting agreement disagreement in online discussions. In this work we show that by using a Siamese inspired architecture to encode the discussions, we no longer need to rely on hand-crafted features to exploit the meta thread structure. We evaluate our model on existing online discussio... | Previous work in this field focused a lot on spoken dialogues. @cite_13 @cite_27 @cite_16 used spurt level agreement annotations from the ICSI corpus @cite_8 . @cite_30 presents detection of agreements in multi-party conversations using the AMI meeting corpus @cite_28 . @cite_31 presents a conditional random field base... | {
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1708.05582 | 2749333275 | This paper presents models for detecting agreement disagreement in online discussions. In this work we show that by using a Siamese inspired architecture to encode the discussions, we no longer need to rely on hand-crafted features to exploit the meta thread structure. We evaluate our model on existing online discussio... | Recently, researchers have turned their attention towards (dis)agreement detection in online discussions. The prior work was geared towards performing 2-way classification of agreement disagreement. @cite_49 used various sentiment, emotional and durational features to detect local and global (dis)agreement in discussio... | {
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1708.05582 | 2749333275 | This paper presents models for detecting agreement disagreement in online discussions. In this work we show that by using a Siamese inspired architecture to encode the discussions, we no longer need to rely on hand-crafted features to exploit the meta thread structure. We evaluate our model on existing online discussio... | (Dis)agreement detection is related to other similar NLP tasks like stance detection and argument mining but is not exactly the same. Stance detection is the task of identifying whether the author of the text is in favor or against or neutral towards a target, while argument mining focuses on tasks like automatic extra... | {
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"This paper provides the results of experiments on the detection of arguments in texts among which are legal texts. The detection is seen as... |
1708.05587 | 2749420821 | We study models of weighted exponential random graphs in the large network limit. These models have recently been proposed to model weighted network data arising from a host of applications including socio-econometric data such as migration flows and neuroscience desmarais2012statistical . Analogous to fundamental resu... | Weighted exponential random graph models were theoretically analyzed in @cite_14 when the base measure is supported on a bounded interval and in @cite_18 the authors analyzed the phase transition phenomenon for a class of base measures supported on @math . In @cite_14 the no-phase transition" result for standard normal... | {
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1708.05775 | 2750321818 | FJRW theory is a formulation of physical Landau-Ginzburg models with a rich algebraic structure, rooted in enumerative geometry. As a consequence of a major physical conjecture, called the Landau-Ginzburg Calabi-Yau correspondence, several birational morphisms of Calabi-Yau orbifolds should correspond to isomorphisms i... | Their result relies on the assumption that @math . In order to understand this restriction better, consider that there are two possible weight systems for @math yielding an elliptic curve and 44 possible weight systems for @math yielding a K3 surface with involution. Recall in this construction, we require our polynomi... | {
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"We prove that the Borcea-Voisin mirror pairs of Calabi-Yau three- folds admit projective birational models that satisfy the Berglund-Hubsch- Chiodo-Ruan transposition rule. This shows that the two mirror constructions provide the ... |
1708.05775 | 2750321818 | FJRW theory is a formulation of physical Landau-Ginzburg models with a rich algebraic structure, rooted in enumerative geometry. As a consequence of a major physical conjecture, called the Landau-Ginzburg Calabi-Yau correspondence, several birational morphisms of Calabi-Yau orbifolds should correspond to isomorphisms i... | In @cite_0 , the last author has considered exactly the form of mirror symmetry we propose here with the restriction that the defining polynomials must be Fermat type. In fact, he was able to show that for the mirror pairs we consider here, there is a mirror map relating the FJRW invariants of the A--model to the Picar... | {
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1708.05932 | 2750338112 | In phase retrieval we want to recover an unknown signal @math from @math quadratic measurements of the form @math where @math are known sensing vectors and @math is measurement noise. We ask the following weak recovery question: what is the minimum number of measurements @math needed to produce an estimator @math that ... | The performance of the spectral methods for phase retrieval was first considered in @cite_8 . In the present notation, @cite_8 uses @math and proves that there exists a constant @math such that weak recovery can be achieved for @math . The same paper also gives an iterative procedure to improve over the spectral method... | {
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1708.05932 | 2750338112 | In phase retrieval we want to recover an unknown signal @math from @math quadratic measurements of the form @math where @math are known sensing vectors and @math is measurement noise. We ask the following weak recovery question: what is the minimum number of measurements @math needed to produce an estimator @math that ... | In @cite_46 , the authors introduce the PhaseMax relaxation and prove an exact recovery result for phase retrieval, which depends on the correlation between the true signal and the initial estimate given to the algorithm. The same idea was independently proposed in @cite_23 . Furthermore, the analysis in @cite_23 allow... | {
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1708.05932 | 2750338112 | In phase retrieval we want to recover an unknown signal @math from @math quadratic measurements of the form @math where @math are known sensing vectors and @math is measurement noise. We ask the following weak recovery question: what is the minimum number of measurements @math needed to produce an estimator @math that ... | As previously mentioned, our analysis of spectral methods builds on the recent work of Lu and Li @cite_38 that compute the exact spectral threshold for a matrix of the form ) with @math . Here we generalize this result to signed pre-processing functions @math , and construct a function of this type that achieves the in... | {
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1708.05827 | 2746391148 | We introduce a general framework for visual forecasting, which directly imitates visual sequences without additional supervision. As a result, our model can be applied at several semantic levels and does not require any domain knowledge or handcrafted features. We achieve this by formulating visual forecasting as an in... | There has been growing interest in developing computational models of human activities that can extrapolate unseen information and predict future unobserved activities @cite_50 @cite_22 @cite_8 @cite_34 @cite_38 @cite_0 @cite_5 @cite_53 . Some of the existing approaches @cite_50 @cite_22 @cite_38 @cite_44 @cite_0 @cite... | {
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1708.05827 | 2746391148 | We introduce a general framework for visual forecasting, which directly imitates visual sequences without additional supervision. As a result, our model can be applied at several semantic levels and does not require any domain knowledge or handcrafted features. We achieve this by formulating visual forecasting as an in... | Reinforcement learning (RL) achieves remarkable success in multiple domains ranging from robotics @cite_14 , computer vision @cite_45 @cite_13 @cite_3 and natural language processing @cite_23 @cite_41 . In the RL setting, the reward function that the agent aims to maximize is given as signal for training, where the goa... | {
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1708.05827 | 2746391148 | We introduce a general framework for visual forecasting, which directly imitates visual sequences without additional supervision. As a result, our model can be applied at several semantic levels and does not require any domain knowledge or handcrafted features. We achieve this by formulating visual forecasting as an in... | Our extension of generative adversarial imitation learning @cite_51 is related to recent progress in generative adversarial networks (GAN) @cite_20 . While there has been multiple works on applying GAN to image and video @cite_10 @cite_31 @cite_38 @cite_16 , we extend it to long-term prediction of natural visual sequen... | {
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1906.00588 | 2947756088 | Neural Networks (NNs) have been extensively used for a wide spectrum of real-world regression tasks, where the goal is to predict a numerical outcome such as revenue, effectiveness, or a quantitative result. In many such tasks, the point prediction is not enough, but also the uncertainty (i.e. risk, or confidence) of t... | There has been significant interest in combining NNs with probabilistic Bayesian models. An early approach was Bayesian Neural Networks, in which a prior distribution is defined on the weights and biases of a NN, and a posterior distribution is then inferred from the training data @cite_28 @cite_9 . Traditional variati... | {
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1906.00402 | 2947069245 | In dealing with constrained multi-objective optimization problems (CMOPs), a key issue of multi-objective evolutionary algorithms (MOEAs) is to balance the convergence and diversity of working populations. | The push and pull search (PPS) framework was introduced by @cite_15 . Unlike other constraint handling mechanisms, the search process of PPS is divided into two different stages: the push search and the pull search, and follows a procedure of "push first and pull second", by which the working population is pushed towar... | {
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1906.00402 | 2947069245 | In dealing with constrained multi-objective optimization problems (CMOPs), a key issue of multi-objective evolutionary algorithms (MOEAs) is to balance the convergence and diversity of working populations. | Employing a number of sub-populations to solve problems in a collaborative way @cite_26 is a widely used approach, which can help an algorithm balance its convergence and diversity. One of the most popular methods is the M2M population decomposition approach @cite_41 , which decomposes a multi-objective optimization pr... | {
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1906.00642 | 2947251021 | As an important semi-supervised learning task, positive-unlabeled (PU) learning aims to learn a binary classifier only from positive and unlabeled data. In this article, we develop a novel PU learning framework, called discriminative adversarial networks, which contains two discriminative models represented by deep neu... | An important idea of DAN is to approximate @math by matching @math and @math , which has in fact been investigated in literature (see, e.g., @cite_14 @cite_24 @cite_35 @cite_12 @cite_20 ). However, the direct approximation based on ) involves the probability density estimation and is difficult for high-dimensional appl... | {
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1906.00642 | 2947251021 | As an important semi-supervised learning task, positive-unlabeled (PU) learning aims to learn a binary classifier only from positive and unlabeled data. In this article, we develop a novel PU learning framework, called discriminative adversarial networks, which contains two discriminative models represented by deep neu... | It is also interesting to compare DAN to GenPU, a GAN based PU learning method @cite_23 , since they share the similar adversarial training architecture. In DAN, the discriminative model @math plays the role of the generative model in GAN by approximating positive data distribution in an implicit way, and can be effici... | {
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"In this work, we consider the task of classifying binary positive-unlabeled (PU) data. The existing discriminative learning based PU models attempt to seek an optimal reweighting strategy for U data, so that a decent decision boun... |
1906.00424 | 2947626630 | Unilateral contracts, such as terms of service, play a substantial role in modern digital life. However, few users read these documents before accepting the terms within, as they are too long and the language too complicated. We propose the task of summarizing such legal documents in plain English, which would enable u... | The dataset we present summarizes contracts in plain English . While there is no precise definition of plain English, the general philosophy is to make a text readily accessible for as many English speakers as possible. @cite_21 @cite_20 . Guidelines for plain English often suggest a preference for words with Saxon ety... | {
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1906.00360 | 2947973288 | Modern smartphones have all the sensing capabilities required for accurate and robust navigation and tracking. In specific environments some data streams may be absent, less reliable, or flat out wrong. In particular, the GNSS signal can become flawed or silent inside buildings or in streets with tall buildings. In thi... | The classical inertial navigation literature is extensive (see the books @cite_3 @cite_27 @cite_18 @cite_15 , for example) but is mainly focused on navigation of large vehicles with relatively high quality inertial sensors. Even though the theory is solid and general, practice has shown that a lot of hand-tailoring of ... | {
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1906.00360 | 2947973288 | Modern smartphones have all the sensing capabilities required for accurate and robust navigation and tracking. In specific environments some data streams may be absent, less reliable, or flat out wrong. In particular, the GNSS signal can become flawed or silent inside buildings or in streets with tall buildings. In thi... | Besides SHS and VIO approaches, there are also pure inertial navigation approaches which estimate the full motion trajectory in 3D by using foot-mounted consumer-grade inertial sensors @cite_28 @cite_0 . With foot-mounted sensors the inertial navigation problem is considerably easier than in the general case since the ... | {
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1906.00360 | 2947973288 | Modern smartphones have all the sensing capabilities required for accurate and robust navigation and tracking. In specific environments some data streams may be absent, less reliable, or flat out wrong. In particular, the GNSS signal can become flawed or silent inside buildings or in streets with tall buildings. In thi... | On the more technical side, we apply iterative filtering methods in this paper. Kalman filters and smoothers (see, , @cite_19 for an excellent overview of non-linear filtering) are recursive estimation schemes and thus iterative already per definition. Iterated filtering often refers to local ( inner-loop') iterations ... | {
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1906.00360 | 2947973288 | Modern smartphones have all the sensing capabilities required for accurate and robust navigation and tracking. In specific environments some data streams may be absent, less reliable, or flat out wrong. In particular, the GNSS signal can become flawed or silent inside buildings or in streets with tall buildings. In thi... | In this paper, we take a general INS approach, without assuming legged or otherwise constrained motion, and compensate the limitations of low quality IMUs by fusing them with GNSS position fixes, which may be potentially sparse and infrequent containing large gaps in signal reception. As mentioned, there are relatively... | {
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1906.00452 | 2947132063 | Data imbalance remains one of the most widespread problems affecting contemporary machine learning. The negative effect data imbalance can have on the traditional learning algorithms is most severe in combination with other dataset difficulty factors, such as small disjuncts, presence of outliers and insufficient numbe... | The most fundamental choice during the design of both oversampling and undersampling algorithms for handling data imbalance is the question of defining the regions of interest: the areas in which either the new instances are to be placed, in case of oversampling, or from which the existing instances are to be removed, ... | {
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1906.00452 | 2947132063 | Data imbalance remains one of the most widespread problems affecting contemporary machine learning. The negative effect data imbalance can have on the traditional learning algorithms is most severe in combination with other dataset difficulty factors, such as small disjuncts, presence of outliers and insufficient numbe... | Another family of methods that can be distinguished are the cluster-based undersampling algorithms, notably the methods proposed by Yen and Lee @cite_36 , which use clustering to select the most representative subset of data. Finally, as has been originally demonstrated by @cite_11 , undersampling algorithms are well-s... | {
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1906.00452 | 2947132063 | Data imbalance remains one of the most widespread problems affecting contemporary machine learning. The negative effect data imbalance can have on the traditional learning algorithms is most severe in combination with other dataset difficulty factors, such as small disjuncts, presence of outliers and insufficient numbe... | Despite the abundance of different strategies of dealing with data imbalance, it often remains unclear under what conditions a given method is expected to guarantee a satisfactory performance. Furthermore, taking into the account the no free lunch theorem @cite_39 it is unreasonable to expect that any single method wil... | {
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1906.00452 | 2947132063 | Data imbalance remains one of the most widespread problems affecting contemporary machine learning. The negative effect data imbalance can have on the traditional learning algorithms is most severe in combination with other dataset difficulty factors, such as small disjuncts, presence of outliers and insufficient numbe... | In the context of the imbalanced data classification, one of the criteria that can influence the applicability of different resampling strategies are the characteristics of the minority class distribution. Napierała and Stefanowski @cite_10 proposed a method of categorization of different types of minority objects that... | {
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1906.00535 | 2947458343 | There is a high demand for high-quality Non-Player Characters (NPCs) in video games. Hand-crafting their behavior is a labor intensive and error prone engineering process with limited controls exposed to the game designers. We propose to create such NPC behaviors interactively by training an agent in the target environ... | Using human demonstrations helps training artificial agents in many applications and in particular in video games @cite_18 , @cite_13 , @cite_19 . Off-policy human demonstrations are easier to use and are abundant in player telemetry data. Supervised behavior cloning, imitation learning (IL), apprenticeship learning (e... | {
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1906.00535 | 2947458343 | There is a high demand for high-quality Non-Player Characters (NPCs) in video games. Hand-crafting their behavior is a labor intensive and error prone engineering process with limited controls exposed to the game designers. We propose to create such NPC behaviors interactively by training an agent in the target environ... | Direct inclusion of a human in the control loop can potentially alleviate the problem of limited generalization. Dataset Aggregation, DAGGER @cite_8 , allows for an effective way of doing that when a human provides consistent optimal input, which may not be realistic in many environments. Another way of such inclusion ... | {
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1906.00580 | 2947218620 | Language style transfer has attracted more and more attention in the past few years. Recent researches focus on improving neural models targeting at transferring from one style to the other with labeled data. However, transferring across multiple styles is often very useful in real-life applications. Previous researche... | The need to leverage unlabeled data draws a lot of interests of NMT researchers. Researches like @cite_26 @cite_20 , @cite_17 , and @cite_24 propose methods to build semi-supervised or unsupervised models. However, these techniques mainly designed for NMT tasks, and they haven't been widely used for style transfer task... | {
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1906.00580 | 2947218620 | Language style transfer has attracted more and more attention in the past few years. Recent researches focus on improving neural models targeting at transferring from one style to the other with labeled data. However, transferring across multiple styles is often very useful in real-life applications. Previous researche... | The core inspiration for our proposed system comes from the idea of multi-agent system design. A P2P self-organization system @cite_11 have been successfully applied in practical security systems. They design policies for agents to choose useful neighbors to produce better predictions. It enlightens us to build style t... | {
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1906.00628 | 2946911432 | We present an efficient technique, which allows to train classification networks which are verifiably robust against norm-bounded adversarial attacks. This framework is built upon the work of , who applies the interval arithmetic to bound the activations at each layer and keeps the prediction invariant to the input per... | To speed up the training of verifiably robust models, one can bound a set of activations reachable through a norm-bounded perturbation @cite_14 @cite_35 . In @cite_24 , linear programming was used to find the convex outer bound for ReLU networks. This approach was later extended to general non-ReLU neurons @cite_33 . A... | {
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1906.00423 | 2946912408 | Consider a two-player zero-sum stochastic game where the transition function can be embedded in a given feature space. We propose a two-player Q-learning algorithm for approximating the Nash equilibrium strategy via sampling. The algorithm is shown to find an @math -optimal strategy using sample size linear to the numb... | In the special case of MDP, there exist a large body of works on its sample complexity and sampling-based algorithms. For the tabular setting (finitely many state and actions), sample complexity of MDP with a sampling oracle has been studied in @cite_8 @cite_2 @cite_7 @cite_13 @cite_34 @cite_14 @cite_33 . Lower bounds ... | {
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1906.00423 | 2946912408 | Consider a two-player zero-sum stochastic game where the transition function can be embedded in a given feature space. We propose a two-player Q-learning algorithm for approximating the Nash equilibrium strategy via sampling. The algorithm is shown to find an @math -optimal strategy using sample size linear to the numb... | As for general stochastic games, the minimax Q-learning algorithm and the friend-and-foe Q-learning algorithm is introduced in @cite_37 and @cite_15 , respectively. The Nash Q-learning algorithm is proposed for zero-sum games in @cite_4 and for general-sum games in @cite_40 @cite_23 . Also in @cite_21 , the error of ap... | {
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1906.00377 | 2912317488 | High accuracy video label prediction (classification) models are attributed to large scale data. These data could be frame feature sequences extracted by a pre-trained convolutional-neural-network, which promote the efficiency for creating models. Unsupervised solutions such as feature average pooling, as a simple labe... | Video feature sequence classification is essentially the the task of aggregating video features, that is, to aggregate @math @math -dimensional features into one @math -dimensional feature by mining statistical relationships between these @math features. The aggregated @math -dimensional feature is a highly concentrate... | {
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1708.05482 | 2748618075 | Emotion cause extraction aims to identify the reasons behind a certain emotion expressed in text. It is a much more difficult task compared to emotion classification. Inspired by recent advances in using deep memory networks for question answering (QA), we propose a new approach which considers emotion cause identifica... | Identifying emotion categories in text is one of the key tasks in NLP @cite_29 . Going one step further, emotion cause extraction can reveal important information about what causes a certain emotion and why there is an emotion change . In this section, we introduce related work on emotion analysis including emotion cau... | {
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1708.05482 | 2748618075 | Emotion cause extraction aims to identify the reasons behind a certain emotion expressed in text. It is a much more difficult task compared to emotion classification. Inspired by recent advances in using deep memory networks for question answering (QA), we propose a new approach which considers emotion cause identifica... | Existing work in emotion analysis mostly focuses on emotion classification @cite_6 @cite_23 and emotion information extraction @cite_1 . used a coarse to fine method to classify emotions in Chinese blogs. proposed a joint model to co-train a polarity classifier and an emotion classifier. proposed a Multi-task Gaussian-... | {
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1708.05482 | 2748618075 | Emotion cause extraction aims to identify the reasons behind a certain emotion expressed in text. It is a much more difficult task compared to emotion classification. Inspired by recent advances in using deep memory networks for question answering (QA), we propose a new approach which considers emotion cause identifica... | first proposed a task on emotion cause extraction. They manually constructed a corpus from the Academia Sinica Balanced Chinese Corpus. Based on this corpus, proposed a rule based method to detect emotion causes based on manually define linguistic rules. Some studies @cite_3 @cite_15 @cite_0 extended the rule based met... | {
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1708.05509 | 2747543643 | Automatic generation of facial images has been well studied after the Generative Adversarial Network (GAN) came out. There exists some attempts applying the GAN model to the problem of generating facial images of anime characters, but none of the existing work gives a promising result. In this work, we explore the trai... | Generative Adversarial Network (GAN) @cite_12 , proposed by , shows impressive results in image generation @cite_25 , image transfer @cite_8 , super-resolution @cite_26 and many other generation tasks. The essence of GAN can be summarized as training a model and a model simultaneously, where the discriminator model tri... | {
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1708.05509 | 2747543643 | Automatic generation of facial images has been well studied after the Generative Adversarial Network (GAN) came out. There exists some attempts applying the GAN model to the problem of generating facial images of anime characters, but none of the existing work gives a promising result. In this work, we explore the trai... | Although the training process is quiet simple, optimizing such models often lead to , in which the generator will always produce the same image. To train GANs stably, @cite_9 suggests rendering Discriminator omniscient whenever necessary. By learning a loss function to separate generated samples from their real example... | {
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1708.05509 | 2747543643 | Automatic generation of facial images has been well studied after the Generative Adversarial Network (GAN) came out. There exists some attempts applying the GAN model to the problem of generating facial images of anime characters, but none of the existing work gives a promising result. In this work, we explore the trai... | Many variants of GAN have been proposed for generating images. @cite_25 applied convolutional neural network in GAN to generate images from latent vector inputs. Instead of generating images from latent vectors, serval methods use the same adversarial idea for generating images with more meaningful input. Mirza & intro... | {
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1708.05096 | 2750197405 | For many, this is no longer a valid question and the case is considered settled with SDN NFV (Software Defined Networking Network Function Virtualization) providing the inevitable innovation enablers solving many outstanding management issues regarding 5G. However, given the monumental task of softwarization of radio a... | In a recent and most comprehensive survey of SDN and virtualization research for LTE mobile networks @cite_51 , the authors have provided a general overview of SDN and virtualization technologies and their respective benefits. They have developed a taxonomy to survey the research space based on the elements of modern c... | {
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1708.05096 | 2750197405 | For many, this is no longer a valid question and the case is considered settled with SDN NFV (Software Defined Networking Network Function Virtualization) providing the inevitable innovation enablers solving many outstanding management issues regarding 5G. However, given the monumental task of softwarization of radio a... | Another recent survey @cite_120 briefly surveys all technologies and applications associated with 5G. The survey also touches upon SDN and only superficially covers some research work under the theme. A more in-depth analysis of some of SDN-based mobile network architectures, i.e., @cite_34 @cite_91 @cite_146 @cite_137... | {
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1708.05137 | 2747668150 | We propose a novel video object segmentation algorithm based on pixel-level matching using Convolutional Neural Networks (CNN). Our network aims to distinguish the target area from the background on the basis of the pixel-level similarity between two object units. The proposed network represents a target object using f... | Most recent approaches @cite_16 @cite_13 @cite_10 @cite_34 @cite_26 @cite_17 separate discriminative objects from a background by optimizing an energy equation under various pixel graph relationships. For instance, fully connected graphs have been proposed in @cite_6 to construct a long range spatio-temporal graph stru... | {
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1708.05468 | 2747901247 | The privacy-utility tradeoff problem is formulated as determining the privacy mechanism (random mapping) that minimizes the mutual information (a metric for privacy leakage) between the private features of the original dataset and a released version. The minimization is studied with two types of constraints on the dist... | An alternative approach to more general distortion constraints is considered in @cite_8 and referred to as footnote 0 We have changed their notation from @math -separable to @math -separable, in order to avoid confusion with our notation. . In @cite_8 , a multi-letter distortion measure @math is defined as @math -separ... | {
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1708.05468 | 2747901247 | The privacy-utility tradeoff problem is formulated as determining the privacy mechanism (random mapping) that minimizes the mutual information (a metric for privacy leakage) between the private features of the original dataset and a released version. The minimization is studied with two types of constraints on the dist... | In the context of privacy, the privacy utility tradeoff with distinct @math and @math is studied in @cite_23 and more extensively in @cite_6 , but the utility metric is only restricted to identity cost functions, i.e. @math . Generalizing this to the excess distortion constraint was considered by @cite_20 . In @cite_20... | {
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1708.05468 | 2747901247 | The privacy-utility tradeoff problem is formulated as determining the privacy mechanism (random mapping) that minimizes the mutual information (a metric for privacy leakage) between the private features of the original dataset and a released version. The minimization is studied with two types of constraints on the dist... | In @cite_20 , we also allow the mechanisms to be either memoryless (also referred to as ) or general. This approach has also been considered in the context of differential privacy (DP) (see for example @cite_21 @cite_24 @cite_18 @cite_4 @cite_10 ). In the information theoretic context, it is useful to understand how me... | {
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1708.05349 | 2746073525 | We present a simple nearest-neighbor (NN) approach that synthesizes high-frequency photorealistic images from an "incomplete" signal such as a low-resolution image, a surface normal map, or edges. Current state-of-the-art deep generative models designed for such conditional image synthesis lack two important things: (1... | Synthesis with CNNs: Convolutional Neural Networks (CNNs) have enjoyed great success for various discriminative pixel-level tasks such as segmentation @cite_9 @cite_45 , depth and surface normal estimation @cite_25 @cite_9 @cite_1 @cite_37 , semantic boundary detection @cite_9 @cite_34 etc. Such networks are usually tr... | {
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1708.05349 | 2746073525 | We present a simple nearest-neighbor (NN) approach that synthesizes high-frequency photorealistic images from an "incomplete" signal such as a low-resolution image, a surface normal map, or edges. Current state-of-the-art deep generative models designed for such conditional image synthesis lack two important things: (1... | Interpretability and user-control: Interpreting and explaining the outputs of generative deep networks is an open problem. As a community, we do not have a clear understanding of what, where, and how outputs are generated. Our work is fundamentally based on information via nearest neighbors, which explicitly reveals ho... | {
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1708.05349 | 2746073525 | We present a simple nearest-neighbor (NN) approach that synthesizes high-frequency photorealistic images from an "incomplete" signal such as a low-resolution image, a surface normal map, or edges. Current state-of-the-art deep generative models designed for such conditional image synthesis lack two important things: (1... | Correspondence: An important byproduct of pixelwise NN is the generation of pixelwise correspondences between the synthesized output and training examples. Establishing such pixel-level correspondence has been one of the core challenges in computer vision @cite_29 @cite_17 @cite_51 @cite_20 @cite_50 @cite_30 @cite_12 .... | {
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1708.05349 | 2746073525 | We present a simple nearest-neighbor (NN) approach that synthesizes high-frequency photorealistic images from an "incomplete" signal such as a low-resolution image, a surface normal map, or edges. Current state-of-the-art deep generative models designed for such conditional image synthesis lack two important things: (1... | Nonparametrics: Our work closely follows data-driven approaches that make use of nearest neighbors @cite_7 @cite_49 @cite_40 @cite_27 @cite_36 @cite_19 . Hays and Efros @cite_49 match a query image to 2 million training images for various tasks such as image completion. We make use of dramatically smaller training sets... | {
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1708.05122 | 2747206248 | As AI continues to advance, human-AI teams are inevitable. However, progress in AI is routinely measured in isolation, without a human in the loop. It is crucial to benchmark progress in AI, not just in isolation, but also in terms of how it translates to helping humans perform certain tasks, i.e., the performance of h... | Visual Conversational Agents. Our AI agents are visual conversational models, which have recently emerged as a popular research area in visually-grounded language modeling @cite_25 @cite_4 @cite_6 @cite_26 . @cite_25 introduced the task of Visual Dialog and collected the VisDial dataset by pairing subjects on Amazon Me... | {
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1708.05122 | 2747206248 | As AI continues to advance, human-AI teams are inevitable. However, progress in AI is routinely measured in isolation, without a human in the loop. It is crucial to benchmark progress in AI, not just in isolation, but also in terms of how it translates to helping humans perform certain tasks, i.e., the performance of h... | Human Computation Games. Human computation games have been shown to be time- and cost-efficient, reliable, intrinsically engaging for participants @cite_23 @cite_29 , and hence an effective method to collect data annotations. There is a long line of work on designing such Games with a Purpose (GWAP) @cite_11 for data l... | {
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1708.05122 | 2747206248 | As AI continues to advance, human-AI teams are inevitable. However, progress in AI is routinely measured in isolation, without a human in the loop. It is crucial to benchmark progress in AI, not just in isolation, but also in terms of how it translates to helping humans perform certain tasks, i.e., the performance of h... | Evaluating Conversational Agents. Goal-driven (non-visual) conversational models have typically been evaluated on task-completion rate or time-to-task-completion @cite_5 , so shorter conversations are better. At the other end of the spectrum, free-form conversation models are often evaluated by metrics that rely on n-g... | {
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1708.05122 | 2747206248 | As AI continues to advance, human-AI teams are inevitable. However, progress in AI is routinely measured in isolation, without a human in the loop. It is crucial to benchmark progress in AI, not just in isolation, but also in terms of how it translates to helping humans perform certain tasks, i.e., the performance of h... | Turing Test. Finally, our game is in line with ideas in @cite_19 , re-imagining the traditional Turing Test for state-of-the-art AI systems, taking the pragmatic view that an effective AI teammate need not appear human-like, act or be mistaken for one, provided its behavior does not feel jarring or baffle teammates, le... | {
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1708.05133 | 2749330229 | A growing demand for natural-scene text detection has been witnessed by the computer vision community since text information plays a significant role in scene understanding and image indexing. Deep neural networks are being used due to their strong capabilities of pixel-wise classification or word localization, similar... | In this paper, we focus on the use of convolutional neural networks (CNNs) in scene-text detection. It can date back to 2012, when Wang al @cite_7 presented a sliding-window approach to detect individual characters. The convolutional network was being used as a 62-category classifier. With the emergence of dedicated ne... | {
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1708.05133 | 2749330229 | A growing demand for natural-scene text detection has been witnessed by the computer vision community since text information plays a significant role in scene understanding and image indexing. Deep neural networks are being used due to their strong capabilities of pixel-wise classification or word localization, similar... | Another group of methods are based on image segmentation networks. Zhang al @cite_23 use the Fully Convolutional Network (FCN) @cite_19 to obtain salient maps with the foreground as candidates of text lines. The trouble is that the candidates may stick to each other, and their boundaries are often blurry. To make the f... | {
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1708.05234 | 2964325361 | Although tremendous strides have been made in face detection, one of the remaining open challenges is to achieve real-time speed on the CPU as well as maintain high performance, since effective models for face detection tend to be computationally prohibitive. To address this challenge, we propose a novel face detector,... | Previous face detection systems are mostly based on hand-craft features. Since the seminal Viola-Jones face detector @cite_23 that proposes to combine Haar feature, Adaboost learning and cascade inference for face detection, many subsequent works are proposed for real-time face detection, such as new local features @ci... | {
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1708.05234 | 2964325361 | Although tremendous strides have been made in face detection, one of the remaining open challenges is to achieve real-time speed on the CPU as well as maintain high performance, since effective models for face detection tend to be computationally prohibitive. To address this challenge, we propose a novel face detector,... | Besides the cascade framework, methods based on structural models progressively achieve better performance and become more and more efficient. Some researches @cite_10 @cite_26 @cite_47 introduce the deformable part model (DPM) into face detection tasks. These works use supervised parts, more pose partition, better tra... | {
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1708.05234 | 2964325361 | Although tremendous strides have been made in face detection, one of the remaining open challenges is to achieve real-time speed on the CPU as well as maintain high performance, since effective models for face detection tend to be computationally prohibitive. To address this challenge, we propose a novel face detector,... | The first use of CNN for face detection can be traced back to 1994. @cite_19 use a trained CNN in a sliding windows manner to detect faces. @cite_7 @cite_48 introduce a retinally connected neural network for upright frontal face detection, and a router" network designed to estimate the orientation for rotation invarian... | {
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1708.05234 | 2964325361 | Although tremendous strides have been made in face detection, one of the remaining open challenges is to achieve real-time speed on the CPU as well as maintain high performance, since effective models for face detection tend to be computationally prohibitive. To address this challenge, we propose a novel face detector,... | Recent years have witnessed the advance of CNN based face detectors. CCF @cite_6 uses boosting on top of CNN features for face detection. @cite_38 fine-tune CNN model trained on 1k ImageNet classification task for face and non-face classification task. Faceness @cite_14 trains a series of CNNs for facial attribute reco... | {
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1708.05271 | 2743573407 | Image captioning often requires a large set of training image-sentence pairs. In practice, however, acquiring sufficient training pairs is always expensive, making the recent captioning models limited in their ability to describe objects outside of training corpora (i.e., novel objects). In this paper, we present Long ... | The research on image captioning has proceeded along three different dimensions: template-based methods @cite_28 @cite_26 @cite_16 , search-based approaches @cite_24 @cite_19 @cite_3 , and language-based models @cite_10 @cite_6 @cite_14 @cite_9 @cite_0 @cite_13 @cite_12 . | {
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1708.05271 | 2743573407 | Image captioning often requires a large set of training image-sentence pairs. In practice, however, acquiring sufficient training pairs is always expensive, making the recent captioning models limited in their ability to describe objects outside of training corpora (i.e., novel objects). In this paper, we present Long ... | Template-based methods predefine the template for sentence generation and split sentence into several parts (e.g., subject, verb, and object). With such sentence fragments, many works align each part with visual content (e.g., CRF in @cite_28 and HMM in @cite_16 ) and then generate the sentence for the image. Obviously... | {
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1708.05271 | 2743573407 | Image captioning often requires a large set of training image-sentence pairs. In practice, however, acquiring sufficient training pairs is always expensive, making the recent captioning models limited in their ability to describe objects outside of training corpora (i.e., novel objects). In this paper, we present Long ... | Different from template-based and search-based models, language-based models aim to learn the probability distribution in the common space of visual content and textual sentence to generate novel sentences with more flexible syntactical structures. In this direction, recent works explore such probability distribution m... | {
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1708.05271 | 2743573407 | Image captioning often requires a large set of training image-sentence pairs. In practice, however, acquiring sufficient training pairs is always expensive, making the recent captioning models limited in their ability to describe objects outside of training corpora (i.e., novel objects). In this paper, we present Long ... | The novel object captioning is a new problem that has received increasing attention most recently, which leverages additional image-sentence paired data @cite_4 or unpaired image text data @cite_8 @cite_15 to describe novel objects in existing RNN-based image captioning frameworks. @cite_4 is one of the early works tha... | {
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1708.05340 | 2748080090 | Commercial off the shelf (COTS) 3D scanners are capable of generating point clouds covering visible portions of a face with sub-millimeter accuracy at close range, but lack the coverage and specialized anatomic registration provided by more expensive 3D facial scanners. We demonstrate an effective pipeline for joint al... | The proposed alignment method begins by using sparse localized landmarks, but as dense 3D information is available and real time performance is not necessary, additional steps are taken to refine the initial alignment by registering each scan to the subject-specific mesh geometry. Mesh geometry is computed by finding a... | {
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"abstract": [
"We show how to extend the ICP framework to nonrigid registration, while retaining the convergence properties of the original algorithm. The resulting optimal step nonrigid ICP framework allows the use of different regularisations, ... |
1708.05286 | 2749129571 | Stance classification determines the attitude, or stance, in a (typically short) text. The task has powerful applications, such as the detection of fake news or the automatic extraction of attitudes toward entities or events in the media. This paper describes a surprisingly simple and efficient classification approach ... | The first study that tackles automatic stance classification is that of . With a dataset containing 10K tweets and using a Bayesian classifier and three types of features categorised as content'', network'' and Twitter specific memes'', the authors achieved an accuracy of 93.5 use a rule-based method and show that it o... | {
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"abstract": [
"PHEME attempts to identify four kinds of false claim in social media and on the web, in real time: rumours, disinformation, misinformation ... |
1708.05237 | 2750317406 | This paper presents a real-time face detector, named Single Shot Scale-invariant Face Detector (S @math FD), which performs superiorly on various scales of faces with a single deep neural network, especially for small faces. Specifically, we try to solve the common problem that anchor-based detectors deteriorate dramat... | Face detection has attracted extensive research attention in past decades. The milestone work of Viola-Jones @cite_29 uses Haar feature and AdaBoost to train a cascade of face non-face classifiers that achieves a good accuracy with real-time efficiency. After that, lots of works have focused on improving the performanc... | {
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1708.05237 | 2750317406 | This paper presents a real-time face detector, named Single Shot Scale-invariant Face Detector (S @math FD), which performs superiorly on various scales of faces with a single deep neural network, especially for small faces. Specifically, we try to solve the common problem that anchor-based detectors deteriorate dramat... | Recent years have witnessed the advance of CNN-based face detectors. CascadeCNN @cite_49 develops a cascade architecture built on CNNs with powerful discriminative capability and high performance. @cite_0 proposes to jointly train CascadeCNN to realize end-to-end optimization. Faceness @cite_18 trains a series of CNNs ... | {
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"abstract": [
"In this paper, we propose a novel deep convolutional network (DCN) that achieves outstanding pe... |
1708.05237 | 2750317406 | This paper presents a real-time face detector, named Single Shot Scale-invariant Face Detector (S @math FD), which performs superiorly on various scales of faces with a single deep neural network, especially for small faces. Specifically, we try to solve the common problem that anchor-based detectors deteriorate dramat... | Additionally, face detection has inherited some achievements from generic object detection tasks. @cite_34 applies Faster R-CNN in face detection and achieves promising results. CMS-RCNN @cite_30 uses Faster R-CNN in face detection with body contextual information. Convnet @cite_31 integrates CNN with 3D face model in ... | {
"cite_N": [
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"abstract": [
"Robu... |
1906.00742 | 2947283491 | Word embeddings learnt from massive text collections have demonstrated significant levels of discriminative biases such as gender, racial or ethnic biases, which in turn bias the down-stream NLP applications that use those word embeddings. Taking gender-bias as a working example, we propose a debiasing method that pres... | proposed Gender-Neutral Global Vectors (GN-GloVe) by adding a constraint to the Global Vectors (GloVe) @cite_12 objective such that the gender-related information is confined to a sub-vector. During optimisation, the squared @math distance between gender-related sub-vectors are maximised, while simultaneously minimisin... | {
"cite_N": [
"@cite_12"
],
"mid": [
"2250539671"
],
"abstract": [
"Recent methods for learning vector space representations of words have succeeded in capturing fine-grained semantic and syntactic regularities using vector arithmetic, but the origin of these regularities has remained opaque. We a... |
1906.00742 | 2947283491 | Word embeddings learnt from massive text collections have demonstrated significant levels of discriminative biases such as gender, racial or ethnic biases, which in turn bias the down-stream NLP applications that use those word embeddings. Taking gender-bias as a working example, we propose a debiasing method that pres... | Debiasing can be seen as a problem of information related to a attribute such as gender, for which adversarial learning methods @cite_17 @cite_5 @cite_30 have been proposed in the fairness-aware machine learning community @cite_33 . In these approaches, inputs are first encoded, and then two classifiers are trained -- ... | {
"cite_N": [
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"abstract": [
"",
"Machine learning is a means to derive artificial intelligence by discovering patterns in existing data. Here, we show tha... |
1906.00939 | 2947576064 | Prediction of user traffic in cellular networks has attracted profound attention for improving resource utilization. In this paper, we study the problem of network traffic traffic prediction and classification by employing standard machine learning and statistical learning time series prediction methods, including long... | Traffic classification has been a hot topic in computer communication networks for more than two decades due to its vastly diverse applications in resource provisioning, billing and service prioritization, and security and anomaly detection @cite_13 @cite_15 . While different statistical and machine learning tools have... | {
"cite_N": [
"@cite_15",
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"mid": [
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],
"abstract": [
"The identification of network applications through observation of associated packet traffic flows is vital to the areas of networ... |
1906.00850 | 2947982151 | Interest in smart cities is rapidly rising due to the global rise in urbanization and the wide-scale instrumentation of modern cities. Due to the considerable infrastructural cost of setting up smart cities and smart communities, researchers are exploring the use of existing vehicles on the roads as "message ferries" f... | The literature is rich with research that deals with network issues in smart communities. @cite_3 presented the networking requirements for different smart city applications and additionally presented network architectures for different smart city systems. In @cite_8 , the authors discussed the networking and communica... | {
"cite_N": [
"@cite_13",
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"mid": [
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],
"abstract": [
"Smart cities are a hot topic nowadays for several reasons. For city managers and citizens a smart city is a concept that should allow providing better services and ... |
1906.00850 | 2947982151 | Interest in smart cities is rapidly rising due to the global rise in urbanization and the wide-scale instrumentation of modern cities. Due to the considerable infrastructural cost of setting up smart cities and smart communities, researchers are exploring the use of existing vehicles on the roads as "message ferries" f... | @cite_7 present a system where public and semi-public vehicles are used for transporting data between stations distributed around the city and the main server. @cite_4 introduce the concept of Smart Vehicle as a Service (SVaaS). They predict the future location of the vehicle in order to guarantee a continuous vehicle ... | {
"cite_N": [
"@cite_10",
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"@cite_12",
"@cite_7"
],
"mid": [
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"2787288190",
"2512054878",
"2568227438"
],
"abstract": [
"Efficient and cost effective data collection from smart city sensors through vehicular networks is crucial for many applications, ... |
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