aid stringlengths 9 15 | mid stringlengths 7 10 | abstract stringlengths 78 2.56k | related_work stringlengths 92 1.77k | ref_abstract dict |
|---|---|---|---|---|
1907.13329 | 2925427079 | We propose a process algebra for link layer protocols, featuring a unique mechanism for modelling frame collisions. We also formalise suitable liveness properties for link layer protocols specified in this framework. To show applicability we model and analyse two versions of the Carrier-Sense Multiple Access with Colli... | Multiple analyses were performed for the CSMA CD protocol (CSMA with collision detection), a predecessor of CSMA CA that has a constant backoff, i.e. the backoff time is not increased exponentially, see @cite_12 @cite_3 @cite_24 @cite_5 @cite_8 . In all these approaches frame collisions have to be modelled explicitly, ... | {
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"Probabilistic model checking is a formal verification technique for the analysis of systems... |
1907.13329 | 2925427079 | We propose a process algebra for link layer protocols, featuring a unique mechanism for modelling frame collisions. We also formalise suitable liveness properties for link layer protocols specified in this framework. To show applicability we model and analyse two versions of the Carrier-Sense Multiple Access with Colli... | @cite_12 @cite_3 use probabilistic timed automata (PTAs) to model the protocol, and use probabilistic model checking ( ) and approximate model checking ( ) for their analysis. The model explained in @cite_24 is based on PTAs as well, but uses the model checker as verification tool. These approaches, although formal, ha... | {
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"Reachability analysis for timed automata can be done by enumeration of time zones, which are conjunctions of atomic formulas of the form x-y≤(<)n. This paper shows... |
1907.13329 | 2925427079 | We propose a process algebra for link layer protocols, featuring a unique mechanism for modelling frame collisions. We also formalise suitable liveness properties for link layer protocols specified in this framework. To show applicability we model and analyse two versions of the Carrier-Sense Multiple Access with Colli... | @cite_5 use models of CSMA CD to compare the tools SPIN and . Their models are much more abstract than ours. It is proven that no collisions will ever occur, without stating the exact conditions under which this statement holds. | {
"cite_N": [
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"abstract": [
"This paper compares the tools SPIN and UPPAAL by modelling and verifying a Collision Avoidance Protocol for an Ethernet-like medium. We find that SPIN is well suited for modelling the untimed aspects of the protocol processes and f... |
1907.13329 | 2925427079 | We propose a process algebra for link layer protocols, featuring a unique mechanism for modelling frame collisions. We also formalise suitable liveness properties for link layer protocols specified in this framework. To show applicability we model and analyse two versions of the Carrier-Sense Multiple Access with Colli... | There are far fewer formal analyses techniques available when it comes to CSMA CA (with and without virtual medium sensing). Traditional approaches to the analysis of network protocols are simulation and test-bed experiments. This is also the case for CSMA CA (e.g. @cite_11 ). While these are important and valid method... | {
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"To satisfy the needs of wireless data networking, study group 802.11 was formed under IEEE project 802 to recommend an international standard for Wireless Local Area Networks (WLANs). A key part of standard are the Medium Access C... |
1907.13329 | 2925427079 | We propose a process algebra for link layer protocols, featuring a unique mechanism for modelling frame collisions. We also formalise suitable liveness properties for link layer protocols specified in this framework. To show applicability we model and analyse two versions of the Carrier-Sense Multiple Access with Colli... | -3pt Following the spirit of the above-mentioned research of model checking CSMA, Fruth @cite_18 analyses CSMA CA using PTAs and . He considers properties such as the minimum probability of two nodes successfully completing their transmissions, and maximum expected number of collisions until two nodes have successfully... | {
"cite_N": [
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"The international standard IEEE 802.15.4 defines low-rate wireless personal area networks, a central communication infrastructure of pervasive computing. In order to avoid conflicts caused by multiple devices transmitting at the s... |
1907.13329 | 2925427079 | We propose a process algebra for link layer protocols, featuring a unique mechanism for modelling frame collisions. We also formalise suitable liveness properties for link layer protocols specified in this framework. To show applicability we model and analyse two versions of the Carrier-Sense Multiple Access with Colli... | Beyond model checking, simulation and test-bed experiments, we are only aware of two other formal approaches. In @cite_4 Markov chains are used to derive an accurate, analytical model to compute the throughput of CSMA CA. Calculating throughput is an orthogonal task to our vision of proving (functional) correctness. | {
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"The IEEE has standardized the 802.11 protocol for wireless local area networks. The primary medium access control (MAC) technique of 802.11 is called the distributed coordination function (DCF). The DCF is a carrier sense multiple ... |
1907.13329 | 2925427079 | We propose a process algebra for link layer protocols, featuring a unique mechanism for modelling frame collisions. We also formalise suitable liveness properties for link layer protocols specified in this framework. To show applicability we model and analyse two versions of the Carrier-Sense Multiple Access with Colli... | An approach aiming at proving the correctness of CSMA CA with virtual carrier sensing ( ), and hence related to ours, is presented in @cite_7 . Based on stochastic bigraphs with sharing it uses rewrite rules to analyse quantitative properties. Although it is an approach that is capable to analyse arbitrary topologies, ... | {
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"Stochastic bigraphical reactive systems (SBRS) is a recent formalism for modelling systems that evolve in time and space. However, the underlying spatial model is based on sets of trees and thus cannot represent spatial locations t... |
1907.13359 | 2966761695 | Deep learning algorithms have achieved excellent performance lately in a wide range of fields (e.g., computer version). However, a severe challenge faced by deep learning is the high dependency on hyper-parameters. The algorithm results may fluctuate dramatically under the different configuration of hyper-parameters. A... | Apart from the aforementioned methods, the orthogonal array based hyper-parameter tuning already used in a range of research areas such as mechanical engineering and electrical engineering. J.A @cite_6 applied orthogonal array based approach to optimize the cutting parameters in the end milling. S.S. @cite_10 optimized... | {
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"Wire electrical discharge machining (WEDM) is extensively used in machining of conductive materials when precision is of prime importance. Rough cutting operation in WEDM is treated as a challengin... |
1907.13216 | 2965944882 | Recently, the posit numerical format has shown promise for DNN data representation and compute with ultra-low precision ([5..8]-bit). However, majority of studies focus only on DNN inference. In this work, we propose DNN training using posits and compare with the floating point training. We evaluate on both MNIST and F... | As early as the 1980s, low-precision arithmetic has been explored in shallow neural networks to decrease both compute and memory complexity for training and inference without deteriorating performance @cite_21 @cite_3 @cite_14 @cite_12 . In some scenarios, this bit-precision constraint also improves DNN performance due... | {
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1907.13216 | 2965944882 | Recently, the posit numerical format has shown promise for DNN data representation and compute with ultra-low precision ([5..8]-bit). However, majority of studies focus only on DNN inference. In this work, we propose DNN training using posits and compare with the floating point training. We evaluate on both MNIST and F... | Aside from the BFP numerical format, Narang explored mixed-precision floating point @cite_11 using 16-bit floating point weights, activations, and gradients during both the forward and backward passes. To prevent accuracy loss caused by underflow in 16-bit floating point, the weights are updated with 32-bit floating po... | {
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"Increasing the size of a neural network typically improves accuracy but also increases the memory and compute requirements for training the model. We introduce methodology for training deep neural networks using half-precision flo... |
1907.13216 | 2965944882 | Recently, the posit numerical format has shown promise for DNN data representation and compute with ultra-low precision ([5..8]-bit). However, majority of studies focus only on DNN inference. In this work, we propose DNN training using posits and compare with the floating point training. We evaluate on both MNIST and F... | Recently, Wang and Mellempudi propose a method to reduce the bit-precision of weights, activations, and gradients to 8 bits by exhaustively analyzing DNN parameters during training @cite_7 @cite_4 . In @cite_4 , a new chunk-based addition is presented to solve the truncation issue caused by the addition of large- and s... | {
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"This paper presents the first comprehensive empirical study demonstrating the efficacy of the Brain Floating Point (BFLOAT16) half-precision format for Deep Learnin... |
1907.13216 | 2965944882 | Recently, the posit numerical format has shown promise for DNN data representation and compute with ultra-low precision ([5..8]-bit). However, majority of studies focus only on DNN inference. In this work, we propose DNN training using posits and compare with the floating point training. We evaluate on both MNIST and F... | This research builds on earlier studies @cite_31 @cite_35 @cite_9 @cite_19 @cite_33 and for the first time studies feedforward neural network training with posits on MNIST and Fashion MNIST datasets . | {
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"Deep neural networks (DNNs) have been demonstrated as effective prognostic models across variou... |
1907.13314 | 2965544063 | Many evaluation methods have been used to assess the usefulness of Visual Analytics (VA) solutions. These methods stem from a variety of origins with different assumptions and goals, which cause confusion about their proofing capabilities. Moreover, the lack of discussion about the evaluation processes may limit our po... | Multiple studies have surveyed existing evaluation practices. Lam @cite_59 suggest that it is reasonable to generate a taxonomy of evaluation studies by defining scenarios of evaluation practices that are common in the literature. Their extensive survey is unique and provides many insights for researchers. Specifically... | {
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"We present an assessment of the state and historic development of evaluation practices as reported in papers published at the IEEE Visualization conference. Our goal is to reflect on a meta-level ... |
1907.13314 | 2965544063 | Many evaluation methods have been used to assess the usefulness of Visual Analytics (VA) solutions. These methods stem from a variety of origins with different assumptions and goals, which cause confusion about their proofing capabilities. Moreover, the lack of discussion about the evaluation processes may limit our po... | An early study that introduces McGrath's work to the information visualization evaluation context is done by Carpendale @cite_67 , who provides a summary of different quantitative, qualitative and mixed methodologies along with a discussion about their limitations and challenges. A more recent work by Crisan and Elliot... | {
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"Information visualization research is becoming more established, and as a result, it is becoming increasingly important that research in this field is validated. With the general increase in informat... |
1907.13314 | 2965544063 | Many evaluation methods have been used to assess the usefulness of Visual Analytics (VA) solutions. These methods stem from a variety of origins with different assumptions and goals, which cause confusion about their proofing capabilities. Moreover, the lack of discussion about the evaluation processes may limit our po... | One argument made by Munzner @cite_15 was the necessity of summative evaluation during each stage of design studies to evaluate the outcome of that individual stage. Sedlmair @cite_49 and Mckenna @cite_27 made similar arguments while describing the process of design studies. They make the case for considering non-quant... | {
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"An important aspect in visualization design is the connection between what a designer does and the decisions the designer makes. Existing design process models, h... |
1907.13495 | 2965311640 | We develop a novel hierarchy for zero-dimensional persistence pairs, i.e., connected components, which is capable of capturing more fine-grained spatial relations between persistence pairs. Our work is motivated by a lack of spatial relationships between features in persistence diagrams, leading to a limited expressive... | We refer the reader to Edelsbrunner and Harer @cite_8 for a detailed overview of persistence and related concepts. There are several related approaches for creating a hierarchy of persistence information. @cite_2 calculate a topological saliency of critical points in a scalar field based on their spatial arrangement. C... | {
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"The goal of this thesis is to bring together two different theories about critical points of a scalar function and their relation to topology: Discrete Morse theory and Persi... |
1907.13368 | 2965737826 | The digital retina in smart cities is to select what the City Eye tells the City Brain, and convert the acquired visual data from front-end visual sensors to features in an intelligent sensing manner. By deploying deep learning and or handcrafted models in front-end devices, the compact features can be extracted and su... | The deep neural network transmission aims to utilize and deliver the knowledge concentrated in the network model to facilitate different intelligent applications. In @cite_5 , the model compression is formulated from the perspective of transmission. As such, the redundancy among different models can be further exploite... | {
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"With the advances of artificial intelligence, recent years have witnessed a gradual transition from the big data to the big knowledge. Based on the knowledge-powered deep learning models, the big data such as the vast text, images ... |
1907.13196 | 2966684444 | Reinforcement learning algorithms, though successful, tend to over-fit to training environments hampering their application to the real-world. This paper proposes WR @math L; a robust reinforcement learning algorithm with significant robust performance on low and high-dimensional control tasks. Our method formalises ro... | There is a long-standing thread of research on robustness in the classical control community, and the literature in this area is vast, with the @math method being a standard approach [] doyle2013feedback . This approach was introduced into reinforcement learning by @cite_7 . In that paper, a continuous time reinforceme... | {
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"This letter proposes a new reinforcement learning (RL) paradigm that explicitly takes into account input disturbance as well as modeling errors. The use of environmental models in RL is quite popular for both offline learning using... |
1907.13196 | 2966684444 | Reinforcement learning algorithms, though successful, tend to over-fit to training environments hampering their application to the real-world. This paper proposes WR @math L; a robust reinforcement learning algorithm with significant robust performance on low and high-dimensional control tasks. Our method formalises ro... | The CVaR criterion is also adopted in @cite_13 , in which, rather than sampling trajectories and finding a quantile in terms of performance, two policies are trained simultaneously: a protagonist'' which aims to optimise performance, and an adversary which aims to disrupt the protagonist. The protagonist and adversary ... | {
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"Deep neural networks coupled with fast simulation and improved computation have led to recent successes in the field of reinforcement learning (RL). However, most current RL-based approaches fail to generalize since: (a) the gap b... |
1907.13196 | 2966684444 | Reinforcement learning algorithms, though successful, tend to over-fit to training environments hampering their application to the real-world. This paper proposes WR @math L; a robust reinforcement learning algorithm with significant robust performance on low and high-dimensional control tasks. Our method formalises ro... | More recently, @cite_2 studies robustness with respect to action perturbations. There are two forms of perturbation addressed: (i) Probabilistic Action Robust MDP (PR-MDP), and (ii) Noisy Action Robust MDP (NR-MDP). In PR-MDP, when an action is taken by an agent, with probability @math , a different, possibly adversari... | {
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"Sample complexity and safety are major challenges when learning policies with reinforcement learning for real-world tasks, especially when the policies are represe... |
1907.13196 | 2966684444 | Reinforcement learning algorithms, though successful, tend to over-fit to training environments hampering their application to the real-world. This paper proposes WR @math L; a robust reinforcement learning algorithm with significant robust performance on low and high-dimensional control tasks. Our method formalises ro... | In @cite_4 a non-stationary Markov Decision Process model is considered, where the dynamics can change from one time step to another. The constraint is based on Wasserstein distance, specifically, the Wasserstein distance between dynamics at time @math and @math is bounded by @math , i.e., is @math -Lipschitz with resp... | {
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"This work tackles the problem of robust zero-shot planning in non-stationary stochastic environments. We study Markov Decision Processes (MDPs) evolving over time and consider Model-Based Reinforcement Learning algorithms in this s... |
1907.13196 | 2966684444 | Reinforcement learning algorithms, though successful, tend to over-fit to training environments hampering their application to the real-world. This paper proposes WR @math L; a robust reinforcement learning algorithm with significant robust performance on low and high-dimensional control tasks. Our method formalises ro... | To summarise, our paper uses the Wasserstein distance for addressing, in common with @cite_4 , but is suited to applying deep neural networks for continuous state and action spaces. Our paper does not require a full dynamics available to it, merely a parameterisable dynamics. It competes well with the above papers, and... | {
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"This work tackles the problem of robust zero-shot planning in non-stationary stochastic environments. We study Markov Decision Processes (MDPs) evolving over time and consider Model-Based Reinforcement Learning algorithms in this s... |
1907.13285 | 2964987353 | Text-entry aims to provide an effective and efficient pathway for humans to deliver their messages to computers. With the advent of mobile computing, the recent focus of text-entry research has moved from physical keyboards to soft keyboards. Current soft keyboards, however, increase the typo rate due to lack of tactil... | First of all, gesture-based text-entry allows drawing-like typing @cite_17 @cite_26 . Drawing-like typing removes the need for localizing each key position and users can start drawing from any place on the screen in an eyes-free manner. Though gesture-based text-entry offers concise eyes-free typing interfaces, it requ... | {
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"In this paper, we propose a complete gesture recognition framework based on maximum cosine similarity and fast nearest neighbor (NN... |
1907.13285 | 2964987353 | Text-entry aims to provide an effective and efficient pathway for humans to deliver their messages to computers. With the advent of mobile computing, the recent focus of text-entry research has moved from physical keyboards to soft keyboards. Current soft keyboards, however, increase the typo rate due to lack of tactil... | For the second point, optimized text-entry supplies accessible and comfortable typing interfaces by optimizing the size, shape, and position of keys @cite_8 @cite_5 . Current optimized text-entry methods require users to learn new typing interfaces @cite_1 because knowledge transfer seldom occurs for novel typing inter... | {
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"In this paper the authors propose IPPITSU, an eyes-free, Braille-based text entry method for touch panels. In IPPITSU the user inputs a Braille cell by selecting the r... |
1907.13285 | 2964987353 | Text-entry aims to provide an effective and efficient pathway for humans to deliver their messages to computers. With the advent of mobile computing, the recent focus of text-entry research has moved from physical keyboards to soft keyboards. Current soft keyboards, however, increase the typo rate due to lack of tactil... | Last but not least, imaginary keyboards, which are invisible to users, save invaluable screen resources and enables multi-tasking in the context of mobile computing @cite_27 . Imaginary keyboards reduce constraints during interaction and users can freely and comfortably deliver their messages. In addition, the imaginar... | {
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"The lack of dedicated multitasking interface features in smartphones has resulted in users attempting a sequential form of multitasking via frequent app switching. In addition to the obvious tempo... |
1907.13285 | 2964987353 | Text-entry aims to provide an effective and efficient pathway for humans to deliver their messages to computers. With the advent of mobile computing, the recent focus of text-entry research has moved from physical keyboards to soft keyboards. Current soft keyboards, however, increase the typo rate due to lack of tactil... | Ten finger typing is one of the most natural and common text-entry methods @cite_28 . Users can achieve typing speed of 60 - 100 words per minute (WPM) by ten finger typing on physical keyboards @cite_19 . Ten finger typing experience stored in muscle memory and tactile feedback from mechanical keys enable eyes-free ty... | {
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"This paper introduces a new text input device called the chording glove. The keys of a chord keyboard ar... |
1907.13285 | 2964987353 | Text-entry aims to provide an effective and efficient pathway for humans to deliver their messages to computers. With the advent of mobile computing, the recent focus of text-entry research has moved from physical keyboards to soft keyboards. Current soft keyboards, however, increase the typo rate due to lack of tactil... | A number of works have attempted to understand the user behavior with ten finger typing with soft keyboards. The major findings are as follows: : The typing speed with soft keyboards drops dramatically compared to the speed with physical keyboards @cite_12 . : The distribution of touch points resembles the mechanical k... | {
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"Touch screen surfaces large enough for ten-finger input have become increasingly popular, yet t... |
1907.13285 | 2964987353 | Text-entry aims to provide an effective and efficient pathway for humans to deliver their messages to computers. With the advent of mobile computing, the recent focus of text-entry research has moved from physical keyboards to soft keyboards. Current soft keyboards, however, increase the typo rate due to lack of tactil... | In summary, ten-finger eyes-free typing on virtual keyboards, which is most natural and easy to transfer knowledge directly from physical keyboards @cite_19 , is feasible according to the previous research results, though a couple of obstacles need to be resolved. The proposed DND handles hand drift, tab variability an... | {
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"Touch typing on flat surfaces (e.g. interactive tabletop) is challenging due to lack of tactile feedback and hand drifting. In this paper, we present TOAST, an eyes-free keyboard technique for enabling efficient touch typing on to... |
1907.13285 | 2964987353 | Text-entry aims to provide an effective and efficient pathway for humans to deliver their messages to computers. With the advent of mobile computing, the recent focus of text-entry research has moved from physical keyboards to soft keyboards. Current soft keyboards, however, increase the typo rate due to lack of tactil... | Classical statistical decoding algorithms translate user inputs (key strokes) into characters or words using probabilistic models. These statistical decoding algorithms have proved their effectiveness in a few controlled environments @cite_24 . The goal of statistical decoding is to find the sequence of characters that... | {
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"abstract": [
"Abstract Typing on tiny QWERTY keyboards on smartwatches is considered challenging or even impractical due to the limited screen space. In this paper, we describe ... |
1907.13285 | 2964987353 | Text-entry aims to provide an effective and efficient pathway for humans to deliver their messages to computers. With the advent of mobile computing, the recent focus of text-entry research has moved from physical keyboards to soft keyboards. Current soft keyboards, however, increase the typo rate due to lack of tactil... | Conventional statistical decoding algorithms, however, cannot perfectly deal with the complex dynamics of user inputs. The independence assumption applied in these methods cannot count both long-term and short-term dependencies among the key strokes. The independence assumption confines the conventional approaches to r... | {
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"Touch typing on flat surfaces (e.g. interactive tabletop) is challenging due to lack of tactile feedback and hand drifting. In this paper, we present TOAST, an eyes-free keyboard technique for enabling efficient touch typing on to... |
1907.13463 | 2966452173 | Zeroth-order (gradient-free) method is a class of powerful optimization tool for many machine learning problems because it only needs function values (not gradient) in the optimization. In particular, zeroth-order method is very suitable for many complex problems such as black-box attacks and bandit feedback, whose exp... | * -8pt ADMM @cite_35 @cite_22 is a popular optimization method in solving the composite and constrained problems in machine learning. Due to the flexibility in splitting the objective function into loss and complex penalty, the ADMM can relatively easily solve some problems with complicated structure penalty such as th... | {
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1907.13463 | 2966452173 | Zeroth-order (gradient-free) method is a class of powerful optimization tool for many machine learning problems because it only needs function values (not gradient) in the optimization. In particular, zeroth-order method is very suitable for many complex problems such as black-box attacks and bandit feedback, whose exp... | So far, the above ADMM methods need to repeatedly calculate gradients of the loss function over the iterations. However, in many machine learning problems, the gradients of objective functions are difficult or infeasible to obtain. For example, in adversarial attack to black-box DNNs @cite_4 @cite_23 , only evaluation ... | {
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"Deep neural networks (DNNs) are one of the most prominent technologies of our time, as ... |
1907.13357 | 2965376428 | We propose a new regularization technique, named Hybrid Spatio-Spectral Total Variation (HSSTV), for hyperspectral (HS) image denoising and compressed sensing. Regularization techniques based on total variation (TV) focus on local differences of an HS image to model its underlying smoothness and have been recognized as... | Yuan proposed HTV @cite_13 for HS image denoising. HTV can be seen as a generalization of the standard color TV @cite_21 , and its formulation is given as follows: where @math and @math are vertical and horizontal differences for @math th pixel of @math th band in an HS image, respectively. From this definition, one ca... | {
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"We propose a regularization algorithm for color vectorial images which is fast, easy to code and mathematically well-posed. More precisely, the regularization model is based on the dual formulatio... |
1907.13357 | 2965376428 | We propose a new regularization technique, named Hybrid Spatio-Spectral Total Variation (HSSTV), for hyperspectral (HS) image denoising and compressed sensing. Regularization techniques based on total variation (TV) focus on local differences of an HS image to model its underlying smoothness and have been recognized as... | Addesso proposed to use CTV @cite_57 for HS image inpainting @cite_61 . CTV is defined by It evaluates spatial piecewise smoothness by using @math norm. In addition, the method can also use the Schatten- @math norm as ) |_ S^p ^ q )^ 1 q . CTV can be seen as a generalization of HTV, which is equivalent to HTV when @mat... | {
"cite_N": [
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"abstract": [
"Even after two decades, the total variation (TV) remains one of the most popular regularizations for image processing problems and has sparked a tremendous amount of research, particularly on movi... |
1907.13357 | 2965376428 | We propose a new regularization technique, named Hybrid Spatio-Spectral Total Variation (HSSTV), for hyperspectral (HS) image denoising and compressed sensing. Regularization techniques based on total variation (TV) focus on local differences of an HS image to model its underlying smoothness and have been recognized as... | He proposed ASSTV @cite_58 for HS image denoising. ASSTV simultaneously evaluates direct spatial and spectral differences, which is defined by where @math , @math , and @math are vertical, horizontal, and spectral differences for the @math th pixel of an HS image, respectively, and @math , @math and @math are balancing... | {
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"Hyperspectral images (HSIs) are usually contaminated by various kinds of noise, such as stripes, deadlines, impulse noise, Gaussian noise, and so on, which significantly limits their subsequent application. In this paper, we model... |
1907.13432 | 2966528571 | We propose two neural network based mixture models in this article. The proposed mixture models are explicit in nature. The explicit models have analytical forms with the advantages of computing likelihood and efficiency of generating samples. Computation of likelihood is an important aspect of our models. Expectation-... | While GANs have high success in many applications, they are known to suffer in a mode dropping problem where a generator of a GAN is unable to capture all modes of an underlying probability distribution of data @cite_13 . To address diversity in data and model multiple modes in a distribution, variants of generative mo... | {
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"abstract": [
"Real images often lie on a union of disjoint manifolds rathe... |
1907.13432 | 2966528571 | We propose two neural network based mixture models in this article. The proposed mixture models are explicit in nature. The explicit models have analytical forms with the advantages of computing likelihood and efficiency of generating samples. Computation of likelihood is an important aspect of our models. Expectation-... | Typically, for a GAN, the latent variable is assumed to follow a known and fixed distribution, e.g., Gaussian. The latent signal for a given data sample can not be obtained since generators which are usually based on neural networks are non-invertible. The mapping from a data sample to its corresponding latent signal i... | {
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"The ability of the Generative Adversarial Networks (GANs) framework to learn generative models mapping from simple latent distributions to arbitrarily complex data distribut... |
1907.13418 | 2965317766 | Deep learning (DL) has shown great potential in medical image enhancement problems, such as super-resolution or image synthesis. However, to date, little consideration has been given to uncertainty quantification over the output image. Here we introduce methods to characterise different components of uncertainty in suc... | However, within the context of medical image enhancement, these lines of research performed only limited validation of the quality and utility of uncertainty modelling. In this work, we formalise and extend the preliminary ideas in Tanno @cite_81 and provide a comprehensive set of experiments to evaluate the proposed u... | {
"cite_N": [
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"In this work, we investigate the value of uncertainty modelling in 3D super-resolution with convolutional neural networks (CNNs). Deep learning has shown success in a plethora of medical image transformation problems, such as supe... |
1907.13496 | 2965224253 | Techniques from computational topology, in particular persistent homology, are becoming increasingly relevant for data analysis. Their stable metrics permit the use of many distance-based data analysis methods, such as multidimensional scaling, while providing a firm theoretical ground. Many modern machine learning alg... | Recognizing that persistence diagrams can be analyzed at multiple scales as well in order to facilitate hierarchical comparisons, there are some approaches that provide approximations to persistence diagrams based on, e.g., a smoothing parameter. Among these, the stable kernel of @cite_21 is particularly suited for top... | {
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"Many data sets can be viewed as a noisy sampling of an underlying space, and tools from topological data analysis can characterize this structure for the purpose of knowledge discovery. One such to... |
1907.13496 | 2965224253 | Techniques from computational topology, in particular persistent homology, are becoming increasingly relevant for data analysis. Their stable metrics permit the use of many distance-based data analysis methods, such as multidimensional scaling, while providing a firm theoretical ground. Many modern machine learning alg... | Recently, Bubenik @cite_16 introduced , a functional summary of persistence diagrams. Within his framework, PIF can be considered to represent a summary (or projection) of the . Our definition of PIF is more straightforward and easier to implement, however. Since PIF share several properties of persistence landscapes--... | {
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"abstract": [
"Persistent homology probes topological properties from point clouds and functions. By looking at multiple scales simultaneously, one can record the births and deaths of topological features as the ... |
1907.13286 | 2964427276 | Recommender systems are known to suffer from the popularity bias problem: popular (i.e. frequently rated) items get a lot of exposure while less popular ones are under-represented in the recommendations. Research in this area has been mainly focusing on finding ways to tackle this issue by increasing the number of reco... | And finally, @cite_12 compared different recommendation algorithms in terms of accuracy and popularity bias. In that paper they observed some algorithms concentrate more on popular items than the others. In our work, we are mainly interested in seeing the popularity bias from the users' expectations perspective. | {
"cite_N": [
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"abstract": [
"Most real-world recommender systems are deployed in a commercial context or designed to represent a value-adding service, e.g., on shopping or Social Web platforms, and typical success indicators for such systems include conversio... |
1907.13351 | 2964404395 | Synthesizing geometrical shapes from human brain activities is an interesting and meaningful but very challenging topic. Recently, the advancements of deep generative models like Generative Adversarial Networks (GANs) have supported the object generation from neurological signals. However, the Electroencephalograph (EE... | Recent years' research in neuroscience and neuroimaging @cite_11 indicated that human perception of visual stimuli can be decoded through some techniques in neuroimaging. To be specific, a few works gave evidence about decoding the brain signals to human activity by using the Functional Magnetic Resonance Imaging (fMRI... | {
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"Recent advancements in generative adversarial networks (GANs), using deep convolutional models, h... |
1907.13351 | 2964404395 | Synthesizing geometrical shapes from human brain activities is an interesting and meaningful but very challenging topic. Recently, the advancements of deep generative models like Generative Adversarial Networks (GANs) have supported the object generation from neurological signals. However, the Electroencephalograph (EE... | Most of the visual object reconstruction methods are based on Generative Adversarial Networks (GANs) and the variations. GANs @cite_5 , as the typical deep learning frameworks, was used widely in image generation. The standard GANs are composed of a generator network which generates images from the random sampled noise... | {
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"Generative Adversarial Nets [8] were recently introduced as a novel way to train generative models. In this work we introduce the conditional version of generative adv... |
1907.13351 | 2964404395 | Synthesizing geometrical shapes from human brain activities is an interesting and meaningful but very challenging topic. Recently, the advancements of deep generative models like Generative Adversarial Networks (GANs) have supported the object generation from neurological signals. However, the Electroencephalograph (EE... | Most brain signal based image reconstruction work is based on fMRI. Due to the drawbacks of fMRI (e.g., low time resolution, expensive, and low portability), we focus on EEG based geometric shape reconstruction. Compare to the typical EEG-based work like brain2image @cite_3 , we have several technical advantages: 1) we... | {
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"Reading the human mind has been a hot topic in the last decades, and recent research in neuroscience has found evidence on the possibility of decoding, from neuroimaging data, how the human brain works. At the same time, the recent... |
1907.12924 | 2966152490 | Service robots are expected to operate effectively in human-centric environments for long periods of time. In such realistic scenarios, fine-grained object categorization is as important as basic-level object categorization. We tackle this problem by proposing an open-ended object recognition approach which concurrentl... | In the last decade, various research groups have made substantial progress towards the development of learning approaches which support online and incremental object category learning @cite_2 @cite_17 . In recent studies on object recognition, much attention has been given to deep Convolutional Neural Networks (CNNs). ... | {
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1907.12924 | 2966152490 | Service robots are expected to operate effectively in human-centric environments for long periods of time. In such realistic scenarios, fine-grained object categorization is as important as basic-level object categorization. We tackle this problem by proposing an open-ended object recognition approach which concurrentl... | Several types of research have been performed to assess the added-value of structural information. @cite_14 extended an online version of Latent Dirichlet Allocation (LDA) and proposed an incremental Gibbs sampler for LDA (here referred to as I-LDA). In online-LDA and I-LDA, the number of categories is fixed, while in ... | {
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"Inference algorithms for topic models are typically designed to be run over an entire collection of documents after they have been observed. However, in many applications of these models, the colle... |
1907.12924 | 2966152490 | Service robots are expected to operate effectively in human-centric environments for long periods of time. In such realistic scenarios, fine-grained object categorization is as important as basic-level object categorization. We tackle this problem by proposing an open-ended object recognition approach which concurrentl... | Assume at time @math (i.e., first teaching action) a dictionary is learned for category @math , denoted as @math , which represents the distribution of 3D shape features observed up to time @math . Later at time @math , a new training instance, which is represented as a set of spin-images, is taught by a teacher to cat... | {
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"Study of this paper describes the incremental behaviours of partitioning based K-means clustering. This incremental clustering is designed using the cluster’s metadata captured from the K-Means results. Experimental studies shows ... |
1907.13025 | 2964650603 | Due to the availability of large-scale skeleton datasets, 3D human action recognition has recently called the attention of computer vision community. Many works have focused on encoding skeleton data as skeleton image representations based on spatial structure of the skeleton joints, in which the temporal dynamics of t... | @cite_33 @cite_49 present a skeleton representation to represent both spatial configuration and dynamics of joint trajectories into three texture images through color encoding, named Joint Trajectory Maps (JTMs). The authors apply rotations to the skeleton data to mimicking multi-views and also for data enlargement to ... | {
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"We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000 different classes.... |
1907.13025 | 2964650603 | Due to the availability of large-scale skeleton datasets, 3D human action recognition has recently called the attention of computer vision community. Many works have focused on encoding skeleton data as skeleton image representations based on spatial structure of the skeleton joints, in which the temporal dynamics of t... | To overcome the problem of the sparse data generated by skeleton sequence video, @cite_23 represent the temporal dynamics of the skeleton sequence by generating four skeleton representation images. Their approach is closer to @cite_47 method, however they compute the relative positions of the joints to four reference j... | {
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"abstract": [
"Abstract: In this work we investigate the effect of the convolutional network depth on its accuracy in the large-scale image recognition setting. Our main contribution is a... |
1907.13025 | 2964650603 | Due to the availability of large-scale skeleton datasets, 3D human action recognition has recently called the attention of computer vision community. Many works have focused on encoding skeleton data as skeleton image representations based on spatial structure of the skeleton joints, in which the temporal dynamics of t... | @cite_46 claim that the concatenation process of chaining all joints with a fixed order turn into lack of semantic meaning and leads to loss in skeleton structural information. To that end, @cite_46 proposed a representation named Tree Structure Skeleton Image (TSSI) to preserve spatial relations. Their method is creat... | {
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"abstract": [
"Action recognition with 3D skeleton sequences became popular due to its speed and robustness. The recently proposed convolutional neural networks (CNNs)-based methods show a good performance in le... |
1907.12933 | 2965255081 | Artificial Neural networks (ANNs) are powerful computing systems employed for various applications due to their versatility to generalize and to respond to unexpected inputs patterns. However, implementations of ANNs for safety-critical systems might lead to failures, which are hardly predicted in the design phase sinc... | Our ultimate goal is to formally ensure safety for applications that are based on Artificial Intelligence (AI), as described by @cite_4 . In particular, the potential impact of intelligent systems performing tasks in society and how safety guarantees are necessary to prevent damages are the main problem of safety in AN... | {
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"Rapid progress in machine learning and artificial intelligence (AI) has brought increasing attention to the potential impacts of AI technologies on society. In this paper we discuss one such potential impact: the problem of acciden... |
1907.12933 | 2965255081 | Artificial Neural networks (ANNs) are powerful computing systems employed for various applications due to their versatility to generalize and to respond to unexpected inputs patterns. However, implementations of ANNs for safety-critical systems might lead to failures, which are hardly predicted in the design phase sinc... | @cite_34 and @cite_32 have shown how weak ANNs can be if small noises are present in their inputs. They described and evaluated testing and verification approaches based on covering methods and images proximity @cite_34 and how adversarial cases are obtained @cite_32 . In particular, our study resembles that of and @ci... | {
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"abstract": [
"Deep neural networks (DNNs) have a wide range of applications, and software employing them must be thoroughly tested, especially in safety-critical domains. Howeve... |
1907.12933 | 2965255081 | Artificial Neural networks (ANNs) are powerful computing systems employed for various applications due to their versatility to generalize and to respond to unexpected inputs patterns. However, implementations of ANNs for safety-critical systems might lead to failures, which are hardly predicted in the design phase sinc... | @cite_0 presented formal techniques to extract invariants from the decision logic of ANNs. These invariants represent pre- and post-conditions, which hold when transformations of a certain type are applied to ANNs. The authors have proposed two techniques. The first one is called iterative relaxation of decision patter... | {
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"We present techniques for automatically inferring invariant properties of feed-forward neural networks. Our insight is that feed forward networks should be able to ... |
1907.12933 | 2965255081 | Artificial Neural networks (ANNs) are powerful computing systems employed for various applications due to their versatility to generalize and to respond to unexpected inputs patterns. However, implementations of ANNs for safety-critical systems might lead to failures, which are hardly predicted in the design phase sinc... | @cite_13 also proposed a novel approach for automatically identifying safe regions of inputs w.r.t. some labels. The core idea is to identify safe regions w.r.t. labeled targets, i.e., providing a specific safety guarantee that a robust region is robust enough against adversarial perturbations w.r.t. to a target label.... | {
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"Deep neural networks have emerged as a widely used and effective means for tackling complex, real-world problems. However, a major obstacle in applying them to safety-critical systems is the great ... |
1907.12933 | 2965255081 | Artificial Neural networks (ANNs) are powerful computing systems employed for various applications due to their versatility to generalize and to respond to unexpected inputs patterns. However, implementations of ANNs for safety-critical systems might lead to failures, which are hardly predicted in the design phase sinc... | In addition to ESBMC-GPU, there exist other tools able to verify CUDA programs and each one of them uses its approach and targets specific property violations. However, given the current knowledge in software verification, ESBMC-GPU is the first verifier to check for adversarial cases and coverage methods in ANNs imple... | {
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"abstract": [
"CIVL is a framework for static analysis and verification of concurrent programs. One of the main challenges to practical application of these techniques is the lar... |
1907.12933 | 2965255081 | Artificial Neural networks (ANNs) are powerful computing systems employed for various applications due to their versatility to generalize and to respond to unexpected inputs patterns. However, implementations of ANNs for safety-critical systems might lead to failures, which are hardly predicted in the design phase sinc... | Our approach implemented on top of ESBMC-GPU has some similarities with other techniques described here, e.g., covering methods proposed by @cite_34 , model checking to solve adversarial cases proposed by @cite_32 . However, the main contribution is our requirements and how we handle the actual implementations of ANNs.... | {
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"We present a library that provides optimized implementations for deep learning primitives. Deep ... |
1907.12821 | 2966519285 | Pseudo-Boolean monotone functions are unimodal functions which are trivial to optimize for some hillclimbers, but are challenging for a surprising number of evolutionary algorithms (EAs). A general trend is that EAs are efficient if parameters like the mutation rate are set conservatively, but may need exponential time... | The analysis of EAs on monotone functions started in 2010 by the work of Doerr, Jansen, Sudholt, Winzen and Zarges @cite_15 @cite_10 . Their contribution was twofold: firstly, they showed that the , which flips each bit independently with static mutation rate @math , needs time @math on all monotone functions if the mu... | {
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"abstract": [
"Extending previous analyses on function classes like linear functions, we analyze how the simple (1+1) evolutionary algorithm optimizes pseudo-Boolean functions th... |
1907.12821 | 2966519285 | Pseudo-Boolean monotone functions are unimodal functions which are trivial to optimize for some hillclimbers, but are challenging for a surprising number of evolutionary algorithms (EAs). A general trend is that EAs are efficient if parameters like the mutation rate are set conservatively, but may need exponential time... | Most other work on population-based algorithms has shown benefits of larger population sizes, especially when crossover is used @cite_11 @cite_12 @cite_2 @cite_14 . The only exception in which a population has theoretically been proven to be severely disadvantageous is on Ignoble Trails. This rather specific function h... | {
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"Understanding the impact of crossover on performance is a major problem in the theory of geneti... |
1907.12821 | 2966519285 | Pseudo-Boolean monotone functions are unimodal functions which are trivial to optimize for some hillclimbers, but are challenging for a surprising number of evolutionary algorithms (EAs). A general trend is that EAs are efficient if parameters like the mutation rate are set conservatively, but may need exponential time... | Moreover, Lengler and Schaller pointed out an interesting connection between functions and a dynamic optimization problem in @cite_19 , which is arguably more natural. In that paper, the algorithm should optimize a linear function with positive weights, but the weights of the objective function are re-drawn each round ... | {
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"We study the well-known black-box optimisation algorithm (1+1)-EA on a novel type of noise model. In our noise model, the fitness function is linear with positive weights, but the absolute values of the weights may fluctuate in ea... |
1907.12736 | 2965903589 | We present a simple yet effective prediction module for a one-stage detector. The main process is conducted in a coarse-to-fine manner. First, the module roughly adjusts the default boxes to well capture the extent of target objects in an image. Second, given the adjusted boxes, the module aligns the receptive field of... | Two-stage detectors @cite_1 @cite_33 are composed of two parts. The first part generates a sparse set of region proposals, and the second part further classifies and regresses the proposals. These two-stage detectors have occupied top entries of challenging benchmarks @cite_33 @cite_32 @cite_0 . | {
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"Feature pyramids are a basic component in recognition systems for detecting objects at different scales. But pyramid representations... |
1907.12861 | 2965663461 | We introduce LEAF-QA, a comprehensive dataset of @math densely annotated figures charts, constructed from real-world open data sources, along with 2 million question-answer (QA) pairs querying the structure and semantics of these charts. LEAF-QA highlights the problem of multimodal QA, which is notably different from c... | There has been recent interest in analyzing figures and charts, particularly to understand the type of visualization and for data extraction from the chart images. @cite_26 describe algorithms to extract data from pie and bar charts, particularly to re-visualize them. Further, interactive methods for bar chart extracti... | {
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1907.12861 | 2965663461 | We introduce LEAF-QA, a comprehensive dataset of @math densely annotated figures charts, constructed from real-world open data sources, along with 2 million question-answer (QA) pairs querying the structure and semantics of these charts. LEAF-QA highlights the problem of multimodal QA, which is notably different from c... | Learning to answer questions based on natural images has been an area of extensive research in recent years. Several datasets including DAQUAR @cite_6 , COCO-QA @cite_16 , VQA @cite_2 , Visual7w @cite_9 and MovieQA @cite_33 have been proposed to explore different facets of question answering on natural images and video... | {
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1907.12646 | 2964433578 | In this paper, we propose a noise-aware exposure control algorithm for robust robot vision. Our method aims to capture the best-exposed image which can boost the performance of various computer vision and robotics tasks. For this purpose, we carefully design an image quality metric which captures complementary quality ... | Capturing a well-exposed image is an essential condition to apply any vision based algorithms under challenging environments. In this paper, we define the term from a robotics point of view, as an image containing texture details, sharp object boundaries with low noise, saturation, and blur. In fact, these conditions a... | {
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"",
"We present ORB-SLAM2, a complete simultaneous localization and mapping (SLAM) system for monocular, stereo and RGB-D cameras, including map reuse, loop closing, and r... |
1907.12646 | 2964433578 | In this paper, we propose a noise-aware exposure control algorithm for robust robot vision. Our method aims to capture the best-exposed image which can boost the performance of various computer vision and robotics tasks. For this purpose, we carefully design an image quality metric which captures complementary quality ... | The main problem of gradient-based metrics is their tendency to favor high exposures, which, in turn leads to over-exposed images. To avoid such problem, Kim al @cite_17 proposed a gradient weighting scheme based on local image entropy. The optimal exposure is estimated via a Bayesian optimization framework, which find... | {
"cite_N": [
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"abstract": [
"Under- and oversaturation can cause severe image degradation in many vision-based robotic applications. To control camera exposure in dynamic lighting conditions, we introduce a novel metric for image information measure. Measurin... |
1907.12782 | 2964885899 | Bluetooth Low Energy (BLE) has become an intrinsic wireless technology for the Internet of Things (IoT). With the proliferation of BLE-embedded IoT devices, it is important to study the security and privacy implications of BLE. The forefront attack to BLE devices is the wireless sniffing attack, which would lead to mor... | Aforementioned sniffing attacks are based on multi-radio platforms which could be prohibitively expensive for less-capable adversaries. Currently, one popular platform Ubertooth One is an open-source, single-radio and cheap Bluetooth sniffer that was developed by Ryan @cite_17 . This is a powerful sniffer that is relie... | {
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"abstract": [
"We discuss our tools and techniques to monitor and inject packets in Bluetooth Low Energy. Also known as BTLE or Bluetooth Smart, it is found in recent high-end smartphones, sports devices, sensors, and will soon appear in many medi... |
1907.12648 | 2966026106 | In multi-agent path finding (MAPF) the task is to navigate agents from their starting positions to given individual goals. The problem takes place in an undirected graph whose vertices represent positions and edges define the topology. Agents can move to neighbor vertices across edges. In the standard MAPF, space occup... | The idea behind the SAT-based approach is to construct a propositional formula @math such that it is satisfiable if and only if a solution of a given MAPF of sum-of-costs @math exists @cite_3 . Moreover, the approach is constructive; that is, @math exactly reflects the MAPF instance and if satisfiable, solution of MAPF... | {
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"This paper deals with solving cooperative path finding (CPF) problems in a makespan-optimal way. A feasible solution to the CPF problem lies in the moving of mobile agents where each agent has unique initial and goal positions. The... |
1907.12648 | 2966026106 | In multi-agent path finding (MAPF) the task is to navigate agents from their starting positions to given individual goals. The problem takes place in an undirected graph whose vertices represent positions and edges define the topology. Agents can move to neighbor vertices across edges. In the standard MAPF, space occup... | A common measure how to reduce the number of decision variables derived from the time expansion is the use of multi-value decision diagrams (MDDs) @cite_14 . The basic observation that holds for MAPF is that an agent can reach vertices in the distance @math (distance of a vertex is measured as the length of the shortes... | {
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"abstract": [
"We address the problem of optimal pathfinding for multiple agents. Given a start state and a goal state for each of the agents, the task is to find minimal paths for the different agents while avoiding collisions. Previous work on... |
1907.12743 | 2966860738 | Although various image-based domain adaptation (DA) techniques have been proposed in recent years, domain shift in videos is still not well-explored. Most previous works only evaluate performance on small-scale datasets which are saturated. Therefore, we first propose two large-scale video DA datasets with much larger ... | With the rise of deep convolutional neural networks (CNNs), recent work for video classification mainly aims to learn compact spatio-temporal representations by leveraging CNNs for spatial information and designing various architectures to exploit temporal dynamics @cite_55 . In addition to separating spatial and tempo... | {
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1907.12743 | 2966860738 | Although various image-based domain adaptation (DA) techniques have been proposed in recent years, domain shift in videos is still not well-explored. Most previous works only evaluate performance on small-scale datasets which are saturated. Therefore, we first propose two large-scale video DA datasets with much larger ... | Most recent DA approaches are based on deep learning architectures designed for addressing the domain shift problems given the fact that the deep CNN features without any DA method outperform traditional DA methods using hand-crafted features @cite_29 . Most DA approaches follow the two-branch (source and target) archi... | {
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"abstract": [
"We evaluate whether features extracted from the activation of a deep convolutional network trained in a fully supervised fashion on a large, fixed set of object recognition tasks can be repurposed... |
1907.12704 | 2964609265 | Unsupervised feature learning for point clouds has been vital for large-scale point cloud understanding. Recent deep learning based methods depend on learning global geometry from self-reconstruction. However, these methods are still suffering from ineffective learning of local geometry, which significantly limits the ... | Deep learning models have led to significant progress in feature learning for 3D shapes @cite_27 @cite_18 @cite_33 @cite_4 @cite_17 @cite_37 @cite_32 @cite_12 @cite_3 @cite_25 . Here, we focus on reviewing studies on point clouds. For supervised methods, supervised information, such as shape class labels or segmentatio... | {
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1907.12704 | 2964609265 | Unsupervised feature learning for point clouds has been vital for large-scale point cloud understanding. Recent deep learning based methods depend on learning global geometry from self-reconstruction. However, these methods are still suffering from ineffective learning of local geometry, which significantly limits the ... | As a pioneering work, PointNet @cite_28 was proposed to directly learn features from point clouds by deep learning models. However, PointNet is limited in capturing contextual information among points. To resolve this issue, various techniques were proposed to establish graph in a local region to capture the relationsh... | {
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1907.12622 | 2965300374 | The cross-depiction problem refers to the task of recognising visual objects regardless of their depictions; whether photographed, painted, sketched, etc . In the past, some researchers considered cross-depiction to be domain adaptation (DA). More recent work considers cross-depiction as domain generalisation (DG), in ... | The cross-depiction problem refers to the task of recognising visual objects regardless of their depiction whether realistic or artistic. It is an under-researched area. Some work uses constellation models, e.g. Crowley and Zisserman use a DPM to learn figurative art on Greek vases @cite_27 . Others develop the problem... | {
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"abstract": [
"We describe a new system for searching video databases using ... |
1907.12622 | 2965300374 | The cross-depiction problem refers to the task of recognising visual objects regardless of their depictions; whether photographed, painted, sketched, etc . In the past, some researchers considered cross-depiction to be domain adaptation (DA). More recent work considers cross-depiction as domain generalisation (DG), in ... | Deep learning has recently emerged as a truly significant development in Computer Vision. It has been successful on conventional databases, and over a wide range of tasks, with recognition rates in excess of @math Other than this paper, we know of only two studies aimed at assessing the performance of well established ... | {
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"The objective of this work is to recognize object categories (such as animals and vehicles) in paintings, whilst learning these categories f... |
1907.12622 | 2965300374 | The cross-depiction problem refers to the task of recognising visual objects regardless of their depictions; whether photographed, painted, sketched, etc . In the past, some researchers considered cross-depiction to be domain adaptation (DA). More recent work considers cross-depiction as domain generalisation (DG), in ... | Datasets exhibit bias, which can be problematic. In photographic image recognition, bias for particular camera settings and other attributes can prevent models generalising well @cite_12 . This motivated the collection of the multi-domain VLCS dataset: an aggregation of photos from Caltech, LabelMe, Pascal VOC 2007 and... | {
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"The problem of domain generalization is to learn from multiple training domains, and extract a ... |
1907.12622 | 2965300374 | The cross-depiction problem refers to the task of recognising visual objects regardless of their depictions; whether photographed, painted, sketched, etc . In the past, some researchers considered cross-depiction to be domain adaptation (DA). More recent work considers cross-depiction as domain generalisation (DG), in ... | Domain Adaptation (DA) attempts to compensate for bias by adapting a model constructed on one domain to a target domain using examples from that new domain, e.g. @cite_8 . DA has been used in the cross depiction problem with both non-neural @cite_17 and neural algorithms, such as the Domain Separation Network (DSN) @ci... | {
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"abstract": [
"The cost of large scale data collection and annotation often makes the application of machine learning algorithms to new tasks or datasets prohibitively expensive.... |
1907.12622 | 2965300374 | The cross-depiction problem refers to the task of recognising visual objects regardless of their depictions; whether photographed, painted, sketched, etc . In the past, some researchers considered cross-depiction to be domain adaptation (DA). More recent work considers cross-depiction as domain generalisation (DG), in ... | Recently, Domain Generalisation (DG) approaches have gained attention. These differ from DA in that DG algorithms have no access to the target domain. General approaches include learning domain invariant representations, or deriving domain agnostic classifiers by assuming individual domains' classifiers consist of doma... | {
"cite_N": [
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"abstract": [
"The presence of bias in existing object recognition datasets is now well-known in the computer vision comm... |
1907.12707 | 2966474827 | Multiple-antenna backscatter is emerging as a promising approach to offer high communication performance for the data-intensive applications of ambient backscatter communications (AmBC). Although much has been understood about multiple-antenna backscatter in conventional backscatter communications (CoBC), existing anal... | Of the existing studies in AmBC, the majority has focused solely on multiple antennas at the reader, while ignoring the tags. To address the direct link interference from ambient RF source, multiple-antenna readers are proposed in @cite_9 @cite_1 for the joint detection of the legacy and backscatter systems. Previous w... | {
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"abstract": [
"Ambient backscatter communication (AmBC) enables a passive backscatter device to transmit information to a reader using ambient RF signals, and has emerged as a prom... |
1907.12797 | 2966008881 | With the aim to propose a non parametric hypothesis test, this paper carries out a study on the Matching Error (ME), a comparison index of two partitions obtained from the same data set, using for example two clustering methods. This index is related to the misclassifica-tion error in supervised learning. Some properti... | @cite_14 introduced an index called inspired from the misclassification error used in supervised learning. Consider that one of the two compared clusterings ( @math for instance) corresponds to the true labels of each observation and the other clustering ( @math ) to the predicted ones. The supervised classification er... | {
"cite_N": [
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"2127042504"
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"abstract": [
"We compare the three basic algorithms for model-based clustering on high-dimensional discrete-variable datasets. All three algorithms use the same underlying model: a naive-Bayes model with a hidden root node, also known as a mult... |
1907.12797 | 2966008881 | With the aim to propose a non parametric hypothesis test, this paper carries out a study on the Matching Error (ME), a comparison index of two partitions obtained from the same data set, using for example two clustering methods. This index is related to the misclassifica-tion error in supervised learning. Some properti... | where @math is an injective mapping of @math into @math ( @cite_4 ). The @math index may be complex to compute when the number of clusters is large. A polynomial time algorithm has been proposed by @cite_10 to compute it efficiently. We will study the distributional properties of this index in the next section. | {
"cite_N": [
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"abstract": [
"We herein introduce a new method of interpretable clustering that uses unsupervised binary trees. It is a three-stage procedure, the first stage of which entails a series of recursive binary splits... |
1907.12797 | 2966008881 | With the aim to propose a non parametric hypothesis test, this paper carries out a study on the Matching Error (ME), a comparison index of two partitions obtained from the same data set, using for example two clustering methods. This index is related to the misclassifica-tion error in supervised learning. Some properti... | The entropy of a partition @math is defined by @math where @math is the estimate of the probability that an element is in cluster @math . The can be used to measure the independence of two partitions @math and @math . It is given by: @math , where @math is the estimate of the probability that an element belongs to clus... | {
"cite_N": [
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"abstract": [
"We address the problem of robust clustering by combining data partitions (forming a clustering ensemble) produced by multiple clusterings. We formulate robust cluste... |
1907.12797 | 2966008881 | With the aim to propose a non parametric hypothesis test, this paper carries out a study on the Matching Error (ME), a comparison index of two partitions obtained from the same data set, using for example two clustering methods. This index is related to the misclassifica-tion error in supervised learning. Some properti... | In @cite_19 and @cite_13 several indices are compared on artificially simulated partitions with various configurations; partitions are either balanced or unbalanced, dependent or independent, varying number of clusters. They show that the indices based on set overlaps have better performance than those based on countin... | {
"cite_N": [
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"For highly imbalanced data sets, almost all the instances are labeled as one class, whereas far fewer examples are labeled as the other classes. In this paper, we present an empirical comparison o... |
1907.12797 | 2966008881 | With the aim to propose a non parametric hypothesis test, this paper carries out a study on the Matching Error (ME), a comparison index of two partitions obtained from the same data set, using for example two clustering methods. This index is related to the misclassifica-tion error in supervised learning. Some properti... | @cite_6 study the behavior of the Rand, Adjusted Rand, Jaccard and Fowlkes Mallows indices. They compare the partitions produced by hierarchical algorithms with the true partitions, varying the number of groups with a sample of 50 observations and conclude that the adjusted Rand index seems to be more appropriate for c... | {
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"abstract": [
"A cluster operator takes a set of data points and partitions the points into clusters (subsets). As with any scientific model, the scientific content of a cluster op... |
1907.12868 | 2965035401 | Collagen fiber orientations in bones, visible with Second Harmonic Generation (SHG) microscopy, represent the inner structure and its alteration due to influences like cancer. While analyses of these orientations are valuable for medical research, it is not feasible to analyze the needed large amounts of local orientat... | Currently neural networks are state-of-the-art in the field of image data classification (e.g. ImageNet @cite_20 ). A variety of neural networks have emerged over the years @cite_3 @cite_0 @cite_23 @cite_11 @cite_15 @cite_14 . These networks started with a simple architecture (e.g. VGG-16 @cite_0 ). They integrated new... | {
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"Very deep convolutional netw... |
1907.12868 | 2965035401 | Collagen fiber orientations in bones, visible with Second Harmonic Generation (SHG) microscopy, represent the inner structure and its alteration due to influences like cancer. While analyses of these orientations are valuable for medical research, it is not feasible to analyze the needed large amounts of local orientat... | Semantic segmentation gives a classification for every pixel in an image and is an extension of a classification problem. @cite_24 first proposed to use fully convolutional networks to solve semantic segmentation. U-Net @cite_25 is a network for semantic segmentation which was designed for medical images. Often semanti... | {
"cite_N": [
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"abstract": [
"Convolutional networks are powerful visual models that yield hierarchies of features. We show that convolutional networks by themselves, trained end-to-end, pixels-to-pixels, exceed the state-of-t... |
1907.12868 | 2965035401 | Collagen fiber orientations in bones, visible with Second Harmonic Generation (SHG) microscopy, represent the inner structure and its alteration due to influences like cancer. While analyses of these orientations are valuable for medical research, it is not feasible to analyze the needed large amounts of local orientat... | However, the current state-of-the-art approaches for image classification and semantic segmentation have two major drawbacks in the context of uncertain local fiber orientation classification. We have 3D data and a high uncertainty for the borders. Most research focuses on 2D data while @cite_12 showed that it is benef... | {
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"abstract": [
"This paper introduces a network for volumetric segmentation that learns from sparsely annotated volumetric images. We outline two attractive use cases of this meth... |
1907.12868 | 2965035401 | Collagen fiber orientations in bones, visible with Second Harmonic Generation (SHG) microscopy, represent the inner structure and its alteration due to influences like cancer. While analyses of these orientations are valuable for medical research, it is not feasible to analyze the needed large amounts of local orientat... | While 3D extensions of Inception-ResNet-v2 have been presented in @cite_2 @cite_22 the usage of 2D pretraining is not so widely used. Parallel to our research proposed a 2D weight transfer strategy to 3D @cite_17 which is most similar to ours (see subsec:weight ). | {
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"abstract": [
"Low-dose computed tomography (LDCT) has attracted major attention in the medical imaging field, since CT-associated X-ray radiation carries health risks for patien... |
1907.12868 | 2965035401 | Collagen fiber orientations in bones, visible with Second Harmonic Generation (SHG) microscopy, represent the inner structure and its alteration due to influences like cancer. While analyses of these orientations are valuable for medical research, it is not feasible to analyze the needed large amounts of local orientat... | Collagen structures in SHG images have been analyzed in several publications @cite_19 @cite_10 @cite_18 @cite_21 @cite_9 @cite_1 @cite_6 . They were analyzed in tissue @cite_19 and bones @cite_18 @cite_10 . @cite_1 presented how Fourier analysis can be used to investigate the orientation of collagen fibers. The Fourier... | {
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"Interfaces provide the struct... |
1907.12868 | 2965035401 | Collagen fiber orientations in bones, visible with Second Harmonic Generation (SHG) microscopy, represent the inner structure and its alteration due to influences like cancer. While analyses of these orientations are valuable for medical research, it is not feasible to analyze the needed large amounts of local orientat... | @cite_13 state to be the first to analyze SHG images with neural networks. They estimated the elastic properties of collagenous tissue. A classification or segmentation of fibers were not part of their investigation. | {
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"abstract": [
"Abstract Biological collagenous tissues comprised of networks of collagen fibers are suitable for a broad spectrum of medical applications owing to their attractive mechanical properties. In this study, we developed a noninvasive ... |
1907.12400 | 2965074212 | In light of the rising demand for biometric-authentication systems, preventing face spoofing attacks is a critical issue for the safe deployment of face recognition systems. Here, we propose an efficient liveness detection algorithm that requires minimal hardware and only a small database, making it suitable for resour... | The current liveness detection technologies aimed against spoofing attacks are summarized below. Face spoofing attacks can be subdivided into two major categories: 2D attacks and 3D attacks. The former includes print-attacks and video-replay attacks, while the latter includes 3D spoofing mask attacks. Several publicly ... | {
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"Face antispoofing has now attracted intensive attention, aim... |
1907.12400 | 2965074212 | In light of the rising demand for biometric-authentication systems, preventing face spoofing attacks is a critical issue for the safe deployment of face recognition systems. Here, we propose an efficient liveness detection algorithm that requires minimal hardware and only a small database, making it suitable for resour... | The recent 3D reconstruction and printing technologies have given malicious users the ability to produce realistic spoofing masks @cite_9 . One example countermeasure against such a 3D attack is multispectral imaging. @cite_24 have reported the effectiveness of short-wave infrared (SWIR) imaging for detecting masks. An... | {
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"abstract": [
"Recent studies point out that spoofing attacks using facial masks still are a severe problem for current biometric face recognition (FR) systems. As such systems a... |
1907.12508 | 2964542684 | Many real-world datasets are labeled with natural orders, i.e., ordinal labels. Ordinal regression is a method to predict ordinal labels that finds a wide range of applications in data-rich science domains, such as medical, social and economic sciences. Most existing approaches work well for a single ordinal regression... | Ordinal regression is an approach aiming at classifying the data with natural ordered labels and plays an important role in many data-rich science domains. According to the commonly used taxonomy of ordinal regression @cite_62 , the existing methods are categorized into: naive approaches, ordinal binary decomposition a... | {
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"When we have several related tasks, solving them simultaneously is shown to be more effective than solving them individually. This approach is called multi-task lear... |
1907.12508 | 2964542684 | Many real-world datasets are labeled with natural orders, i.e., ordinal labels. Ordinal regression is a method to predict ordinal labels that finds a wide range of applications in data-rich science domains, such as medical, social and economic sciences. Most existing approaches work well for a single ordinal regression... | Ordinal binary decomposition approaches are proposed to decompose the ordinal labels into several binary ones that are then estimated by multiple models @cite_50 @cite_54 . For example, @cite_50 transforms the data from @math -classes ordinal problems to @math ordered binary classification problems and then they are tr... | {
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1907.12508 | 2964542684 | Many real-world datasets are labeled with natural orders, i.e., ordinal labels. Ordinal regression is a method to predict ordinal labels that finds a wide range of applications in data-rich science domains, such as medical, social and economic sciences. Most existing approaches work well for a single ordinal regression... | In @cite_45 , support vector ordinal regression (SVOR) is achieved by finding multiple thresholds that partition the real line of ordinal values into several consecutive intervals for representing ordered segments; however, it does not consider the ordinal inequalities on the thresholds. In @cite_44 @cite_56 , the auth... | {
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"In this paper, we propose two new support vector approaches for ordinal regression, which optimize multiple thresholds to define... |
1907.12508 | 2964542684 | Many real-world datasets are labeled with natural orders, i.e., ordinal labels. Ordinal regression is a method to predict ordinal labels that finds a wide range of applications in data-rich science domains, such as medical, social and economic sciences. Most existing approaches work well for a single ordinal regression... | Generalized linear models perform ordinal regression by fitting a coefficient vector and a set of thresholds, e.g., ordered logit @cite_46 @cite_23 and ordered probit @cite_17 @cite_32 . The margin functions are defined based on the cumulative probability of training instances' ordinal labels. Different link functions ... | {
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"abstract": [
"This article describes the gologit2 program for generalized ordered logit models. gologit2 is inspired by Vincent Fu’s gologit r... |
1907.12508 | 2964542684 | Many real-world datasets are labeled with natural orders, i.e., ordinal labels. Ordinal regression is a method to predict ordinal labels that finds a wide range of applications in data-rich science domains, such as medical, social and economic sciences. Most existing approaches work well for a single ordinal regression... | Recently, MTL has been combined with many deep learning approaches @cite_10 . MTL can be implemented in the DNN based approaches in two ways, i.e., soft and hard parameter sharing of hidden layers. In the soft parameter sharing, all tasks do not share representation layers and the distance among their own representatio... | {
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],
"abstract": [
"We propose a framework for training multiple neural networks simultaneously. The parameters from all models are regularised by the tensor trace norm, so that each... |
1907.12508 | 2964542684 | Many real-world datasets are labeled with natural orders, i.e., ordinal labels. Ordinal regression is a method to predict ordinal labels that finds a wide range of applications in data-rich science domains, such as medical, social and economic sciences. Most existing approaches work well for a single ordinal regression... | Hard parameter sharing is the most commonly used approach in DNN based MTL @cite_10 . In the hard parameter sharing, all tasks share the representation layers to reduce the risk of overfitting @cite_24 and keep some task-specific layers to preserve characteristics of each task @cite_40 . In this paper, we use the hard ... | {
"cite_N": [
"@cite_24",
"@cite_40",
"@cite_10"
],
"mid": [
"2143419558",
"2951657494",
"2624871570"
],
"abstract": [
"A Bayesian model of learning to learn by sampling from multiple tasks is presented. The multiple tasks are themselves generated by sampling from a distribution ov... |
1907.12363 | 2966207284 | Training models on highly unbalanced data is admitted to be a challenging task for machine learning algorithms. Current studies on deep learning mainly focus on data sets with balanced class labels, or unbalanced data but with massive amount of samples available, like in speech recognition. However, the capacities of d... | In their review, @cite_2 of methods and applications for learning on unbalanced data, authors cite as domains extensively explored the topic Taxonomy, Chemical engineering, financial management, information technology, energy management, security management.Most of the related experimentation tend to show that since ye... | {
"cite_N": [
"@cite_2"
],
"mid": [
"2562319768"
],
"abstract": [
"527 articles related to imbalanced data and rare events are reviewed.Viewing reviewed papers from both technical and practical perspectives.Summarizing existing methods and corresponding statistics by a new taxonomy idea.Categorizi... |
1907.12363 | 2966207284 | Training models on highly unbalanced data is admitted to be a challenging task for machine learning algorithms. Current studies on deep learning mainly focus on data sets with balanced class labels, or unbalanced data but with massive amount of samples available, like in speech recognition. However, the capacities of d... | In @cite_5 , authors outline the performance of several popular decision tree splitting criteria – information gain, Gini measure, and DKM – can be used to form decision trees, and improve performances of tree construction method applied to unbalanced data. | {
"cite_N": [
"@cite_5"
],
"mid": [
"1831729862"
],
"abstract": [
"Learning from unbalanced datasets presents a convoluted problem in which traditional learning algorithms may perform poorly. The objective functions used for learning the classifiers typically tend to favor the larger, less importa... |
1907.12363 | 2966207284 | Training models on highly unbalanced data is admitted to be a challenging task for machine learning algorithms. Current studies on deep learning mainly focus on data sets with balanced class labels, or unbalanced data but with massive amount of samples available, like in speech recognition. However, the capacities of d... | Authors of @cite_6 discuss the use of 108 different classification models to determine the most fitting model, capable of dealing with the imbalanced data issue coming from a biomedical literature corpus and achieve the most satisfying results with a LMT decision tree classifier previously used with success in a unbala... | {
"cite_N": [
"@cite_1",
"@cite_6"
],
"mid": [
"2071049913",
"2062707524"
],
"abstract": [
"Numerous initiatives have allowed users to share knowledge or opinions using collaborative platforms. In most cases, the users provide a textual description of their knowledge, following very limite... |
1907.12363 | 2966207284 | Training models on highly unbalanced data is admitted to be a challenging task for machine learning algorithms. Current studies on deep learning mainly focus on data sets with balanced class labels, or unbalanced data but with massive amount of samples available, like in speech recognition. However, the capacities of d... | In the domain of credit applications, authors of @cite_11 compare several techniques that can be used in the analysis of imbalanced credit scoring data sets. The results from this empirical study indicate that the random forest and gradient boosting classifiers perform very well in a credit scoring context and are able... | {
"cite_N": [
"@cite_11"
],
"mid": [
"2052611008"
],
"abstract": [
"In this paper, we set out to compare several techniques that can be used in the analysis of imbalanced credit scoring data sets. In a credit scoring context, imbalanced data sets frequently occur as the number of defaulting loans ... |
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