Split (2)

train · 433k rows

id stringlengths 9 16	title stringlengths 4 278	abstract stringlengths 3 4.08k	cs.HC bool 2 classes	cs.CE bool 2 classes	cs.SD bool 2 classes	cs.SI bool 2 classes	cs.AI bool 2 classes	cs.IR bool 2 classes	cs.LG bool 2 classes	cs.RO bool 2 classes	cs.CL bool 2 classes	cs.IT bool 2 classes	cs.SY bool 2 classes	cs.CV bool 2 classes	cs.CR bool 2 classes	cs.CY bool 2 classes	cs.MA bool 2 classes	cs.NE bool 2 classes	cs.DB bool 2 classes	Other bool 2 classes	__index_level_0__ int64 0 541k
1908.02432	DronePick: Object Picking and Delivery Teleoperation with the Drone Controlled by a Wearable Tactile Display	We report on the teleoperation system DronePick which provides remote object picking and delivery by a human-controlled quadcopter. The main novelty of the proposed system is that the human user continuously gets the visual and haptic feedback for accurate teleoperation. DronePick consists of a quadcopter equipped with...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	141,001
2312.08291	VQ-HPS: Human Pose and Shape Estimation in a Vector-Quantized Latent Space	Previous works on Human Pose and Shape Estimation (HPSE) from RGB images can be broadly categorized into two main groups: parametric and non-parametric approaches. Parametric techniques leverage a low-dimensional statistical body model for realistic results, whereas recent non-parametric methods achieve higher precisio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	415,256
1205.6309	Improper Signaling on the Two-user SISO Interference Channel	On a single-input-single-out (SISO) interference channel (IC), conventional non-cooperative strategies encourage players selfishly maximizing their transmit data rates, neglecting the deficit of performance caused by and to other players. In the case of proper complex Gaussian noise, the maximum entropy theorem shows t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	16,215
1902.07776	Perceptual Quality-preserving Black-Box Attack against Deep Learning Image Classifiers	Deep neural networks provide unprecedented performance in all image classification problems, taking advantage of huge amounts of data available for training. Recent studies, however, have shown their vulnerability to adversarial attacks, spawning an intense research effort in this field. With the aim of building better...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	122,053
2205.14969	Guided Diffusion Model for Adversarial Purification	With wider application of deep neural networks (DNNs) in various algorithms and frameworks, security threats have become one of the concerns. Adversarial attacks disturb DNN-based image classifiers, in which attackers can intentionally add imperceptible adversarial perturbations on input images to fool the classifiers....	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	299,557
2203.10006	Ultra-low Latency Spiking Neural Networks with Spatio-Temporal Compression and Synaptic Convolutional Block	Spiking neural networks (SNNs), as one of the brain-inspired models, has spatio-temporal information processing capability, low power feature, and high biological plausibility. The effective spatio-temporal feature makes it suitable for event streams classification. However, neuromorphic datasets, such as N-MNIST, CIFA...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	286,366
1708.08289	Generating Query Suggestions to Support Task-Based Search	We address the problem of generating query suggestions to support users in completing their underlying tasks (which motivated them to search in the first place). Given an initial query, these query suggestions should provide a coverage of possible subtasks the user might be looking for. We propose a probabilistic model...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	79,624
2111.03396	FedLess: Secure and Scalable Federated Learning Using Serverless Computing	The traditional cloud-centric approach for Deep Learning (DL) requires training data to be collected and processed at a central server which is often challenging in privacy-sensitive domains like healthcare. Towards this, a new learning paradigm called Federated Learning (FL) has been proposed that brings the potential...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	265,154
2110.13366	Newtonian Mechanics Based Transient Stability PART IV: Equivalent Machine	This paper analyzes the mechanisms of the equivalent machine and also its advantages in TSA. Based on the two group separations, an equivalent machine is modeled through the equivalence of the motions of all machines inside each group. This "motion equivalence" fully ensures the modeling of the two-machine system and t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	263,150
1703.02610	Multi-Robot Active Information Gathering with Periodic Communication	A team of robots sharing a common goal can benefit from coordination of the activities of team members, helping the team to reach the goal more reliably or quickly. We address the problem of coordinating the actions of a team of robots with periodic communication capability executing an information gathering task. We c...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	69,582
1210.7403	Resolution Enhancement of Range Images via Color-Image Segmentation	We report a method for super-resolution of range images. Our approach leverages the interpretation of LR image as sparse samples on the HR grid. Based on this interpretation, we demonstrate that our recently reported approach, which reconstructs dense range images from sparse range data by exploiting a registered colou...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	19,432
2111.00633	Settling the Horizon-Dependence of Sample Complexity in Reinforcement Learning	Recently there is a surge of interest in understanding the horizon-dependence of the sample complexity in reinforcement learning (RL). Notably, for an RL environment with horizon length $H$, previous work have shown that there is a probably approximately correct (PAC) algorithm that learns an $O(1)$-optimal policy usin...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	264,285
2108.01789	Monte Carlo Tree Search for high precision manufacturing	Monte Carlo Tree Search (MCTS) has shown its strength for a lot of deterministic and stochastic examples, but literature lacks reports of applications to real world industrial processes. Common reasons for this are that there is no efficient simulator of the process available or there exist problems in applying MCTS to...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	249,124
2208.04202	Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning	We present Bit Diffusion: a simple and generic approach for generating discrete data with continuous state and continuous time diffusion models. The main idea behind our approach is to first represent the discrete data as binary bits, and then train a continuous diffusion model to model these bits as real numbers which...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	312,026
1711.07980	Finding Algebraic Structure of Care in Time: A Deep Learning Approach	Understanding the latent processes from Electronic Medical Records could be a game changer in modern healthcare. However, the processes are complex due to the interaction between at least three dynamic components: the illness, the care and the recording practice. Existing methods are inadequate in capturing the dynamic...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	85,110
2210.11275	Causal Structural Hypothesis Testing and Data Generation Models	A vast amount of expert and domain knowledge is captured by causal structural priors, yet there has been little research on testing such priors for generalization and data synthesis purposes. We propose a novel model architecture, Causal Structural Hypothesis Testing, that can use nonparametric, structural causal knowl...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	325,257
1801.08212	Multi-optional Many-sorted Past Present Future structures and its description	The cognitive theory of true conditions (CTTC) is a proposal to describe the model-theoretic semantics of symbolic cognitive architectures and design the implementation of cognitive abilities. The CTTC is formulated mathematically using the multi-optional many-sorted past present future(MMPPF) structures. This article ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	88,917
2107.09710	TLA: Twitter Linguistic Analysis	Linguistics has been instrumental in developing a deeper understanding of human nature. Words are indispensable to bequeath the thoughts, emotions, and purpose of any human interaction, and critically analyzing these words can elucidate the social and psychological behavior and characteristics of these social animals. ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	247,101
2501.19256	Objective Metrics for Human-Subjects Evaluation in Explainable Reinforcement Learning	Explanation is a fundamentally human process. Understanding the goal and audience of the explanation is vital, yet existing work on explainable reinforcement learning (XRL) routinely does not consult humans in their evaluations. Even when they do, they routinely resort to subjective metrics, such as confidence or under...	true	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	529,081
2312.12227	HuTuMotion: Human-Tuned Navigation of Latent Motion Diffusion Models with Minimal Feedback	We introduce HuTuMotion, an innovative approach for generating natural human motions that navigates latent motion diffusion models by leveraging few-shot human feedback. Unlike existing approaches that sample latent variables from a standard normal prior distribution, our method adapts the prior distribution to better ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	416,882
1806.07123	Cooperative Queuing Policies for Effective Human-Multi-Robot Interaction	We consider multi-robot applications, where a team of robots can ask for the intervention of a human operator to handle difficult situations. As the number of requests grows, team members will have to wait for the operator attention, hence the operator becomes a bottleneck for the system. Our aim in this context is to ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	100,845
2309.11338	TRAVID: An End-to-End Video Translation Framework	In today's globalized world, effective communication with people from diverse linguistic backgrounds has become increasingly crucial. While traditional methods of language translation, such as written text or voice-only translations, can accomplish the task, they often fail to capture the complete context and nuanced i...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	393,371
1711.02207	Towards Language-Universal End-to-End Speech Recognition	Building speech recognizers in multiple languages typically involves replicating a monolingual training recipe for each language, or utilizing a multi-task learning approach where models for different languages have separate output labels but share some internal parameters. In this work, we exploit recent progress in e...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	84,019
1607.04593	Spatial Context based Angular Information Preserving Projection for Hyperspectral Image Classification	Dimensionality reduction is a crucial preprocessing for hyperspectral data analysis - finding an appropriate subspace is often required for subsequent image classification. In recent work, we proposed supervised angular information based dimensionality reduction methods to find effective subspaces. Since unlabeled data...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	58,636
2103.10056	Dementia Severity Classification under Small Sample Size and Weak Supervision in Thick Slice MRI	Early detection of dementia through specific biomarkers in MR images plays a critical role in developing support strategies proactively. Fazekas scale facilitates an accurate quantitative assessment of the severity of white matter lesions and hence the disease. Imaging Biomarkers of dementia are multiple and comprehens...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	225,337
1904.11141	HAR-Net: Joint Learning of Hybrid Attention for Single-stage Object Detection	Object detection has been a challenging task in computer vision. Although significant progress has been made in object detection with deep neural networks, the attention mechanism is far from development. In this paper, we propose the hybrid attention mechanism for single-stage object detection. First, we present the m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	128,796
2108.04275	The covering radius of permutation designs	A notion of $t$-designs in the symmetric group on $n$ letters was introduced by Godsil in 1988. In particular $t$-transitive sets of permutations form a $t$-design. We derive upper bounds on the covering radius of these designs, as a function of $n$ and $t$ and in terms of the largest zeros of Charlier polynomials.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	249,951
1606.03380	Low-Complexity MIMO Precoding for Finite-Alphabet Signals	This paper investigates the design of precoders for single-user multiple-input multiple-output (MIMO) channels, and in particular for finite-alphabet signals. Based on an asymptotic expression for the mutual information of channels exhibiting line-of-sight components and rather general antenna correlations, precoding s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	57,090
2012.02594	To Schedule or not to Schedule: Extracting Task Specific Temporal Entities and Associated Negation Constraints	State of the art research for date-time entity extraction from text is task agnostic. Consequently, while the methods proposed in literature perform well for generic date-time extraction from texts, they don't fare as well on task specific date-time entity extraction where only a subset of the date-time entities presen...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	209,821
1105.5462	Variational Probabilistic Inference and the QMR-DT Network	We describe a variational approximation method for efficient inference in large-scale probabilistic models. Variational methods are deterministic procedures that provide approximations to marginal and conditional probabilities of interest. They provide alternatives to approximate inference methods based on stochastic s...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	10,537
2403.00016	Deep Sensitivity Analysis for Objective-Oriented Combinatorial Optimization	Pathogen control is a critical aspect of modern poultry farming, providing important benefits for both public health and productivity. Effective poultry management measures to reduce pathogen levels in poultry flocks promote food safety by lowering risks of food-borne illnesses. They also support animal health and welf...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	433,829
2308.05869	Shared Memory-contention-aware Concurrent DNN Execution for Diversely Heterogeneous System-on-Chips	Two distinguishing features of state-of-the-art mobile and autonomous systems are 1) there are often multiple workloads, mainly deep neural network (DNN) inference, running concurrently and continuously; and 2) they operate on shared memory system-on-chips (SoC) that embed heterogeneous accelerators tailored for specif...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	384,933
2103.14726	Random line graphs and edge-attributed network inference	We extend the latent position random graph model to the line graph of a random graph, which is formed by creating a vertex for each edge in the original random graph, and connecting each pair of edges incident to a common vertex in the original graph. We prove concentration inequalities for the spectrum of a line graph...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	226,951
2403.01994	Vanilla Transformers are Transfer Capability Teachers	Recently, Mixture of Experts (MoE) Transformers have garnered increasing attention due to their advantages in model capacity and computational efficiency. However, studies have indicated that MoE Transformers underperform vanilla Transformers in many downstream tasks, significantly diminishing the practical value of Mo...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	434,668
2405.20183	A Survey Study on the State of the Art of Programming Exercise Generation using Large Language Models	This paper analyzes Large Language Models (LLMs) with regard to their programming exercise generation capabilities. Through a survey study, we defined the state of the art, extracted their strengths and weaknesses and finally proposed an evaluation matrix, helping researchers and educators to decide which LLM is the be...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	459,232
2409.12034	Multi-Sensor Deep Learning for Glacier Mapping	The more than 200,000 glaciers outside the ice sheets play a crucial role in our society by influencing sea-level rise, water resource management, natural hazards, biodiversity, and tourism. However, only a fraction of these glaciers benefit from consistent and detailed in-situ observations that allow for assessing the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	489,410
2303.11717	A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?	As ChatGPT goes viral, generative AI (AIGC, a.k.a AI-generated content) has made headlines everywhere because of its ability to analyze and create text, images, and beyond. With such overwhelming media coverage, it is almost impossible for us to miss the opportunity to glimpse AIGC from a certain angle. In the era of A...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	true	352,975
2212.14674	A Comprehensive Gold Standard and Benchmark for Comics Text Detection and Recognition	This study focuses on improving the optical character recognition (OCR) data for panels in the COMICS dataset, the largest dataset containing text and images from comic books. To do this, we developed a pipeline for OCR processing and labeling of comic books and created the first text detection and recognition datasets...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	338,691
2205.13087	New Explicit Good Linear Sum-Rank-Metric Codes	Sum-rank-metric codes have wide applications in universal error correction, multishot network coding, space-time coding and the construction of partial-MDS codes for repair in distributed storage. Fundamental properties of sum-rank-metric codes have been studied and some explicit or probabilistic constructions of good ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	298,798
1511.00461	Circle detection using isosceles triangles sampling	Detection of circular objects in digital images is an important problem in several vision applications. Circle detection using randomized sampling has been developed in recent years to reduce the computational intensity. Randomized sampling, however, is sensitive to noise that can lead to reduced accuracy and false-pos...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	48,415
1906.10120	Assembly line balancing with task division	In a commonly-used version of the Simple Assembly Line Balancing Problem (SALBP-1) tasks are assigned to stations along an assembly line with a fixed cycle time in order to minimize the required number of stations. It has traditionally been assumed that the total work needed for each product unit has been partitioned i...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	136,364
2211.14927	BEV-Locator: An End-to-end Visual Semantic Localization Network Using Multi-View Images	Accurate localization ability is fundamental in autonomous driving. Traditional visual localization frameworks approach the semantic map-matching problem with geometric models, which rely on complex parameter tuning and thus hinder large-scale deployment. In this paper, we propose BEV-Locator: an end-to-end visual sema...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	333,047
2301.00552	Neural source/sink phase connectivity in developmental dyslexia by means of interchannel causality	While the brain connectivity network can inform the understanding and diagnosis of developmental dyslexia, its cause-effect relationships have not yet enough been examined. Employing electroencephalography signals and band-limited white noise stimulus at 4.8 Hz (prosodic-syllabic frequency), we measure the phase Grange...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	338,943
2109.00573	Pulmonary Disease Classification Using Globally Correlated Maximum Likelihood: an Auxiliary Attention mechanism for Convolutional Neural Networks	Convolutional neural networks (CNN) are now being widely used for classifying and detecting pulmonary abnormalities in chest radiographs. Two complementary generalization properties of CNNs, translation invariance and equivariance, are particularly useful in detecting manifested abnormalities associated with pulmonary ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	253,147
1905.08110	Image Captioning based on Deep Learning Methods: A Survey	Image captioning is a challenging task and attracting more and more attention in the field of Artificial Intelligence, and which can be applied to efficient image retrieval, intelligent blind guidance and human-computer interaction, etc. In this paper, we present a survey on advances in image captioning based on Deep L...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	131,408
1804.02693	Path to Stochastic Stability: Comparative Analysis of Stochastic Learning Dynamics in Games	Stochastic stability is a popular solution concept for stochastic learning dynamics in games. However, a critical limitation of this solution concept is its inability to distinguish between different learning rules that lead to the same steady-state behavior. We address this limitation for the first time and develop a ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	94,463
1807.10229	On Optimizing Power Allocation For Reliable Communication over Fading Channels with Uninformed Transmitter	We investigate energy efficient packet scheduling and power allocation problem for the services which require reliable communication to guarantee a certain quality of experience (QoE). We establish links between average transmit power and reliability of data transfer, which depends on both average amount of data transf...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	103,900
2108.04350	VirtualConductor: Music-driven Conducting Video Generation System	In this demo, we present VirtualConductor, a system that can generate conducting video from any given music and a single user's image. First, a large-scale conductor motion dataset is collected and constructed. Then, we propose Audio Motion Correspondence Network (AMCNet) and adversarial-perceptual learning to learn th...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	249,970
1812.01465	Cross-spectral Periocular Recognition: A Survey	Among many biometrics such as face, iris, fingerprint and others, periocular region has the advantages over other biometrics because it is non-intrusive and serves as a balance between iris or eye region (very stringent, small area) and the whole face region (very relaxed large area). Research have shown that this is t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	115,523
1905.08586	Marginalized Average Attentional Network for Weakly-Supervised Learning	In weakly-supervised temporal action localization, previous works have failed to locate dense and integral regions for each entire action due to the overestimation of the most salient regions. To alleviate this issue, we propose a marginalized average attentional network (MAAN) to suppress the dominant response of the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	131,503
2210.05073	Self-supervised Model Based on Masked Autoencoders Advance CT Scans Classification	The coronavirus pandemic has been going on since the year 2019, and the trend is still not abating. Therefore, it is particularly important to classify medical CT scans to assist in medical diagnosis. At present, Supervised Deep Learning algorithms have made a great success in the classification task of medical CT scan...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	322,689
1811.04719	End-to-End Non-Autoregressive Neural Machine Translation with Connectionist Temporal Classification	Autoregressive decoding is the only part of sequence-to-sequence models that prevents them from massive parallelization at inference time. Non-autoregressive models enable the decoder to generate all output symbols independently in parallel. We present a novel non-autoregressive architecture based on connectionist temp...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	113,157
1712.00369	Reachability Analysis of Large Linear Systems with Uncertain Inputs in the Krylov Subspace	One often wishes for the ability to formally analyze large-scale systems---typically, however, one can either formally analyze a rather small system or informally analyze a large-scale system. This work tries to further close this performance gap for reachability analysis of linear systems. Reachability analysis can ca...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	85,883
1902.11132	Generative Models for Low-Rank Video Representation and Reconstruction	Finding compact representation of videos is an essential component in almost every problem related to video processing or understanding. In this paper, we propose a generative model to learn compact latent codes that can efficiently represent and reconstruct a video sequence from its missing or under-sampled measuremen...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	122,875
1702.02211	Fixing the Infix: Unsupervised Discovery of Root-and-Pattern Morphology	We present an unsupervised and language-agnostic method for learning root-and-pattern morphology in Semitic languages. This form of morphology, abundant in Semitic languages, has not been handled in prior unsupervised approaches. We harness the syntactico-semantic information in distributed word representations to solv...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	67,941
2010.00925	Multi-Resolution 3D Convolutional Neural Networks for Automatic Coronary Centerline Extraction in Cardiac CT Angiography Scans	We propose a deep learning-based automatic coronary artery tree centerline tracker (AuCoTrack) extending the vessel tracker by Wolterink (arXiv:1810.03143). A dual pathway Convolutional Neural Network (CNN) operating on multi-scale 3D inputs predicts the direction of the coronary arteries as well as the presence of a b...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	198,448
1105.1406	Comparison Latent Semantic and WordNet Approach for Semantic Similarity Calculation	Information exchange among many sources in Internet is more autonomous, dynamic and free. The situation drive difference view of concepts among sources. For example, word 'bank' has meaning as economic institution for economy domain, but for ecology domain it will be defined as slope of river or lake. In this aper, we ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	10,279
cmp-lg/9410032	Planning Argumentative Texts	This paper presents \proverb\, a text planner for argumentative texts. \proverb\'s main feature is that it combines global hierarchical planning and unplanned organization of text with respect to local derivation relations in a complementary way. The former splits the task of presenting a particular proof into subtasks...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,214
1911.07710	Feedback Control for Online Training of Neural Networks	Convolutional neural networks (CNNs) are commonly used for image classification tasks, raising the challenge of their application on data flows. During their training, adaptation is often performed by tuning the learning rate. Usual learning rate strategies are time-based i.e. monotonously decreasing. In this paper, we...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	153,945
1909.07095	RuDaS: Synthetic Datasets for Rule Learning and Evaluation Tools	Logical rules are a popular knowledge representation language in many domains, representing background knowledge and encoding information that can be derived from given facts in a compact form. However, rule formulation is a complex process that requires deep domain expertise,and is further challenged by today's often ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	145,589
1305.2938	Temporal networks: slowing down diffusion by long lasting interactions	Interactions among units in complex systems occur in a specific sequential order thus affecting the flow of information, the propagation of diseases, and general dynamical processes. We investigate the Laplacian spectrum of temporal networks and compare it with that of the corresponding aggregate network. First, we sho...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	24,560
2306.08803	Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning	Thompson sampling (TS) is widely used in sequential decision making due to its ease of use and appealing empirical performance. However, many existing analytical and empirical results for TS rely on restrictive assumptions on reward distributions, such as belonging to conjugate families, which limits their applicabilit...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	373,546
2204.00392	When to Classify Events in Open Times Series?	In numerous applications, for instance in predictive maintenance, there is a pression to predict events ahead of time with as much accuracy as possible while not delaying the decision unduly. This translates in the optimization of a trade-off between earliness and accuracy of the decisions, that has been the subject of...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	289,243
2401.05314	ANIM-400K: A Large-Scale Dataset for Automated End-To-End Dubbing of Video	The Internet's wealth of content, with up to 60% published in English, starkly contrasts the global population, where only 18.8% are English speakers, and just 5.1% consider it their native language, leading to disparities in online information access. Unfortunately, automated processes for dubbing of video - replacing...	false	false	true	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	420,713
1412.1526	Parsing Occluded People by Flexible Compositions	This paper presents an approach to parsing humans when there is significant occlusion. We model humans using a graphical model which has a tree structure building on recent work [32, 6] and exploit the connectivity prior that, even in presence of occlusion, the visible nodes form a connected subtree of the graphical mo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	38,113
2411.05878	Joint-Optimized Unsupervised Adversarial Domain Adaptation in Remote Sensing Segmentation with Prompted Foundation Model	Unsupervised Domain Adaptation for Remote Sensing Semantic Segmentation (UDA-RSSeg) addresses the challenge of adapting a model trained on source domain data to target domain samples, thereby minimizing the need for annotated data across diverse remote sensing scenes. This task presents two principal challenges: (1) se...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	506,866
1907.09209	Automatic Calibration of Artificial Neural Networks for Zebrafish Collective Behaviours using a Quality Diversity Algorithm	During the last two decades, various models have been proposed for fish collective motion. These models are mainly developed to decipher the biological mechanisms of social interaction between animals. They consider very simple homogeneous unbounded environments and it is not clear that they can simulate accurately the...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	139,303
2007.10202	Can we cover navigational perception needs of the visually impaired by panoptic segmentation?	Navigational perception for visually impaired people has been substantially promoted by both classic and deep learning based segmentation methods. In classic visual recognition methods, the segmentation models are mostly object-dependent, which means a specific algorithm has to be devised for the object of interest. In...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	188,203
2008.11333	Actuator Dynamics Compensation in Stabilization of Abstract Linear Systems	This is the first part of four series papers, aiming at the problem of actuator dynamics compensation for linear systems. We consider the stabilization of a type of cascade abstract linear systems which model the actuator dynamics compensation for linear systems where both the control plant and its actuator dynamics ca...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	193,241
2005.08210	Multi-Entity and Multi-Enrollment Key Agreement with Correlated Noise	A basic model for key agreement with a remote (or hidden) source is extended to a multi-user model with joint secrecy and privacy constraints over all entities that do not trust each other after key agreement. Multiple entities using different measurements of the same source through broadcast channels (BCs) to agree on...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	true	177,551
1508.07175	Competitive and Penalized Clustering Auto-encoder	The paper has been withdrawn since more effective experiments should be completed. Auto-encoders (AE) has been widely applied in different fields of machine learning. However, as a deep model, there are a large amount of learnable parameters in the AE, which would cause over-fitting and slow learning speed in practic...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	46,384
2401.12761	MUSES: The Multi-Sensor Semantic Perception Dataset for Driving under Uncertainty	Achieving level-5 driving automation in autonomous vehicles necessitates a robust semantic visual perception system capable of parsing data from different sensors across diverse conditions. However, existing semantic perception datasets often lack important non-camera modalities typically used in autonomous vehicles, o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	423,490
2106.05837	Niche to normality -- an interdisciplinary review of Vehicle-to-Grid	Vehicle-to-Grid (V2G) capabilities, which enable electric vehicles to discharge power from their batteries for external uses, epitomise the coupling of the electricity and transport sectors. To thrive at the nexus of these large and well-established sectors V2G services must deliver technical, economic and social value...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	240,244
1706.08270	Multilevel Monte Carlo Method for Statistical Model Checking of Hybrid Systems	We study statistical model checking of continuous-time stochastic hybrid systems. The challenge in applying statistical model checking to these systems is that one cannot simulate such systems exactly. We employ the multilevel Monte Carlo method (MLMC) and work on a sequence of discrete-time stochastic processes whose ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	75,971
2204.08895	Invertible Mask Network for Face Privacy-Preserving	Face privacy-preserving is one of the hotspots that arises dramatic interests of research. However, the existing face privacy-preserving methods aim at causing the missing of semantic information of face and cannot preserve the reusability of original facial information. To achieve the naturalness of the processed face...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	292,247
1005.0608	Informal Concepts in Machines	This paper constructively proves the existence of an effective procedure generating a computable (total) function that is not contained in any given effectively enumerable set of such functions. The proof implies the existence of machines that process informal concepts such as computable (total) functions beyond the li...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	6,400
2405.20283	TetSphere Splatting: Representing High-Quality Geometry with Lagrangian Volumetric Meshes	We introduce TetSphere Splatting, a Lagrangian geometry representation designed for high-quality 3D shape modeling. TetSphere splatting leverages an underused yet powerful geometric primitive -- volumetric tetrahedral meshes. It represents 3D shapes by deforming a collection of tetrahedral spheres, with geometric regul...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	459,274
1401.3922	Discrete Convexity and Stochastic Approximation for Cross-layer On-off Transmission Control	This paper considers the discrete convexity of a cross-layer on-off transmission control problem in wireless communications. In this system, a scheduler decides whether or not to transmit in order to optimize the long-term quality of service (QoS) incurred by the queueing effects in the data link layer and the transmis...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	30,021
2412.17271	Multi-view Fuzzy Graph Attention Networks for Enhanced Graph Learning	Fuzzy Graph Attention Network (FGAT), which combines Fuzzy Rough Sets and Graph Attention Networks, has shown promise in tasks requiring robust graph-based learning. However, existing models struggle to effectively capture dependencies from multiple perspectives, limiting their ability to model complex data. To address...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	519,900
2202.10541	Online Learning for Orchestration of Inference in Multi-User End-Edge-Cloud Networks	Deep-learning-based intelligent services have become prevalent in cyber-physical applications including smart cities and health-care. Deploying deep-learning-based intelligence near the end-user enhances privacy protection, responsiveness, and reliability. Resource-constrained end-devices must be carefully managed in o...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	281,552
1909.10472	Event-triggered boundary control of constant-parameter reaction-diffusion PDEs: a small-gain approach	This paper deals with an event-triggered boundary control of constant-parameters reaction-diffusion PDE systems. The approach relies on the emulation of backstepping control along with a suitable triggering condition which establishes the time instants at which the control value needs to be sampled/updated. In this pap...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	146,556
2103.04635	FEDS -- Filtered Edit Distance Surrogate	This paper proposes a procedure to train a scene text recognition model using a robust learned surrogate of edit distance. The proposed method borrows from self-paced learning and filters out the training examples that are hard for the surrogate. The filtering is performed by judging the quality of the approximation, u...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	223,708
1904.03289	In the Wild Human Pose Estimation Using Explicit 2D Features and Intermediate 3D Representations	Convolutional Neural Network based approaches for monocular 3D human pose estimation usually require a large amount of training images with 3D pose annotations. While it is feasible to provide 2D joint annotations for large corpora of in-the-wild images with humans, providing accurate 3D annotations to such in-the-wild...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	126,666
1908.02660	SpatialSense: An Adversarially Crowdsourced Benchmark for Spatial Relation Recognition	Understanding the spatial relations between objects in images is a surprisingly challenging task. A chair may be "behind" a person even if it appears to the left of the person in the image (depending on which way the person is facing). Two students that appear close to each other in the image may not in fact be "next t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	141,061
1302.3567	Efficient Approximations for the Marginal Likelihood of Incomplete Data Given a Bayesian Network	We discuss Bayesian methods for learning Bayesian networks when data sets are incomplete. In particular, we examine asymptotic approximations for the marginal likelihood of incomplete data given a Bayesian network. We consider the Laplace approximation and the less accurate but more efficient BIC/MDL approximation. We ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	22,033
1603.08071	Classification of Large-Scale Fundus Image Data Sets: A Cloud-Computing Framework	Large medical image data sets with high dimensionality require substantial amount of computation time for data creation and data processing. This paper presents a novel generalized method that finds optimal image-based feature sets that reduce computational time complexity while maximizing overall classification accura...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	53,712
2306.02639	Evaluating robustness of support vector machines with the Lagrangian dual approach	Adversarial examples bring a considerable security threat to support vector machines (SVMs), especially those used in safety-critical applications. Thus, robustness verification is an essential issue for SVMs, which can provide provable robustness against various kinds of adversary attacks. The evaluation results obtai...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	370,992
2404.11132	A Novel ICD Coding Method Based on Associated and Hierarchical Code Description Distillation	ICD(International Classification of Diseases) coding involves assigning ICD codes to patients visit based on their medical notes. ICD coding is a challenging multilabel text classification problem due to noisy medical document inputs. Recent advancements in automated ICD coding have enhanced performance by integrating ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	447,395
2204.07434	ERGO: Event Relational Graph Transformer for Document-level Event Causality Identification	Document-level Event Causality Identification (DECI) aims to identify causal relations between event pairs in a document. It poses a great challenge of across-sentence reasoning without clear causal indicators. In this paper, we propose a novel Event Relational Graph TransfOrmer (ERGO) framework for DECI, which improve...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	291,703
1908.07170	Endotracheal Tube Detection and Segmentation in Chest Radiographs using Synthetic Data	Chest radiographs are frequently used to verify the correct intubation of patients in the emergency room. Fast and accurate identification and localization of the endotracheal (ET) tube is critical for the patient. In this study we propose a novel automated deep learning scheme for accurate detection and segmentation o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	142,226
1803.08073	Olive Oil is Made of Olives, Baby Oil is Made for Babies: Interpreting Noun Compounds using Paraphrases in a Neural Model	Automatic interpretation of the relation between the constituents of a noun compound, e.g. olive oil (source) and baby oil (purpose) is an important task for many NLP applications. Recent approaches are typically based on either noun-compound representations or paraphrases. While the former has initially shown promisin...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	93,189
2002.08241	A Differential-form Pullback Programming Language for Higher-order Reverse-mode Automatic Differentiation	Building on the observation that reverse-mode automatic differentiation (AD) -- a generalisation of backpropagation -- can naturally be expressed as pullbacks of differential 1-forms, we design a simple higher-order programming language with a first-class differential operator, and present a reduction strategy which ex...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	164,690
2308.16705	Exploring Cross-Cultural Differences in English Hate Speech Annotations: From Dataset Construction to Analysis	Warning: this paper contains content that may be offensive or upsetting. Most hate speech datasets neglect the cultural diversity within a single language, resulting in a critical shortcoming in hate speech detection. To address this, we introduce CREHate, a CRoss-cultural English Hate speech dataset. To construct CR...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	389,084
2104.06084	On the efficiency of polar-like decoding for symmetric codes	The recently introduced polar codes constitute a breakthrough in coding theory due to their capacityachieving property. This goes hand in hand with a quasilinear construction, encoding, and successive cancellation list decoding procedures based on the Plotkin construction. The decoding algorithm can be applied with sli...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	229,958
1705.03326	Low-Density Code-Domain NOMA: Better Be Regular	A closed-form analytical expression is derived for the limiting empirical squared singular value density of a spreading (signature) matrix corresponding to sparse low-density code-domain (LDCD) non-orthogonal multiple-access (NOMA) with regular random user-resource allocation. The derivation relies on associating the s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	73,161
2011.05716	Filtered Manifold Alignment	Domain adaptation is an essential task in transfer learning to leverage data in one domain to bolster learning in another domain. In this paper, we present a new semi-supervised manifold alignment technique based on a two-step approach of projecting and filtering the source and target domains to low dimensional spaces ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	206,021
1908.00788	Deformable Medical Image Registration Using a Randomly-Initialized CNN as Regularization Prior	We present deformable unsupervised medical image registration using a randomly-initialized deep convolutional neural network (CNN) as regularization prior. Conventional registration methods predict a transformation by minimizing dissimilarities between an image pair. The minimization is usually regularized with manuall...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	140,603
2403.15011	Cell Tracking according to Biological Needs -- Strong Mitosis-aware Multi-Hypothesis Tracker with Aleatoric Uncertainty	Cell tracking and segmentation assist biologists in extracting insights from large-scale microscopy time-lapse data. Driven by local accuracy metrics, current tracking approaches often suffer from a lack of long-term consistency and the ability to reconstruct lineage trees correctly. To address this issue, we introduce...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	440,349
1207.3871	Performance Analysis of Wavelet Based MC-CDMA System with Implementation of Various Antenna Diversity Schemes	The impact of using wavelet based technique on the performance of a MC-CDMA wireless communication system has been investigated. The system under proposed study incorporates Walsh Hadamard codes to discriminate the message signal for individual user. A computer program written in Mathlab source code is developed and th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	17,514
2407.17755	Enhancing Eye Disease Diagnosis with Deep Learning and Synthetic Data Augmentation	In recent years, the focus is on improving the diagnosis of diabetic retinopathy (DR) using machine learning and deep learning technologies. Researchers have explored various approaches, including the use of high-definition medical imaging, AI-driven algorithms such as convolutional neural networks (CNNs) and generativ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	476,098

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