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
1106.3655	Bayesian multitask inverse reinforcement learning	We generalise the problem of inverse reinforcement learning to multiple tasks, from multiple demonstrations. Each one may represent one expert trying to solve a different task, or as different experts trying to solve the same task. Our main contribution is to formalise the problem as statistical preference elicitation,...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	10,898
2304.04022	A Reinforcement Learning-assisted Genetic Programming Algorithm for Team Formation Problem Considering Person-Job Matching	An efficient team is essential for the company to successfully complete new projects. To solve the team formation problem considering person-job matching (TFP-PJM), a 0-1 integer programming model is constructed, which considers both person-job matching and team members' willingness to communicate on team efficiency, w...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	357,040
1810.03961	Intelligent Reflecting Surface Enhanced Wireless Network via Joint Active and Passive Beamforming	Intelligent reflecting surface (IRS) is envisioned to be a new and revolutionizing technology for achieving spectrum and energy efficient wireless communication networks cost-effectively in the future. Specifically, an IRS consists of a large number of low-cost passive elements each reflecting the incident signal with ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	109,915
2309.04426	Advanced Computing and Related Applications Leveraging Brain-inspired Spiking Neural Networks	In the rapid evolution of next-generation brain-inspired artificial intelligence and increasingly sophisticated electromagnetic environment, the most bionic characteristics and anti-interference performance of spiking neural networks show great potential in terms of computational speed, real-time information processing...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	390,720
1412.5090	Belief as Willingness to Bet	We investigate modal logics of high probability having two unary modal operators: an operator $K$ expressing probabilistic certainty and an operator $B$ expressing probability exceeding a fixed rational threshold $c\geq\frac 12$. Identifying knowledge with the former and belief with the latter, we may think of $c$ as t...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	38,454
2407.01646	ESALE: Enhancing Code-Summary Alignment Learning for Source Code Summarization	(Source) code summarization aims to automatically generate succinct natural language summaries for given code snippets. Such summaries play a significant role in promoting developers to understand and maintain code. Inspired by neural machine translation, deep learning-based code summarization techniques widely adopt a...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	469,405
1212.3900	A Tutorial on Probabilistic Latent Semantic Analysis	In this tutorial, I will discuss the details about how Probabilistic Latent Semantic Analysis (PLSA) is formalized and how different learning algorithms are proposed to learn the model.	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	20,438
2101.01036	VIS30K: A Collection of Figures and Tables from IEEE Visualization Conference Publications	We present the VIS30K dataset, a collection of 29,689 images that represents 30 years of figures and tables from each track of the IEEE Visualization conference series (Vis, SciVis, InfoVis, VAST). VIS30K's comprehensive coverage of the scientific literature in visualization not only reflects the progress of the field ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	214,262
2310.17217	Beyond MLE: Convex Learning for Text Generation	Maximum likelihood estimation (MLE) is a statistical method used to estimate the parameters of a probability distribution that best explain the observed data. In the context of text generation, MLE is often used to train generative language models, which can then be used to generate new text. However, we argue that MLE...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	403,049
1503.04877	An Automated System for Discovering Neighborhood Patterns in Ego Networks	Generally, social network analysis has often focused on the topology of the network without considering the characteristics of individuals involved in them. Less attention is given to study the behavior of individuals, considering they are the basic entity of a graph. Given a mobile social network graph, what are good ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	41,188
1708.08557	A parameterized activation function for learning fuzzy logic operations in deep neural networks	We present a deep learning architecture for learning fuzzy logic expressions. Our model uses an innovative, parameterized, differentiable activation function that can learn a number of logical operations by gradient descent. This activation function allows a neural network to determine the relationships between its inp...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	79,654
1905.12430	Norm-based generalisation bounds for multi-class convolutional neural networks	We show generalisation error bounds for deep learning with two main improvements over the state of the art. (1) Our bounds have no explicit dependence on the number of classes except for logarithmic factors. This holds even when formulating the bounds in terms of the $L^2$-norm of the weight matrices, where previous bo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	132,768
2312.02212	Portrait Diffusion: Training-free Face Stylization with Chain-of-Painting	Face stylization refers to the transformation of a face into a specific portrait style. However, current methods require the use of example-based adaptation approaches to fine-tune pre-trained generative models so that they demand lots of time and storage space and fail to achieve detailed style transformation. This pa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	412,765
2210.00856	A forensic analysis of the Google Home: repairing compressed data without error correction	This paper provides a detailed explanation of the steps taken to extract and repair a Google Home's internal data. Starting with reverse engineering the hardware of a commercial off-the-shelf Google Home, internal data is then extracted by desoldering and dumping the flash memory. As error correction is performed by th...	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	321,030
2108.10580	Detection of Criminal Texts for the Polish State Border Guard	This paper describes research on the detection of Polish criminal texts appearing on the Internet. We carried out experiments to find the best available setup for the efficient classification of unbalanced and noisy data. The best performance was achieved when our model was fine-tuned on a pre-trained Polish-based tran...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	251,944
1602.01410	A Framework for Fast Image Deconvolution with Incomplete Observations	In image deconvolution problems, the diagonalization of the underlying operators by means of the FFT usually yields very large speedups. When there are incomplete observations (e.g., in the case of unknown boundaries), standard deconvolution techniques normally involve non-diagonalizable operators, resulting in rather ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	51,695
1706.05839	On Optimal Group Claims at Voting in a Stochastic Environment	There is a paradox in the model of social dynamics determined by voting in a stochastic environment (the ViSE model) called "pit of losses." It consists in the fact that a series of democratic decisions may systematically lead the society to the states unacceptable for all the voters. The paper examines how this parado...	false	false	false	true	false	false	false	false	false	false	true	false	false	false	true	false	false	false	75,585
2208.05863	GEM-2: Next Generation Molecular Property Prediction Network by Modeling Full-range Many-body Interactions	Molecular property prediction is a fundamental task in the drug and material industries. Physically, the properties of a molecule are determined by its own electronic structure, which is a quantum many-body system and can be exactly described by the Schr"odinger equation. Full-range many-body interactions between elect...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	312,527
2304.11275	Semantic-Aware Graph Matching Mechanism for Multi-Label Image Recognition	Multi-label image recognition aims to predict a set of labels that present in an image. The key to deal with such problem is to mine the associations between image contents and labels, and further obtain the correct assignments between images and their labels. In this paper, we treat each image as a bag of instances, a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	359,746
1208.3855	Effects of delayed immune-response in tumor immune-system interplay	Tumors constitute a wide family of diseases kinetically characterized by the co-presence of multiple spatio-temporal scales. So, tumor cells ecologically interplay with other kind of cells, e.g. endothelial cells or immune system effectors, producing and exchanging various chemical signals. As such, tumor growth is an ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	18,155
2402.01729	Contextualization Distillation from Large Language Model for Knowledge Graph Completion	While textual information significantly enhances the performance of pre-trained language models (PLMs) in knowledge graph completion (KGC), the static and noisy nature of existing corpora collected from Wikipedia articles or synsets definitions often limits the potential of PLM-based KGC models. To surmount these chall...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	426,177
2407.04621	OneRestore: A Universal Restoration Framework for Composite Degradation	In real-world scenarios, image impairments often manifest as composite degradations, presenting a complex interplay of elements such as low light, haze, rain, and snow. Despite this reality, existing restoration methods typically target isolated degradation types, thereby falling short in environments where multiple de...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	470,637
2008.12046	Inner Eye Canthus Localization for Human Body Temperature Screening	In this paper, we propose an automatic approach for localizing the inner eye canthus in thermal face images. We first coarsely detect 5 facial keypoints corresponding to the center of the eyes, the nosetip and the ears. Then we compute a sparse 2D-3D points correspondence using a 3D Morphable Face Model (3DMM). This co...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	193,472
2202.14037	Understanding Contrastive Learning Requires Incorporating Inductive Biases	Contrastive learning is a popular form of self-supervised learning that encourages augmentations (views) of the same input to have more similar representations compared to augmentations of different inputs. Recent attempts to theoretically explain the success of contrastive learning on downstream classification tasks p...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	282,828
1912.00700	ReD-CaNe: A Systematic Methodology for Resilience Analysis and Design of Capsule Networks under Approximations	Recent advances in Capsule Networks (CapsNets) have shown their superior learning capability, compared to the traditional Convolutional Neural Networks (CNNs). However, the extremely high complexity of CapsNets limits their fast deployment in real-world applications. Moreover, while the resilience of CNNs have been ext...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	155,860
1811.07146	The Impatient May Use Limited Optimism to Minimize Regret	Discounted-sum games provide a formal model for the study of reinforcement learning, where the agent is enticed to get rewards early since later rewards are discounted. When the agent interacts with the environment, she may regret her actions, realizing that a previous choice was suboptimal given the behavior of the en...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	113,687
2302.10720	Learning to Play Text-based Adventure Games with Maximum Entropy Reinforcement Learning	Text-based games are a popular testbed for language-based reinforcement learning (RL). In previous work, deep Q-learning is commonly used as the learning agent. Q-learning algorithms are challenging to apply to complex real-world domains due to, for example, their instability in training. Therefore, in this paper, we a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	346,914
2203.16280	CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis	In large-scale online services, crucial metrics, a.k.a., key performance indicators (KPIs), are monitored periodically to check their running statuses. Generally, KPIs are aggregated along multiple dimensions and derived by complex calculations among fundamental metrics from the raw data. Once abnormal KPI values are o...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	288,728
2106.00872	On the Efficacy of Adversarial Data Collection for Question Answering: Results from a Large-Scale Randomized Study	In adversarial data collection (ADC), a human workforce interacts with a model in real time, attempting to produce examples that elicit incorrect predictions. Researchers hope that models trained on these more challenging datasets will rely less on superficial patterns, and thus be less brittle. However, despite ADC's ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	238,280
2402.00295	Comparative Evaluation of Traditional and Deep Learning-Based Segmentation Methods for Spoil Pile Delineation Using UAV Images	The stability of mine dumps is contingent upon the precise arrangement of spoil piles, taking into account their geological and geotechnical attributes. Yet, on-site characterisation of individual piles poses a formidable challenge. The utilisation of image-based techniques for spoil pile characterisation, employing re...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	425,547
2403.12900	Toward Sustainable GenAI using Generation Directives for Carbon-Friendly Large Language Model Inference	The rapid advancement of Generative Artificial Intelligence (GenAI) across diverse sectors raises significant environmental concerns, notably the carbon emissions from their cloud and high performance computing (HPC) infrastructure. This paper presents Sprout, an innovative framework designed to address these concerns ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	true	439,382
1607.03189	A Framework for Estimating Long Term Driver Behavior	The authors present a cyber-physical systems study on the estimation of driver behavior in autonomous vehicles and vehicle safety systems. Extending upon previous work, the approach described is suitable for the long term estimation and tracking of autonomous vehicle behavior. The proposed system makes use of a previou...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	58,466
2305.10329	G-Adapter: Towards Structure-Aware Parameter-Efficient Transfer Learning for Graph Transformer Networks	It has become a popular paradigm to transfer the knowledge of large-scale pre-trained models to various downstream tasks via fine-tuning the entire model parameters. However, with the growth of model scale and the rising number of downstream tasks, this paradigm inevitably meets the challenges in terms of computation c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	365,005
2109.04872	Negative Sample Matters: A Renaissance of Metric Learning for Temporal Grounding	Temporal grounding aims to localize a video moment which is semantically aligned with a given natural language query. Existing methods typically apply a detection or regression pipeline on the fused representation with the research focus on designing complicated prediction heads or fusion strategies. Instead, from a pe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	254,574
2403.18327	$\forall$uto$\exists$val: Autonomous Assessment of LLMs in Formal Synthesis and Interpretation Tasks	This paper presents $\forall$uto$\exists$val, a new approach for scaling LLM assessment in translating formal syntax -- such as first-order logic, regular expressions, etc -- to natural language (interpretation) or vice versa (compilation), thereby facilitating their use in applications such as generating/explaining lo...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	441,885
2203.10507	Soft-CP: A Credible and Effective Data Augmentation for Semantic Segmentation of Medical Lesions	The medical datasets are usually faced with the problem of scarcity and data imbalance. Moreover, annotating large datasets for semantic segmentation of medical lesions is domain-knowledge and time-consuming. In this paper, we propose a new object-blend method(short in soft-CP) that combines the Copy-Paste augmentation...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	286,570
2501.07358	Deep Generative Clustering with VAEs and Expectation-Maximization	We propose a novel deep clustering method that integrates Variational Autoencoders (VAEs) into the Expectation-Maximization (EM) framework. Our approach models the probability distribution of each cluster with a VAE and alternates between updating model parameters by maximizing the Evidence Lower Bound (ELBO) of the lo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	524,368
1907.09615	Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems	Machine learning based decision making systems are increasingly affecting humans. An individual can suffer an undesirable outcome under such decision making systems (e.g. denied credit) irrespective of whether the decision is fair or accurate. Individual recourse pertains to the problem of providing an actionable set o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	139,417
2407.06513	Computer vision tasks for intelligent aerospace missions: An overview	Computer vision tasks are crucial for aerospace missions as they help spacecraft to understand and interpret the space environment, such as estimating position and orientation, reconstructing 3D models, and recognizing objects, which have been extensively studied to successfully carry out the missions. However, traditi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	471,421
2409.01871	Real-Time Indoor Object Detection based on hybrid CNN-Transformer Approach	Real-time object detection in indoor settings is a challenging area of computer vision, faced with unique obstacles such as variable lighting and complex backgrounds. This field holds significant potential to revolutionize applications like augmented and mixed realities by enabling more seamless interactions between di...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	485,490
2412.05345	Osteoporosis Prediction from Hand X-ray Images Using Segmentation-for-Classification and Self-Supervised Learning	Osteoporosis is a widespread and chronic metabolic bone disease that often remains undiagnosed and untreated due to limited access to bone mineral density (BMD) tests like Dual-energy X-ray absorptiometry (DXA). In response to this challenge, current advancements are pivoting towards detecting osteoporosis by examining...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	514,800
1805.02912	The Complexity of Limited Belief Reasoning -- The Quantifier-Free Case	The classical view of epistemic logic is that an agent knows all the logical consequences of their knowledge base. This assumption of logical omniscience is often unrealistic and makes reasoning computationally intractable. One approach to avoid logical omniscience is to limit reasoning to a certain belief level, which...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	96,947
2010.04676	A Clustering-Based Method for Automatic Educational Video Recommendation Using Deep Face-Features of Lecturers	Discovering and accessing specific content within educational video bases is a challenging task, mainly because of the abundance of video content and its diversity. Recommender systems are often used to enhance the ability to find and select content. But, recommendation mechanisms, especially those based on textual inf...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	199,828
2311.08278	ARTEMIS: Using GANs with Multiple Discriminators to Generate Art	We propose a novel method for generating abstract art. First an autoencoder is trained to encode and decode the style representations of images, which are extracted from source images with a pretrained VGG network. Then, the decoder component of the autoencoder is extracted and used as a generator in a GAN. The generat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	407,658
1901.11095	Saliency detection for seismic applications using multi-dimensional spectral projections and directional comparisons	In this paper, we propose a novel approach for saliency detection for seismic applications using 3D-FFT local spectra and multi-dimensional plane projections. We develop a projection scheme by dividing a 3D-FFT local spectrum of a data volume into three distinct components, each depicting changes along a different dime...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	120,165
2009.07923	Hiding in Plain Sight: A Measurement and Analysis of Kids' Exposure to Malicious URLs on YouTube	The Internet has become an essential part of children's and adolescents' daily life. Social media platforms are used as educational and entertainment resources on daily bases by young users, leading enormous efforts to ensure their safety when interacting with various social media platforms. In this paper, we investiga...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	196,075
2109.02171	Right Ventricular Segmentation from Short- and Long-Axis MRIs via Information Transition	Right ventricular (RV) segmentation from magnetic resonance imaging (MRI) is a crucial step for cardiac morphology and function analysis. However, automatic RV segmentation from MRI is still challenging, mainly due to the heterogeneous intensity, the complex variable shapes, and the unclear RV boundary. Moreover, curre...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	253,658
2410.06124	Learning AND-OR Templates for Professional Photograph Parsing and Guidance	Since the development of photography art, many so-called "templates" have been formed, namely visual styles summarized from a series of themed and stylized photography works. In this paper, we propose to analysize and and summarize these 'templates' in photography by learning composite templates of photography images. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	496,060
2112.00557	3D Reconstruction Using a Linear Laser Scanner and a Camera	With the rapid development of computer graphics and vision, several three-dimensional (3D) reconstruction techniques have been proposed and used to obtain the 3D representation of objects in the form of point cloud models, mesh models, and geometric models. The cost of 3D reconstruction is declining due to the maturing...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	269,171
2103.03114	Self-supervised Geometric Perception	We present self-supervised geometric perception (SGP), the first general framework to learn a feature descriptor for correspondence matching without any ground-truth geometric model labels (e.g., camera poses, rigid transformations). Our first contribution is to formulate geometric perception as an optimization problem...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	223,179
2409.06904	Applied Federated Model Personalisation in the Industrial Domain: A Comparative Study	The time-consuming nature of training and deploying complicated Machine and Deep Learning (DL) models for a variety of applications continues to pose significant challenges in the field of Machine Learning (ML). These challenges are particularly pronounced in the federated domain, where optimizing models for individual...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	487,314
2203.01304	Supervised Hebbian Learning	In neural network's Literature, Hebbian learning traditionally refers to the procedure by which the Hopfield model and its generalizations store archetypes (i.e., definite patterns that are experienced just once to form the synaptic matrix). However, the term "Learning" in Machine Learning refers to the ability of the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	283,331
2309.13292	Beyond Fairness: Age-Harmless Parkinson's Detection via Voice	Parkinson's disease (PD), a neurodegenerative disorder, often manifests as speech and voice dysfunction. While utilizing voice data for PD detection has great potential in clinical applications, the widely used deep learning models currently have fairness issues regarding different ages of onset. These deep models perf...	false	false	true	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	394,144
2408.06261	Open-Source Molecular Processing Pipeline for Generating Molecules	Generative models for molecules have shown considerable promise for use in computational chemistry, but remain difficult to use for non-experts. For this reason, we introduce open-source infrastructure for easily building generative molecular models into the widely used DeepChem [Ramsundar et al., 2019] library with th...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	480,133
2212.02752	An Index Policy for Minimizing the Uncertainty-of-Information of Markov Sources	This paper focuses on the information freshness of finite-state Markov sources, using the uncertainty of information (UoI) as the performance metric. Measured by Shannon's entropy, UoI can capture not only the transition dynamics of the Markov source but also the different evolutions of information quality caused by th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	334,872
1906.00499	Budgeted Policy Learning for Task-Oriented Dialogue Systems	This paper presents a new approach that extends Deep Dyna-Q (DDQ) by incorporating a Budget-Conscious Scheduling (BCS) to best utilize a fixed, small amount of user interactions (budget) for learning task-oriented dialogue agents. BCS consists of (1) a Poisson-based global scheduler to allocate budget over different st...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	true	false	false	133,411
2406.02616	Adaptive Layer Splitting for Wireless LLM Inference in Edge Computing: A Model-Based Reinforcement Learning Approach	Optimizing the deployment of large language models (LLMs) in edge computing environments is critical for enhancing privacy and computational efficiency. Toward efficient wireless LLM inference in edge computing, this study comprehensively analyzes the impact of different splitting points in mainstream open-source LLMs....	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	460,868
2306.14357	PolicyClusterGCN: Identifying Efficient Clusters for Training Graph Convolutional Networks	Graph convolutional networks (GCNs) have achieved huge success in several machine learning (ML) tasks on graph-structured data. Recently, several sampling techniques have been proposed for the efficient training of GCNs and to improve the performance of GCNs on ML tasks. Specifically, the subgraph-based sampling approa...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	375,653
2012.05999	An IoT Framework for Heart Disease Prediction based on MDCNN Classifier	Nowadays, heart disease is the leading cause of death worldwide. Predicting heart disease is a complex task since it requires experience along with advanced knowledge. Internet of Things (IoT) technology has lately been adopted in healthcare systems to collect sensor values for heart disease diagnosis and prediction. M...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	210,951
2106.10662	FedXGBoost: Privacy-Preserving XGBoost for Federated Learning	Federated learning is the distributed machine learning framework that enables collaborative training across multiple parties while ensuring data privacy. Practical adaptation of XGBoost, the state-of-the-art tree boosting framework, to federated learning remains limited due to high cost incurred by conventional privacy...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	242,104
2106.11596	Multi-layered Semantic Representation Network for Multi-label Image Classification	Multi-label image classification (MLIC) is a fundamental and practical task, which aims to assign multiple possible labels to an image. In recent years, many deep convolutional neural network (CNN) based approaches have been proposed which model label correlations to discover semantics of labels and learn semantic repr...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	242,459
1404.6813	Diffusion LMS over Multitask Networks	The diffusion LMS algorithm has been extensively studied in recent years. This efficient strategy allows to address distributed optimization problems over networks in the case where nodes have to collaboratively estimate a single parameter vector. Problems of this type are referred to as single-task problems. Neverthel...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	32,634
1911.07524	The Devil is in the Details: Delving into Unbiased Data Processing for Human Pose Estimation	Being a fundamental component in training and inference, data processing has not been systematically considered in human pose estimation community, to the best of our knowledge. In this paper, we focus on this problem and find that the devil of human pose estimation evolution is in the biased data processing. Specifica...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	153,883
2003.11154	A Systematic Evaluation: Fine-Grained CNN vs. Traditional CNN Classifiers	To make the best use of the underlying minute and subtle differences, fine-grained classifiers collect information about inter-class variations. The task is very challenging due to the small differences between the colors, viewpoint, and structure in the same class entities. The classification becomes more difficult du...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	169,529
2312.05966	Fake It Till Make It: Federated Learning with Consensus-Oriented Generation	In federated learning (FL), data heterogeneity is one key bottleneck that causes model divergence and limits performance. Addressing this, existing methods often regard data heterogeneity as an inherent property and propose to mitigate its adverse effects by correcting models. In this paper, we seek to break this inher...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	414,316
2010.06392	Projection techniques to update the truncated SVD of evolving matrices	This paper considers the problem of updating the rank-k truncated Singular Value Decomposition (SVD) of matrices subject to the addition of new rows and/or columns over time. Such matrix problems represent an important computational kernel in applications such as Latent Semantic Indexing and Recommender Systems. Noneth...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	200,469
2402.12415	Vehicle-group-based Crash Risk Prediction and Interpretation on Highways	Previous studies in predicting crash risks primarily associated the number or likelihood of crashes on a road segment with traffic parameters or geometric characteristics, usually neglecting the impact of vehicles' continuous movement and interactions with nearby vehicles. Recent technology advances, such as Connected ...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	430,843
1801.04953	Fast Uplink Grant for Machine Type Communications: Challenges and Opportunities	The notion of a fast uplink grant is emerging as a promising solution for enabling massive machine type communications (MTCs) in the Internet of Things over cellular networks. By using the fast uplink grant, machine type devices (MTD) will no longer require random access (RA) channels to send scheduling requests. Inste...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	88,364
2311.06680	Extremum Seeking for Stefan PDE with Moving Boundary	This paper presents the design and analysis of the extremum seeking for static maps with input passed through a partial differential equation (PDE) of the diffusion type defined on a time-varying spatial domain whose boundary position is governed by an ordinary differential equation (ODE). This is the first effort to p...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	407,030
2305.09786	A Comparative Study of GAN-Generated Handwriting Images and MNIST Images using t-SNE Visualization	The quality of GAN-generated images on the MNIST dataset was explored in this paper by comparing them to the original images using t-distributed stochastic neighbor embedding (t- SNE) visualization. A GAN was trained with the dataset to generate images and the result of generating all synthetic images, the correspondin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	364,771
1811.04516	Agent Embeddings: A Latent Representation for Pole-Balancing Networks	We show that it is possible to reduce a high-dimensional object like a neural network agent into a low-dimensional vector representation with semantic meaning that we call agent embeddings, akin to word or face embeddings. This can be done by collecting examples of existing networks, vectorizing their weights, and then...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	113,109
1411.2169	The Sum-Product Algorithm for Degree-2 Check Nodes and Trapping Sets	The sum-product algorithm for decoding of binary codes is analyzed for bipartite graphs in which the check nodes all have degree $2$. The algorithm simplifies dramatically and may be expressed using linear algebra. Exact results about the convergence of the algorithm are derived and applied to trapping sets.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	37,392
1407.1809	Decomposed Interval Type-2 Fuzzy Systems with Application to Inverted Pendulum	This article introduces the idea of decomposition of interval Type-2 fuzzy logic system into two parallel type-1 fuzzy systems. This decomposition avoids the problems associated with type-reduction techniques normally needed in type-2 fuzzy systems. Next, we compare the performance of a decomposed type-2 controller to ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	34,474
2202.04238	Parametric t-Stochastic Neighbor Embedding With Quantum Neural Network	t-Stochastic Neighbor Embedding (t-SNE) is a non-parametric data visualization method in classical machine learning. It maps the data from the high-dimensional space into a low-dimensional space, especially a two-dimensional plane, while maintaining the relationship, or similarities, between the surrounding points. In ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	279,498
2210.07497	Distributed Emergency Frequency Control Considering Transient Stability Constraints in Multi-Infeed Hybrid AC-DC System	Due to possible emergency faults and frequency regulation reserve shortage in the multi-infeed hybrid AC-DC (MIDC) system, the emergency frequency control (EFC) with LCC-HVDC systems participating is important for system frequency stability. Nevertheless, the existing decentralized EFC strategies cannot guarantee the t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	323,740
2308.13727	Dynamic Mode Decomposition for data-driven analysis and reduced-order modelling of ExB plasmas: II. dynamics forecasting	In part I of the article, we demonstrated that a variant of the Dynamic Mode Decomposition (DMD) algorithm based on variable projection optimization, called Optimized DMD (OPT-DMD), enables a robust identification of the dominant spatiotemporally coherent modes underlying the data across various test cases representing...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	388,027
2308.13772	Boosting Residual Networks with Group Knowledge	Recent research understands the residual networks from a new perspective of the implicit ensemble model. From this view, previous methods such as stochastic depth and stimulative training have further improved the performance of the residual network by sampling and training of its subnets. However, they both use the sa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	388,047
2008.09236	Spatial Language Representation with Multi-Level Geocoding	We present a multi-level geocoding model (MLG) that learns to associate texts to geographic locations. The Earth's surface is represented using space-filling curves that decompose the sphere into a hierarchy of similarly sized, non-overlapping cells. MLG balances generalization and accuracy by combining losses across m...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	192,647
1804.05482	Binary Matrix Factorization via Dictionary Learning	Matrix factorization is a key tool in data analysis; its applications include recommender systems, correlation analysis, signal processing, among others. Binary matrices are a particular case which has received significant attention for over thirty years, especially within the field of data mining. Dictionary learning ...	false	false	false	false	false	true	true	false	false	true	false	true	false	false	false	false	false	false	95,087
1903.11461	Tracking the Consumption Junction: Temporal Dependencies between Articles and Advertisements in Dutch Newspapers	Historians have regularly debated whether advertisements can be used as a viable source to study the past. Their main concern centered on the question of agency. Were advertisements a reflection of historical events and societal debates, or were ad makers instrumental in shaping society and the ways people interacted w...	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	125,523
2007.10539	Verification and Parameter Synthesis for Real-Time Programs using Refinement of Trace Abstraction	We address the safety verification and synthesis problems for real-time systems. We introduce real-time programs that are made of instructions that can perform assignments to discrete and real-valued variables. They are general enough to capture interesting classes of timed systems such as timed automata, stopwatch aut...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	188,299
2202.11064	Occupation similarity through bipartite graphs	Similarity between occupations is a crucial piece of information when making career decisions. However, the notion of a single and unified occupation similarity measure is more of a limitation than an asset. The goal of the study is to assess multiple explainable occupation similarity measures that can provide differen...	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	false	281,758
2206.04449	Segmentation Enhanced Lameness Detection in Dairy Cows from RGB and Depth Video	Cow lameness is a severe condition that affects the life cycle and life quality of dairy cows and results in considerable economic losses. Early lameness detection helps farmers address illnesses early and avoid negative effects caused by the degeneration of cows' condition. We collected a dataset of short clips of cow...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	301,632
2501.01648	Dual Mutual Learning Network with Global-local Awareness for RGB-D Salient Object Detection	RGB-D salient object detection (SOD), aiming to highlight prominent regions of a given scene by jointly modeling RGB and depth information, is one of the challenging pixel-level prediction tasks. Recently, the dual-attention mechanism has been devoted to this area due to its ability to strengthen the detection process....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	522,152
2404.09384	Tasks People Prompt: A Taxonomy of LLM Downstream Tasks in Software Verification and Falsification Approaches	Prompting has become one of the main approaches to leverage emergent capabilities of Large Language Models [Brown et al. NeurIPS 2020, Wei et al. TMLR 2022, Wei et al. NeurIPS 2022]. Recently, researchers and practitioners have been "playing" with prompts (e.g., In-Context Learning) to see how to make the most of pre-t...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	true	446,647
2305.03111	Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs	Text-to-SQL parsing, which aims at converting natural language instructions into executable SQLs, has gained increasing attention in recent years. In particular, Codex and ChatGPT have shown impressive results in this task. However, most of the prevalent benchmarks, i.e., Spider, and WikiSQL, focus on database schema w...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	362,272
2206.14658	Cut Inner Layers: A Structured Pruning Strategy for Efficient U-Net GANs	Pruning effectively compresses overparameterized models. Despite the success of pruning methods for discriminative models, applying them for generative models has been relatively rarely approached. This study conducts structured pruning on U-Net generators of conditional GANs. A per-layer sensitivity analysis confirms ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	305,358
2207.05456	TransFA: Transformer-based Representation for Face Attribute Evaluation	Face attribute evaluation plays an important role in video surveillance and face analysis. Although methods based on convolution neural networks have made great progress, they inevitably only deal with one local neighborhood with convolutions at a time. Besides, existing methods mostly regard face attribute evaluation ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	307,544
2311.05808	Scale-MIA: A Scalable Model Inversion Attack against Secure Federated Learning via Latent Space Reconstruction	Federated learning is known for its capability to safeguard the participants' data privacy. However, recently emerged model inversion attacks (MIAs) have shown that a malicious parameter server can reconstruct individual users' local data samples from model updates. The state-of-the-art attacks either rely on computati...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	406,712
2407.02371	OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation	Text-to-video (T2V) generation has recently garnered significant attention thanks to the large multi-modality model Sora. However, T2V generation still faces two important challenges: 1) Lacking a precise open sourced high-quality dataset. The previous popular video datasets, e.g. WebVid-10M and Panda-70M, are either w...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	469,700
2412.18905	External Bias and Opinion Clustering in Cooperative Networks	In this work, we consider a group of n agents which interact with each other in a cooperative framework. A Laplacian-based model is proposed to govern the evolution of opinions in the group when the agents are subjected to external biases like agents' traits, news, etc. The objective of the paper is to design a control...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	520,628
1807.06288	PointSeg: Real-Time Semantic Segmentation Based on 3D LiDAR Point Cloud	In this paper, we propose PointSeg, a real-time end-to-end semantic segmentation method for road-objects based on spherical images. We take the spherical image, which is transformed from the 3D LiDAR point clouds, as input of the convolutional neural networks (CNNs) to predict the point-wise semantic map. To make Point...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	103,096
2306.06643	Detection and Recovery of Hidden Submatrices	In this paper, we study the problems of detection and recovery of hidden submatrices with elevated means inside a large Gaussian random matrix. We consider two different structures for the planted submatrices. In the first model, the planted matrices are disjoint, and their row and column indices can be arbitrary. Insp...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	372,696
1904.02580	Online Convex Matrix Factorization with Representative Regions	Matrix factorization (MF) is a versatile learning method that has found wide applications in various data-driven disciplines. Still, many MF algorithms do not adequately scale with the size of available datasets and/or lack interpretability. To improve the computational efficiency of the method, an online (streaming) M...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	126,465
1810.10093	Structured Domain Randomization: Bridging the Reality Gap by Context-Aware Synthetic Data	We present structured domain randomization (SDR), a variant of domain randomization (DR) that takes into account the structure and context of the scene. In contrast to DR, which places objects and distractors randomly according to a uniform probability distribution, SDR places objects and distractors randomly according...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	111,194
2502.06911	Foundation Models for Anomaly Detection: Vision and Challenges	As data continues to grow in volume and complexity across domains such as finance, manufacturing, and healthcare, effective anomaly detection is essential for identifying irregular patterns that may signal critical issues. Recently, foundation models (FMs) have emerged as a powerful tool for advancing anomaly detection...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	532,343
2403.18853	Spatio-seasonal risk assessment of upward lightning at tall objects using meteorological reanalysis data	This study investigates lightning at tall objects and evaluates the risk of upward lightning (UL) over the eastern Alps and its surrounding areas. While uncommon, UL poses a threat, especially to wind turbines, as the long-duration current of UL can cause significant damage. Current risk assessment methods overlook the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	442,107
1210.4846	Variational Dual-Tree Framework for Large-Scale Transition Matrix Approximation	In recent years, non-parametric methods utilizing random walks on graphs have been used to solve a wide range of machine learning problems, but in their simplest form they do not scale well due to the quadratic complexity. In this paper, a new dual-tree based variational approach for approximating the transition matrix...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	19,174
2006.10325	When OT meets MoM: Robust estimation of Wasserstein Distance	Issued from Optimal Transport, the Wasserstein distance has gained importance in Machine Learning due to its appealing geometrical properties and the increasing availability of efficient approximations. In this work, we consider the problem of estimating the Wasserstein distance between two probability distributions wh...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	182,847
2312.00886	Nash Learning from Human Feedback	Reinforcement learning from human feedback (RLHF) has emerged as the main paradigm for aligning large language models (LLMs) with human preferences. Typically, RLHF involves the initial step of learning a reward model from human feedback, often expressed as preferences between pairs of text generations produced by a pr...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	true	412,224

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