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
2101.00401	Border basis computation with gradient-weighted normalization	Normalization of polynomials plays a vital role in the approximate basis computation of vanishing ideals. Coefficient normalization, which normalizes a polynomial with its coefficient norm, is the most common method in computer algebra. This study proposes the gradient-weighted normalization method for the approximate ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	214,075
2412.08680	Distinguishing Scams and Fraud with Ensemble Learning	Users increasingly query LLM-enabled web chatbots for help with scam defense. The Consumer Financial Protection Bureau's complaints database is a rich data source for evaluating LLM performance on user scam queries, but currently the corpus does not distinguish between scam and non-scam fraud. We developed an LLM ensem...	true	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	516,198
2006.00894	Reducing DNN Labelling Cost using Surprise Adequacy: An Industrial Case Study for Autonomous Driving	Deep Neural Networks (DNNs) are rapidly being adopted by the automotive industry, due to their impressive performance in tasks that are essential for autonomous driving. Object segmentation is one such task: its aim is to precisely locate boundaries of objects and classify the identified objects, helping autonomous car...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	179,605
2502.05491	Lie-algebra Adaptive Tracking Control for Rigid Body Dynamics	Adaptive tracking control for rigid body dynamics is of critical importance in control and robotics, particularly for addressing uncertainties or variations in system model parameters. However, most existing adaptive control methods are designed for systems with states in vector spaces, often neglecting the manifold co...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	531,638
1803.02914	Translating Questions into Answers using DBPedia n-triples	In this paper we present a question answering system using a neural network to interpret questions learned from the DBpedia repository. We train a sequence-to-sequence neural network model with n-triples extracted from the DBpedia Infobox Properties. Since these properties do not represent the natural language, we furt...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	92,154
2304.07646	Herder Ants: Ant Colony Optimization with Aphids for Discrete Event-Triggered Dynamic Optimization Problems	Currently available dynamic optimization strategies for Ant Colony Optimization (ACO) algorithm offer a trade-off of slower algorithm convergence or significant penalty to solution quality after each dynamic change occurs. This paper proposes a discrete dynamic optimization strategy called Ant Colony Optimization (ACO)...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	358,423
2107.14549	Evaluating the COVID-19 Identification ResNet (CIdeR) on the INTERSPEECH COVID-19 from Audio Challenges	We report on cross-running the recent COVID-19 Identification ResNet (CIdeR) on the two Interspeech 2021 COVID-19 diagnosis from cough and speech audio challenges: ComParE and DiCOVA. CIdeR is an end-to-end deep learning neural network originally designed to classify whether an individual is COVID-positive or COVID-neg...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	248,492
1802.07417	Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms	Mixture-of-Experts (MoE) is a widely popular model for ensemble learning and is a basic building block of highly successful modern neural networks as well as a component in Gated Recurrent Units (GRU) and Attention networks. However, present algorithms for learning MoE including the EM algorithm, and gradient descent a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	90,888
2411.15844	Unveiling the Superior Paradigm: A Comparative Study of Source-Free Domain Adaptation and Unsupervised Domain Adaptation	In domain adaptation, there are two popular paradigms: Unsupervised Domain Adaptation (UDA), which aligns distributions using source data, and Source-Free Domain Adaptation (SFDA), which leverages pre-trained source models without accessing source data. Evaluating the superiority of UDA versus SFDA is an open and timel...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	510,798
2406.13626	Fine-Tuning Gemma-7B for Enhanced Sentiment Analysis of Financial News Headlines	In this study, we explore the application of sentiment analysis on financial news headlines to understand investor sentiment. By leveraging Natural Language Processing (NLP) and Large Language Models (LLM), we analyze sentiment from the perspective of retail investors. The FinancialPhraseBank dataset, which contains ca...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	465,924
2406.11463	Just How Flexible are Neural Networks in Practice?	It is widely believed that a neural network can fit a training set containing at least as many samples as it has parameters, underpinning notions of overparameterized and underparameterized models. In practice, however, we only find solutions accessible via our training procedure, including the optimizer and regularize...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	464,904
1912.03437	Early Prediction for Merged vs Abandoned Code Changes in Modern Code Reviews	The modern code review process is an integral part of the current software development practice. Considerable effort is given here to inspect code changes, find defects, suggest an improvement, and address the suggestions of the reviewers. In a code review process, usually, several iterations take place where an author...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	156,587
2305.18969	MS-DETR: Natural Language Video Localization with Sampling Moment-Moment Interaction	Given a query, the task of Natural Language Video Localization (NLVL) is to localize a temporal moment in an untrimmed video that semantically matches the query. In this paper, we adopt a proposal-based solution that generates proposals (i.e., candidate moments) and then select the best matching proposal. On top of mod...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	369,322
2310.20030	Scaling Riemannian Diffusion Models	Riemannian diffusion models draw inspiration from standard Euclidean space diffusion models to learn distributions on general manifolds. Unfortunately, the additional geometric complexity renders the diffusion transition term inexpressible in closed form, so prior methods resort to imprecise approximations of the score...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	404,220
2308.15870	Deontic Paradoxes in ASP with Weak Constraints	The rise of powerful AI technology for a range of applications that are sensitive to legal, social, and ethical norms demands decision-making support in presence of norms and regulations. Normative reasoning is the realm of deontic logics, that are challenged by well-known benchmark problems (deontic paradoxes), and la...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	true	false	false	true	388,826
2312.05248	Topology-Based Reconstruction Prevention for Decentralised Learning	Decentralised learning has recently gained traction as an alternative to federated learning in which both data and coordination are distributed. To preserve the confidentiality of users' data, decentralised learning relies on differential privacy, multi-party computation, or both. However, running multiple privacy-pres...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	413,997
1912.02105	Influence Maximization for Social Good: Use of Social Networks in Low Resource Communities	This thesis proposal makes the following technical contributions: (i) we provide a definition of the Dynamic Influence Maximization Under Uncertainty (or DIME) problem, which models the problem faced by homeless shelters accurately; (ii) we propose a novel Partially Observable Markov Decision Process (POMDP) model for ...	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	false	156,259
2312.06706	UNeR3D: Versatile and Scalable 3D RGB Point Cloud Generation from 2D Images in Unsupervised Reconstruction	In the realm of 3D reconstruction from 2D images, a persisting challenge is to achieve high-precision reconstructions devoid of 3D Ground Truth data reliance. We present UNeR3D, a pioneering unsupervised methodology that sets a new standard for generating detailed 3D reconstructions solely from 2D views. Our model sign...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	414,643
2409.01092	Two-Timescale Synchronization and Migration for Digital Twin Networks: A Multi-Agent Deep Reinforcement Learning Approach	Digital twins (DTs) have emerged as a promising enabler for representing the real-time states of physical worlds and realizing self-sustaining systems. In practice, DTs of physical devices, such as mobile users (MUs), are commonly deployed in multi-access edge computing (MEC) networks for the sake of reducing latency. ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	485,208
1812.10033	MMFNet: A Multi-modality MRI Fusion Network for Segmentation of Nasopharyngeal Carcinoma	Segmentation of nasopharyngeal carcinoma (NPC) from Magnetic Resonance Images (MRI) is a crucial prerequisite for NPC radiotherapy. However, manually segmenting of NPC is time-consuming and labor-intensive. Additionally, single-modality MRI generally cannot provide enough information for its accurate delineation. There...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	117,278
1602.04450	Bayesian Optimization with Safety Constraints: Safe and Automatic Parameter Tuning in Robotics	Robotic algorithms typically depend on various parameters, the choice of which significantly affects the robot's performance. While an initial guess for the parameters may be obtained from dynamic models of the robot, parameters are usually tuned manually on the real system to achieve the best performance. Optimization...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	52,136
2012.12599	Dynamics of a Stratified Population of Optimum Seeking Agents on a Network -- Part I: Modeling and Convergence Analysis	In this work, we consider a population composed of a continuum of agents that seek to maximize a payoff function by moving on a network. The nodes in the network may represent physical locations or abstract choices. The population is stratified and hence agents opting for the same choice may not get the same payoff. In...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	212,991
1107.2781	Face Recognition using Curvelet Transform	Face recognition has been studied extensively for more than 20 years now. Since the beginning of 90s the subject has became a major issue. This technology is used in many important real-world applications, such as video surveillance, smart cards, database security, internet and intranet access. This report reviews rece...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	11,290
2011.01436	Developing High Quality Training Samples for Deep Learning Based Local Climate Zone Classification in Korea	Two out of three people will be living in urban areas by 2050, as projected by the United Nations, emphasizing the need for sustainable urban development and monitoring. Common urban footprint data provide high-resolution city extents but lack essential information on the distribution, pattern, and characteristics. The...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	204,581
2408.02253	Advancing Post-OCR Correction: A Comparative Study of Synthetic Data	This paper explores the application of synthetic data in the post-OCR domain on multiple fronts by conducting experiments to assess the impact of data volume, augmentation, and synthetic data generation methods on model performance. Furthermore, we introduce a novel algorithm that leverages computer vision feature dete...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	478,564
2407.11236	Toward RAPS: the Robot Autonomy Perception Scale	Human-robot interactions can change significantly depending on how autonomous humans perceive a robot to be. Yet, while previous work in the HRI community measured perceptions of human autonomy, there is little work on measuring perceptions of robot autonomy. In this paper, we present our progress toward the creation o...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	473,354
2407.19503	Discrete Spectrum Analysis of Vector OFDM Signals	Vector OFDM (VOFDM) is equivalent to OTFS and is good for time-varying channels. However, due to its vector form, its signal spectrum is not as clear as that of the conventional OFDM. In this paper, we study the discrete spectrum of discrete VOFDM signals. We obtain a linear relationship between a vector of information...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	476,814
2308.04082	Application-Oriented Benchmarking of Quantum Generative Learning Using QUARK	Benchmarking of quantum machine learning (QML) algorithms is challenging due to the complexity and variability of QML systems, e.g., regarding model ansatzes, data sets, training techniques, and hyper-parameters selection. The QUantum computing Application benchmaRK (QUARK) framework simplifies and standardizes benchma...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	384,287
2111.04475	Identifying the Leading Factors of Significant Weight Gains Using a New Rule Discovery Method	Overweight and obesity remain a major global public health concern and identifying the individualized patterns that increase the risk of future weight gains has a crucial role in preventing obesity and numerous sub-sequent diseases associated with obesity. In this work, we use a rule discovery method to study this prob...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	265,496
1806.00600	Semantic-Aware Generative Adversarial Nets for Unsupervised Domain Adaptation in Chest X-ray Segmentation	In spite of the compelling achievements that deep neural networks (DNNs) have made in medical image computing, these deep models often suffer from degraded performance when being applied to new test datasets with domain shift. In this paper, we present a novel unsupervised domain adaptation approach for segmentation ta...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	99,345
2204.10850	Control-NeRF: Editable Feature Volumes for Scene Rendering and Manipulation	We present a novel method for performing flexible, 3D-aware image content manipulation while enabling high-quality novel view synthesis. While NeRF-based approaches are effective for novel view synthesis, such models memorize the radiance for every point in a scene within a neural network. Since these models are scene-...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	292,940
2206.10996	ProtoCLIP: Prototypical Contrastive Language Image Pretraining	Contrastive Language Image Pretraining (CLIP) has received widespread attention, since its learned representations can be transferred well to various downstream tasks. During the training process of the CLIP model, the InfoNCE objective aligns positive image-text pairs and separates negative ones. We show an underlying...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	304,114
2411.02126	Unsupervised detection of semantic correlations in big data	In real-world data, information is stored in extremely large feature vectors. These variables are typically correlated due to complex interactions involving many features simultaneously. Such correlations qualitatively correspond to semantic roles and are naturally recognized by both the human brain and artificial neur...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	505,365
2208.14552	Optimal possibly nonlinear 3-PIR codes of small size	First, we state a generalization of the minimum-distance bound for PIR codes. Then we describe a construction for linear PIR codes using packing designs and use it to construct some new 5-PIR codes. Finally, we show that no encoder (linear or nonlinear) for the binary $r$-th order Hamming code produces a 3-PIR code exc...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	315,347
1001.1221	Boosting k-NN for categorization of natural scenes	The k-nearest neighbors (k-NN) classification rule has proven extremely successful in countless many computer vision applications. For example, image categorization often relies on uniform voting among the nearest prototypes in the space of descriptors. In spite of its good properties, the classic k-NN rule suffers fro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	5,293
2004.10908	Taskflow: A Lightweight Parallel and Heterogeneous Task Graph Computing System	Taskflow aims to streamline the building of parallel and heterogeneous applications using a lightweight task graph-based approach. Taskflow introduces an expressive task graph programming model to assist developers in the implementation of parallel and heterogeneous decomposition strategies on a heterogeneous computing...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	173,753
2310.19642	Consistent Query Answering for Primary Keys on Rooted Tree Queries	We study the data complexity of consistent query answering (CQA) on databases that may violate the primary key constraints. A repair is a maximal subset of the database satisfying the primary key constraints. For a Boolean query q, the problem CERTAINTY(q) takes a database as input, and asks whether or not each repair ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	404,067
2201.00785	Implicit Autoencoder for Point-Cloud Self-Supervised Representation Learning	This paper advocates the use of implicit surface representation in autoencoder-based self-supervised 3D representation learning. The most popular and accessible 3D representation, i.e., point clouds, involves discrete samples of the underlying continuous 3D surface. This discretization process introduces sampling varia...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	274,068
2005.02762	Recurrent neural networks and Koopman-based frameworks for temporal predictions in a low-order model of turbulence	The capabilities of recurrent neural networks and Koopman-based frameworks are assessed in the prediction of temporal dynamics of the low-order model of near-wall turbulence by Moehlis et al. (New J. Phys. 6, 56, 2004). Our results show that it is possible to obtain excellent reproductions of the long-term statistics a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	175,965
1412.1732	Statistical models and regularization strategies in statistical image reconstruction of low-dose X-ray CT: a survey	Statistical image reconstruction (SIR) methods have shown potential to substantially improve the image quality of low-dose X-ray computed tomography (CT) as compared to the conventional filtered back-projection (FBP) method for various clinical tasks. According to the maximum a posterior (MAP) estimation, the SIR metho...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	38,131
2104.06410	Reward Shaping with Subgoals for Social Navigation	Social navigation has been gaining attentions with the growth in machine intelligence. Since reinforcement learning can select an action in the prediction phase at a low computational cost, it has been formulated in a social navigation tasks. However, reinforcement learning takes an enormous number of iterations until ...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	230,069
1807.02425	Beamforming in Millimeter Wave Systems: Prototyping and Measurement Results	Demonstrating the feasibility of large antenna array beamforming is essential for realizing mmWave communication systems. This is due to the dependency of these systems on the large array beamforming gains to provide sufficient received signal power. In this paper, the design of a proof-of-concept prototype that demons...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	102,267
1701.08528	Self-Adaptation of Activity Recognition Systems to New Sensors	Traditional activity recognition systems work on the basis of training, taking a fixed set of sensors into account. In this article, we focus on the question how pattern recognition can leverage new information sources without any, or with minimal user input. Thus, we present an approach for opportunistic activity reco...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	67,484
2309.07887	Some notes concerning a generalized KMM-type optimization method for density ratio estimation	In the present paper we introduce new optimization algorithms for the task of density ratio estimation. More precisely, we consider extending the well-known KMM method using the construction of a suitable loss function, in order to encompass more general situations involving the estimation of density ratio with respect...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	391,941
0810.5663	Effective Complexity and its Relation to Logical Depth	Effective complexity measures the information content of the regularities of an object. It has been introduced by M. Gell-Mann and S. Lloyd to avoid some of the disadvantages of Kolmogorov complexity, also known as algorithmic information content. In this paper, we give a precise formal definition of effective complexi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	2,590
2106.06911	An Interaction-based Convolutional Neural Network (ICNN) Towards Better Understanding of COVID-19 X-ray Images	The field of Explainable Artificial Intelligence (XAI) aims to build explainable and interpretable machine learning (or deep learning) methods without sacrificing prediction performance. Convolutional Neural Networks (CNNs) have been successful in making predictions, especially in image classification. However, these f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	240,681
1601.00524	Ideal Databases	From algebraic geometry perspective database relations are succinctly defined as Finite Varieties. After establishing basic framework, we give analytic proof of Heath theorem from Database Dependency theory. Next, we leverage Algebra/Geometry dictionary and focus on algebraic counterparts of finite varieties, polynomia...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	50,650
1911.13029	Progressive-Growing of Generative Adversarial Networks for Metasurface Optimization	Generative adversarial networks, which can generate metasurfaces based on a training set of high performance device layouts, have the potential to significantly reduce the computational cost of the metasurface design process. However, basic GAN architectures are unable to fully capture the detailed features of topologi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	155,562
2403.13737	EthioLLM: Multilingual Large Language Models for Ethiopian Languages with Task Evaluation	Large language models (LLMs) have gained popularity recently due to their outstanding performance in various downstream Natural Language Processing (NLP) tasks. However, low-resource languages are still lagging behind current state-of-the-art (SOTA) developments in the field of NLP due to insufficient resources to trai...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	439,754
1009.5249	Defining and Generating Axial Lines from Street Center Lines for better Understanding of Urban Morphologies	Axial lines are defined as the longest visibility lines for representing individual linear spaces in urban environments. The least number of axial lines that cover the free space of an urban environment or the space between buildings constitute what is often called an axial map. This is a fundamental tool in space synt...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	7,691
2412.08029	NeRF-NQA: No-Reference Quality Assessment for Scenes Generated by NeRF and Neural View Synthesis Methods	Neural View Synthesis (NVS) has demonstrated efficacy in generating high-fidelity dense viewpoint videos using a image set with sparse views. However, existing quality assessment methods like PSNR, SSIM, and LPIPS are not tailored for the scenes with dense viewpoints synthesized by NVS and NeRF variants, thus, they oft...	true	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	515,907
2502.13344	K-Paths: Reasoning over Graph Paths for Drug Repurposing and Drug Interaction Prediction	Drug discovery is a complex and time-intensive process that requires identifying and validating new therapeutic candidates. Computational approaches using large-scale biomedical knowledge graphs (KGs) offer a promising solution to accelerate this process. However, extracting meaningful insights from large-scale KGs rem...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	535,322
2408.12590	xGen-VideoSyn-1: High-fidelity Text-to-Video Synthesis with Compressed Representations	We present xGen-VideoSyn-1, a text-to-video (T2V) generation model capable of producing realistic scenes from textual descriptions. Building on recent advancements, such as OpenAI's Sora, we explore the latent diffusion model (LDM) architecture and introduce a video variational autoencoder (VidVAE). VidVAE compresses v...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	482,793
2412.04896	Comprehensive Analysis and Improvements in Pansharpening Using Deep Learning	Pansharpening is a crucial task in remote sensing, enabling the generation of high-resolution multispectral images by fusing low-resolution multispectral data with high-resolution panchromatic images. This paper provides a comprehensive analysis of traditional and deep learning-based pansharpening methods. While state-...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	514,618
2005.13449	Segmentation Loss Odyssey	Loss functions are one of the crucial ingredients in deep learning-based medical image segmentation methods. Many loss functions have been proposed in existing literature, but are studied separately or only investigated with few other losses. In this paper, we present a systematic taxonomy to sort existing loss functio...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	179,012
2011.10508	Planning Folding Motion with Simulation in the Loop Using Laser Forming Origami and Thermal Behaviors as an Example	Designing a robot or structure that can fold itself into a target shape is a process that involves challenges originated from multiple sources. For example, the designer of rigid self-folding robots must consider foldability from geometric and kinematic aspects to avoid self-intersection and undesired deformations. Rec...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	207,531
1610.02481	Frequency Estimation of Multiple Sinusoids with Three Sub-Nyquist Channels	Frequency estimation of multiple sinusoids is significant in both theory and application. In some application scenarios, only sub-Nyquist samples are available to estimate the frequencies. A conventional approach is to sample the signals at several lower rates. In this paper, we address frequency estimation of the sign...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	62,104
2006.07212	Task-similarity Aware Meta-learning through Nonparametric Kernel Regression	This paper investigates the use of nonparametric kernel-regression to obtain a tasksimilarity aware meta-learning algorithm. Our hypothesis is that the use of tasksimilarity helps meta-learning when the available tasks are limited and may contain outlier/ dissimilar tasks. While existing meta-learning approaches implic...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,721
2004.04699	Scalable Active Learning for Object Detection	Deep Neural Networks trained in a fully supervised fashion are the dominant technology in perception-based autonomous driving systems. While collecting large amounts of unlabeled data is already a major undertaking, only a subset of it can be labeled by humans due to the effort needed for high-quality annotation. There...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	171,966
1901.05744	The Oracle of DLphi	We present a novel technique based on deep learning and set theory which yields exceptional classification and prediction results. Having access to a sufficiently large amount of labelled training data, our methodology is capable of predicting the labels of the test data almost always even if the training data is entir...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	118,849
2403.11706	Generalized Multi-Source Inference for Text Conditioned Music Diffusion Models	Multi-Source Diffusion Models (MSDM) allow for compositional musical generation tasks: generating a set of coherent sources, creating accompaniments, and performing source separation. Despite their versatility, they require estimating the joint distribution over the sources, necessitating pre-separated musical data, wh...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	438,824
2408.08543	Language-Driven Interactive Shadow Detection	Traditional shadow detectors often identify all shadow regions of static images or video sequences. This work presents the Referring Video Shadow Detection (RVSD), which is an innovative task that rejuvenates the classic paradigm by facilitating the segmentation of particular shadows in videos based on descriptive natu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	481,034
1405.1359	Latent semantics of action verbs reflect phonetic parameters of intensity and emotional content	Conjuring up our thoughts, language reflects statistical patterns of word co-occurrences which in turn come to describe how we perceive the world. Whether counting how frequently nouns and verbs combine in Google search queries, or extracting eigenvectors from term document matrices made up of Wikipedia lines and Shake...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	32,862
1912.05344	Reconfigurable Intelligent Surfaces: Bridging the gap between scattering and reflection	In this work we address the distance dependence of reconfigurable intelligent surfaces (RIS). As differentiating factor to other works in the literature, we focus on the array near-field, what allows us to comprehend and expose the promising potential of RIS. The latter mostly implies an interplay between the physical ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	157,085
1701.04645	Une mesure d'expertise pour le crowdsourcing	Crowdsourcing, a major economic issue, is the fact that the firm outsources internal task to the crowd. It is a form of digital subcontracting for the general public. The evaluation of the participants work quality is a major issue in crowdsourcing. Indeed, contributions must be controlled to ensure the effectiveness a...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	66,876
2203.09390	A Cube Algebra with Comparative Operations: Containment, Overlap, Distance and Usability	In this paper, we provide a comprehensive rigorous modeling for multidimensional spaces with hierarchically structured dimensions in several layers of abstractions and data cubes that live in such spaces. We model cube queries and their semantics and define typical OLAP operators like Selections, Roll-Up, Drill-Down, e...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	286,141
2012.06644	Regularizing Action Policies for Smooth Control with Reinforcement Learning	A critical problem with the practical utility of controllers trained with deep Reinforcement Learning (RL) is the notable lack of smoothness in the actions learned by the RL policies. This trend often presents itself in the form of control signal oscillation and can result in poor control, high power consumption, and u...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	211,168
2107.03465	An audiovisual and contextual approach for categorical and continuous emotion recognition in-the-wild	In this work we tackle the task of video-based audio-visual emotion recognition, within the premises of the 2nd Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW2). Poor illumination conditions, head/body orientation and low image resolution constitute factors that can potentially hinder perform...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	245,170
2403.18438	Global Vegetation Modeling with Pre-Trained Weather Transformers	Accurate vegetation models can produce further insights into the complex interaction between vegetation activity and ecosystem processes. Previous research has established that long-term trends and short-term variability of temperature and precipitation affect vegetation activity. Motivated by the recent success of Tra...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	441,939
1902.02992	A Wrapped Normal Distribution on Hyperbolic Space for Gradient-Based Learning	Hyperbolic space is a geometry that is known to be well-suited for representation learning of data with an underlying hierarchical structure. In this paper, we present a novel hyperbolic distribution called \textit{pseudo-hyperbolic Gaussian}, a Gaussian-like distribution on hyperbolic space whose density can be evalua...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	120,992
2209.13850	Bimanual rope manipulation skill synthesis through context dependent correction policy learning from human demonstration	Learning from demonstration (LfD) provides a convenient means to equip robots with dexterous skills when demonstration can be obtained in robot intrinsic coordinates. However, the problem of compounding errors in long and complex skills reduces its wide deployment. Since most such complex skills are composed of smaller...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	320,051
2102.07704	Multi-Class Unsourced Random Access via Coded Demixing	Unsourced random access (URA) is a recently proposed communication paradigm attuned to machine-driven data transfers. In the original URA formulation, all the active devices share the same number of bits per packet. The scenario where several classes of devices transmit concurrently has so far received little attention...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	220,194
2403.17844	Mechanistic Design and Scaling of Hybrid Architectures	The development of deep learning architectures is a resource-demanding process, due to a vast design space, long prototyping times, and high compute costs associated with at-scale model training and evaluation. We set out to simplify this process by grounding it in an end-to-end mechanistic architecture design (MAD) pi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	441,653
2310.06282	MuseChat: A Conversational Music Recommendation System for Videos	Music recommendation for videos attracts growing interest in multi-modal research. However, existing systems focus primarily on content compatibility, often ignoring the users' preferences. Their inability to interact with users for further refinements or to provide explanations leads to a less satisfying experience. W...	false	false	false	false	false	true	true	false	false	false	false	true	false	false	false	false	false	false	398,506
2412.12654	CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning	Few-Shot Class-Incremental Learning (FSCIL) defines a practical but challenging task where models are required to continuously learn novel concepts with only a few training samples. Due to data scarcity, existing FSCIL methods resort to training a backbone with abundant base data and then keeping it frozen afterward. H...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	517,969
1111.2259	A Survey on Open Problems for Mobile Robots	Gathering mobile robots is a widely studied problem in robotic research. This survey first introduces the related work, summarizing models and results. Then, the focus shifts on the open problem of gathering fat robots. In this context, "fat" means that the robot is not represented by a point in a bidimensional space, ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	12,976
2311.05367	Reducing Disorder: An Information-Theory Formulation of MEV	Maximal Extractable Value (MEV) has garnered significant attention in the cryptocurrency community. Such attention is a consequence of the revenue that can be generated from MEV, as well as the risks MEV poses to the fundamental value proposition of the underlying blockchain technology. In this work, we provide an info...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	406,557
2312.10306	Mapping Housing Stock Characteristics from Drone Images for Climate Resilience in the Caribbean	Comprehensive information on housing stock is crucial for climate adaptation initiatives aiming to reduce the adverse impacts of climate-extreme hazards in high-risk regions like the Caribbean. In this study, we propose a workflow for rapidly generating critical baseline housing stock data using very high-resolution dr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	416,101
1301.0552	A constraint satisfaction approach to the robust spanning tree problem with interval data	Robust optimization is one of the fundamental approaches to deal with uncertainty in combinatorial optimization. This paper considers the robust spanning tree problem with interval data, which arises in a variety of telecommunication applications. It proposes a constraint satisfaction approach using a combinatorial low...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	20,734
2410.16013	Information-Theoretic Minimax Regret Bounds for Reinforcement Learning based on Duality	We study agents acting in an unknown environment where the agent's goal is to find a robust policy. We consider robust policies as policies that achieve high cumulative rewards for all possible environments. To this end, we consider agents minimizing the maximum regret over different environment parameters, leading to ...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	500,841
1909.00657	Economic Evaluation of the Portuguese PV and Energy Storage Residential Applications	In the residential sector, energy micro-generation and its intelligent management have been creating novel energy market models, considering new concepts of energy use and distribution, in which the prosumer has an active role in the energy generation and its self-consumption. The configuration of the solar photovoltai...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	143,686
2201.03450	Leveraging Social Influence based on Users Activity Centers for Point-of-Interest Recommendation	Recommender Systems (RSs) aim to model and predict the user preference while interacting with items, such as Points of Interest (POIs). These systems face several challenges, such as data sparsity, limiting their effectiveness. In this paper, we address this problem by incorporating social, geographical, and temporal i...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	274,857
1908.06327	Language Features Matter: Effective Language Representations for Vision-Language Tasks	Shouldn't language and vision features be treated equally in vision-language (VL) tasks? Many VL approaches treat the language component as an afterthought, using simple language models that are either built upon fixed word embeddings trained on text-only data or are learned from scratch. We believe that language featu...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	141,981
2405.14437	Combining Denoising Autoencoders with Contrastive Learning to fine-tune Transformer Models	Recently, using large pretrained Transformer models for transfer learning tasks has evolved to the point where they have become one of the flagship trends in the Natural Language Processing (NLP) community, giving rise to various outlooks such as prompt-based, adapters or combinations with unsupervised approaches, amon...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	456,427
2411.12906	Experimental Study of Underwater Acoustic Reconfigurable Intelligent Surfaces with In-Phase and Quadrature Modulation	This paper presents an underwater acoustic reconfigurable intelligent surfaces (UA-RIS) designed for long-range, high-speed, and environmentally friendly communication in oceanic environments. The proposed UA-RIS comprises multiple pairs of acoustic reflectors that utilize in-phase and quadrature (IQ) modulation to fle...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	509,591
1807.07761	Controllability of Social Networks and the Strategic Use of Random Information	This work is aimed at studying realistic social control strategies for social networks based on the introduction of random information into the state of selected driver agents. Deliberately exposing selected agents to random information is a technique already experimented in recommender systems or search engines, and r...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	103,376
2305.13904	Deep GEM-Based Network for Weakly Supervised UWB Ranging Error Mitigation	Ultra-wideband (UWB)-based techniques, while becoming mainstream approaches for high-accurate positioning, tend to be challenged by ranging bias in harsh environments. The emerging learning-based methods for error mitigation have shown great performance improvement via exploiting high semantic features from raw data. H...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	366,754
1401.1549	Optimal Demand Response Using Device Based Reinforcement Learning	Demand response (DR) for residential and small commercial buildings is estimated to account for as much as 65% of the total energy savings potential of DR, and previous work shows that a fully automated Energy Management System (EMS) is a necessary prerequisite to DR in these areas. In this paper, we propose a novel EM...	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	29,663
2303.11407	Distributed Resilient Interval Observers for Bounded-Error LTI Systems Subject to False Data Injection Attacks	This paper proposes a novel distributed interval-valued simultaneous state and input observer for linear time-invariant (LTI) systems that are subject to attacks or unknown inputs injected both on their sensors and actuators. Each agent in the network leverages a singular value decomposition (SVD) based transformation ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	352,832
1901.02495	Presence-absence estimation in audio recordings of tropical frog communities	One non-invasive way to study frog communities is by analyzing long-term samples of acoustic material containing calls. This immense task has been optimized by the development of Machine Learning tools to extract ecological information. We explored a likelihood-ratio audio detector based on Gaussian mixture model class...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	118,217
2304.07358	Exact Subspace Diffusion for Decentralized Multitask Learning	Classical paradigms for distributed learning, such as federated or decentralized gradient descent, employ consensus mechanisms to enforce homogeneity among agents. While these strategies have proven effective in i.i.d. scenarios, they can result in significant performance degradation when agents follow heterogeneous ob...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	358,316
2407.11433	CycleHOI: Improving Human-Object Interaction Detection with Cycle Consistency of Detection and Generation	Recognition and generation are two fundamental tasks in computer vision, which are often investigated separately in the exiting literature. However, these two tasks are highly correlated in essence as they both require understanding the underline semantics of visual concepts. In this paper, we propose a new learning fr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	473,457
2211.16462	Will My Robot Achieve My Goals? Predicting the Probability that an MDP Policy Reaches a User-Specified Behavior Target	As an autonomous system performs a task, it should maintain a calibrated estimate of the probability that it will achieve the user's goal. If that probability falls below some desired level, it should alert the user so that appropriate interventions can be made. This paper considers settings where the user's goal is sp...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	333,638
2208.04541	Coverage Increase at THz Frequencies: A Cooperative Rate-Splitting Approach	Numerous studies claim that terahertz (THz) communication will be an essential piece of sixth-generation wireless communication systems. Its promising potential also comes with major challenges, in particular the reduced coverage due to harsh propagation loss, hardware constraints, and blockage vulnerability. To increa...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	312,144
2101.02338	Max-Affine Spline Insights Into Deep Network Pruning	In this paper, we study the importance of pruning in Deep Networks (DNs) and the yin & yang relationship between (1) pruning highly overparametrized DNs that have been trained from random initialization and (2) training small DNs that have been "cleverly" initialized. As in most cases practitioners can only resort to r...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	214,589
2109.04411	Non-autoregressive End-to-end Speech Translation with Parallel Autoregressive Rescoring	This article describes an efficient end-to-end speech translation (E2E-ST) framework based on non-autoregressive (NAR) models. End-to-end speech translation models have several advantages over traditional cascade systems such as inference latency reduction. However, conventional AR decoding methods are not fast enough ...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	254,398
2411.05224	Beyond the Numbers: Transparency in Relation Extraction Benchmark Creation and Leaderboards	This paper investigates the transparency in the creation of benchmarks and the use of leaderboards for measuring progress in NLP, with a focus on the relation extraction (RE) task. Existing RE benchmarks often suffer from insufficient documentation, lacking crucial details such as data sources, inter-annotator agreemen...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	506,583
1407.3474	Multichannel group sparsity methods for compressive channel estimation in doubly selective multicarrier MIMO systems (extended version)	We consider channel estimation within pulse-shaping multicarrier multiple-input multiple-output (MIMO) systems transmitting over doubly selective MIMO channels. This setup includes MIMO orthogonal frequency-division multiplexing (MIMO-OFDM) systems as a special case. We show that the component channels tend to exhibit ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	34,623
2004.14171	SE-KGE: A Location-Aware Knowledge Graph Embedding Model for Geographic Question Answering and Spatial Semantic Lifting	Learning knowledge graph (KG) embeddings is an emerging technique for a variety of downstream tasks such as summarization, link prediction, information retrieval, and question answering. However, most existing KG embedding models neglect space and, therefore, do not perform well when applied to (geo)spatial data and ta...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	true	false	174,798
2303.15792	SDAT: Sub-Dataset Alternation Training for Improved Image Demosaicing	Image demosaicing is an important step in the image processing pipeline for digital cameras. In data centric approaches, such as deep learning, the distribution of the dataset used for training can impose a bias on the networks' outcome. For example, in natural images most patches are smooth, and high-content patches a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	354,624

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