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
1605.00392	Revisiting Human Action Recognition: Personalization vs. Generalization	By thoroughly revisiting the classic human action recognition paradigm, this paper aims at proposing a new approach for the design of effective action classification systems. Taking as testbed publicly available three-dimensional (MoCap) action/activity datasets, we analyzed and validated different training/testing str...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	55,337
2309.11091	Learning Segment Similarity and Alignment in Large-Scale Content Based Video Retrieval	With the explosive growth of web videos in recent years, large-scale Content-Based Video Retrieval (CBVR) becomes increasingly essential in video filtering, recommendation, and copyright protection. Segment-level CBVR (S-CBVR) locates the start and end time of similar segments in finer granularity, which is beneficial ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	393,276
2410.12676	Identity Emergence in the Context of Vaccine Criticism in France	This study investigates the emergence of collective identity among individuals critical of vaccination policies in France during the COVID-19 pandemic. As concerns grew over mandated health measures, a loose collective formed on Twitter to assert autonomy over vaccination decisions. Using analyses of pronoun usage, out...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	499,137
2005.11077	Driver Identification through Stochastic Multi-State Car-Following Modeling	Intra-driver and inter-driver heterogeneity has been confirmed to exist in human driving behaviors by many studies. In this study, a joint model of the two types of heterogeneity in car-following behavior is proposed as an approach of driver profiling and identification. It is assumed that all drivers share a pool of d...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	178,376
1612.08034	Push Recovery of a Humanoid Robot Based on Model Predictive Control and Capture Point	The three bio-inspired strategies that have been used for balance recovery of biped robots are the ankle, hip and stepping Strategies. However, there are several cases for a biped robot where stepping is not possible, e. g. when the available contact surfaces are limited. In this situation, the balance recovery by modu...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	66,017
1902.06554	MetaGrasp: Data Efficient Grasping by Affordance Interpreter Network	Data-driven approach for grasping shows significant advance recently. But these approaches usually require much training data. To increase the efficiency of grasping data collection, this paper presents a novel grasp training system including the whole pipeline from data collection to model inference. The system can co...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	121,789
2406.01906	ProGEO: Generating Prompts through Image-Text Contrastive Learning for Visual Geo-localization	Visual Geo-localization (VG) refers to the process to identify the location described in query images, which is widely applied in robotics field and computer vision tasks, such as autonomous driving, metaverse, augmented reality, and SLAM. In fine-grained images lacking specific text descriptions, directly applying pur...	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	460,514
2107.02621	Energy Consumption of Deep Generative Audio Models	In most scientific domains, the deep learning community has largely focused on the quality of deep generative models, resulting in highly accurate and successful solutions. However, this race for quality comes at a tremendous computational cost, which incurs vast energy consumption and greenhouse gas emissions. At the ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	244,883
2011.04328	Risk Assessment for Machine Learning Models	In this paper we propose a framework for assessing the risk associated with deploying a machine learning model in a specified environment. For that we carry over the risk definition from decision theory to machine learning. We develop and implement a method that allows to define deployment scenarios, test the machine l...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	205,550
2312.07637	Responsibility in Extensive Form Games	Two different forms of responsibility, counterfactual and seeing-to-it, have been extensively discussed in the philosophy and AI in the context of a single agent or multiple agents acting simultaneously. Although the generalisation of counterfactual responsibility to a setting where multiple agents act in some order is...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	415,008
2408.12153	DimeRec: A Unified Framework for Enhanced Sequential Recommendation via Generative Diffusion Models	Sequential Recommendation (SR) plays a pivotal role in recommender systems by tailoring recommendations to user preferences based on their non-stationary historical interactions. Achieving high-quality performance in SR requires attention to both item representation and diversity. However, designing an SR method that s...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	482,615
2111.09395	FinRL: Deep Reinforcement Learning Framework to Automate Trading in Quantitative Finance	Deep reinforcement learning (DRL) has been envisioned to have a competitive edge in quantitative finance. However, there is a steep development curve for quantitative traders to obtain an agent that automatically positions to win in the market, namely \textit{to decide where to trade, at what price} and \textit{what qu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	266,997
2312.10920	Domain adaption and physical constrains transfer learning for shale gas production	Effective prediction of shale gas production is crucial for strategic reservoir development. However, in new shale gas blocks, two main challenges are encountered: (1) the occurrence of negative transfer due to insufficient data, and (2) the limited interpretability of deep learning (DL) models. To tackle these problem...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	416,366
2307.03833	Back to Optimization: Diffusion-based Zero-Shot 3D Human Pose Estimation	Learning-based methods have dominated the 3D human pose estimation (HPE) tasks with significantly better performance in most benchmarks than traditional optimization-based methods. Nonetheless, 3D HPE in the wild is still the biggest challenge for learning-based models, whether with 2D-3D lifting, image-to-3D, or diffu...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	378,165
2104.00660	Recognizing and Splitting Conditional Sentences for Automation of Business Processes Management	Business Process Management (BPM) is the discipline which is responsible for management of discovering, analyzing, redesigning, monitoring, and controlling business processes. One of the most crucial tasks of BPM is discovering and modelling business processes from text documents. In this paper, we present our system t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	228,071
1106.5626	A distributed control strategy for reactive power compensation in smart microgrids	We consider the problem of optimal reactive power compensation for the minimization of power distribution losses in a smart microgrid. We first propose an approximate model for the power distribution network, which allows us to cast the problem into the class of convex quadratic, linearly constrained, optimization prob...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	11,046
2312.15346	Learning Multi-Step Manipulation Tasks from A Single Human Demonstration	Learning from human demonstrations has exhibited remarkable achievements in robot manipulation. However, the challenge remains to develop a robot system that matches human capabilities and data efficiency in learning and generalizability, particularly in complex, unstructured real-world scenarios. We propose a system t...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	417,978
2103.00545	Snowy Night-to-Day Translator and Semantic Segmentation Label Similarity for Snow Hazard Indicator	In 2021, Japan recorded more than three times as much snowfall as usual, so road user maybe come across dangerous situation. The poor visibility caused by snow triggers traffic accidents. For example, 2021 January 19, due to the dry snow and the strong wind speed of 27 m / s, blizzards occurred and the outlook has been...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	222,320
2412.01949	Identifying Key Nodes for the Influence Spread using a Machine Learning Approach	The identification of key nodes in complex networks is an important topic in many network science areas. It is vital to a variety of real-world applications, including viral marketing, epidemic spreading and influence maximization. In recent years, machine learning algorithms have proven to outperform the conventional,...	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	false	513,319
2502.14462	Single-image Reflectance and Transmittance Estimation from Any Flatbed Scanner	Flatbed scanners have emerged as promising devices for high-resolution, single-image material capture. However, existing approaches assume very specific conditions, such as uniform diffuse illumination, which are only available in certain high-end devices, hindering their scalability and cost. In contrast, in this work...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	true	535,843
1301.3860	Maximum Entropy and the Glasses You Are Looking Through	We give an interpretation of the Maximum Entropy (MaxEnt) Principle in game-theoretic terms. Based on this interpretation, we make a formal distinction between different ways of {em applying/} Maximum Entropy distributions. MaxEnt has frequently been criticized on the grounds that it leads to highly representation depe...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	21,172
1910.09858	Fixed Pattern Noise Reduction for Infrared Images Based on Cascade Residual Attention CNN	Existing fixed pattern noise reduction (FPNR) methods are easily affected by the motion state of the scene and working condition of the image sensor, which leads to over smooth effects, ghosting artifacts as well as slow convergence rate. To address these issues, we design an innovative cascade convolution neural netwo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	150,322
2008.07707	RTFN: Robust Temporal Feature Network	Time series analysis plays a vital role in various applications, for instance, healthcare, weather prediction, disaster forecast, etc. However, to obtain sufficient shapelets by a feature network is still challenging. To this end, we propose a novel robust temporal feature network (RTFN) that contains temporal feature ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	192,192
1806.09533	Using NLP on news headlines to predict index trends	This paper attempts to provide a state of the art in trend prediction using news headlines. We present the research done on predicting DJIA trends using Natural Language Processing. We will explain the different algorithms we have used as well as the various embedding techniques attempted. We rely on statistical and de...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	101,371
2408.04369	Analyzing Consumer Reviews for Understanding Drivers of Hotels Ratings: An Indian Perspective	In the internet era, almost every business entity is trying to have its digital footprint in digital media and other social media platforms. For these entities, word of mouse is also very important. Particularly, this is quite crucial for the hospitality sector dealing with hotels, restaurants etc. Consumers do read ot...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	479,361
2309.04422	Video Task Decathlon: Unifying Image and Video Tasks in Autonomous Driving	Performing multiple heterogeneous visual tasks in dynamic scenes is a hallmark of human perception capability. Despite remarkable progress in image and video recognition via representation learning, current research still focuses on designing specialized networks for singular, homogeneous, or simple combination of task...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	390,719
2411.15385	Gradient dynamics for low-rank fine-tuning beyond kernels	LoRA has emerged as one of the de facto methods for fine-tuning foundation models with low computational cost and memory footprint. The idea is to only train a low-rank perturbation to the weights of a pre-trained model, given supervised data for a downstream task. Despite its empirical sucess, from a mathematical pers...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	510,585
2303.08600	MSeg3D: Multi-modal 3D Semantic Segmentation for Autonomous Driving	LiDAR and camera are two modalities available for 3D semantic segmentation in autonomous driving. The popular LiDAR-only methods severely suffer from inferior segmentation on small and distant objects due to insufficient laser points, while the robust multi-modal solution is under-explored, where we investigate three c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	351,707
2305.06289	Learning Video-Conditioned Policies for Unseen Manipulation Tasks	The ability to specify robot commands by a non-expert user is critical for building generalist agents capable of solving a large variety of tasks. One convenient way to specify the intended robot goal is by a video of a person demonstrating the target task. While prior work typically aims to imitate human demonstration...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	363,476
2205.10805	Deep Learning-Based Synchronization for Uplink NB-IoT	We propose a neural network (NN)-based algorithm for device detection and time of arrival (ToA) and carrier frequency offset (CFO) estimation for the narrowband physical random-access channel (NPRACH) of narrowband internet of things (NB-IoT). The introduced NN architecture leverages residual convolutional networks as ...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	297,881
2405.03667	Fault Detection and Monitoring using a Data-Driven Information-Based Strategy: Method, Theory, and Application	The ability to detect when a system undergoes an incipient fault is of paramount importance in preventing a critical failure. Classic methods for fault detection (including model-based and data-driven approaches) rely on thresholding error statistics or simple input-residual dependencies but face difficulties with non-...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	452,268
2103.05939	A Review and Refinement of Surprise Adequacy	Surprise Adequacy (SA) is one of the emerging and most promising adequacy criteria for Deep Learning (DL) testing. As an adequacy criterion, it has been used to assess the strength of DL test suites. In addition, it has also been used to find inputs to a Deep Neural Network (DNN) which were not sufficiently represented...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	224,137
2212.07172	Quotations, Coreference Resolution, and Sentiment Annotations in Croatian News Articles: An Exploratory Study	This paper presents a corpus annotated for the task of direct-speech extraction in Croatian. The paper focuses on the annotation of the quotation, co-reference resolution, and sentiment annotation in SETimes news corpus in Croatian and on the analysis of its language-specific differences compared to English. From this,...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	336,326
2005.09336	A systematic comparison of grapheme-based vs. phoneme-based label units for encoder-decoder-attention models	Following the rationale of end-to-end modeling, CTC, RNN-T or encoder-decoder-attention models for automatic speech recognition (ASR) use graphemes or grapheme-based subword units based on e.g. byte-pair encoding (BPE). The mapping from pronunciation to spelling is learned completely from data. In contrast to this, cla...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	177,900
0908.1597	A quantum diffusion network	Wong's diffusion network is a stochastic, zero-input Hopfield network with a Gibbs stationary distribution over a bounded, connected continuum. Previously, logarithmic thermal annealing was demonstrated for the diffusion network and digital versions of it were studied and applied to imaging. Recently, "quantum" anneale...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	4,263
1312.6808	Socially-Aware Venue Recommendation for Conference Participants	Current research environments are witnessing high enormities of presentations occurring in different sessions at academic conferences. This situation makes it difficult for researchers (especially juniors) to attend the right presentation session(s) for effective collaboration. In this paper, we propose an innovative v...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	29,402
2407.16923	Handling Device Heterogeneity for Deep Learning-based Localization	Deep learning-based fingerprinting is one of the current promising technologies for outdoor localization in cellular networks. However, deploying such localization systems for heterogeneous phones affects their accuracy as the cellular received signal strength (RSS) readings vary for different types of phones. In this ...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	475,781
2410.13389	Dynamic Input Mapping Inversion for Algebraic Loop-Free Control in Hydraulic Actuators	The application of nonlinear control schemes to electro-hydraulic actuators often requires several alterations in the design of the controllers during their implementation. This is to overcome the challenges that frequently arise from the inherent complexity of such control algorithms owning to model nonlinearities. Mo...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	499,512
1601.06108	Decision Aids for Adversarial Planning in Military Operations: Algorithms, Tools, and Turing-test-like Experimental Validation	Use of intelligent decision aids can help alleviate the challenges of planning complex operations. We describe integrated algorithms, and a tool capable of translating a high-level concept for a tactical military operation into a fully detailed, actionable plan, producing automatically (or with human guidance) plans wi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	51,226
1503.01250	A new method on deterministic construction of the measurement matrix in compressed sensing	Construction on the measurement matrix $A$ is a central problem in compressed sensing. Although using random matrices is proven optimal and successful in both theory and applications. A deterministic construction on the measurement matrix is still very important and interesting. In fact, it is still an open problem pro...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	40,809
2501.11406	Efficient Reduction of Interconnected Subsystem Models using Abstracted Environments	We present two frameworks for structure-preserving model order reduction of interconnected subsystems, improving tractability of the reduction methods while ensuring stability and accuracy bounds of the reduced interconnected model. Instead of reducing each subsystem independently, we take a low-order abstraction of it...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	525,910
2104.01854	Integrating 2D and 3D Digital Plant Information Towards Automatic Generation of Digital Twins	Ongoing standardization in Industry 4.0 supports tool vendor neutral representations of Piping and Instrumentation diagrams as well as 3D pipe routing. However, a complete digital plant model requires combining these two representations. 3D pipe routing information is essential for building any accurate first-principle...	false	false	false	false	true	false	false	false	false	true	true	true	false	false	false	false	false	true	228,504
1912.07959	Multi-focus Image Fusion Based on Similarity Characteristics	A novel multi-focus image fusion algorithm performed in spatial domain based on similarity characteristics is proposed incorporating with region segmentation. In this paper, a new similarity measure is developed based on the structural similarity (SSIM) index, which is more suitable for multi-focus image segmentation. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	157,729
2007.11086	Converse Barrier Functions via Lyapunov Functions	We prove a robust converse barrier function theorem via the converse Lyapunov theory. While the use of a Lyapunov function as a barrier function is straightforward, the existence of a converse Lyapunov function as a barrier function for a given safety set is not. We establish this link by a robustness argument. We show...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	188,456
2402.13916	Bias correction of wind power forecasts with SCADA data and continuous learning	Wind energy plays a critical role in the transition towards renewable energy sources. However, the uncertainty and variability of wind can impede its full potential and the necessary growth of wind power capacity. To mitigate these challenges, wind power forecasting methods are employed for applications in power manage...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	431,459
2409.01628	CTG-KrEW: Generating Synthetic Structured Contextually Correlated Content by Conditional Tabular GAN with K-Means Clustering and Efficient Word Embedding	Conditional Tabular Generative Adversarial Networks (CTGAN) and their various derivatives are attractive for their ability to efficiently and flexibly create synthetic tabular data, showcasing strong performance and adaptability. However, there are certain critical limitations to such models. The first is their inabili...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	485,417
2210.06720	LIME: Weakly-Supervised Text Classification Without Seeds	In weakly-supervised text classification, only label names act as sources of supervision. Predominant approaches to weakly-supervised text classification utilize a two-phase framework, where test samples are first assigned pseudo-labels and are then used to train a neural text classifier. In most previous work, the pse...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	323,412
2412.13395	Enhancing Talk Moves Analysis in Mathematics Tutoring through Classroom Teaching Discourse	Human tutoring interventions play a crucial role in supporting student learning, improving academic performance, and promoting personal growth. This paper focuses on analyzing mathematics tutoring discourse using talk moves - a framework of dialogue acts grounded in Accountable Talk theory. However, scaling the collect...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	518,271
2209.08807	A Deep Learning Approach for Parallel Imaging and Compressed Sensing MRI Reconstruction	Parallel imaging accelerates MRI data acquisition by acquiring additional sensitivity information with an array of receiver coils, resulting in fewer phase encoding steps. Because of fewer data requirements than parallel imaging, compressed sensing magnetic resonance imaging (CS-MRI) has gained popularity in the field ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	318,277
2302.02881	Enhancing Human-Robot Collaboration Transportation through Obstacle-Aware Vibrotactile Feedback	Transporting large and heavy objects can benefit from Human-Robot Collaboration (HRC), increasing the contribution of robots to our daily tasks and reducing the risk of injuries to the human operator. This approach usually posits the human collaborator as the leader, while the robot has the follower role. Hence, it is ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	344,138
2212.08235	A Simple Decentralized Cross-Entropy Method	Cross-Entropy Method (CEM) is commonly used for planning in model-based reinforcement learning (MBRL) where a centralized approach is typically utilized to update the sampling distribution based on only the top-$k$ operation's results on samples. In this paper, we show that such a centralized approach makes CEM vulnera...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	336,676
2308.15863	Inductive Learning of Declarative Domain-Specific Heuristics for ASP	Domain-specific heuristics are a crucial technique for the efficient solving of problems that are large or computationally hard. Answer Set Programming (ASP) systems support declarative specifications of domain-specific heuristics to improve solving performance. However, such heuristics must be invented manually so far...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	388,822
2109.10450	Towards cyber-physical systems robust to communication delays: A differential game approach	Collaboration between interconnected cyber-physical systems is becoming increasingly pervasive. Time-delays in communication channels between such systems are known to induce catastrophic failure modes, like high frequency oscillations in robotic manipulators in bilateral teleoperation or string instability in platoons...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	256,609
2011.11890	Cross-Camera Convolutional Color Constancy	We present "Cross-Camera Convolutional Color Constancy" (C5), a learning-based method, trained on images from multiple cameras, that accurately estimates a scene's illuminant color from raw images captured by a new camera previously unseen during training. C5 is a hypernetwork-like extension of the convolutional color ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	207,980
2106.00161	Integrative Use of Computer Vision and Unmanned Aircraft Technologies in Public Inspection: Foreign Object Debris Image Collection	Unmanned Aircraft Systems (UAS) have become an important resource for public service providers and smart cities. The purpose of this study is to expand this research area by integrating computer vision and UAS technology to automate public inspection. As an initial case study for this work, a dataset of common foreign ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	238,009
1812.07079	Rethinking Epistemic Logic with Belief Bases	We introduce a new semantics for a logic of explicit and implicit beliefs based on the concept of multi-agent belief base. Differently from existing Kripke-style semantics for epistemic logic in which the notions of possible world and doxastic/epistemic alternative are primitive, in our semantics they are non-primitive...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	116,739
2208.09793	FastCPH: Efficient Survival Analysis for Neural Networks	The Cox proportional hazards model is a canonical method in survival analysis for prediction of the life expectancy of a patient given clinical or genetic covariates -- it is a linear model in its original form. In recent years, several methods have been proposed to generalize the Cox model to neural networks, but none...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	313,837
1910.04388	First Order Ambisonics Domain Spatial Augmentation for DNN-based Direction of Arrival Estimation	In this paper, we propose a novel data augmentation method for training neural networks for Direction of Arrival (DOA) estimation. This method focuses on expanding the representation of the DOA subspace of a dataset. Given some input data, it applies a transformation to it in order to change its DOA information and sim...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	148,757
1304.2743	Comparisons of Reasoning Mechanisms for Computer Vision	An evidential reasoning mechanism based on the Dempster-Shafer theory of evidence is introduced. Its performance in real-world image analysis is compared with other mechanisms based on the Bayesian formalism and a simple weight combination method.	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	23,752
2210.05582	Digital Twin-Based Multiple Access Optimization and Monitoring via Model-Driven Bayesian Learning	Commonly adopted in the manufacturing and aerospace sectors, digital twin (DT) platforms are increasingly seen as a promising paradigm to control and monitor software-based, "open", communication systems, which play the role of the physical twin (PT). In the general framework presented in this work, the DT builds a Bay...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	322,918
2410.05071	Function Gradient Approximation with Random Shallow ReLU Networks with Control Applications	Neural networks are widely used to approximate unknown functions in control. A common neural network architecture uses a single hidden layer (i.e. a shallow network), in which the input parameters are fixed in advance and only the output parameters are trained. The typical formal analysis asserts that if output paramet...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	495,553
2501.13887	What Does an Audio Deepfake Detector Focus on? A Study in the Time Domain	Adding explanations to audio deepfake detection (ADD) models will boost their real-world application by providing insight on the decision making process. In this paper, we propose a relevancy-based explainable AI (XAI) method to analyze the predictions of transformer-based ADD models. We compare against standard Grad-C...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	526,861
1310.4977	Learning Tensors in Reproducing Kernel Hilbert Spaces with Multilinear Spectral Penalties	We present a general framework to learn functions in tensor product reproducing kernel Hilbert spaces (TP-RKHSs). The methodology is based on a novel representer theorem suitable for existing as well as new spectral penalties for tensors. When the functions in the TP-RKHS are defined on the Cartesian product of finite ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	27,856
1409.3021	Semantic web service discovery approaches: overview and limitations	The semantic Web service discovery has been given massive attention within the last few years. With the increasing number of Web services available on the web, looking for a particular service has become very difficult, especially with the evolution of the clients needs. In this context, various approaches to discover ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	35,954
2101.11260	Modeling opinion leader's role in the diffusion of innovation	The diffusion of innovations is an important topic for the consumer markets. Early research focused on how innovations spread on the level of the whole society. To get closer to the real world scenarios agent based models (ABM) started focusing on individual-level agents. In our work we will translate an existing ABM t...	false	false	false	true	true	false	false	false	false	false	false	false	false	true	false	false	false	false	217,215
2411.07595	Entropy Controllable Direct Preference Optimization	In the post-training of large language models (LLMs), Reinforcement Learning from Human Feedback (RLHF) is an effective approach to achieve generation aligned with human preferences. Direct Preference Optimization (DPO) allows for policy training with a simple binary cross-entropy loss without a reward model. The objec...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	507,606
1802.03889	Convergence Analysis of Alternating Projection Method for Nonconvex Sets	Alternating projection method has been used in a wide range of engineering applications since it is a gradient-free method (without requiring tuning the step size) and usually has fast speed of convergence. In this paper, we formalize two properties of proper, lower semi-continuous and semi-algebraic sets: the three-po...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	90,093
1702.00298	Cascading Failures in Interdependent Systems: Impact of Degree Variability and Dependence	We study cascading failures in a system comprising interdependent networks/systems, in which nodes rely on other nodes both in the same system and in other systems to perform their function. The (inter-)dependence among nodes is modeled using a dependence graph, where the degree vector of a node determines the number o...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	67,642
2403.17525	Equipping Sketch Patches with Context-Aware Positional Encoding for Graphic Sketch Representation	The drawing order of a sketch records how it is created stroke-by-stroke by a human being. For graphic sketch representation learning, recent studies have injected sketch drawing orders into graph edge construction by linking each patch to another in accordance to a temporal-based nearest neighboring strategy. However,...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	441,501
2109.10691	Query Evaluation in DatalogMTL -- Taming Infinite Query Results	In this paper, we investigate finite representations of DatalogMTL models. First, we discuss sufficient conditions for detecting programs that have finite models. Then, we study infinite models that eventually become constant and introduce sufficient criteria for programs that allow for such representation. We proceed ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	true	256,713
1902.01520	Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting	We study contextual bandit learning with an abstract policy class and continuous action space. We obtain two qualitatively different regret bounds: one competes with a smoothed version of the policy class under no continuity assumptions, while the other requires standard Lipschitz assumptions. Both bounds exhibit data-...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	120,674
1907.04629	Evolutionary techniques in lattice sieving algorithms	Lattice-based cryptography has recently emerged as a prominent candidate for secure communication in the quantum age. Its security relies on the hardness of certain lattice problems, and the inability of known lattice algorithms, such as lattice sieving, to solve these problems efficiently. In this paper we investigate...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	138,155
2309.08968	Sorted LLaMA: Unlocking the Potential of Intermediate Layers of Large Language Models for Dynamic Inference	Large language models (LLMs) have revolutionized natural language processing (NLP) by excelling at understanding and generating human-like text. However, their widespread deployment can be prohibitively expensive. SortedNet is a recent training technique for enabling dynamic inference by leveraging the modularity in ne...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	392,417
2009.01315	When Image Decomposition Meets Deep Learning: A Novel Infrared and Visible Image Fusion Method	Infrared and visible image fusion, as a hot topic in image processing and image enhancement, aims to produce fused images retaining the detail texture information in visible images and the thermal radiation information in infrared images. A critical step for this issue is to decompose features in different scales and t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	194,269
cs/0508057	On the Performance of Turbo Codes in Quasi-Static Fading Channels	In this paper, we investigate in detail the performance of turbo codes in quasi-static fading channels both with and without antenna diversity. First, we develop a simple and accurate analytic technique to evaluate the performance of turbo codes in quasi-static fading channels. The proposed analytic technique relates t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	538,884
2307.04390	CT-based Subchondral Bone Microstructural Analysis in Knee Osteoarthritis via MR-Guided Distillation Learning	Background: MR-based subchondral bone effectively predicts knee osteoarthritis. However, its clinical application is limited by the cost and time of MR. Purpose: We aim to develop a novel distillation-learning-based method named SRRD for subchondral bone microstructural analysis using easily-acquired CT images, which l...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	378,387
2011.11912	Variational Monocular Depth Estimation for Reliability Prediction	Self-supervised learning for monocular depth estimation is widely investigated as an alternative to supervised learning approach, that requires a lot of ground truths. Previous works have successfully improved the accuracy of depth estimation by modifying the model structure, adding objectives, and masking dynamic obje...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	207,990
1804.04694	A Variational U-Net for Conditional Appearance and Shape Generation	Deep generative models have demonstrated great performance in image synthesis. However, results deteriorate in case of spatial deformations, since they generate images of objects directly, rather than modeling the intricate interplay of their inherent shape and appearance. We present a conditional U-Net for shape-guide...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	94,914
2104.08415	Risk score learning for COVID-19 contact tracing apps	Digital contact tracing apps for COVID, such as the one developed by Google and Apple, need to estimate the risk that a user was infected during a particular exposure, in order to decide whether to notify the user to take precautions, such as entering into quarantine, or requesting a test. Such risk score models contai...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	230,785
1801.02613	Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality	Deep Neural Networks (DNNs) have recently been shown to be vulnerable against adversarial examples, which are carefully crafted instances that can mislead DNNs to make errors during prediction. To better understand such attacks, a characterization is needed of the properties of regions (the so-called 'adversarial subsp...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	87,955
1303.6020	Multi-Group Testing for Items with Real-Valued Status under Standard Arithmetic	This paper proposes a novel generalization of group testing, called multi-group testing, which relaxes the notion of "testing subset" in group testing to "testing multi-set". The generalization aims to learn more information of each item to be tested rather than identify only defectives as was done in conventional grou...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	23,236
2110.07234	On the Stability of Low Pass Graph Filter With a Large Number of Edge Rewires	Recently, the stability of graph filters has been studied as one of the key theoretical properties driving the highly successful graph convolutional neural networks (GCNs). The stability of a graph filter characterizes the effect of topology perturbation on the output of a graph filter, a fundamental building block for...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	260,910
2310.14566	HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models	We introduce HallusionBench, a comprehensive benchmark designed for the evaluation of image-context reasoning. This benchmark presents significant challenges to advanced large visual-language models (LVLMs), such as GPT-4V(Vision), Gemini Pro Vision, Claude 3, and LLaVA-1.5, by emphasizing nuanced understanding and int...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	401,921
2307.11758	A Comprehensive Introduction of Visual-Inertial Navigation	In this article, a tutorial introduction to visual-inertial navigation(VIN) is presented. Visual and inertial perception are two complementary sensing modalities. Cameras and inertial measurement units (IMU) are the corresponding sensors for these two modalities. The low cost and light weight of camera-IMU sensor combi...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	381,009
2002.00842	Mi YouTube es Su YouTube? Analyzing the Cultures using YouTube Thumbnails of Popular Videos	YouTube, a world-famous video sharing website, maintains a list of the top trending videos on the platform. Due to its huge amount of users, it enables researchers to understand people's preference by analyzing the trending videos. Trending videos vary from country to country. By analyzing such differences and changes,...	false	false	false	true	false	false	false	false	false	false	false	true	false	true	false	false	false	false	162,491
2404.01991	Kallaama: A Transcribed Speech Dataset about Agriculture in the Three Most Widely Spoken Languages in Senegal	This work is part of the Kallaama project, whose objective is to produce and disseminate national languages corpora for speech technologies developments, in the field of agriculture. Except for Wolof, which benefits from some language data for natural language processing, national languages of Senegal are largely ignor...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	443,676
1909.04885	Addressing Algorithmic Bottlenecks in Elastic Machine Learning with Chicle	Distributed machine learning training is one of the most common and important workloads running on data centers today, but it is rarely executed alone. Instead, to reduce costs, computing resources are consolidated and shared by different applications. In this scenario, elasticity and proper load balancing are vital to...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	144,931
2003.03612	Frozen Binomials on the Web: Word Ordering and Language Conventions in Online Text	There is inherent information captured in the order in which we write words in a list. The orderings of binomials --- lists of two words separated by `and' or `or' --- has been studied for more than a century. These binomials are common across many areas of speech, in both formal and informal text. In the last century,...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	167,292
2501.12919	Contrastive Language-Structure Pre-training Driven by Materials Science Literature	Understanding structure-property relationships is an essential yet challenging aspect of materials discovery and development. To facilitate this process, recent studies in materials informatics have sought latent embedding spaces of crystal structures to capture their similarities based on properties and functionalitie...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	526,486
2202.00530	Coordinated Frequency Control through Safe Reinforcement Learning	With widespread deployment of renewables, the electric power grids are experiencing increasing dynamics and uncertainties, with its secure operation being threatened. Existing frequency control schemes based on day-ahead offline analysis and minute-level online sensitivity calculations are difficult to adapt to rapidly...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	278,176
2109.05257	Towards a Rigorous Evaluation of Time-series Anomaly Detection	In recent years, proposed studies on time-series anomaly detection (TAD) report high F1 scores on benchmark TAD datasets, giving the impression of clear improvements in TAD. However, most studies apply a peculiar evaluation protocol called point adjustment (PA) before scoring. In this paper, we theoretically and experi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	254,726
2111.13445	How Well Do Sparse Imagenet Models Transfer?	Transfer learning is a classic paradigm by which models pretrained on large "upstream" datasets are adapted to yield good results on "downstream" specialized datasets. Generally, more accurate models on the "upstream" dataset tend to provide better transfer accuracy "downstream". In this work, we perform an in-depth in...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	268,294
1509.05506	Energy-Efficient Design of MIMO Heterogeneous Networks with Wireless Backhaul	As future networks aim to meet the ever-increasing requirements of high data rate applications, dense and heterogeneous networks (HetNets) will be deployed to provide better coverage and throughput. Besides the important implications for energy consumption, the trend towards densification calls for more and more wirele...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	47,057
2311.15531	Sleep When Everything Looks Fine: Self-Triggered Monitoring for Signal Temporal Logic Tasks	Online monitoring is a widely used technique in assessing if the performance of the system satisfies some desired requirements during run-time operation. Existing works on online monitoring usually assume that the monitor can acquire system information periodically at each time instant. However, such a periodic mechani...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	410,543
1701.01095	Estimating Quality in Multi-Objective Bandits Optimization	Many real-world applications are characterized by a number of conflicting performance measures. As optimizing in a multi-objective setting leads to a set of non-dominated solutions, a preference function is required for selecting the solution with the appropriate trade-off between the objectives. The question is: how g...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	66,358
2410.14118	Skill Generalization with Verbs	It is imperative that robots can understand natural language commands issued by humans. Such commands typically contain verbs that signify what action should be performed on a given object and that are applicable to many objects. We propose a method for generalizing manipulation skills to novel objects using verbs. Our...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	499,876
2209.04881	On The Computational Complexity of Self-Attention	Transformer architectures have led to remarkable progress in many state-of-art applications. However, despite their successes, modern transformers rely on the self-attention mechanism, whose time- and space-complexity is quadratic in the length of the input. Several approaches have been proposed to speed up self-attent...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	316,915
1109.3311	Escort entropies and divergences and related canonical distribution	We discuss two families of two-parameter entropies and divergences, derived from the standard R\'enyi and Tsallis entropies and divergences. These divergences and entropies are found as divergences or entropies of escort distributions. Exploiting the nonnegativity of the divergences, we derive the expression of the can...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	12,175
2401.16937	Segmentation and Characterization of Macerated Fibers and Vessels Using Deep Learning	Wood comprises different cell types, such as fibers, tracheids and vessels, defining its properties. Studying cells' shape, size, and arrangement in microscopy images is crucial for understanding wood characteristics. Typically, this involves macerating (soaking) samples in a solution to separate cells, then spreading ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	425,037
1407.7103	On Joint Source-Channel Coding for Correlated Sources Over Multiple-Access Relay Channels	We study the transmission of correlated sources over discrete memoryless (DM) multiple-access-relay channels (MARCs), in which both the relay and the destination have access to side information arbitrarily correlated with the sources. As the optimal transmission scheme is an open problem, in this work we propose a new ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	34,911

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