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
2303.12821	Towards A Visual Programming Tool to Create Deep Learning Models	Deep Learning (DL) developers come from different backgrounds, e.g., medicine, genomics, finance, and computer science. To create a DL model, they must learn and use high-level programming languages (e.g., Python), thus needing to handle related setups and solve programming errors. This paper presents DeepBlocks, a vis...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	353,426
1301.7395	Incremental Tradeoff Resolution in Qualitative Probabilistic Networks	Qualitative probabilistic reasoning in a Bayesian network often reveals tradeoffs: relationships that are ambiguous due to competing qualitative influences. We present two techniques that combine qualitative and numeric probabilistic reasoning to resolve such tradeoffs, inferring the qualitative relationship between no...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	21,629
2412.04836	Adaptive Dropout for Pruning Conformers	This paper proposes a method to effectively perform joint training-and-pruning based on adaptive dropout layers with unit-wise retention probabilities. The proposed method is based on the estimation of a unit-wise retention probability in a dropout layer. A unit that is estimated to have a small retention probability c...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	514,591
2401.08136	Bias-Compensated State of Charge and State of Health Joint Estimation for Lithium Iron Phosphate Batteries	Accurate estimation of the state of charge (SOC) and state of health (SOH) is crucial for the safe and reliable operation of batteries. Voltage measurement bias highly affects state estimation accuracy, especially in Lithium Iron Phosphate (LFP) batteries, which are susceptible due to their flat open-circuit voltage (O...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	421,778
2008.00565	Geometrically Enriched Latent Spaces	A common assumption in generative models is that the generator immerses the latent space into a Euclidean ambient space. Instead, we consider the ambient space to be a Riemannian manifold, which allows for encoding domain knowledge through the associated Riemannian metric. Shortest paths can then be defined accordingly...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	190,047
2007.14152	At-Scale Sparse Deep Neural Network Inference with Efficient GPU Implementation	This paper presents GPU performance optimization and scaling results for inference models of the Sparse Deep Neural Network Challenge 2020. Demands for network quality have increased rapidly, pushing the size and thus the memory requirements of many neural networks beyond the capacity of available accelerators. Sparse ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	189,319
2310.16809	Exploring OCR Capabilities of GPT-4V(ision) : A Quantitative and In-depth Evaluation	This paper presents a comprehensive evaluation of the Optical Character Recognition (OCR) capabilities of the recently released GPT-4V(ision), a Large Multimodal Model (LMM). We assess the model's performance across a range of OCR tasks, including scene text recognition, handwritten text recognition, handwritten mathem...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	402,885
1803.07531	Hybrid Contact Preintegration for Visual-Inertial-Contact State Estimation Using Factor Graphs	The factor graph framework is a convenient modeling technique for robotic state estimation where states are represented as nodes, and measurements are modeled as factors. When designing a sensor fusion framework for legged robots, one often has access to visual, inertial, joint encoder, and contact sensors. While visua...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	93,075
2211.04230	On Multi-Robot Path Planning Based on Petri Net Models and LTL specifications	This work considers the path planning problem for a team of identical robots evolving in a known environment. The robots should satisfy a global specification given as a Linear Temporal Logic (LTL) formula over a set of regions of interest. The proposed method exploits the advantages of Petri net models for the team of...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	329,179
2012.00058	PMLB v1.0: An open source dataset collection for benchmarking machine learning methods	Motivation: Novel machine learning and statistical modeling studies rely on standardized comparisons to existing methods using well-studied benchmark datasets. Few tools exist that provide rapid access to many of these datasets through a standardized, user-friendly interface that integrates well with popular data scien...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	209,002
2407.08720	UNRealNet: Learning Uncertainty-Aware Navigation Features from High-Fidelity Scans of Real Environments	Traversability estimation in rugged, unstructured environments remains a challenging problem in field robotics. Often, the need for precise, accurate traversability estimation is in direct opposition to the limited sensing and compute capability present on affordable, small-scale mobile robots. To address this issue, w...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	472,282
2410.03878	SPARTUN3D: Situated Spatial Understanding of 3D World in Large Language Models	Integrating the 3D world into large language models (3D-based LLMs) has been a promising research direction for 3D scene understanding. However, current 3D-based LLMs fall short in situated understanding due to two key limitations: 1) existing 3D datasets are constructed from a global perspective of the 3D scenes and l...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	495,021
1810.02766	Hierarchical Recurrent Filtering for Fully Convolutional DenseNets	Generating a robust representation of the environment is a crucial ability of learning agents. Deep learning based methods have greatly improved perception systems but still fail in challenging situations. These failures are often not solvable on the basis of a single image. In this work, we present a parameter-efficie...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	109,657
2407.06658	TriQXNet: Forecasting Dst Index from Solar Wind Data Using an Interpretable Parallel Classical-Quantum Framework with Uncertainty Quantification	Geomagnetic storms, caused by solar wind energy transfer to Earth's magnetic field, can disrupt critical infrastructure like GPS, satellite communications, and power grids. The disturbance storm-time (Dst) index measures storm intensity. Despite advancements in empirical, physics-based, and machine-learning models usin...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	471,486
2006.02682	Some Theoretical Insights into Wasserstein GANs	Generative Adversarial Networks (GANs) have been successful in producing outstanding results in areas as diverse as image, video, and text generation. Building on these successes, a large number of empirical studies have validated the benefits of the cousin approach called Wasserstein GANs (WGANs), which brings stabili...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	180,112
1912.06977	Estimation and Validation of Ratio-based Conditional Average Treatment Effects Using Observational Data	While sample sizes in randomized clinical trials are large enough to estimate the average treatment effect well, they are often insufficient for estimation of treatment-covariate interactions critical to studying data-driven precision medicine. Observational data from real world practice may play an important role in a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	157,481
2304.09121	Fast Neural Scene Flow	Neural Scene Flow Prior (NSFP) is of significant interest to the vision community due to its inherent robustness to out-of-distribution (OOD) effects and its ability to deal with dense lidar points. The approach utilizes a coordinate neural network to estimate scene flow at runtime, without any training. However, it is...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	358,950
2302.11426	Mining compact high utility sequential patterns	High utility sequential pattern mining (HUSPM) aims to mine all patterns that yield a high utility (profit) in a sequence dataset. HUSPM is useful for several applications such as market basket analysis, marketing, and website clickstream analysis. In these applications, users may also consider high utility patterns fr...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	347,206
2210.04143	Strong Gravitational Lensing Parameter Estimation with Vision Transformer	Quantifying the parameters and corresponding uncertainties of hundreds of strongly lensed quasar systems holds the key to resolving one of the most important scientific questions: the Hubble constant ($H_{0}$) tension. The commonly used Markov chain Monte Carlo (MCMC) method has been too time-consuming to achieve this ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	322,322
2111.10557	HybNet: A Hybrid Deep Learning -- Matched Filter Approach for IoT Signal Detection	Random access schemes are widely used in IoT wireless access networks to accommodate simplicity and power consumption constraints. As a result, the interference arising from overlapping IoT transmissions is a significant issue in such networks. Traditional signal detection methods are based on the well-established matc...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	267,361
1707.07816	Small-Scale, Local Area, and Transitional Millimeter Wave Propagation for 5G Communications	This paper studies radio propagation mechanisms that impact handoffs, air interface design, beam steering, and MIMO for 5G mobile communication systems. Knife edge diffraction (KED) and a creeping wave linear model are shown to predict diffraction loss around typical building objects from 10 to 26 GHz, and human blocka...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	77,700
2502.04384	Enhancing Reasoning to Adapt Large Language Models for Domain-Specific Applications	This paper presents SOLOMON, a novel Neuro-inspired Large Language Model (LLM) Reasoning Network architecture that enhances the adaptability of foundation models for domain-specific applications. Through a case study in semiconductor layout design, we demonstrate how SOLOMON enables swift adaptation of general-purpose ...	false	false	false	false	true	false	true	false	true	false	true	false	false	false	false	false	false	false	531,124
1401.3830	Interactive Cost Configuration Over Decision Diagrams	In many AI domains such as product configuration, a user should interactively specify a solution that must satisfy a set of constraints. In such scenarios, offline compilation of feasible solutions into a tractable representation is an important approach to delivering efficient backtrack-free user interaction online. I...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	29,948
2310.14581	Leveraging Image-Text Similarity and Caption Modification for the DataComp Challenge: Filtering Track and BYOD Track	Large web crawl datasets have already played an important role in learning multimodal features with high generalization capabilities. However, there are still very limited studies investigating the details or improvements of data design. Recently, a DataComp challenge has been designed to propose the best training data...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	401,928
1012.3951	Diffusion-geometric maximally stable component detection in deformable shapes	Maximally stable component detection is a very popular method for feature analysis in images, mainly due to its low computation cost and high repeatability. With the recent advance of feature-based methods in geometric shape analysis, there is significant interest in finding analogous approaches in the 3D world. In thi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	8,577
2110.04182	Temporal Convolutions for Multi-Step Quadrotor Motion Prediction	Model-based control methods for robotic systems such as quadrotors, autonomous driving vehicles and flexible manipulators require motion models that generate accurate predictions of complex nonlinear system dynamics over long periods of time. Temporal Convolutional Networks (TCNs) can be adapted to this challenge by fo...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	259,789
2110.14980	Multivariate Empirical Mode Decomposition based Hybrid Model for Day-ahead Peak Load Forecasting	Accurate day-ahead peak load forecasting is crucial not only for power dispatching but also has a great interest to investors and energy policy maker as well as government. Literature reveals that 1% error drop of forecast can reduce 10 million pounds operational cost. Thus, this study proposed a novel hybrid predictiv...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	263,717
2402.16421	Outline-Guided Object Inpainting with Diffusion Models	Instance segmentation datasets play a crucial role in training accurate and robust computer vision models. However, obtaining accurate mask annotations to produce high-quality segmentation datasets is a costly and labor-intensive process. In this work, we show how this issue can be mitigated by starting with small anno...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	432,566
2410.14934	Development of a Simple and Novel Digital Twin Framework for Industrial Robots in Intelligent robotics manufacturing	This paper has proposed an easily replicable and novel approach for developing a Digital Twin (DT) system for industrial robots in intelligent manufacturing applications. Our framework enables effective communication via Robot Web Service (RWS), while a real-time simulation is implemented in Unity 3D and Web-based Plat...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	500,269
2402.01768	Enriched Physics-informed Neural Networks for Dynamic Poisson-Nernst-Planck Systems	This paper proposes a meshless deep learning algorithm, enriched physics-informed neural networks (EPINNs), to solve dynamic Poisson-Nernst-Planck (PNP) equations with strong coupling and nonlinear characteristics. The EPINNs takes the traditional physics-informed neural networks as the foundation framework, and adds t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	426,208
1804.02980	Compact Formulation of the First Evolution Equation for Optimal Control Computation	The first evolution equation is derived under the Variation Evolving Method (VEM) that seeks optimal solutions with the variation evolution principle. To improve the performance, its compact form is developed. By replacing the states and costates variation evolution with that of the controls, the dimension-reduced Evol...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	94,535
2303.02309	Interactive Trajectory Planner for Mandatory Lane Changing in Dense Non-Cooperative Traffic	When the traffic stream is extremely congested and surrounding vehicles are not cooperative, the mandatory lane changing can be significantly difficult. In this work, we propose an interactive trajectory planner, which will firstly attempt to change lanes as long as safety is ensured. Based on receding horizon planning...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	349,298
2303.10323	Dynamic Graph Enhanced Contrastive Learning for Chest X-ray Report Generation	Automatic radiology reporting has great clinical potential to relieve radiologists from heavy workloads and improve diagnosis interpretation. Recently, researchers have enhanced data-driven neural networks with medical knowledge graphs to eliminate the severe visual and textual bias in this task. The structures of such...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	352,395
1712.07512	Ethical Questions in NLP Research: The (Mis)-Use of Forensic Linguistics	Ideas from forensic linguistics are now being used frequently in Natural Language Processing (NLP), using machine learning techniques. While the role of forensic linguistics was more benign earlier, it is now being used for purposes which are questionable. Certain methods from forensic linguistics are employed, without...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	87,057
2102.13382	Batch Bayesian Optimization on Permutations using the Acquisition Weighted Kernel	In this work we propose a batch Bayesian optimization method for combinatorial problems on permutations, which is well suited for expensive-to-evaluate objectives. We first introduce LAW, an efficient batch acquisition method based on determinantal point processes using the acquisition weighted kernel. Relying on multi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	222,047
2404.10318	SRGS: Super-Resolution 3D Gaussian Splatting	Recently, 3D Gaussian Splatting (3DGS) has gained popularity as a novel explicit 3D representation. This approach relies on the representation power of Gaussian primitives to provide a high-quality rendering. However, primitives optimized at low resolution inevitably exhibit sparsity and texture deficiency, posing a ch...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	447,049
2306.02866	Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance	We present a novel framework to overcome the limitations of equivariant architectures in learning functions with group symmetries. In contrary to equivariant architectures, we use an arbitrary base model such as an MLP or a transformer and symmetrize it to be equivariant to the given group by employing a small equivari...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	371,089
1206.0338	Poisson noise reduction with non-local PCA	Photon-limited imaging arises when the number of photons collected by a sensor array is small relative to the number of detector elements. Photon limitations are an important concern for many applications such as spectral imaging, night vision, nuclear medicine, and astronomy. Typically a Poisson distribution is used t...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	16,291
2011.01578	Risk-Averse Planning via CVaR Barrier Functions: Application to Bipedal Robot Locomotion	Enforcing safety in the presence of stochastic uncertainty is a challenging problem. Traditionally, researchers have proposed safety in the statistical mean as a safety measure in this case. However, ensuring safety in the statistical mean is only reasonable if system's safe behavior in the large number of runs is of i...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	204,635
2412.00773	DIVD: Deblurring with Improved Video Diffusion Model	Video deblurring presents a considerable challenge owing to the complexity of blur, which frequently results from a combination of camera shakes, and object motions. In the field of video deblurring, many previous works have primarily concentrated on distortion-based metrics, such as PSNR. However, this approach often ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	512,813
1609.08442	Collaborative Learning for Language and Speaker Recognition	This paper presents a unified model to perform language and speaker recognition simultaneously and altogether. The model is based on a multi-task recurrent neural network where the output of one task is fed as the input of the other, leading to a collaborative learning framework that can improve both language and speak...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	61,599
2410.20806	Transformer-Based Tooth Alignment Prediction With Occlusion And Collision Constraints	The planning of digital orthodontic treatment requires providing tooth alignment, which not only consumes a lot of time and labor to determine manually but also relays clinical experiences heavily. In this work, we proposed a lightweight tooth alignment neural network based on Swin-transformer. We first re-organized 3D...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	502,972
1709.04969	Cross-Platform Emoji Interpretation: Analysis, a Solution, and Applications	Most social media platforms are largely based on text, and users often write posts to describe where they are, what they are seeing, and how they are feeling. Because written text lacks the emotional cues of spoken and face-to-face dialogue, ambiguities are common in written language. This problem is exacerbated in the...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	80,759
1606.07784	Satellite Images Analysis with Symbolic Time Series: A Case Study of the Algerian Zone	Satellite Image Time Series (SITS) are an important source of information for studying land occupation and its evolution. Indeed, the very large volumes of digital data stored, usually are not ready to a direct analysis. In order to both reduce the dimensionality and information extraction, time series data mining gene...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	57,782
2210.15808	Hyper-Connected Transformer Network for Multi-Modality PET-CT Segmentation	[18F]-Fluorodeoxyglucose (FDG) positron emission tomography - computed tomography (PET-CT) has become the imaging modality of choice for diagnosing many cancers. Co-learning complementary PET-CT imaging features is a fundamental requirement for automatic tumor segmentation and for developing computer aided cancer diagn...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	327,092
1612.02177	Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurring	Non-uniform blind deblurring for general dynamic scenes is a challenging computer vision problem as blurs arise not only from multiple object motions but also from camera shake, scene depth variation. To remove these complicated motion blurs, conventional energy optimization based methods rely on simple assumptions suc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	65,199
2103.03700	Analyzing the Influence of Dataset Composition for Emotion Recognition	Recognizing emotions from text in multimodal architectures has yielded promising results, surpassing video and audio modalities under certain circumstances. However, the method by which multimodal data is collected can be significant for recognizing emotional features in language. In this paper, we address the influenc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	223,378
2403.05874	SPAFormer: Sequential 3D Part Assembly with Transformers	We introduce SPAFormer, an innovative model designed to overcome the combinatorial explosion challenge in the 3D Part Assembly (3D-PA) task. This task requires accurate prediction of each part's poses in sequential steps. As the number of parts increases, the possible assembly combinations increase exponentially, leadi...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	436,197
1902.09697	Polyglot Contextual Representations Improve Crosslingual Transfer	We introduce Rosita, a method to produce multilingual contextual word representations by training a single language model on text from multiple languages. Our method combines the advantages of contextual word representations with those of multilingual representation learning. We produce language models from dissimilar ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	122,475
1905.07469	4D Seismic History Matching Incorporating Unsupervised Learning	The work discussed and presented in this paper focuses on the history matching of reservoirs by integrating 4D seismic data into the inversion process using machine learning techniques. A new integrated scheme for the reconstruction of petrophysical properties with a modified Ensemble Smoother with Multiple Data Assimi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	131,240
2008.12692	Challenges and opportunities of inertia estimation and forecasting in low-inertia power systems	Accurate inertia estimates and forecasts are crucial to support the system operation in future low-inertia power systems. A large literature on inertia estimation methods is available. This paper aims to provide an overview and classification of inertia estimation methods. The classification considers the time horizon ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	193,654
2209.06427	Efficient low-thrust trajectory data generation based on generative adversarial network	Deep learning-based techniques have been introduced into the field of trajectory optimization in recent years. Deep Neural Networks (DNNs) are trained and used as the surrogates of conventional optimization process. They can provide low thrust (LT) transfer cost estimation and enable more complex preliminary mission de...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	317,402
2412.19002	Tempus Core: Area-Power Efficient Temporal-Unary Convolution Core for Low-Precision Edge DLAs	The increasing complexity of deep neural networks (DNNs) poses significant challenges for edge inference deployment due to resource and power constraints of edge devices. Recent works on unary-based matrix multiplication hardware aim to leverage data sparsity and low-precision values to enhance hardware efficiency. How...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	520,674
1108.5140	A convex formulation of strict anisotropic norm bounded real lemma	This paper is aimed at extending the H-infinity Bounded Real Lemma to stochastic systems under random disturbances with imprecisely known probability distributions. The statistical uncertainty is measured in entropy theoretic terms using the mean anisotropy functional. The disturbance attenuation capabilities of the sy...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	11,817
2401.08117	E2HQV: High-Quality Video Generation from Event Camera via Theory-Inspired Model-Aided Deep Learning	The bio-inspired event cameras or dynamic vision sensors are capable of asynchronously capturing per-pixel brightness changes (called event-streams) in high temporal resolution and high dynamic range. However, the non-structural spatial-temporal event-streams make it challenging for providing intuitive visualization wi...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	true	false	true	421,770
2401.05373	Dynamic Spiking Framework for Graph Neural Networks	The integration of Spiking Neural Networks (SNNs) and Graph Neural Networks (GNNs) is gradually attracting attention due to the low power consumption and high efficiency in processing the non-Euclidean data represented by graphs. However, as a common problem, dynamic graph representation learning faces challenges such ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	420,740
1910.09716	A deep active learning system for species identification and counting in camera trap images	Biodiversity conservation depends on accurate, up-to-date information about wildlife population distributions. Motion-activated cameras, also known as camera traps, are a critical tool for population surveys, as they are cheap and non-intrusive. However, extracting useful information from camera trap images is a cumber...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	150,279
2012.10384	Hybrid Genetic Search for the CVRP: Open-Source Implementation and SWAP* Neighborhood	The vehicle routing problem is one of the most studied combinatorial optimization topics, due to its practical importance and methodological interest. Yet, despite extensive methodological progress, many recent studies are hampered by the limited access to simple and efficient open-source solution methods. Given the so...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	212,331
2210.00001	Geometrically exact isogeometric Bernoulli-Euler beam based on the Frenet-Serret frame	A novel geometrically exact model of the spatially curved Bernoulli-Euler beam is developed. The formulation utilizes the Frenet-Serret frame as the reference for updating the orientation of a cross section. The weak form is consistently derived and linearized, including the contributions from kinematic constraints and...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	320,687
1904.02663	Algebraic Characterization of Essential Matrices and Their Averaging in Multiview Settings	Essential matrix averaging, i.e., the task of recovering camera locations and orientations in calibrated, multiview settings, is a first step in global approaches to Euclidean structure from motion. A common approach to essential matrix averaging is to separately solve for camera orientations and subsequently for camer...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	126,489
1407.3567	Two approaches to obtain the strong converse exponent of quantum hypothesis testing for general sequences of quantum states	We present two general approaches to obtain the strong converse rate of quantum hypothesis testing for correlated quantum states. One approach requires that the states satisfy a certain factorization property; typical examples of such states are the temperature states of translation-invariant finite-range interactions ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	34,635
2304.00413	The Archive Query Log: Mining Millions of Search Result Pages of Hundreds of Search Engines from 25 Years of Web Archives	The Archive Query Log (AQL) is a previously unused, comprehensive query log collected at the Internet Archive over the last 25 years. Its first version includes 356 million queries, 166 million search result pages, and 1.7 billion search results across 550 search providers. Although many query logs have been studied in...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	355,675
0910.1863	Computational Complexity of Decoding Orthogonal Space-Time Block Codes	The computational complexity of optimum decoding for an orthogonal space-time block code G satisfying the orthogonality property that the Hermitian transpose of G multiplied by G is equal to a constant c times the sum of the squared symbols of the code times an identity matrix, where c is a positive integer is quantifi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	4,696
2203.01826	Improving Non-native Word-level Pronunciation Scoring with Phone-level Mixup Data Augmentation and Multi-source Information	Deep learning-based pronunciation scoring models highly rely on the availability of the annotated non-native data, which is costly and has scalability issues. To deal with the data scarcity problem, data augmentation is commonly used for model pretraining. In this paper, we propose a phone-level mixup, a simple yet eff...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	283,522
1506.04836	Free Space Optical Communication: Challenges and Mitigation Techniques	In recent years, free space optical (FSO) communication has gained significant importance owing to its unique features: large bandwidth, license free spectrum, high data rate, easy and quick deployability, less power and low mass requirement. FSO communication uses optical carrier in the near infrared (IR) and visible ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	44,221
2003.11622	Predicting Unplanned Readmissions with Highly Unstructured Data	Deep learning techniques have been successfully applied to predict unplanned readmissions of patients in medical centers. The training data for these models is usually based on historical medical records that contain a significant amount of free-text from admission reports, referrals, exam notes, etc. Most of the model...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	169,660
1401.2804	Insights into analysis operator learning: From patch-based sparse models to higher-order MRFs	This paper addresses a new learning algorithm for the recently introduced co-sparse analysis model. First, we give new insights into the co-sparse analysis model by establishing connections to filter-based MRF models, such as the Field of Experts (FoE) model of Roth and Black. For training, we introduce a technique cal...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	29,784
1711.07695	Fully Convolutional Neural Networks for Page Segmentation of Historical Document Images	We propose a high-performance fully convolutional neural network (FCN) for historical document segmentation that is designed to process a single page in one step. The advantage of this model beside its speed is its ability to directly learn from raw pixels instead of using preprocessing steps e. g. feature computation ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	85,054
2203.12818	Random Forest Regression for continuous affect using Facial Action Units	In this paper we describe our approach to the arousal and valence track of the 3rd Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW). We extracted facial features using OpenFace and used them to train a multiple output random forest regressor. Our approach performed comparable to the baseline a...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	287,401
2202.06242	Beyond NaN: Resiliency of Optimization Layers in The Face of Infeasibility	Prior work has successfully incorporated optimization layers as the last layer in neural networks for various problems, thereby allowing joint learning and planning in one neural network forward pass. In this work, we identify a weakness in such a set-up where inputs to the optimization layer lead to undefined output o...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	280,151
2411.06011	Exploring the Impact of Reflexivity Theory and Cognitive Social Structures on the Dynamics of Doctor-Patient Social System	Conventional economic and socio-behavioural models assume perfect symmetric access to information and rational behaviour among interacting agents in a social system. However, real-world events and observations appear to contradict such assumptions, leading to the possibility of other, more complex interaction rules exi...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	false	506,930
2408.10040	The Practimum-Optimum Algorithm for Manufacturing Scheduling: A Paradigm Shift Leading to Breakthroughs in Scale and Performance	The Practimum-Optimum (P-O) algorithm represents a paradigm shift in developing automatic optimization products for complex real-life business problems such as large-scale manufacturing scheduling. It leverages deep business domain expertise to create a group of virtual human expert (VHE) agents with different "schools...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	481,695
2004.02844	Complexity of majorants	The minimal Kolmogorov complexity of a total computable function that exceeds everywhere all total computable functions of complexity at most $n$, is $2^{n+O(1)}$. If we replace "everywhere" by "for all sufficiently large inputs", the answer is $n+O(1)$.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	171,361
2403.18260	Toward Interactive Regional Understanding in Vision-Large Language Models	Recent Vision-Language Pre-training (VLP) models have demonstrated significant advancements. Nevertheless, these models heavily rely on image-text pairs that capture only coarse and global information of an image, leading to a limitation in their regional understanding ability. In this work, we introduce \textbf{Region...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	441,850
2307.04312	Robust Feature Learning Against Noisy Labels	Supervised learning of deep neural networks heavily relies on large-scale datasets annotated by high-quality labels. In contrast, mislabeled samples can significantly degrade the generalization of models and result in memorizing samples, further learning erroneous associations of data contents to incorrect annotations....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	378,353
2303.06048	VALERIAN: Invariant Feature Learning for IMU Sensor-based Human Activity Recognition in the Wild	Deep neural network models for IMU sensor-based human activity recognition (HAR) that are trained from controlled, well-curated datasets suffer from poor generalizability in practical deployments. However, data collected from naturalistic settings often contains significant label noise. In this work, we examine two in-...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	350,678
2401.07348	Generative AI in EU Law: Liability, Privacy, Intellectual Property, and Cybersecurity	The advent of Generative AI, particularly through Large Language Models (LLMs) like ChatGPT and its successors, marks a paradigm shift in the AI landscape. Advanced LLMs exhibit multimodality, handling diverse data formats, thereby broadening their application scope. However, the complexity and emergent autonomy of the...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	421,501
1310.1869	Singular Value Decomposition of Images from Scanned Photographic Plates	We want to approximate the mxn image A from scanned astronomical photographic plates (from the Sofia Sky Archive Data Center) by using far fewer entries than in the original matrix. By using rank of a matrix, k we remove the redundant information or noise and use as Wiener filter, when rank k<m or k<n. With this approx...	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	27,608
2406.11325	Deep-Learning-Based Channel Estimation for Distributed MIMO with 1-bit Radio-Over-Fiber Fronthaul	We consider the problem of pilot-aided, uplink channel estimation in a distributed massive multiple-input multiple-output (MIMO) architecture, in which the access points are connected to a central processing unit via fiber-optical fronthaul links, carrying a two-level-quantized version of the received analog radio-freq...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	464,843
2403.12061	Design-Space Exploration of SNN Models using Application-Specific Multi-Core Architectures	With the motivation and the difficulties that currently exist in comprehending and utilizing the promising features of SNNs, we proposed a novel run-time multi-core architecture-based simulator called "RAVSim" (Runtime Analysis and Visualization Simulator), a cutting-edge SNN simulator, developed using LabVIEW and it i...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	439,013
2403.18308	Comparison of different methods for identification of dominant oscillation mode	This paper introduces and compares the various techniques for identification and analysis of low frequency oscillations in a power system. Inter-area electromechanical oscillations are the focus of this paper. After multiresolution decomposition of characteristic signals, physical characteristics of system oscillations...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	441,875
2112.10572	General Greedy De-bias Learning	Neural networks often make predictions relying on the spurious correlations from the datasets rather than the intrinsic properties of the task of interest, facing sharp degradation on out-of-distribution (OOD) test data. Existing de-bias learning frameworks try to capture specific dataset bias by annotations but they f...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	272,471
1809.05818	Unbiased LambdaMART: An Unbiased Pairwise Learning-to-Rank Algorithm	Although click data is widely used in search systems in practice, so far the inherent bias, most notably position bias, has prevented it from being used in training of a ranker for search, i.e., learning-to-rank. Recently, a number of authors have proposed new techniques referred to as 'unbiased learning-to-rank', whic...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	107,879
2210.09843	BIOWISH: Biometric Recognition using Wearable Inertial Sensors detecting Heart Activity	Wearable devices are increasingly used, thanks to the wide set of applications that can be deployed exploiting their ability to monitor physical activity and health-related parameters. Their usage has been recently proposed to perform biometric recognition, leveraging on the uniqueness of the recorded traits to generat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	324,690
2211.13316	Understanding Sample Generation Strategies for Learning Heuristic Functions in Classical Planning	We study the problem of learning good heuristic functions for classical planning tasks with neural networks based on samples represented by states with their cost-to-goal estimates. The heuristic function is learned for a state space and goal condition with the number of samples limited to a fraction of the size of the...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	332,432
2211.09113	On Measuring the Intrinsic Few-Shot Hardness of Datasets	While advances in pre-training have led to dramatic improvements in few-shot learning of NLP tasks, there is limited understanding of what drives successful few-shot adaptation in datasets. In particular, given a new dataset and a pre-trained model, what properties of the dataset make it \emph{few-shot learnable} and a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	330,881
1008.3829	Approximate Judgement Aggregation	In this paper we analyze judgement aggregation problems in which a group of agents independently votes on a set of complex propositions that has some interdependency constraint between them(e.g., transitivity when describing preferences). We consider the issue of judgement aggregation from the perspective of approximat...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	7,344
2411.12036	Prediction-Guided Active Experiments	In this work, we introduce a new framework for active experimentation, the Prediction-Guided Active Experiment (PGAE), which leverages predictions from an existing machine learning model to guide sampling and experimentation. Specifically, at each time step, an experimental unit is sampled according to a designated sam...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	509,269
2409.14163	PromptTA: Prompt-driven Text Adapter for Source-free Domain Generalization	Source-free domain generalization (SFDG) tackles the challenge of adapting models to unseen target domains without access to source domain data. To deal with this challenging task, recent advances in SFDG have primarily focused on leveraging the text modality of vision-language models such as CLIP. These methods involv...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	490,351
2105.12436	Social-IWSTCNN: A Social Interaction-Weighted Spatio-Temporal Convolutional Neural Network for Pedestrian Trajectory Prediction in Urban Traffic Scenarios	Pedestrian trajectory prediction in urban scenarios is essential for automated driving. This task is challenging because the behavior of pedestrians is influenced by both their own history paths and the interactions with others. Previous research modeled these interactions with pooling mechanisms or aggregating with ha...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	237,012
1309.1516	On Secrecy Capacity of Fast Fading MIMOME Wiretap Channels With Statistical CSIT	In this paper, we consider secure transmissions in ergodic Rayleigh fast-faded multiple-input multiple-output multiple-antenna-eavesdropper (MIMOME) wiretap channels with only statistical channel state information at the transmitter (CSIT). When the legitimate receiver has more (or equal) antennas than the eavesdropper...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	26,866
2501.14625	Accelerated Preference Elicitation with LLM-Based Proxies	Bidders in combinatorial auctions face significant challenges when describing their preferences to an auctioneer. Classical work on preference elicitation focuses on query-based techniques inspired from proper learning--often via proxies that interface between bidders and an auction mechanism--to incrementally learn bi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	527,191
1302.4937	Decision Flexibility	The development of new methods and representations for temporal decision-making requires a principled basis for characterizing and measuring the flexibility of decision strategies in the face of uncertainty. Our goal in this paper is to provide a framework - not a theory - for observing how decision policies behave in ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	22,211
2303.04997	Optimization-Based Eye Tracking using Deflectometric Information	Eye tracking is an important tool with a wide range of applications in Virtual, Augmented, and Mixed Reality (VR/AR/MR) technologies. State-of-the-art eye tracking methods are either reflection-based and track reflections of sparse point light sources, or image-based and exploit 2D features of the acquired eye image. I...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	350,292
2306.15898	Pseudo-Labeling Enhanced by Privileged Information and Its Application to In Situ Sequencing Images	Various strategies for label-scarce object detection have been explored by the computer vision research community. These strategies mainly rely on assumptions that are specific to natural images and not directly applicable to the biological and biomedical vision domains. For example, most semi-supervised learning strat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	376,193
1707.02745	Object Handover Prediction using Gaussian Processes clustered with Trajectory Classification	A robotic system which approximates the user intention and appropriate complimentary motion is critical for successful human-robot interaction. %While the existing wearable sensors can monitor human movements in real-time, prediction of human movement is a significant challenge due to its highly non-linear motions opti...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	76,749
2408.10357	Beyond Relevant Documents: A Knowledge-Intensive Approach for Query-Focused Summarization using Large Language Models	Query-focused summarization (QFS) is a fundamental task in natural language processing with broad applications, including search engines and report generation. However, traditional approaches assume the availability of relevant documents, which may not always hold in practical scenarios, especially in highly specialize...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	481,818
2303.08070	Victoria Amazonica Optimization (VAO): An Algorithm Inspired by the Giant Water Lily Plant	The Victoria Amazonica plant, often known as the Giant Water Lily, has the largest floating spherical leaf in the world, with a maximum leaf diameter of 3 meters. It spreads its leaves by the force of its spines and creates a large shadow underneath, killing any plants that require sunlight. These water tyrants use the...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	351,496
2203.12201	Towards Expressive Speaking Style Modelling with Hierarchical Context Information for Mandarin Speech Synthesis	Previous works on expressive speech synthesis mainly focus on current sentence. The context in adjacent sentences is neglected, resulting in inflexible speaking style for the same text, which lacks speech variations. In this paper, we propose a hierarchical framework to model speaking style from context. A hierarchical...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	287,179
2011.08181	A Random Matrix Theory Approach to Damping in Deep Learning	We conjecture that the inherent difference in generalisation between adaptive and non-adaptive gradient methods in deep learning stems from the increased estimation noise in the flattest directions of the true loss surface. We demonstrate that typical schedules used for adaptive methods (with low numerical stability or...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	206,802

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