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
1708.01977	Why Adaptively Collected Data Have Negative Bias and How to Correct for It	From scientific experiments to online A/B testing, the previously observed data often affects how future experiments are performed, which in turn affects which data will be collected. Such adaptivity introduces complex correlations between the data and the collection procedure. In this paper, we prove that when the dat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	78,496
2412.17542	Leveraging Cardiovascular Simulations for In-Vivo Prediction of Cardiac Biomarkers	Whole-body hemodynamics simulators, which model blood flow and pressure waveforms as functions of physiological parameters, are now essential tools for studying cardiovascular systems. However, solving the corresponding inverse problem of mapping observations (e.g., arterial pressure waveforms at specific locations in ...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	520,018
1710.09323	Recursion Aware Modeling and Discovery For Hierarchical Software Event Log Analysis (Extended)	This extended paper presents 1) a novel hierarchy and recursion extension to the process tree model; and 2) the first, recursion aware process model discovery technique that leverages hierarchical information in event logs, typically available for software systems. This technique allows us to analyze the operational pr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	83,192
2208.07756	Time Minimization and Online Synchronization for Multi-agent Systems under Collaborative Temporal Tasks	Multi-agent systems can be extremely efficient when solving a team-wide task in a concurrent manner. However, without proper synchronization, the correctness of the combined behavior is hard to guarantee, such as to follow a specific ordering of sub-tasks or to perform a simultaneous collaboration. This work addresses ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	313,148
2005.07939	Predicting into unknown space? Estimating the area of applicability of spatial prediction models	Predictive modelling using machine learning has become very popular for spatial mapping of the environment. Models are often applied to make predictions far beyond sampling locations where new geographic locations might considerably differ from the training data in their environmental properties. However, areas in the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	177,445
2308.10875	Applications of Nature-Inspired Metaheuristic Algorithms for Tackling Optimization Problems Across Disciplines	Nature-inspired metaheuristic algorithms are important components of artificial intelligence, and are increasingly used across disciplines to tackle various types of challenging optimization problems. This paper demonstrates the usefulness of such algorithms for solving a variety of challenging optimization problems in...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	386,920
1606.05664	Linear Classification of data with Support Vector Machines and Generalized Support Vector Machines	In this paper, we study the support vector machine and introduced the notion of generalized support vector machine for classification of data. We show that the problem of generalized support vector machine is equivalent to the problem of generalized variational inequality and establish various results for the existence...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	57,441
1904.02331	Extract and Edit: An Alternative to Back-Translation for Unsupervised Neural Machine Translation	The overreliance on large parallel corpora significantly limits the applicability of machine translation systems to the majority of language pairs. Back-translation has been dominantly used in previous approaches for unsupervised neural machine translation, where pseudo sentence pairs are generated to train the models ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	126,396
2311.15545	Out-of-Distribution Generalized Dynamic Graph Neural Network for Human Albumin Prediction	Human albumin is essential for indicating the body's overall health. Accurately predicting plasma albumin levels and determining appropriate doses are urgent clinical challenges, particularly in critically ill patients, to maintain optimal blood levels. However, human albumin prediction is non-trivial that has to lever...	false	true	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	410,550
2002.00797	Stochastic geometry to generalize the Mondrian Process	The stable under iterated tessellation (STIT) process is a stochastic process that produces a recursive partition of space with cut directions drawn independently from a distribution over the sphere. The case of random axis-aligned cuts is known as the Mondrian process. Random forests and Laplace kernel approximations ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	162,472
1402.6763	Linear Programming for Large-Scale Markov Decision Problems	We consider the problem of controlling a Markov decision process (MDP) with a large state space, so as to minimize average cost. Since it is intractable to compete with the optimal policy for large scale problems, we pursue the more modest goal of competing with a low-dimensional family of policies. We use the dual lin...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	31,200
1603.07954	Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning	Most successful information extraction systems operate with access to a large collection of documents. In this work, we explore the task of acquiring and incorporating external evidence to improve extraction accuracy in domains where the amount of training data is scarce. This process entails issuing search queries, ex...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	53,689
2403.07889	Reconfigurable Intelligent Surfaces for THz: Hardware Design and Signal Processing Challenges	Wireless communications in the THz frequency band is an envisioned revolutionary technology for sixth Generation (6G) networks. However, such frequencies impose certain coverage and device design challenges that need to be efficiently overcome. To this end, the development of cost- and energy-efficient approaches for s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	437,073
2208.06988	IRL with Partial Observations using the Principle of Uncertain Maximum Entropy	The principle of maximum entropy is a broadly applicable technique for computing a distribution with the least amount of information possible while constrained to match empirically estimated feature expectations. However, in many real-world applications that use noisy sensors computing the feature expectations may be c...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	312,899
2501.16396	TopoNets: High Performing Vision and Language Models with Brain-Like Topography	Neurons in the brain are organized such that nearby cells tend to share similar functions. AI models lack this organization, and past efforts to introduce topography have often led to trade-offs between topography and task performance. In this work, we present TopoLoss, a new loss function that promotes spatially organ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	527,958
2302.05206	The Wisdom of Hindsight Makes Language Models Better Instruction Followers	Reinforcement learning has seen wide success in finetuning large language models to better align with instructions via human feedback. The so-called algorithm, Reinforcement Learning with Human Feedback (RLHF) demonstrates impressive performance on the GPT series models. However, the underlying Reinforcement Learning (...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	344,968
2306.12525	LPFormer: LiDAR Pose Estimation Transformer with Multi-Task Network	Due to the difficulty of acquiring large-scale 3D human keypoint annotation, previous methods for 3D human pose estimation (HPE) have often relied on 2D image features and sequential 2D annotations. Furthermore, the training of these networks typically assumes the prediction of a human bounding box and the accurate ali...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	374,966
2305.02795	Class-Distribution-Aware Pseudo Labeling for Semi-Supervised Multi-Label Learning	Pseudo-labeling has emerged as a popular and effective approach for utilizing unlabeled data. However, in the context of semi-supervised multi-label learning (SSMLL), conventional pseudo-labeling methods encounter difficulties when dealing with instances associated with multiple labels and an unknown label count. These...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	362,175
2006.13575	Large-scale detection and categorization of oil spills from SAR images with deep learning	We propose a deep learning framework to detect and categorize oil spills in synthetic aperture radar (SAR) images at a large scale. By means of a carefully designed neural network model for image segmentation trained on an extensive dataset, we are able to obtain state-of-the-art performance in oil spill detection, ach...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	183,963
2312.03807	Achieving ${O}(\epsilon^{-1.5})$ Complexity in Hessian/Jacobian-free Stochastic Bilevel Optimization	In this paper, we revisit the bilevel optimization problem, in which the upper-level objective function is generally nonconvex and the lower-level objective function is strongly convex. Although this type of problem has been studied extensively, it still remains an open question how to achieve an ${O}(\epsilon^{-1.5})$...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	413,445
2105.14421	VersatileGait: A Large-Scale Synthetic Gait Dataset Towards in-the-Wild Simulation	Gait recognition has a rapid development in recent years. However, gait recognition in the wild is not well explored yet. An obvious reason could be ascribed to the lack of diverse training data from the perspective of intrinsic and extrinsic factors. To remedy this problem, we propose to construct a large-scale gait d...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	237,662
2208.08910	Learned Indexing in Proteins: Extended Work on Substituting Complex Distance Calculations with Embedding and Clustering Techniques	Despite the constant evolution of similarity searching research, it continues to face the same challenges stemming from the complexity of the data, such as the curse of dimensionality and computationally expensive distance functions. Various machine learning techniques have proven capable of replacing elaborate mathema...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	313,533
2207.06726	Octuplet Loss: Make Face Recognition Robust to Image Resolution	Image resolution, or in general, image quality, plays an essential role in the performance of today's face recognition systems. To address this problem, we propose a novel combination of the popular triplet loss to improve robustness against image resolution via fine-tuning of existing face recognition models. With oct...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	307,972
2012.01536	Improving KernelSHAP: Practical Shapley Value Estimation via Linear Regression	The Shapley value concept from cooperative game theory has become a popular technique for interpreting ML models, but efficiently estimating these values remains challenging, particularly in the model-agnostic setting. Here, we revisit the idea of estimating Shapley values via linear regression to understand and improv...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	209,442
0905.2311	Residus de 2-formes differentielles sur les surfaces algebriques et applications aux codes correcteurs d'erreurs	The theory of algebraic-geometric codes has been developed in the beginning of the 80's after a paper of V.D. Goppa. Given a smooth projective algebraic curve X over a finite field, there are two different constructions of error-correcting codes. The first one, called "functional", uses some rational functions on X and...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	3,683
2403.06354	Amharic LLaMA and LLaVA: Multimodal LLMs for Low Resource Languages	Large Language Models (LLMs) like GPT-4 and LLaMA have shown incredible proficiency at natural language processing tasks and have even begun to excel at tasks across other modalities such as vision and audio. Despite their success, LLMs often struggle to perform well on low-resource languages because there is so little...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	436,407
1706.07639	Causal Embeddings for Recommendation	Many current applications use recommendations in order to modify the natural user behavior, such as to increase the number of sales or the time spent on a website. This results in a gap between the final recommendation objective and the classical setup where recommendation candidates are evaluated by their coherence wi...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	75,879
1902.03782	Exploring Explicit Domain Supervision for Latent Space Disentanglement in Unpaired Image-to-Image Translation	Image-to-image translation tasks have been widely investigated with Generative Adversarial Networks (GANs). However, existing approaches are mostly designed in an unsupervised manner while little attention has been paid to domain information within unpaired data. In this paper, we treat domain information as explicit s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	121,200
2202.13239	QOC: Quantum On-Chip Training with Parameter Shift and Gradient Pruning	Parameterized Quantum Circuits (PQC) are drawing increasing research interest thanks to its potential to achieve quantum advantages on near-term Noisy Intermediate Scale Quantum (NISQ) hardware. In order to achieve scalable PQC learning, the training process needs to be offloaded to real quantum machines instead of usi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	282,535
2301.12082	Pushing the Limits of Fewshot Anomaly Detection in Industry Vision: Graphcore	In the area of fewshot anomaly detection (FSAD), efficient visual feature plays an essential role in memory bank M-based methods. However, these methods do not account for the relationship between the visual feature and its rotated visual feature, drastically limiting the anomaly detection performance. To push the limi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	342,390
2207.10953	Visible and Near Infrared Image Fusion Based on Texture Information	Multi-sensor fusion is widely used in the environment perception system of the autonomous vehicle. It solves the interference caused by environmental changes and makes the whole driving system safer and more reliable. In this paper, a novel visible and near-infrared fusion method based on texture information is propose...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	309,457
2408.17005	Efficient Camera Exposure Control for Visual Odometry via Deep Reinforcement Learning	The stability of visual odometry (VO) systems is undermined by degraded image quality, especially in environments with significant illumination changes. This study employs a deep reinforcement learning (DRL) framework to train agents for exposure control, aiming to enhance imaging performance in challenging conditions....	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	484,539
2407.14953	AgileDART: An Agile and Scalable Edge Stream Processing Engine	Edge applications generate a large influx of sensor data on massive scales, and these massive data streams must be processed shortly to derive actionable intelligence. However, traditional data processing systems are not well-suited for these edge applications as they often do not scale well with a large number of conc...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	474,970
1607.04730	Spatio-Temporal Saliency Networks for Dynamic Saliency Prediction	Computational saliency models for still images have gained significant popularity in recent years. Saliency prediction from videos, on the other hand, has received relatively little interest from the community. Motivated by this, in this work, we study the use of deep learning for dynamic saliency prediction and propos...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	58,649
2405.00217	GMC-PINNs: A new general Monte Carlo PINNs method for solving fractional partial differential equations on irregular domains	Physics-Informed Neural Networks (PINNs) have been widely used for solving partial differential equations (PDEs) of different types, including fractional PDEs (fPDES) [29]. Herein, we propose a new general (quasi) Monte Carlo PINN for solving fPDEs on irregular domains. Specifically, instead of approximating fractional...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	450,832
2211.00543	Geo-Information Harvesting from Social Media Data	As unconventional sources of geo-information, massive imagery and text messages from open platforms and social media form a temporally quasi-seamless, spatially multi-perspective stream, but with unknown and diverse quality. Due to its complementarity to remote sensing data, geo-information from these sources offers pr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	327,911
2406.12362	Certified ML Object Detection for Surveillance Missions	In this paper, we present a development process of a drone detection system involving a machine learning object detection component. The purpose is to reach acceptable performance objectives and provide sufficient evidences, required by the recommendations (soon to be published) of the ED 324 / ARP 6983 standard, to ga...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	465,363
2309.04370	Seeing-Eye Quadruped Navigation with Force Responsive Locomotion Control	Seeing-eye robots are very useful tools for guiding visually impaired people, potentially producing a huge societal impact given the low availability and high cost of real guide dogs. Although a few seeing-eye robot systems have already been demonstrated, none considered external tugs from humans, which frequently occu...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	390,703
1909.01648	Regression-based sparse polynomial chaos for uncertainty quantification of subsurface flow models	Surrogate-modelling techniques including Polynomial Chaos Expansion (PCE) is commonly used for statistical estimation (aka. Uncertainty Quantification) of quantities of interests obtained from expensive computational models. PCE is a data-driven regression-based technique that relies on spectral polynomials as basis-fu...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	143,967
1805.10726	A Neurobiological Evaluation Metric for Neural Network Model Search	Neuroscience theory posits that the brain's visual system coarsely identifies broad object categories via neural activation patterns, with similar objects producing similar neural responses. Artificial neural networks also have internal activation behavior in response to stimuli. We hypothesize that networks exhibiting...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	98,754
2212.02848	SignNet: Single Channel Sign Generation using Metric Embedded Learning	A true interpreting agent not only understands sign language and translates to text, but also understands text and translates to signs. Much of the AI work in sign language translation to date has focused mainly on translating from signs to text. Towards the latter goal, we propose a text-to-sign translation model, Sig...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	334,912
2111.06386	Keyless Authentication for AWGN Channels	This work establishes that the physical layer can be used to perform information-theoretic authentication in additive white Gaussian noise channels, as long as the adversary is not omniscient. The model considered consists of an encoder, decoder, and adversary, where the adversary has access to the message, a non-causa...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	266,058
2409.19270	OpenSep: Leveraging Large Language Models with Textual Inversion for Open World Audio Separation	Audio separation in real-world scenarios, where mixtures contain a variable number of sources, presents significant challenges due to limitations of existing models, such as over-separation, under-separation, and dependence on predefined training sources. We propose OpenSep, a novel framework that leverages large langu...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	492,610
2412.06352	SeFENet: Robust Deep Homography Estimation via Semantic-Driven Feature Enhancement	Images captured in harsh environments often exhibit blurred details, reduced contrast, and color distortion, which hinder feature detection and matching, thereby affecting the accuracy and robustness of homography estimation. While visual enhancement can improve contrast and clarity, it may introduce visual-tolerant ar...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	515,215
1702.08410	Clustering in Discrete Path Planning for Approximating Minimum Length Paths	In this paper we consider discrete robot path planning problems on metric graphs. We propose a clustering method, Gamma-Clustering for the planning graph that significantly reduces the number of feasible solutions, yet retains a solution within a constant factor of the optimal. By increasing the input parameter Gamma, ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	68,979
2006.06158	0-MMS: Zero-Shot Multi-Motion Segmentation With A Monocular Event Camera	Segmentation of moving objects in dynamic scenes is a key process in scene understanding for navigation tasks. Classical cameras suffer from motion blur in such scenarios rendering them effete. On the contrary, event cameras, because of their high temporal resolution and lack of motion blur, are tailor-made for this pr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	181,329
1511.05538	Material degradation due to moisture and temperature. Part 1: Mathematical model, analysis, and analytical solutions	The mechanical response, serviceability, and load bearing capacity of materials and structural components can be adversely affected due to external stimuli, which include exposure to a corrosive chemical species, high temperatures, temperature fluctuations (i.e., freezing-thawing), cyclic mechanical loading, just to na...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	49,058
2309.09864	Learning Spatial and Temporal Hierarchies: Hierarchical Active Inference for navigation in Multi-Room Maze Environments	Cognitive maps play a crucial role in facilitating flexible behaviour by representing spatial and conceptual relationships within an environment. The ability to learn and infer the underlying structure of the environment is crucial for effective exploration and navigation. This paper introduces a hierarchical active in...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	392,771
2011.00573	Two-Level K-FAC Preconditioning for Deep Learning	In the context of deep learning, many optimization methods use gradient covariance information in order to accelerate the convergence of Stochastic Gradient Descent. In particular, starting with Adagrad, a seemingly endless line of research advocates the use of diagonal approximations of the so-called empirical Fisher ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	204,275
2207.11782	Enhancements to the BOUN Treebank Reflecting the Agglutinative Nature of Turkish	In this study, we aim to offer linguistically motivated solutions to resolve the issues of the lack of representation of null morphemes, highly productive derivational processes, and syncretic morphemes of Turkish in the BOUN Treebank without diverging from the Universal Dependencies framework. In order to tackle the...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	309,781
2006.00284	Unit Commitment Considering the Impact of Deep Cycling	Wind energy has been integrated into the power system with the hope that it improves the energy efficiency and decreases greenhouse gas emission. However, several studies over the world imply that the result was in the opposite way that was hoped mainly because of the negative correlation between wind availability and ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	179,426
2209.13831	Supervised Class-pairwise NMF for Data Representation and Classification	Various Non-negative Matrix factorization (NMF) based methods add new terms to the cost function to adapt the model to specific tasks, such as clustering, or to preserve some structural properties in the reduced space (e.g., local invariance). The added term is mainly weighted by a hyper-parameter to control the balanc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	320,040
2210.13669	Help me write a poem: Instruction Tuning as a Vehicle for Collaborative Poetry Writing	Recent work in training large language models (LLMs) to follow natural language instructions has opened up exciting opportunities for natural language interface design. Building on the prior success of LLMs in the realm of computer-assisted creativity, we aim to study if LLMs can improve the quality of user-generated c...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	326,253
2205.10115	Testing predictive automated driving systems: lessons learned and future recommendations	Conventional vehicles are certified through classical approaches, where different physical certification tests are set up on test tracks to assess required safety levels. These approaches are well suited for vehicles with limited complexity and limited interactions with other entities as last-second resources. However,...	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	false	false	297,565
1907.10710	Generic Intent Representation in Web Search	This paper presents GEneric iNtent Encoder (GEN Encoder) which learns a distributed representation space for user intent in search. Leveraging large scale user clicks from Bing search logs as weak supervision of user intent, GEN Encoder learns to map queries with shared clicks into similar embeddings end-to-end and the...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	139,685
2310.00924	Simulation Assessment Guidelines towards Independent Safety Assurance of Autonomous Vehicles	This Simulation Assessment Guidelines document is a public guidelines document developed by the Centre of Excellence for Testing & Research of AVs - NTU (CETRAN) in collaboration with the Land Transport Authority (LTA) of Singapore. It is primarily intended to help the developers of Autonomous Vehicles (AVs) in Singapo...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	396,211
2301.13833	A Mathematical Model for Curriculum Learning for Parities	Curriculum learning (CL) - training using samples that are generated and presented in a meaningful order - was introduced in the machine learning context around a decade ago. While CL has been extensively used and analysed empirically, there has been very little mathematical justification for its advantages. We introdu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	343,049
2303.07787	One Size Cannot Fit All: a Self-Adaptive Dispatcher for Skewed Hash Join in Shared-nothing RDBMSs	Shared-nothing architecture has been widely adopted in various commercial distributed RDBMSs. Thanks to the architecture, query can be processed in parallel and accelerated by scaling up the cluster horizontally on demand. In spite of that, load balancing has been a challenging issue in all distributed RDBMSs, includin...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	351,379
1604.08708	Mobile Robot Navigation on Partially Known Maps using a Fast A Star Algorithm Version	Mobile robot navigation in total or partially unknown environments is still an open problem. The path planning algorithms lack completeness and/or performance. Thus, there is the need for complete (i.e., the algorithm determines in finite time either a solution or correctly reports that there is none) and performance (...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	55,242
2211.10228	GNS: A generalizable Graph Neural Network-based simulator for particulate and fluid modeling	We develop a PyTorch-based Graph Network Simulator (GNS) that learns physics and predicts the flow behavior of particulate and fluid systems. GNS discretizes the domain with nodes representing a collection of material points and the links connecting the nodes representing the local interaction between particles or clus...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	331,243
1906.08318	REflex: Flexible Framework for Relation Extraction in Multiple Domains	Systematic comparison of methods for relation extraction (RE) is difficult because many experiments in the field are not described precisely enough to be completely reproducible and many papers fail to report ablation studies that would highlight the relative contributions of their various combined techniques. In this ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	135,831
2402.02516	Adaptive scheduling for adaptive sampling in POS taggers construction	We introduce an adaptive scheduling for adaptive sampling as a novel way of machine learning in the construction of part-of-speech taggers. The goal is to speed up the training on large data sets, without significant loss of performance with regard to an optimal configuration. In contrast to previous methods using a ra...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	426,598
2409.15584	FACET: Fast and Accurate Event-Based Eye Tracking Using Ellipse Modeling for Extended Reality	Eye tracking is a key technology for gaze-based interactions in Extended Reality (XR), but traditional frame-based systems struggle to meet XR's demands for high accuracy, low latency, and power efficiency. Event cameras offer a promising alternative due to their high temporal resolution and low power consumption. In t...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	490,971
1908.11337	CCKS 2019 Shared Task on Inter-Personal Relationship Extraction	The CCKS2019 shared task was devoted to inter-personal relationship extraction. Given two person entities and at least one sentence containing these two entities, participating teams are asked to predict the relationship between the entities according to a given relation list. This year, 358 teams from various universi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	143,356
2410.21254	Are BabyLMs Second Language Learners?	This paper describes a linguistically-motivated approach to the 2024 edition of the BabyLM Challenge (Warstadt et al. 2023). Rather than pursuing a first language learning (L1) paradigm, we approach the challenge from a second language (L2) learning perspective. In L2 learning, there is a stronger focus on learning exp...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	503,147
2004.04330	The Secrecy Capacity of Cost-Constrained Wiretap Channels	In many information-theoretic channel coding problems, adding an input cost constraint to the operational setup amounts to restricting the optimization domain in the capacity formula. This paper shows that, in contrast to common belief, such a simple modification does not hold for the cost-constrained (CC) wiretap chan...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	171,847
2208.07472	Towards Inclusive HRI: Using Sim2Real to Address Underrepresentation in Emotion Expression Recognition	Robots and artificial agents that interact with humans should be able to do so without bias and inequity, but facial perception systems have notoriously been found to work more poorly for certain groups of people than others. In our work, we aim to build a system that can perceive humans in a more transparent and inclu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	313,056
2412.06204	You KAN Do It in a Single Shot: Plug-and-Play Methods with Single-Instance Priors	The use of Plug-and-Play (PnP) methods has become a central approach for solving inverse problems, with denoisers serving as regularising priors that guide optimisation towards a clean solution. In this work, we introduce KAN-PnP, an optimisation framework that incorporates Kolmogorov-Arnold Networks (KANs) as denoiser...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	515,147
2107.08396	GraphGen-Redux: a Fast and Lightweight Recurrent Model for labeled Graph Generation	The problem of labeled graph generation is gaining attention in the Deep Learning community. The task is challenging due to the sparse and discrete nature of graph spaces. Several approaches have been proposed in the literature, most of which require to transform the graphs into sequences that encode their structure an...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	246,719
2408.00676	An effect analysis of the balancing techniques on the counterfactual explanations of student success prediction models	In the past decade, we have experienced a massive boom in the usage of digital solutions in higher education. Due to this boom, large amounts of data have enabled advanced data analysis methods to support learners and examine learning processes. One of the dominant research directions in learning analytics is predictiv...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	477,928
1711.07377	Pixel-wise object tracking	In this paper, we propose a novel pixel-wise visual object tracking framework that can track any anonymous object in a noisy background. The framework consists of two submodels, a global attention model and a local segmentation model. The global model generates a region of interests (ROI) that the object may lie in the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	84,980
1812.00913	The Right (Angled) Perspective: Improving the Understanding of Road Scenes Using Boosted Inverse Perspective Mapping	Many tasks performed by autonomous vehicles such as road marking detection, object tracking, and path planning are simpler in bird's-eye view. Hence, Inverse Perspective Mapping (IPM) is often applied to remove the perspective effect from a vehicle's front-facing camera and to remap its images into a 2D domain, resulti...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	115,385
2106.06304	Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance	Finding the best configuration of algorithms' hyperparameters for a given optimization problem is an important task in evolutionary computation. We compare in this work the results of four different hyperparameter tuning approaches for a family of genetic algorithms on 25 diverse pseudo-Boolean optimization problems. M...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	240,440
2203.04187	RankSeg: Adaptive Pixel Classification with Image Category Ranking for Segmentation	The segmentation task has traditionally been formulated as a complete-label pixel classification task to predict a class for each pixel from a fixed number of predefined semantic categories shared by all images or videos. Yet, following this formulation, standard architectures will inevitably encounter various challeng...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	284,376
2202.10774	Social Computational Design Method for Generating Product Shapes with GAN and Transformer Models	A social computational design method is established, aiming at taking advantages of the fast-developing artificial intelligence technologies for intelligent product design. Supported with multi-agent system, shape grammar, Generative adversarial network, Bayesian network, Transformer, etc., the method is able to define...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	281,661
2302.12289	Beyond Moments: Robustly Learning Affine Transformations with Asymptotically Optimal Error	We present a polynomial-time algorithm for robustly learning an unknown affine transformation of the standard hypercube from samples, an important and well-studied setting for independent component analysis (ICA). Specifically, given an $\epsilon$-corrupted sample from a distribution $D$ obtained by applying an unknown...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	347,505
1911.05567	DARTS: DenseUnet-based Automatic Rapid Tool for brain Segmentation	Quantitative, volumetric analysis of Magnetic Resonance Imaging (MRI) is a fundamental way researchers study the brain in a host of neurological conditions including normal maturation and aging. Despite the availability of open-source brain segmentation software, widespread clinical adoption of volumetric analysis has ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	153,302
1502.04137	Non-Adaptive Learning a Hidden Hipergraph	We give a new deterministic algorithm that non-adaptively learns a hidden hypergraph from edge-detecting queries. All previous non-adaptive algorithms either run in exponential time or have non-optimal query complexity. We give the first polynomial time non-adaptive learning algorithm for learning hypergraph that asks ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	40,221
2206.03943	Robust Environment Perception for Automated Driving: A Unified Learning Pipeline for Visual-Infrared Object Detection	The RGB complementary metal-oxidesemiconductor (CMOS) sensor works within the visible light spectrum. Therefore it is very sensitive to environmental light conditions. On the contrary, a long-wave infrared (LWIR) sensor operating in 8-14 micro meter spectral band, functions independent of visible light. In this paper...	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	301,461
2208.06379	Microscopic fluctuations in power-grid frequency recordings at the sub-second scale	Complex systems, such as the power grid, are essential for our daily lives. Many complex systems display (multi-)fractal behavior, correlated fluctuations and power laws. Whether the power-grid frequency, an indicator about the balance on supply and demand in the electricity grid, also displays such complexity remains ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	312,698
2106.14306	3D Reconstruction through Fusion of Cross-View Images	3D recovery from multi-stereo and stereo images, as an important application of the image-based perspective geometry, serves many applications in computer vision, remote sensing and Geomatics. In this chapter, the authors utilize the imaging geometry and present approaches that perform 3D reconstruction from cross-view...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	243,360
1812.11600	Constrained Inverse Optimal Control with Application to a Human Manipulation Task	This paper presents an inverse optimal control methodology and its application to training a predictive model of human motor control from a manipulation task. It introduces a convex formulation for learning both objective function and constraints of an infinite-horizon constrained optimal control problem with nonlinear...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	117,596
2312.04355	Secure Cell-Free Integrated Sensing and Communication in the Presence of Information and Sensing Eavesdroppers	This paper studies a secure cell-free integrated sensing and communication (ISAC) system, in which multiple ISAC transmitters collaboratively send confidential information to multiple communication users (CUs) and concurrently conduct target detection. Different from prior works investigating communication security aga...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	413,649
2202.03038	Deep Networks on Toroids: Removing Symmetries Reveals the Structure of Flat Regions in the Landscape Geometry	We systematize the approach to the investigation of deep neural network landscapes by basing it on the geometry of the space of implemented functions rather than the space of parameters. Grouping classifiers into equivalence classes, we develop a standardized parameterization in which all symmetries are removed, result...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	279,049
2108.01595	Extending a Physics-Based Constitutive Model using Genetic Programming	In material science, models are derived to predict emergent material properties (e.g. elasticity, strength, conductivity) and their relations to processing conditions. A major drawback is the calibration of model parameters that depend on processing conditions. Currently, these parameters must be optimized to fit measu...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	249,075
1804.01614	Pigeonring: A Principle for Faster Thresholded Similarity Search	The pigeonhole principle states that if $n$ items are contained in $m$ boxes, then at least one box has no more than $n / m$ items. It is utilized to solve many data management problems, especially for thresholded similarity searches. Despite many pigeonhole principle-based solutions proposed in the last few decades, t...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	true	94,252
1603.08150	Data-Driven Dynamic Decision Models	This article outlines a method for automatically generating models of dynamic decision-making that both have strong predictive power and are interpretable in human terms. This is useful for designing empirically grounded agent-based simulations and for gaining direct insight into observed dynamic processes. We use an e...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	false	true	53,735
2412.18884	HV-BEV: Decoupling Horizontal and Vertical Feature Sampling for Multi-View 3D Object Detection	The application of vision-based multi-view environmental perception system has been increasingly recognized in autonomous driving technology, especially the BEV-based models. Current state-of-the-art solutions primarily encode image features from each camera view into the BEV space through explicit or implicit depth pr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	520,621
2412.16276	SGAC: A Graph Neural Network Framework for Imbalanced and Structure-Aware AMP Classification	Classifying antimicrobial peptides(AMPs) from the vast array of peptides mined from metagenomic sequencing data is a significant approach to addressing the issue of antibiotic resistance. However, current AMP classification methods, primarily relying on sequence-based data, neglect the spatial structure of peptides, th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	519,457
1610.09975	Neural Speech Recognizer: Acoustic-to-Word LSTM Model for Large Vocabulary Speech Recognition	We present results that show it is possible to build a competitive, greatly simplified, large vocabulary continuous speech recognition system with whole words as acoustic units. We model the output vocabulary of about 100,000 words directly using deep bi-directional LSTM RNNs with CTC loss. The model is trained on 125,...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	63,143
2410.18441	The Nature of Mathematical Modeling and Probabilistic Optimization Engineering in Generative AI	In this paper, we give an in-depth analysis on the mathematical problem formulations and the probabilistic optimization explorations for some of the key components in Transformer model [33] in the field of generative AI. We explore and discuss some potential further enhancement for current state of the art methods for ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	501,886
2208.00141	Distributed Scheduling at Non-Signalized Intersections with Mixed Cooperative and Non-Cooperative Vehicles	Intersection management with mixed cooperative and non-cooperative vehicles is crucial in next-generation transportation systems. For fully non-cooperative systems, a minimax scheduling framework was established, while it is inefficient in mixed systems as the benefit of cooperation is not exploited. This letter focuse...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	310,751
2406.16851	Losing Visual Needles in Image Haystacks: Vision Language Models are Easily Distracted in Short and Long Contexts	We present LoCoVQA, a dynamic benchmark generator for evaluating long-context extractive reasoning in vision language models (VLMs). LoCoVQA augments test examples for mathematical reasoning, VQA, and character recognition tasks with increasingly long visual contexts composed of both in-distribution and out-of-distribu...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	467,300
2108.00270	Opinion Prediction with User Fingerprinting	Opinion prediction is an emerging research area with diverse real-world applications, such as market research and situational awareness. We identify two lines of approaches to the problem of opinion prediction. One uses topic-based sentiment analysis with time-series modeling, while the other uses static embedding of t...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	248,652
1703.00152	Saliency Detection by Forward and Backward Cues in Deep-CNNs	As prior knowledge of objects or object features helps us make relations for similar objects on attentional tasks, pre-trained deep convolutional neural networks (CNNs) can be used to detect salient objects on images regardless of the object class is in the network knowledge or not. In this paper, we propose a top-down...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	69,119
2301.00008	Effects of Data Geometry in Early Deep Learning	Deep neural networks can approximate functions on different types of data, from images to graphs, with varied underlying structure. This underlying structure can be viewed as the geometry of the data manifold. By extending recent advances in the theoretical understanding of neural networks, we study how a randomly init...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	338,768
2001.08809	Universal Data Anomaly Detection via Inverse Generative Adversary Network	The problem of detecting data anomaly is considered. Under the null hypothesis that models anomaly-free data, measurements are assumed to be from an unknown distribution with some authenticated historical samples. Under the composite alternative hypothesis, measurements are from an unknown distribution positive distanc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	161,390
1703.04159	Any-Angle Pathfinding for Multiple Agents Based on SIPP Algorithm	The problem of finding conflict-free trajectories for multiple agents of identical circular shape, operating in shared 2D workspace, is addressed in the paper and decoupled, e.g., prioritized, approach is used to solve this problem. Agents' workspace is tessellated into the square grid on which any-angle moves are allo...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	69,848
cs/0611132	The specifications making in complex CAD-system of renovation of the enterprises on the basis of modules in the drawing and electronic catalogues	The experience of automation of the specifications making of the projects of renovation of the industrial enterprises is described, being based on the special modules in the drawing containing the visible image and additional parameters, and electronic catalogues	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	539,913
1902.00683	Nonlinear System Identification: A User-Oriented Roadmap	The goal of this article is twofold. Firstly, nonlinear system identification is introduced to a wide audience, guiding practicing engineers and newcomers in the field to a sound solution of their data driven modeling problems for nonlinear dynamic systems. In addition, the article also provides a broad perspective on ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	120,478

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