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
2412.19813	Coverage Path Planning in Precision Agriculture: Algorithms, Applications, and Key Benefits	Coverage path planning (CPP) is the task of computing an optimal path within a region to completely scan or survey an area of interest using one or multiple mobile robots. Robots equipped with sensors and cameras can collect vast amounts of data on crop health, soil conditions, and weather patterns. Advanced analytics ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	520,976
1801.05449	ConvSRC: SmartPhone based Periocular Recognition using Deep Convolutional Neural Network and Sparsity Augmented Collaborative Representation	Smartphone based periocular recognition has gained significant attention from biometric research community because of the limitations of biometric modalities like face, iris etc. Most of the existing methods for periocular recognition employ hand-crafted features. Recently, learning based image representation technique...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	88,457
2103.03923	Surface Warping Incorporating Machine Learning Assisted Domain Likelihood Estimation: A New Paradigm in Mine Geology Modelling and Automation	This paper illustrates an application of machine learning (ML) within a complex system that performs grade estimation. In surface mining, assay measurements taken from production drilling often provide useful information that allows initially inaccurate surfaces created using sparse exploration data to be revised and s...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	223,454
1311.3633	A coordination model for ultra-large scale systems of systems	The ultra large multi-agent systems are becoming increasingly popular due to quick decay of the individual production costs and the potential of speeding up the solving of complex problems. Examples include nano-robots, or systems of nano-satellites for dangerous meteorite detection, or cultures of stem cells for organ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	28,423
2311.04948	Explained anomaly detection in text reviews: Can subjective scenarios be correctly evaluated?	This paper presents a pipeline to detect and explain anomalous reviews in online platforms. The pipeline is made up of three modules and allows the detection of reviews that do not generate value for users due to either worthless or malicious composition. The classifications are accompanied by a normality score and an ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	406,422
1712.07078	Tables, bounds and graphics of short linear codes with covering radius 3 and codimension 4 and 5	The length function $\ell_q(r,R)$ is the smallest length of a $q$-ary linear code of codimension (redundancy) $r$ and covering radius $R$. The $d$-length function $\ell_q(r,R,d)$ is the smallest length of a $q$-ary linear code with codimension $r$, covering radius $R$, and minimum distance $d$. By computer search in wi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	86,983
1401.7377	Improved Robust Node Position Estimation in Wireless Sensor Networks	A new method for estimating the relative positions of location-unaware nodes from the location-aware nodes and the received signal strength (RSS) between the nodes, in a wireless sensor network (WSN), is proposed. In the method, a regularization term is incorporated in the optimization problem leading to significant im...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	30,450
1910.02059	Fairness and Efficiency in DAG-based Cryptocurrencies	Bitcoin is a decentralised digital currency that serves as an alternative to existing transaction systems based on an external central authority for security. Although Bitcoin has many desirable properties, one of its fundamental shortcomings is its inability to process transactions at high rates. To address this chall...	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	true	148,122
2001.03549	Zooming into chaos for a fast, light and reliable cryptosystem	In previous work, the $k$-logistic map [Machicao and Bruno, Chaos, vol. 27, 053116 (2017)] was introduced as a transformation operating in the $k$ less significant digits of the Logistic map. It exploited the map's pseudo-randomness character that is present in its less significant digits. In this work, we comprehensiv...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	160,009
1707.01210	Per-Tone model for Common Mode sensor based alien noise cancellation for Downstream xDSL	For xDSL systems, alien noise cancellation using an additional common mode sensor at the downstream receiver can be thought of as interference cancellation in a Single Input Dual Output (SIDO) system. The coupling between the common mode and differential mode can be modelled as an LTI system with a long impulse respons...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	76,493
2502.08522	Abstract questionnaires and FS-decision digraphs	A questionnaire is a sequence of multiple choice questions aiming to collect data on a population. We define an abstract questionnaire as an ordered pair $(N,{\cal M})$, where $N$ is a positive integer and ${\cal M}=(m_0,m_1,\ldots,m_{N-1})$ is an $N$-tuple of positive integers, with $m_i$, for $i \in \{0, 1, \ldots, N...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	533,041
2108.06898	Neural-to-Tree Policy Distillation with Policy Improvement Criterion	While deep reinforcement learning has achieved promising results in challenging decision-making tasks, the main bones of its success --- deep neural networks are mostly black-boxes. A feasible way to gain insight into a black-box model is to distill it into an interpretable model such as a decision tree, which consists...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	250,769
2410.20118	GeoFUSE: A High-Efficiency Surrogate Model for Seawater Intrusion Prediction and Uncertainty Reduction	Seawater intrusion into coastal aquifers poses a significant threat to groundwater resources, especially with rising sea levels due to climate change. Accurate modeling and uncertainty quantification of this process are crucial but are often hindered by the high computational costs of traditional numerical simulations....	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	502,660
2410.06195	Entering Real Social World! Benchmarking the Social Intelligence of Large Language Models from a First-person Perspective	Social intelligence is built upon three foundational pillars: cognitive intelligence, situational intelligence, and behavioral intelligence. As large language models (LLMs) become increasingly integrated into our social lives, understanding, evaluating, and developing their social intelligence are becoming increasingly...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	496,090
2306.11623	Mean-field Analysis of Generalization Errors	We propose a novel framework for exploring weak and $L_2$ generalization errors of algorithms through the lens of differential calculus on the space of probability measures. Specifically, we consider the KL-regularized empirical risk minimization problem and establish generic conditions under which the generalization e...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	374,657
2203.11139	Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Clouds	We study the problem of efficient object detection of 3D LiDAR point clouds. To reduce the memory and computational cost, existing point-based pipelines usually adopt task-agnostic random sampling or farthest point sampling to progressively downsample input point clouds, despite the fact that not all points are equally...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	286,810
2410.01225	Perceptual Piercing: Human Visual Cue-based Object Detection in Low Visibility Conditions	This study proposes a novel deep learning framework inspired by atmospheric scattering and human visual cortex mechanisms to enhance object detection under poor visibility scenarios such as fog, smoke, and haze. These conditions pose significant challenges for object recognition, impacting various sectors, including au...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	493,665
2108.03625	Unifying Heterogeneous Electronic Health Records Systems via Text-Based Code Embedding	Substantial increase in the use of Electronic Health Records (EHRs) has opened new frontiers for predictive healthcare. However, while EHR systems are nearly ubiquitous, they lack a unified code system for representing medical concepts. Heterogeneous formats of EHR present a substantial barrier for the training and dep...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	249,728
2012.08296	Gegelati: Lightweight Artificial Intelligence through Generic and Evolvable Tangled Program Graphs	Tangled Program Graph (TPG) is a reinforcement learning technique based on genetic programming concepts. On state-of-the-art learning environments, TPGs have been shown to offer comparable competence with Deep Neural Networks (DNNs), for a fraction of their computational and storage cost. This lightness of TPGs, both f...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	211,732
1508.00349	On the Interference Alignment Designs for Secure Multiuser MIMO Systems	In this paper, we propose two secure multiuser multiple-input multiple-output transmission approaches based on interference alignment (IA) in the presence of an eavesdropper. To deal with the information leakage to the eavesdropper as well as the interference signals from undesired transmitters (Txs) at desired receive...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	45,665
2502.11033	Convergence of Policy Mirror Descent Beyond Compatible Function Approximation	Modern policy optimization methods roughly follow the policy mirror descent (PMD) algorithmic template, for which there are by now numerous theoretical convergence results. However, most of these either target tabular environments, or can be applied effectively only when the class of policies being optimized over satis...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	534,160
2303.07897	Multiparticle Kalman filter for object localization in symmetric environments	This study considers the object localization problem and proposes a novel multiparticle Kalman filter to solve it in complex and symmetric environments. Two well-known classes of filtering algorithms to solve the localization problem are Kalman filter-based methods and particle filter-based methods. We consider these c...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	351,429
1811.08585	Progressive Feature Alignment for Unsupervised Domain Adaptation	Unsupervised domain adaptation (UDA) transfers knowledge from a label-rich source domain to a fully-unlabeled target domain. To tackle this task, recent approaches resort to discriminative domain transfer in virtue of pseudo-labels to enforce the class-level distribution alignment across the source and target domains. ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	114,073
1702.06446	Several Classes of Permutation Trinomials over $\mathbb F_{5^n}$ From Niho Exponents	The construction of permutation trinomials over finite fields attracts people's interest recently due to their simple form and some additional properties. Motivated by some results on the construction of permutation trinomials with Niho exponents, by constructing some new fractional polynomials that permute the set of ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	68,612
2010.06390	Escalation Prediction using Feature Engineering: Addressing Support Ticket Escalations within IBM's Ecosystem	Large software organizations handle many customer support issues every day in the form of bug reports, feature requests, and general misunderstandings as submitted by customers. Strategies to gather, analyze, and negotiate requirements are complemented by efforts to manage customer input after products have been deploy...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	200,468
2010.03140	Finite Meta-Dynamic Neurons in Spiking Neural Networks for Spatio-temporal Learning	Spiking Neural Networks (SNNs) have incorporated more biologically-plausible structures and learning principles, hence are playing critical roles in bridging the gap between artificial and natural neural networks. The spikes are the sparse signals describing the above-threshold event-based firing and under-threshold dy...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	199,292
2308.08151	Optimal Kinematic Design of a Robotic Lizard using Four-Bar and Five-Bar Mechanisms	Designing a mechanism to mimic the motion of a common house gecko is the objective of this work. The body of the robot is designed using four five-bar mechanisms (2-RRRRR and 2-RRPRR) and the leg is designed using four four-bar mechanisms. The 2-RRRRR five-bar mechanisms form the head and tail of the robotic lizard. Th...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	385,782
2112.11641	JoJoGAN: One Shot Face Stylization	A style mapper applies some fixed style to its input images (so, for example, taking faces to cartoons). This paper describes a simple procedure -- JoJoGAN -- to learn a style mapper from a single example of the style. JoJoGAN uses a GAN inversion procedure and StyleGAN's style-mixing property to produce a substantial ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	272,755
2410.09003	Design and Control of an Omnidirectional Aerial Robot with a Miniaturized Haptic Joystick for Physical Interaction	Fully actuated aerial robot proved their superiority for Aerial Physical Interaction (APhI) over the past years. This work proposes a minimal setup for aerial telemanipulation, enhancing accessibility of these technologies. The design and the control of a 6-DoF joystick with 4-DoF haptic feedback is detailed. It is the...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	497,382
2111.06959	Through-Foliage Tracking with Airborne Optical Sectioning	Detecting and tracking moving targets through foliage is difficult, and for many cases even impossible in regular aerial images and videos. We present an initial light-weight and drone-operated 1D camera array that supports parallel synthetic aperture aerial imaging. Our main finding is that color anomaly detection ben...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	266,227
1903.06410	Identifying long-term periodic cycles and memories of collective emotion in online social media	Collective emotion has been traditionally evaluated by questionnaire survey on a limited number of people. Recently, big data of written texts on the Internet has been available for analyzing collective emotion for very large scales. Although short-term reflection between collective emotion and real social phenomena ha...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	124,379
2008.06785	Adversarial Filters for Secure Modulation Classification	Modulation Classification (MC) refers to the problem of classifying the modulation class of a wireless signal. In the wireless communications pipeline, MC is the first operation performed on the received signal and is critical for reliable decoding. This paper considers the problem of secure modulation classification, ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	191,889
2108.02696	A Low Rank Promoting Prior for Unsupervised Contrastive Learning	Unsupervised learning is just at a tipping point where it could really take off. Among these approaches, contrastive learning has seen tremendous progress and led to state-of-the-art performance. In this paper, we construct a novel probabilistic graphical model that effectively incorporates the low rank promoting prior...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	249,414
2206.12390	A Test for Evaluating Performance in Human-Computer Systems	The Turing test for comparing computer performance to that of humans is well known, but, surprisingly, there is no widely used test for comparing how much better human-computer systems perform relative to humans alone, computers alone, or other baselines. Here, we show how to perform such a test using the ratio of mean...	true	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	304,578
2210.08710	Handling Label Uncertainty for Camera Incremental Person Re-Identification	Incremental learning for person re-identification (ReID) aims to develop models that can be trained with a continuous data stream, which is a more practical setting for real-world applications. However, the existing incremental ReID methods make two strong assumptions that the cameras are fixed and the new-emerging dat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	324,255
1702.07560	RNN Decoding of Linear Block Codes	Designing a practical, low complexity, close to optimal, channel decoder for powerful algebraic codes with short to moderate block length is an open research problem. Recently it has been shown that a feed-forward neural network architecture can improve on standard belief propagation decoding, despite the large example...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	true	false	false	68,807
2412.18327	HAUR: Human Annotation Understanding and Recognition Through Text-Heavy Images	Vision Question Answering (VQA) tasks use images to convey critical information to answer text-based questions, which is one of the most common forms of question answering in real-world scenarios. Numerous vision-text models exist today and have performed well on certain VQA tasks. However, these models exhibit signifi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	520,375
2409.01815	Learning State-Dependent Policy Parametrizations for Dynamic Technician Routing with Rework	Home repair and installation services require technicians to visit customers and resolve tasks of different complexity. Technicians often have heterogeneous skills and working experiences. The geographical spread of customers makes achieving only perfect matches between technician skills and task requirements impractic...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	485,478
2308.10610	Ear-Keeper: Real-time Diagnosis of Ear Lesions Utilizing Ultralight-Ultrafast ConvNet and Large-scale Ear Endoscopic Dataset	Deep learning-based ear disease diagnosis technology has proven effective and affordable. However, due to the lack of ear endoscope datasets with diversity, the practical potential of the deep learning model has not been thoroughly studied. Moreover, existing research failed to achieve a good trade-off between model in...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	386,807
2207.07646	Multimodal Open-Vocabulary Video Classification via Pre-Trained Vision and Language Models	Utilizing vision and language models (VLMs) pre-trained on large-scale image-text pairs is becoming a promising paradigm for open-vocabulary visual recognition. In this work, we extend this paradigm by leveraging motion and audio that naturally exist in video. We present \textbf{MOV}, a simple yet effective method for ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	308,263
2407.16012	Data Processing Inequality for The Quantum Guesswork	Non-orthogonal quantum states pose a fundamental challenge in quantum information processing, as they cannot be distinguished with absolute certainty. Conventionally, the focus has been on minimizing error probability in quantum state discrimination tasks. However, another criterion known as quantum guesswork has emerg...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	475,420
1505.01786	Secrecy Analysis on Network Coding in Bidirectional Multibeam Satellite Communications	Network coding is an efficient means to improve the spectrum efficiency of satellite communications. However, its resilience to eavesdropping attacks is not well understood. This paper studies the confidentiality issue in a bidirectional satellite network consisting of two mobile users who want to exchange message via ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	42,881
2501.16303	RAPID: Retrieval-Augmented Parallel Inference Drafting for Text-Based Video Event Retrieval	Retrieving events from videos using text queries has become increasingly challenging due to the rapid growth of multimedia content. Existing methods for text-based video event retrieval often focus heavily on object-level descriptions, overlooking the crucial role of contextual information. This limitation is especiall...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	527,897
2405.20743	Trajectory Forecasting through Low-Rank Adaptation of Discrete Latent Codes	Trajectory forecasting is crucial for video surveillance analytics, as it enables the anticipation of future movements for a set of agents, e.g. basketball players engaged in intricate interactions with long-term intentions. Deep generative models offer a natural learning approach for trajectory forecasting, yet they e...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	459,500
0906.1189	On the Throughput/Bit-Cost Tradeoff in CSMA Based Cooperative Networks	Wireless local area networks (WLAN) still suffer from a severe performance discrepancy between different users in the uplink. This is because of the spatially varying channel conditions provided by the wireless medium. Cooperative medium access control (MAC) protocols as for example CoopMAC were proposed to mitigate th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	3,839
2310.00839	Subsurface Characterization using Ensemble-based Approaches with Deep Generative Models	Estimating spatially distributed properties such as hydraulic conductivity (K) from available sparse measurements is a great challenge in subsurface characterization. However, the use of inverse modeling is limited for ill-posed, high-dimensional applications due to computational costs and poor prediction accuracy with...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	396,173
2412.05728	Integrating YOLO11 and Convolution Block Attention Module for Multi-Season Segmentation of Tree Trunks and Branches in Commercial Apple Orchards	In this study, we developed a customized instance segmentation model by integrating the Convolutional Block Attention Module (CBAM) with the YOLO11 architecture. This model, trained on a mixed dataset of dormant and canopy season apple orchard images, aimed to enhance the segmentation of tree trunks and branches under ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	514,949
2411.01713	Rethinking Weight Decay for Robust Fine-Tuning of Foundation Models	Modern optimizers such as AdamW, equipped with momentum and adaptive learning rate, are designed to escape local minima and explore the vast parameter space. This exploration is beneficial for finding good loss basins when training from scratch. It is not necessarily ideal when resuming from a powerful foundation model...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	505,190
2004.02134	Adversarial-Prediction Guided Multi-task Adaptation for Semantic Segmentation of Electron Microscopy Images	Semantic segmentation is an essential step for electron microscopy (EM) image analysis. Although supervised models have achieved significant progress, the need for labor intensive pixel-wise annotation is a major limitation. To complicate matters further, supervised learning models may not generalize well on a novel da...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	171,133
2006.05787	Image Enhancement and Object Recognition for Night Vision Surveillance	Object recognition is a critical part of any surveillance system. It is the matter of utmost concern to identify intruders and foreign objects in the area where surveillance is done. The performance of surveillance system using the traditional camera in daylight is vastly superior as compared to night. The main problem...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	181,202
2405.16829	PyGS: Large-scale Scene Representation with Pyramidal 3D Gaussian Splatting	Neural Radiance Fields (NeRFs) have demonstrated remarkable proficiency in synthesizing photorealistic images of large-scale scenes. However, they are often plagued by a loss of fine details and long rendering durations. 3D Gaussian Splatting has recently been introduced as a potent alternative, achieving both high-fid...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	457,628
1308.4123	A Likelihood Ratio Approach for Probabilistic Inequalities	We propose a new approach for deriving probabilistic inequalities based on bounding likelihood ratios. We demonstrate that this approach is more general and powerful than the classical method frequently used for deriving concentration inequalities such as Chernoff bounds. We discover that the proposed approach is inher...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	26,528
1407.2628	On the Spectral Efficiency of Full-Duplex Small Cell Wireless Systems	We investigate the spectral efficiency of full-duplex small cell wireless systems, in which a full-duplex capable base station (BS) is designed to send/receive data to/from multiple halfduplex users on the same system resources. The major hurdle for designing such systems is due to the self-interference at the BS and c...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	34,542
2412.12987	Stochastic interior-point methods for smooth conic optimization with applications	Conic optimization plays a crucial role in many machine learning (ML) problems. However, practical algorithms for conic constrained ML problems with large datasets are often limited to specific use cases, as stochastic algorithms for general conic optimization remain underdeveloped. To fill this gap, we introduce a sto...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	518,116
2501.11813	Utilising Deep Learning to Elicit Expert Uncertainty	Recent work [ 14 ] has introduced a method for prior elicitation that utilizes records of expert decisions to infer a prior distribution. While this method provides a promising approach to eliciting expert uncertainty, it has only been demonstrated using tabular data, which may not entirely represent the information us...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	526,045
2206.15478	On the Learning and Learnability of Quasimetrics	Our world is full of asymmetries. Gravity and wind can make reaching a place easier than coming back. Social artifacts such as genealogy charts and citation graphs are inherently directed. In reinforcement learning and control, optimal goal-reaching strategies are rarely reversible (symmetrical). Distance functions sup...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	305,605
2405.11162	LG AI Research & KAIST at EHRSQL 2024: Self-Training Large Language Models with Pseudo-Labeled Unanswerable Questions for a Reliable Text-to-SQL System on EHRs	Text-to-SQL models are pivotal for making Electronic Health Records (EHRs) accessible to healthcare professionals without SQL knowledge. With the advancements in large language models, these systems have become more adept at translating complex questions into SQL queries. Nonetheless, the critical need for reliability ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	455,027
1908.01279	Automatic segmentation of kidney and liver tumors in CT images	Automatic segmentation of hepatic lesions in computed tomography (CT) images is a challenging task to perform due to heterogeneous, diffusive shape of tumors and complex background. To address the problem more and more researchers rely on assistance of deep convolutional neural networks (CNN) with 2D or 3D type archite...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	140,717
2310.10863	Greedy Perspectives: Multi-Drone View Planning for Collaborative Perception in Cluttered Environments	Deployment of teams of aerial robots could enable large-scale filming of dynamic groups of people (actors) in complex environments for applications in areas such as team sports and cinematography. Toward this end, methods for submodular maximization via sequential greedy planning can enable scalable optimization of cam...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	400,413
2007.15433	Novel Modelling and Control Strategies for a Steam Boiler under Fast Load Dynamics	This paper describes a new nonlinear dynamic model for a natural circulation boiler. The model is based on physical principles, i.e. mass, energy and momentum balances. A systematic approach is followed leading to new insights into the physics of drum water level and downcomer mass flow. The model captures fast dynamic...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	189,669
1809.06546	Model-Protected Multi-Task Learning	Multi-task learning (MTL) refers to the paradigm of learning multiple related tasks together. In contrast, in single-task learning (STL) each individual task is learned independently. MTL often leads to better trained models because they can leverage the commonalities among related tasks. However, because MTL algorithm...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	108,085
2005.07158	Training Strategies for Autoencoder-based Detection of False Data Injection Attacks	The security of energy supply in a power grid critically depends on the ability to accurately estimate the state of the system. However, manipulated power flow measurements can potentially hide overloads and bypass the bad data detection scheme to interfere the validity of estimated states. In this paper, we use an aut...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	177,212
2206.09841	Label noise (stochastic) gradient descent implicitly solves the Lasso for quadratic parametrisation	Understanding the implicit bias of training algorithms is of crucial importance in order to explain the success of overparametrised neural networks. In this paper, we study the role of the label noise in the training dynamics of a quadratically parametrised model through its continuous time version. We explicitly chara...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	303,701
2403.00174	A citizen science toolkit to collect human perceptions of urban environments using open street view images	Street View Imagery (SVI) is a valuable data source for studies (e.g., environmental assessments, green space identification or land cover classification). While commercial SVI is available, such providers commonly restrict copying or reuse in ways necessary for research. Open SVI datasets are readily available from le...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	433,877
2109.12662	Improving Question Answering Performance Using Knowledge Distillation and Active Learning	Contemporary question answering (QA) systems, including transformer-based architectures, suffer from increasing computational and model complexity which render them inefficient for real-world applications with limited resources. Further, training or even fine-tuning such models requires a vast amount of labeled data wh...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	257,370
2402.02320	Spin: An Efficient Secure Computation Framework with GPU Acceleration	Accuracy and efficiency remain challenges for multi-party computation (MPC) frameworks. Spin is a GPU-accelerated MPC framework that supports multiple computation parties and a dishonest majority adversarial setup. We propose optimized protocols for non-linear functions that are critical for machine learning, as well a...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	426,491
2304.08442	The MiniPile Challenge for Data-Efficient Language Models	The ever-growing diversity of pre-training text corpora has equipped language models with generalization capabilities across various downstream tasks. However, such diverse datasets are often too large for academic budgets; hence, most research on Transformer architectures, training procedures, optimizers, etc. gets co...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	358,708
2403.01352	Improving Uncertainty Sampling with Bell Curve Weight Function	Typically, a supervised learning model is trained using passive learning by randomly selecting unlabelled instances to annotate. This approach is effective for learning a model, but can be costly in cases where acquiring labelled instances is expensive. For example, it can be time-consuming to manually identify spam ma...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	434,375
2411.13024	Prior-based Objective Inference Mining Potential Uncertainty for Facial Expression Recognition	Annotation ambiguity caused by the inherent subjectivity of visual judgment has always been a major challenge for Facial Expression Recognition (FER) tasks, particularly for largescale datasets from in-the-wild scenarios. A potential solution is the evaluation of relatively objective emotional distributions to help mit...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	509,647
2304.14880	SGAligner : 3D Scene Alignment with Scene Graphs	Building 3D scene graphs has recently emerged as a topic in scene representation for several embodied AI applications to represent the world in a structured and rich manner. With their increased use in solving downstream tasks (eg, navigation and room rearrangement), can we leverage and recycle them for creating 3D map...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	361,128
2407.03594	UniPlane: Unified Plane Detection and Reconstruction from Posed Monocular Videos	We present UniPlane, a novel method that unifies plane detection and reconstruction from posed monocular videos. Unlike existing methods that detect planes from local observations and associate them across the video for the final reconstruction, UniPlane unifies both the detection and the reconstruction tasks in a sing...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	470,210
2401.01991	DApps Ecosystems: Mapping the Network Structure of Smart Contract Interactions	In recent years, decentralized applications (dApps) built on blockchain platforms such as Ethereum and coded in languages such as Solidity, have gained attention for their potential to disrupt traditional centralized systems. Despite their rapid adoption, limited research has been conducted to understand the underlying...	false	false	false	false	false	false	false	false	false	true	false	false	true	true	false	false	false	true	419,559
1908.00532	FCFGS-CV-Based Channel Estimation for Wideband MmWave Massive MIMO Systems with Low-Resolution ADCs	In this paper, the fully corrective forward greedy selection-cross validation-based (FCFGS-CV-based) channel estimator is proposed for wideband millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems with low-resolution analog-to-digital converters (ADCs). The sparse nature of the mmWave virtual ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	140,535
1903.05390	Novel Approach Towards Global Optimality of Optimal Power Flow Using Quadratic Convex Optimization	Optimal Power Flow (OPF) can be modeled as a non-convex Quadratically Constrained Quadratic Program (QCQP). Our purpose is to solve OPF to global optimality. To this end, we specialize the Mixed-Integer Quadratic Convex Reformulation method (MIQCR) to (OPF). This is a method in two steps. First, a Semi-Definite Program...	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	124,158
2409.08276	AnySkin: Plug-and-play Skin Sensing for Robotic Touch	While tactile sensing is widely accepted as an important and useful sensing modality, its use pales in comparison to other sensory modalities like vision and proprioception. AnySkin addresses the critical challenges that impede the use of tactile sensing -- versatility, replaceability, and data reusability. Building on...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	487,842
2210.07089	Experimenting with Selected Automated Approaches for Bias Analysis	This work first presents our attempts to establish an automated model using state-of-the-art approaches for analysing bias in search results of Bing and Google. Experimental results indicate that the current class-wise F1-scores of our best model are not sufficient to establish an automated model for bias analysis. Thu...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	323,569
1803.09786	Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification	Most existing person re-identification (re-id) methods require supervised model learning from a separate large set of pairwise labelled training data for every single camera pair. This significantly limits their scalability and usability in real-world large scale deployments with the need for performing re-id across ma...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	93,573
2108.04219	Pragmatic Image Compression for Human-in-the-Loop Decision-Making	Standard lossy image compression algorithms aim to preserve an image's appearance, while minimizing the number of bits needed to transmit it. However, the amount of information actually needed by a user for downstream tasks -- e.g., deciding which product to click on in a shopping website -- is likely much lower. To ac...	true	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	249,932
2010.12993	Multi-task Supervised Learning via Cross-learning	In this paper we consider a problem known as multi-task learning, consisting of fitting a set of classifier or regression functions intended for solving different tasks. In our novel formulation, we couple the parameters of these functions, so that they learn in their task specific domains while staying close to each o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	202,956
2209.11475	Unsupervised Hashing with Semantic Concept Mining	Recently, to improve the unsupervised image retrieval performance, plenty of unsupervised hashing methods have been proposed by designing a semantic similarity matrix, which is based on the similarities between image features extracted by a pre-trained CNN model. However, most of these methods tend to ignore high-level...	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	319,199
2006.08818	Explaining reputation assessments	Reputation is crucial to enabling human or software agents to select among alternative providers. Although several effective reputation assessment methods exist, they typically distil reputation into a numerical representation, with no accompanying explanation of the rationale behind the assessment. Such explanations w...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	182,315
1712.05615	Fast Hough Transform and approximation properties of dyadic patterns	Hough transform is a popular low-level computer vision algorithm. Its computationally effective modification, Fast Hough transform (FHT), makes use of special subsets of image matrix to approximate geometric lines on it. Because of their special structure, these subset are called dyadic patterns. In this paper variou...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	86,753
1304.1118	Updating with Belief Functions, Ordinal Conditioning Functions and Possibility Measures	This paper discusses how a measure of uncertainty representing a state of knowledge can be updated when a new information, which may be pervaded with uncertainty, becomes available. This problem is considered in various framework, namely: Shafer's evidence theory, Zadeh's possibility theory, Spohn's theory of epistemic...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	23,471
2107.13155	Improving Video Instance Segmentation via Temporal Pyramid Routing	Video Instance Segmentation (VIS) is a new and inherently multi-task problem, which aims to detect, segment, and track each instance in a video sequence. Existing approaches are mainly based on single-frame features or single-scale features of multiple frames, where either temporal information or multi-scale informatio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	248,115
1205.2151	A Converged Algorithm for Tikhonov Regularized Nonnegative Matrix Factorization with Automatic Regularization Parameters Determination	We present a converged algorithm for Tikhonov regularized nonnegative matrix factorization (NMF). We specially choose this regularization because it is known that Tikhonov regularized least square (LS) is the more preferable form in solving linear inverse problems than the conventional LS. Because an NMF problem can be...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	15,884
2005.02537	Conditional Cuckoo Filters	Bloom filters, cuckoo filters, and other approximate set membership sketches have a wide range of applications. Oftentimes, expensive operations can be skipped if an item is not in a data set. These filters provide an inexpensive, memory efficient way to test if an item is in a set and avoid unnecessary operations. Exi...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	175,898
2204.09564	Cross-view Brain Decoding	How the brain captures the meaning of linguistic stimuli across multiple views is still a critical open question in neuroscience. Consider three different views of the concept apartment: (1) picture (WP) presented with the target word label, (2) sentence (S) using the target word, and (3) word cloud (WC) containing the...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	292,475
1801.02890	Symbol-by-Symbol Maximum Likelihood Detection for Cooperative Molecular Communication	In this paper, symbol-by-symbol maximum likelihood (ML) detection is proposed for a cooperative diffusion-based molecular communication (MC) system. In this system, the transmitter (TX) sends a common information symbol to multiple receivers (RXs) and a fusion center (FC) chooses the TX symbol that is more likely, give...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	88,005
2206.05255	Interactively Learning Preference Constraints in Linear Bandits	We study sequential decision-making with known rewards and unknown constraints, motivated by situations where the constraints represent expensive-to-evaluate human preferences, such as safe and comfortable driving behavior. We formalize the challenge of interactively learning about these constraints as a novel linear b...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	301,938
2003.10379	Moment State Dynamical Systems for Nonlinear Chance-Constrained Motion Planning	Chance-constrained motion planning requires uncertainty in dynamics to be propagated into uncertainty in state. When nonlinear models are used, Gaussian assumptions on the state distribution do not necessarily apply since almost all random variables propagated through nonlinear dynamics results in non-Gaussian state di...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	true	169,318
2209.04215	Fast and Accurate Importance Weighting for Correcting Sample Bias	Bias in datasets can be very detrimental for appropriate statistical estimation. In response to this problem, importance weighting methods have been developed to match any biased distribution to its corresponding target unbiased distribution. The seminal Kernel Mean Matching (KMM) method is, nowadays, still considered ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	316,724
2406.04766	Reinforcement Learning and Regret Bounds for Admission Control	The expected regret of any reinforcement learning algorithm is lower bounded by $\Omega\left(\sqrt{DXAT}\right)$ for undiscounted returns, where $D$ is the diameter of the Markov decision process, $X$ the size of the state space, $A$ the size of the action space and $T$ the number of time steps. However, this lower bou...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	461,832
2005.08603	Brain-inspired Distributed Cognitive Architecture	In this paper we present a brain-inspired cognitive architecture that incorporates sensory processing, classification, contextual prediction, and emotional tagging. The cognitive architecture is implemented as three modular web-servers, meaning that it can be deployed centrally or across a network for servers. The expe...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	177,667
2006.04225	Unsupervised Learning for Subterranean Junction Recognition Based on 2D Point Cloud	This article proposes a novel unsupervised learning framework for detecting the number of tunnel junctions in subterranean environments based on acquired 2D point clouds. The implementation of the framework provides valuable information for high level mission planners to navigate an aerial platform in unknown areas or ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	180,613
2307.16518	Continuous-Time Channel Prediction Based on Tensor Neural Ordinary Differential Equation	Channel prediction is critical to address the channel aging issue in mobile scenarios. Existing channel prediction techniques are mainly designed for discrete channel prediction, which can only predict the future channel in a fixed time slot per frame, while the other intra-frame channels are usually recovered by inter...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	382,635
2410.08508	Accelerated Distributed Stochastic Non-Convex Optimization over Time-Varying Directed Networks	Distributed stochastic non-convex optimization problems have recently received attention due to the growing interest of signal processing, computer vision, and natural language processing communities in applications deployed over distributed learning systems (e.g., federated learning). We study the setting where the da...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	497,148
2212.02244	Research on Early Warning and NB-IoT Real-time Monitoring System for Radiation Source Shedding of Gamma Flaw Detection Machine	The system takes the embedded system single chip as the core, and organizes the gamma ray induction module, keying switch, radiation source braid locking mechanism, on-site alarm equipment, NB-IoT communication module, GPS positioning system and other related equipment to realize real-time operators warning and remote ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	334,735
2212.13886	Extrinsic Bayesian Optimizations on Manifolds	We propose an extrinsic Bayesian optimization (eBO) framework for general optimization problems on manifolds. Bayesian optimization algorithms build a surrogate of the objective function by employing Gaussian processes and quantify the uncertainty in that surrogate by deriving an acquisition function. This acquisition ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	338,421
1702.01181	Sensing and Modeling Human Behavior Using Social Media and Mobile Data	In the past years we have witnessed the emergence of the new discipline of computational social science, which promotes a new data-driven and computation-based approach to social sciences. In this article we discuss how the availability of new technologies such as online social media and mobile smartphones has allowed ...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	67,761
1206.0823	Orthogonal Matching Pursuit with Noisy and Missing Data: Low and High Dimensional Results	Many models for sparse regression typically assume that the covariates are known completely, and without noise. Particularly in high-dimensional applications, this is often not the case. This paper develops efficient OMP-like algorithms to deal with precisely this setting. Our algorithms are as efficient as OMP, and im...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	16,317

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