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
2403.18579	On Optimizing Hyperparameters for Quantum Neural Networks	The increasing capabilities of Machine Learning (ML) models go hand in hand with an immense amount of data and computational power required for training. Therefore, training is usually outsourced into HPC facilities, where we have started to experience limits in scaling conventional HPC hardware, as theorized by Moore'...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	441,998
2002.08537	Adaptive Temporal Difference Learning with Linear Function Approximation	This paper revisits the temporal difference (TD) learning algorithm for the policy evaluation tasks in reinforcement learning. Typically, the performance of TD(0) and TD($\lambda$) is very sensitive to the choice of stepsizes. Oftentimes, TD(0) suffers from slow convergence. Motivated by the tight link between the TD(0...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	164,784
2412.14446	VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision	Human drivers rely on commonsense reasoning to navigate diverse and dynamic real-world scenarios. Existing end-to-end (E2E) autonomous driving (AD) models are typically optimized to mimic driving patterns observed in data, without capturing the underlying reasoning processes. This limitation constrains their ability to...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	518,699
1204.1277	Mouse Simulation Using Two Coloured Tapes	In this paper, we present a novel approach for Human Computer Interaction (HCI) where, we control cursor movement using a real-time camera. Current methods involve changing mouse parts such as adding more buttons or changing the position of the tracking ball. Instead, our method is to use a camera and computer vision t...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	15,306
2407.21046	Promises and Pitfalls of Generative Masked Language Modeling: Theoretical Framework and Practical Guidelines	Autoregressive language models are the currently dominant paradigm for text generation, but they have some fundamental limitations that cannot be remedied by scale-for example inherently sequential and unidirectional generation. While alternate classes of models have been explored, we have limited mathematical understa...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	477,378
1201.3059	Delay Sensitive Communications over Cognitive Radio Networks	Supporting the quality of service of unlicensed users in cognitive radio networks is very challenging, mainly due to dynamic resource availability because of the licensed users' activities. In this paper, we study the optimal admission control and channel allocation decisions in cognitive overlay networks in order to s...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	13,820
2210.16451	Robust Boosting Forests with Richer Deep Feature Hierarchy	We propose a robust variant of boosting forest to the various adversarial defense methods, and apply it to enhance the robustness of the deep neural network. We retain the deep network architecture, weights, and middle layer features, then install gradient boosting forest to select the features from each layer of the d...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	327,333
2008.10779	Continuous Authentication of Wearable Device Users from Heart Rate, Gait, and Breathing Data	The security of private information is becoming the bedrock of an increasingly digitized society. While the users are flooded with passwords and PINs, these gold-standard explicit authentications are becoming less popular and valuable. Recent biometric-based authentication methods, such as facial or finger recognition,...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	193,086
1309.0040	Enhanced Flow in Small-World Networks	The small-world property is known to have a profound effect on the navigation efficiency of complex networks [J. M. Kleinberg, Nature 406, 845 (2000)]. Accordingly, the proper addition of shortcuts to a regular substrate can lead to the formation of a highly efficient structure for information propagation. Here we show...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	26,753
2406.08478	What If We Recaption Billions of Web Images with LLaMA-3?	Web-crawled image-text pairs are inherently noisy. Prior studies demonstrate that semantically aligning and enriching textual descriptions of these pairs can significantly enhance model training across various vision-language tasks, particularly text-to-image generation. However, large-scale investigations in this area...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	463,511
2408.15695	G-Style: Stylized Gaussian Splatting	We introduce G-Style, a novel algorithm designed to transfer the style of an image onto a 3D scene represented using Gaussian Splatting. Gaussian Splatting is a powerful 3D representation for novel view synthesis, as -- compared to other approaches based on Neural Radiance Fields -- it provides fast scene renderings an...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	484,042
1906.07789	SEN12MS -- A Curated Dataset of Georeferenced Multi-Spectral Sentinel-1/2 Imagery for Deep Learning and Data Fusion	The availability of curated large-scale training data is a crucial factor for the development of well-generalizing deep learning methods for the extraction of geoinformation from multi-sensor remote sensing imagery. While quite some datasets have already been published by the community, most of them suffer from rather ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	135,682
1901.10895	Generative Adversarial Network with Multi-Branch Discriminator for Cross-Species Image-to-Image Translation	Current approaches have made great progress on image-to-image translation tasks benefiting from the success of image synthesis methods especially generative adversarial networks (GANs). However, existing methods are limited to handling translation tasks between two species while keeping the content matching on the sema...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	120,130
2401.07890	A Strategy for Implementing description Temporal Dynamic Algorithms in Dynamic Knowledge Graphs by SPIN	Planning and reasoning about actions and processes, in addition to reasoning about propositions, are important issues in recent logical and computer science studies. The widespread use of actions in everyday life such as IoT, semantic web services, etc., and the limitations and issues in the action formalisms are two f...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	421,693
0904.2482	Good Concatenated Code Ensembles for the Binary Erasure Channel	In this work, we give good concatenated code ensembles for the binary erasure channel (BEC). In particular, we consider repeat multiple-accumulate (RMA) code ensembles formed by the serial concatenation of a repetition code with multiple accumulators, and the hybrid concatenated code (HCC) ensembles recently introduced...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	3,550
2412.06694	Digital Transformation in the Water Distribution System based on the Digital Twins Concept	Digital Twins have emerged as a disruptive technology with great potential; they can enhance WDS by offering real-time monitoring, predictive maintenance, and optimization capabilities. This paper describes the development of a state-of-the-art DT platform for WDS, introducing advanced technologies such as the Internet...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	515,334
2202.11784	Design and experimental investigation of a vibro-impact self-propelled capsule robot with orientation control	This paper presents a novel design and experimental investigation for a self-propelled capsule robot that can be used for painless colonoscopy during a retrograde progression from the patient's rectum. The steerable robot is driven forward and backward via its internal vibration and impact with orientation control by u...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	281,996
1711.00941	Deep Active Learning over the Long Tail	This paper is concerned with pool-based active learning for deep neural networks. Motivated by coreset dataset compression ideas, we present a novel active learning algorithm that queries consecutive points from the pool using farthest-first traversals in the space of neural activation over a representation layer. We s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	83,802
2301.05646	Data-Assisted Control -- A Framework Development by Exploiting NASA GTM Platform	Today's focus on expanding the capabilities of control systems, resulting from the abundance of data and computational resources, requires data-based alternatives over model-based ones. These alternatives may become the sole tool for analysis and synthesis. Nevertheless, mathematical models are available to some extent...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	340,413
2410.09740	Gaussian Splatting Visual MPC for Granular Media Manipulation	Recent advancements in learned 3D representations have enabled significant progress in solving complex robotic manipulation tasks, particularly for rigid-body objects. However, manipulating granular materials such as beans, nuts, and rice, remains challenging due to the intricate physics of particle interactions, high-...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	497,749
2311.14927	View-Based Luminance Mapping in Open Workplace	This paper introduces a novel computational method for mapping indoor luminance values on the facade of an open workplace to improve its daylight performance. 180-degree fisheye renderings from different indoor locations, view positions, and times of the year are created. These renderings are then transformed from two-...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	410,315
1907.13100	On the Robustness of Median Sampling in Noisy Evolutionary Optimization	Evolutionary algorithms (EAs) are a sort of nature-inspired metaheuristics, which have wide applications in various practical optimization problems. In these problems, objective evaluations are usually inaccurate, because noise is almost inevitable in real world, and it is a crucial issue to weaken the negative effect ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	140,297
2208.09500	Causality-Inspired Taxonomy for Explainable Artificial Intelligence	As two sides of the same coin, causality and explainable artificial intelligence (xAI) were initially proposed and developed with different goals. However, the latter can only be complete when seen through the lens of the causality framework. As such, we propose a novel causality-inspired framework for xAI that creates...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	313,720
2411.13874	Next-Generation Phishing: How LLM Agents Empower Cyber Attackers	The escalating threat of phishing emails has become increasingly sophisticated with the rise of Large Language Models (LLMs). As attackers exploit LLMs to craft more convincing and evasive phishing emails, it is crucial to assess the resilience of current phishing defenses. In this study we conduct a comprehensive eval...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	509,952
2010.01359	Perplexity-free Parametric t-SNE	The t-distributed Stochastic Neighbor Embedding (t-SNE) algorithm is a ubiquitously employed dimensionality reduction (DR) method. Its non-parametric nature and impressive efficacy motivated its parametric extension. It is however bounded to a user-defined perplexity parameter, restricting its DR quality compared to re...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	198,620
2209.12043	Unsupervised domain adaptation for speech recognition with unsupervised error correction	The transcription quality of automatic speech recognition (ASR) systems degrades significantly when transcribing audios coming from unseen domains. We propose an unsupervised error correction method for unsupervised ASR domain adaption, aiming to recover transcription errors caused by domain mismatch. Unlike existing c...	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	319,394
2502.08692	Efficient Split Learning LSTM Models for FPGA-based Edge IoT Devices	Split Learning (SL) recently emerged as an efficient paradigm for distributed Machine Learning (ML) suitable for the Internet Of Things (IoT)-Cloud systems. However, deploying SL on resource-constrained edge IoT platforms poses a significant challenge in terms of balancing the model performance against the processing, ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	533,134
2209.08615	Membership Inference Attacks and Generalization: A Causal Perspective	Membership inference (MI) attacks highlight a privacy weakness in present stochastic training methods for neural networks. It is not well understood, however, why they arise. Are they a natural consequence of imperfect generalization only? Which underlying causes should we address during training to mitigate these atta...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	318,191
1409.5224	Plug-and-play fault diagnosis and control-reconfiguration for a class of nonlinear large-scale constrained systems	This paper deals with a novel Plug-and-Play (PnP) architecture for the control and monitoring of Large-Scale Systems (LSSs). The proposed approach integrates a distributed Model Predictive Control (MPC) strategy with a distributed Fault Detection (FD) architecture and methodology in a PnP framework. The basic concept i...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	36,147
2304.00260	Gaussian Mechanism Design for Prescribed Privacy Sets in Data Releasing Systems	The data transmitted by cyber-physical systems can be intercepted and exploited by malicious individuals to infer privacy-sensitive information regarding the physical system. This motivates us to study the problem of preserving privacy in data releasing of linear dynamical system using stochastic perturbation. In this ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	355,622
2501.00924	On the Low-Complexity of Fair Learning for Combinatorial Multi-Armed Bandit	Combinatorial Multi-Armed Bandit with fairness constraints is a framework where multiple arms form a super arm and can be pulled in each round under uncertainty to maximize cumulative rewards while ensuring the minimum average reward required by each arm. The existing pessimistic-optimistic algorithm linearly combines ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	521,859
1509.04904	Causal Model Analysis using Collider v-structure with Negative Percentage Mapping	A major problem of causal inference is the arrangement of dependent nodes in a directed acyclic graph (DAG) with path coefficients and observed confounders. Path coefficients do not provide the units to measure the strength of information flowing from one node to the other. Here we proposed the method of causal structu...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	46,985
0801.3986	New Lower Bounds on Sizes of Permutation Arrays	A permutation array(or code) of length $n$ and distance $d$, denoted by $(n,d)$ PA, is a set of permutations $C$ from some fixed set of $n$ elements such that the Hamming distance between distinct members $\mathbf{x},\mathbf{y}\in C$ is at least $d$. Let $P(n,d)$ denote the maximum size of an $(n,d)$ PA. This correspon...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	1,213
2311.16143	Ransomware Detection and Classification using Machine Learning	Vicious assaults, malware, and various ransomware pose a cybersecurity threat, causing considerable damage to computer structures, servers, and mobile and web apps across various industries and businesses. These safety concerns are important and must be addressed immediately. Ransomware detection and classification are...	false	false	false	false	true	false	true	false	false	false	false	true	true	false	false	false	false	false	410,791
1805.04836	Building Language Models for Text with Named Entities	Text in many domains involves a significant amount of named entities. Predict- ing the entity names is often challenging for a language model as they appear less frequent on the training corpus. In this paper, we propose a novel and effective approach to building a discriminative language model which can learn the enti...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	97,322
2306.15876	Hybrid Distillation: Connecting Masked Autoencoders with Contrastive Learners	Representation learning has been evolving from traditional supervised training to Contrastive Learning (CL) and Masked Image Modeling (MIM). Previous works have demonstrated their pros and cons in specific scenarios, i.e., CL and supervised pre-training excel at capturing longer-range global patterns and enabling bette...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	376,184
2111.10339	Bi-Mix: Bidirectional Mixing for Domain Adaptive Nighttime Semantic Segmentation	In autonomous driving, learning a segmentation model that can adapt to various environmental conditions is crucial. In particular, copying with severe illumination changes is an impelling need, as models trained on daylight data will perform poorly at nighttime. In this paper, we study the problem of Domain Adaptive Ni...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	267,290
0812.0070	An Integrated Software-based Solution for Modular and Self-independent Networked Robot	An integrated software-based solution for a modular and self-independent networked robot is introduced. The wirelessly operatable robot has been developed mainly for autonomous monitoring works with full control over web. The integrated software solution covers three components : a) the digital signal processing unit f...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	2,727
2208.00904	Revisiting Information Cascades in Online Social Networks	It's by now folklore that to understand the activity pattern of a user in an online social network (OSN) platform, one needs to look at his friends or the ones he follows. The common perception is that these friends exert influence on the user, effecting his decision whether to re-share content or not. Hinging upon thi...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	true	311,013
2304.09840	Optimum Output Long Short-Term Memory Cell for High-Frequency Trading Forecasting	High-frequency trading requires fast data processing without information lags for precise stock price forecasting. This high-paced stock price forecasting is usually based on vectors that need to be treated as sequential and time-independent signals due to the time irregularities that are inherent in high-frequency tra...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	359,194
1801.04263	Efficient Probabilistic Model Checking of Smart Building Maintenance using Fault Maintenance Trees	Cyber-physical systems, like Smart Buildings and power plants, have to meet high standards, both in terms of reliability and availability. Such metrics are typically evaluated using Fault trees (FTs) and do not consider maintenance strategies which can significantly improve lifespan and reliability. Fault Maintenance t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	88,240
2410.11417	VidCompress: Memory-Enhanced Temporal Compression for Video Understanding in Large Language Models	Video-based multimodal large language models (Video-LLMs) possess significant potential for video understanding tasks. However, most Video-LLMs treat videos as a sequential set of individual frames, which results in insufficient temporal-spatial interaction that hinders fine-grained comprehension and difficulty in proc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	498,554
2211.10999	LA-VocE: Low-SNR Audio-visual Speech Enhancement using Neural Vocoders	Audio-visual speech enhancement aims to extract clean speech from a noisy environment by leveraging not only the audio itself but also the target speaker's lip movements. This approach has been shown to yield improvements over audio-only speech enhancement, particularly for the removal of interfering speech. Despite re...	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	331,536
cs/0610067	Language, logic and ontology: uncovering the structure of commonsense knowledge	The purpose of this paper is twofold: (i) we argue that the structure of commonsense knowledge must be discovered, rather than invented; and (ii) we argue that natural language, which is the best known theory of our (shared) commonsense knowledge, should itself be used as a guide to discovering the structure of commons...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	539,781
2409.01646	BEVNav: Robot Autonomous Navigation Via Spatial-Temporal Contrastive Learning in Bird's-Eye View	Goal-driven mobile robot navigation in map-less environments requires effective state representations for reliable decision-making. Inspired by the favorable properties of Bird's-Eye View (BEV) in point clouds for visual perception, this paper introduces a novel navigation approach named BEVNav. It employs deep reinfor...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	485,422
2202.05998	What Makes Good Contrastive Learning on Small-Scale Wearable-based Tasks?	Self-supervised learning establishes a new paradigm of learning representations with much fewer or even no label annotations. Recently there has been remarkable progress on large-scale contrastive learning models which require substantial computing resources, yet such models are not practically optimal for small-scale ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	280,056
2103.02405	Relate and Predict: Structure-Aware Prediction with Jointly Optimized Neural DAG	Understanding relationships between feature variables is one important way humans use to make decisions. However, state-of-the-art deep learning studies either focus on task-agnostic statistical dependency learning or do not model explicit feature dependencies during prediction. We propose a deep neural network framewo...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	222,956
2402.12887	The practice of qualitative parameterisation in the development of Bayesian networks	The typical phases of Bayesian network (BN) structured development include specification of purpose and scope, structure development, parameterisation and validation. Structure development is typically focused on qualitative issues and parameterisation quantitative issues, however there are qualitative and quantitative...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	431,037
2107.07788	Reinforcement Learning for Adaptive Optimal Stationary Control of Linear Stochastic Systems	This paper studies the adaptive optimal stationary control of continuous-time linear stochastic systems with both additive and multiplicative noises, using reinforcement learning techniques. Based on policy iteration, a novel off-policy reinforcement learning algorithm, named optimistic least-squares-based policy itera...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	246,530
2111.13621	An Optimal Algorithm for Finding Champions in Tournament Graphs	A tournament graph is a complete directed graph, which can be used to model a round-robin tournament between $n$ players. In this paper, we address the problem of finding a champion of the tournament, also known as Copeland winner, which is a player that wins the highest number of matches. In detail, we aim to investig...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	268,339
2110.00731	Learning Region of Attraction for Nonlinear Systems	Estimating the region of attraction (ROA) of general nonlinear autonomous systems remains a challenging problem and requires a case-by-case analysis. Leveraging the universal approximation property of neural networks, in this paper, we propose a counterexample-guided method to estimate the ROA of general nonlinear dyna...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	258,510
2205.08754	Revisiting PINNs: Generative Adversarial Physics-informed Neural Networks and Point-weighting Method	Physics-informed neural networks (PINNs) provide a deep learning framework for numerically solving partial differential equations (PDEs), and have been widely used in a variety of PDE problems. However, there still remain some challenges in the application of PINNs: 1) the mechanism of PINNs is unsuitable (at least can...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	297,044
2408.06447	S-SAM: SVD-based Fine-Tuning of Segment Anything Model for Medical Image Segmentation	Medical image segmentation has been traditionally approached by training or fine-tuning the entire model to cater to any new modality or dataset. However, this approach often requires tuning a large number of parameters during training. With the introduction of the Segment Anything Model (SAM) for prompted segmentation...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	480,208
2411.04279	Novel Non-Prehensile Rolling Problem: Modelling and Balance Control of Pendulum-Driven Reconfigurable Disks Motion with Magnetic Coupling in Simulation	This paper presents a novel type of mobile rolling robot designed as a modular platform for non-prehensile manipulation, highlighting the associated control challenges in achieving balancing control of the robotic system. The developed rolling disk modules incorporate an innovative internally actuated magnetic-pendulum...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	506,204
2302.00275	Learning Generalized Zero-Shot Learners for Open-Domain Image Geolocalization	Image geolocalization is the challenging task of predicting the geographic coordinates of origin for a given photo. It is an unsolved problem relying on the ability to combine visual clues with general knowledge about the world to make accurate predictions across geographies. We present $\href{https://huggingface.co/ge...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	343,167
2306.01757	State estimation for one-dimensional agro-hydrological processes with model mismatch	The importance of accurate soil moisture data for the development of modern closed-loop irrigation systems cannot be overstated. Due to the diversity of soil, it is difficult to obtain an accurate model for agro-hydrological system. In this study, soil moisture estimation in 1D agro-hydrological systems with model mism...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	370,589
2307.14453	Predictive Maintenance of Armoured Vehicles using Machine Learning Approaches	Armoured vehicles are specialized and complex pieces of machinery designed to operate in high-stress environments, often in combat or tactical situations. This study proposes a predictive maintenance-based ensemble system that aids in predicting potential maintenance needs based on sensor data collected from these vehi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	381,936
1809.10330	Variance reduction properties of the reparameterization trick	The reparameterization trick is widely used in variational inference as it yields more accurate estimates of the gradient of the variational objective than alternative approaches such as the score function method. Although there is overwhelming empirical evidence in the literature showing its success, there is relative...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	108,890
2003.03220	Deep Active Inference for Autonomous Robot Navigation	Active inference is a theory that underpins the way biological agent's perceive and act in the real world. At its core, active inference is based on the principle that the brain is an approximate Bayesian inference engine, building an internal generative model to drive agents towards minimal surprise. Although this the...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	167,162
2307.06060	Interpreting deep embeddings for disease progression clustering	We propose a novel approach for interpreting deep embeddings in the context of patient clustering. We evaluate our approach on a dataset of participants with type 2 diabetes from the UK Biobank, and demonstrate clinically meaningful insights into disease progression patterns.	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	378,953
1911.11365	ATCSpeech: a multilingual pilot-controller speech corpus from real Air Traffic Control environment	Automatic Speech Recognition (ASR) is greatly developed in recent years, which expedites many applications on other fields. For the ASR research, speech corpus is always an essential foundation, especially for the vertical industry, such as Air Traffic Control (ATC). There are some speech corpora for common application...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	155,099
1608.00339	Crowd-sourcing NLG Data: Pictures Elicit Better Data	Recent advances in corpus-based Natural Language Generation (NLG) hold the promise of being easily portable across domains, but require costly training data, consisting of meaning representations (MRs) paired with Natural Language (NL) utterances. In this work, we propose a novel framework for crowdsourcing high qualit...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	59,274
2212.05602	ResFed: Communication Efficient Federated Learning by Transmitting Deep Compressed Residuals	Federated learning enables cooperative training among massively distributed clients by sharing their learned local model parameters. However, with increasing model size, deploying federated learning requires a large communication bandwidth, which limits its deployment in wireless networks. To address this bottleneck, w...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	335,832
2210.15279	On the Approximation and Complexity of Deep Neural Networks to Invariant Functions	Recent years have witnessed a hot wave of deep neural networks in various domains; however, it is not yet well understood theoretically. A theoretical characterization of deep neural networks should point out their approximation ability and complexity, i.e., showing which architecture and size are sufficient to handle ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	326,885
2201.01745	Atomized Search Length: Beyond User Models	We argue that current IR metrics, modeled on optimizing user experience, measure too narrow a portion of the IR space. If IR systems are weak, these metrics undersample or completely filter out the deeper documents that need improvement. If IR systems are relatively strong, these metrics undersample deeper relevant doc...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	274,337
2211.11130	Safe Stabilization for Stochastic Time-Delay Systems	This paper addresses the safe stabilization problem of stochastic nonlinear time-delay systems. Based on theKrasovskii approach, we first propose a stochastic control Lyapunov-Krasovskii functional to guarantee the stabilization objective and a stochastic control barrier-Krasovskii functional to ensure the safety objec...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	331,592
1811.02949	Instance Retrieval at Fine-grained Level Using Multi-Attribute Recognition	In this paper, we present a method for instance ranking and retrieval at fine-grained level based on the global features extracted from a multi-attribute recognition model which is not dependent on landmarks information or part-based annotations. Further, we make this architecture suitable for mobile-device application...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	112,728
1301.4432	Language learning from positive evidence, reconsidered: A simplicity-based approach	Children learn their native language by exposure to their linguistic and communicative environment, but apparently without requiring that their mistakes are corrected. Such learning from positive evidence has been viewed as raising logical problems for language acquisition. In particular, without correction, how is the...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	21,248
2502.08414	Sparse Estimation of Inverse Covariance and Partial Correlation Matrices via Joint Partial Regression	We present a new method for estimating high-dimensional sparse partial correlation and inverse covariance matrices, which exploits the connection between the inverse covariance matrix and linear regression. The method is a two-stage estimation method wherein each individual feature is regressed on all other features wh...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	533,005
2009.05554	Synthesis of Run-To-Completion Controllers for Discrete Event Systems	A controller for a Discrete Event System must achieve its goals despite that its environment being capable of resolving race conditions between controlled and uncontrolled events.Assuming that the controller loses all races is sometimes unrealistic. In many cases, a realistic assumption is that the controller sometimes...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	195,352
1608.07468	On Mathematical structures on pairwise comparisons matrices with coefficients in a group arising from quantum gravity	We describe the mathematical properties of pairwise comparisons matrices with coefficients in an arbitrary group. We provide a vocabulary adapted for the description of main algebraic properties of inconsistency maps, describe an example where the use of a non abelian group is necessary. Algebraic, topological, geometr...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	60,234
2402.18124	Dark energy reconstruction analysis with artificial neural networks: Application on simulated Supernova Ia data from Rubin Observatory	In this paper, we present an analysis of Supernova Ia (SNIa) distance moduli $\mu(z)$ and dark energy using an Artificial Neural Network (ANN) reconstruction based on LSST simulated three-year SNIa data. The ANNs employed in this study utilize genetic algorithms for hyperparameter tuning and Monte Carlo Dropout for pre...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	433,295
2410.07388	On Densest $k$-Subgraph Mining and Diagonal Loading	The Densest $k$-Subgraph (D$k$S) problem aims to find a subgraph comprising $k$ vertices with the maximum number of edges between them. A continuous reformulation of the binary quadratic D$k$S problem is considered, which incorporates a diagonal loading term. It is shown that this non-convex, continuous relaxation is t...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	496,598
2308.14423	GADePo: Graph-Assisted Declarative Pooling Transformers for Document-Level Relation Extraction	Document-level relation extraction typically relies on text-based encoders and hand-coded pooling heuristics to aggregate information learned by the encoder. In this paper, we leverage the intrinsic graph processing capabilities of the Transformer model and propose replacing hand-coded pooling methods with new tokens i...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	388,329
2411.13683	Extending Video Masked Autoencoders to 128 frames	Video understanding has witnessed significant progress with recent video foundation models demonstrating strong performance owing to self-supervised pre-training objectives; Masked Autoencoders (MAE) being the design of choice. Nevertheless, the majority of prior works that leverage MAE pre-training have focused on rel...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	509,881
2409.08249	Quantifying Aleatoric and Epistemic Dynamics Uncertainty via Local Conformal Calibration	Whether learned, simulated, or analytical, approximations of a robot's dynamics can be inaccurate when encountering novel environments. Many approaches have been proposed to quantify the aleatoric uncertainty of such methods, i.e. uncertainty resulting from stochasticity, however these estimates alone are not enough to...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	487,827
1610.02707	Multi-Objective Deep Reinforcement Learning	We propose Deep Optimistic Linear Support Learning (DOL) to solve high-dimensional multi-objective decision problems where the relative importances of the objectives are not known a priori. Using features from the high-dimensional inputs, DOL computes the convex coverage set containing all potential optimal solutions o...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	62,144
2312.14262	Exploring the intersection of Generative AI and Software Development	In the ever-evolving landscape of Artificial Intelligence (AI), the synergy between generative AI and Software Engineering emerges as a transformative frontier. This whitepaper delves into the unexplored realm, elucidating how generative AI techniques can revolutionize software development. Spanning from project manage...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	417,569
2408.01251	NeRFoot: Robot-Footprint Estimation for Image-Based Visual Servoing	This paper investigates the utility of Neural Radiance Fields (NeRF) models in extending the regions of operation of a mobile robot, controlled by Image-Based Visual Servoing (IBVS) via static CCTV cameras. Using NeRF as a 3D-representation prior, the robot's footprint may be extrapolated geometrically and used to trai...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	478,156
1503.00923	An Interoperable Realization of Smart Cities with Plug and Play based Device Management	The primal problem with Internet of Things (IoT) solutions for smart cities is the lack of interoperability at various levels, and more predominately at the device level. While there exist multitude of platforms from multiple manufacturers, the existing ecosystem still remains highly closed. In this paper, we propose S...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	40,768
2005.05286	From industry-wide parameters to aircraft-centric on-flight inference: improving aeronautics performance prediction with machine learning	Aircraft performance models play a key role in airline operations, especially in planning a fuel-efficient flight. In practice, manufacturers provide guidelines which are slightly modified throughout the aircraft life cycle via the tuning of a single factor, enabling better fuel predictions. However this has limitation...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	176,693
1706.01177	PReP: Path-Based Relevance from a Probabilistic Perspective in Heterogeneous Information Networks	As a powerful representation paradigm for networked and multi-typed data, the heterogeneous information network (HIN) is ubiquitous. Meanwhile, defining proper relevance measures has always been a fundamental problem and of great pragmatic importance for network mining tasks. Inspired by our probabilistic interpretatio...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	74,764
2201.09521	Problife: a Probabilistic Game of Life	This paper presents a probabilistic extension of the well-known cellular automaton, Game of Life. In Game of Life, cells are placed in a grid and then watched as they evolve throughout subsequent generations, as dictated by the rules of the game. In our extension, called ProbLife, these rules now have probabilities ass...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	276,700
2004.01857	Weighted Fisher Discriminant Analysis in the Input and Feature Spaces	Fisher Discriminant Analysis (FDA) is a subspace learning method which minimizes and maximizes the intra- and inter-class scatters of data, respectively. Although, in FDA, all the pairs of classes are treated the same way, some classes are closer than the others. Weighted FDA assigns weights to the pairs of classes to ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	171,031
1811.03494	Testing SPARUS II AUV, an open platform for industrial, scientific and academic applications	This paper describes the experience of preparing and testing the SPARUS II AUV in different applications. The AUV was designed as a lightweight vehicle combining the classical torpedo-shape features with the hovering capability. The robot has a payload area to allow the integration of different equipment depending on t...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	112,852
2205.04166	Residue-based Label Protection Mechanisms in Vertical Logistic Regression	Federated learning (FL) enables distributed participants to collaboratively learn a global model without revealing their private data to each other. Recently, vertical FL, where the participants hold the same set of samples but with different features, has received increased attention. This paper first presents one lab...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	295,558
2205.06779	Scribble2D5: Weakly-Supervised Volumetric Image Segmentation via Scribble Annotations	Recently, weakly-supervised image segmentation using weak annotations like scribbles has gained great attention, since such annotations are much easier to obtain compared to time-consuming and label-intensive labeling at the pixel/voxel level. However, because scribbles lack structure information of region of interest ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	296,350
2212.02448	The Multi-cluster Fluctuating Two-Ray Fading Model	We introduce a new class of fading channels, built as the superposition of two fluctuating specular components with random phases, plus a clustering of scattered waves: the Multi-cluster Fluctuating Two-Ray (MFTR) fading channel. The MFTR model emerges as a natural generalization of both the fluctuating two-ray (FTR) a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	334,790
1806.07351	Opportunistic Scheduling in Underlay Cognitive Radio based Systems: User Selection Probability Analysis	In this paper, an underlay cognitive radio (CR) system is considered with multiple cognitive or secondary users contending to transmit their information to the cognitive destination (e.g., eNodeB) using the spectral resource of a primary user. The novel closed-form expressions are derived for the selection probabilitie...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	100,901
2103.08862	Gumbel-Attention for Multi-modal Machine Translation	Multi-modal machine translation (MMT) improves translation quality by introducing visual information. However, the existing MMT model ignores the problem that the image will bring information irrelevant to the text, causing much noise to the model and affecting the translation quality. This paper proposes a novel Gumbe...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	225,008
2302.12552	Deep Learning for Video-Text Retrieval: a Review	Video-Text Retrieval (VTR) aims to search for the most relevant video related to the semantics in a given sentence, and vice versa. In general, this retrieval task is composed of four successive steps: video and textual feature representation extraction, feature embedding and matching, and objective functions. In the l...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	347,610
2410.13765	Knowledge-Aware Query Expansion with Large Language Models for Textual and Relational Retrieval	Large language models (LLMs) have been used to generate query expansions augmenting original queries for improving information search. Recent studies also explore providing LLMs with initial retrieval results to generate query expansions more grounded to document corpus. However, these methods mostly focus on enhancing...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	499,674
2109.13081	Semi-Autonomous Teleoperation via Learning Non-Prehensile Manipulation Skills	In this paper, we present a semi-autonomous teleoperation framework for a pick-and-place task using an RGB-D sensor. In particular, we assume that the target object is located in a cluttered environment where both prehensile grasping and non-prehensile manipulation are combined for efficient teleoperation. A trajectory...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	257,518
2409.10829	ReXErr: Synthesizing Clinically Meaningful Errors in Diagnostic Radiology Reports	Accurately interpreting medical images and writing radiology reports is a critical but challenging task in healthcare. Both human-written and AI-generated reports can contain errors, ranging from clinical inaccuracies to linguistic mistakes. To address this, we introduce ReXErr, a methodology that leverages Large Langu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	488,895
1712.02121	A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network	In this paper, we propose a novel embedding model, named ConvKB, for knowledge base completion. Our model ConvKB advances state-of-the-art models by employing a convolutional neural network, so that it can capture global relationships and transitional characteristics between entities and relations in knowledge bases. I...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	86,242
2410.05684	Copiloting Diagnosis of Autism in Real Clinical Scenarios via LLMs	Autism spectrum disorder(ASD) is a pervasive developmental disorder that significantly impacts the daily functioning and social participation of individuals. Despite the abundance of research focused on supporting the clinical diagnosis of ASD, there is still a lack of systematic and comprehensive exploration in the fi...	true	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	495,860
2205.15924	Continuous Temporal Graph Networks for Event-Based Graph Data	There has been an increasing interest in modeling continuous-time dynamics of temporal graph data. Previous methods encode time-evolving relational information into a low-dimensional representation by specifying discrete layers of neural networks, while real-world dynamic graphs often vary continuously over time. Hence...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	299,918
2009.07828	Human biases in body measurement estimation	Body measurements, including weight and height, are key indicators of health. Being able to visually assess body measurements reliably is a step towards increased awareness of overweight and obesity and is thus important for public health. Nevertheless it is currently not well understood how accurately humans can asses...	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	196,060
2010.14995	Accelerated Probabilistic Power Flow in Electrical Distribution Networks via Model Order Reduction and Neumann Series Expansion	This paper develops a computationally efficient algorithm which speeds up the probabilistic power flow (PPF) problem by exploiting the inherently low-rank nature of the voltage profile in electrical power distribution networks. The algorithm is accordingly termed the Accelerated-PPF (APPF), since it can accelerate "any...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	203,639
1801.00708	Restricted Deformable Convolution based Road Scene Semantic Segmentation Using Surround View Cameras	Understanding the surrounding environment of the vehicle is still one of the challenges for autonomous driving. This paper addresses 360-degree road scene semantic segmentation using surround view cameras, which are widely equipped in existing production cars. First, in order to address large distortion problem in the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	87,614

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