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
2502.02308	Real-Time Operator Takeover for Visuomotor Diffusion Policy Training	We present a Real-Time Operator Takeover (RTOT) paradigm enabling operators to seamlessly take control of a live visuomotor diffusion policy, guiding the system back into desirable states or reinforcing specific demonstrations. We present new insights in using the Mahalonobis distance to automatically identify undesira...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	530,256
2410.03913	Leveraging Fundamental Analysis for Stock Trend Prediction for Profit	This paper investigates the application of machine learning models, Long Short-Term Memory (LSTM), one-dimensional Convolutional Neural Networks (1D CNN), and Logistic Regression (LR), for predicting stock trends based on fundamental analysis. Unlike most existing studies that predominantly utilize technical or sentime...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	495,038
2106.07020	Generation of the NIR spectral Band for Satellite Images with Convolutional Neural Networks	The near-infrared (NIR) spectral range (from 780 to 2500 nm) of the multispectral remote sensing imagery provides vital information for the landcover classification, especially concerning the vegetation assessment. Despite the usefulness of NIR, common RGB is not always accompanied by it. Modern achievements in image p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	240,734
2207.12840	Partial-Monotone Adaptive Submodular Maximization	Many sequential decision making problems, including pool-based active learning and adaptive viral marketing, can be formulated as an adaptive submodular maximization problem. Most of existing studies on adaptive submodular optimization focus on either monotone case or non-monotone case. Specifically, if the utility fun...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	310,128
2202.03301	Some Results on the Improved Bound and Construction of Optimal $(r,\delta)$ LRCs	Locally repairable codes (LRCs) with $(r,\delta)$ locality were introduced by Prakash \emph{et al.} into distributed storage systems (DSSs) due to their benefit of locally repairing at least $\delta-1$ erasures via other $r$ survival nodes among the same local group. An LRC achieving the $(r,\delta)$ Singleton-type bou...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	279,157
2107.00708	Blind Image Super-Resolution via Contrastive Representation Learning	Image super-resolution (SR) research has witnessed impressive progress thanks to the advance of convolutional neural networks (CNNs) in recent years. However, most existing SR methods are non-blind and assume that degradation has a single fixed and known distribution (e.g., bicubic) which struggle while handling degrad...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	244,245
2201.06435	FourierNet: Shape-Preserving Network for Henle's Fiber Layer Segmentation in Optical Coherence Tomography Images	The Henle's fiber layer (HFL) in the retina carries valuable information on the macular condition of an eye. However, in the common practice, this layer is not separately segmented but rather included in the outer nuclear layer since it is difficult to perceive HFL contours on standard optical coherence tomography (OCT...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	275,727
2211.10338	Deep learning based landslide density estimation on SAR data for rapid response	This work aims to produce landslide density estimates using Synthetic Aperture Radar (SAR) satellite imageries to prioritise emergency resources for rapid response. We use the United States Geological Survey (USGS) Landslide Inventory data annotated by experts after Hurricane Mar\'ia in Puerto Rico on Sept 20, 2017, an...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	331,278
1807.05960	Meta-Learning with Latent Embedding Optimization	Gradient-based meta-learning techniques are both widely applicable and proficient at solving challenging few-shot learning and fast adaptation problems. However, they have practical difficulties when operating on high-dimensional parameter spaces in extreme low-data regimes. We show that it is possible to bypass these ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	103,026
2410.00434	Rapid Integration of LLMs in Healthcare Raises Ethical Concerns: An Investigation into Deceptive Patterns in Social Robots	Conversational agents are increasingly used in healthcare, and the integration of Large Language Models (LLMs) has significantly enhanced their capabilities. When integrated into social robots, LLMs offer the potential for more natural interactions. However, while LLMs promise numerous benefits, they also raise critica...	false	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	493,378
1911.02514	Fuzzy Inference Procedure for Intelligent and Automated Control of Refrigerant Charging	Fuzzy logic controllers are readily customizable in natural language terms and can effectively deal with nonlinearities and uncertainties in control systems. This paper presents an intelligent and automated fuzzy control procedure for the refrigerant charging of refrigerators. The elements that affect the experimental ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	152,379
2103.01988	Self-supervised Pretraining of Visual Features in the Wild	Recently, self-supervised learning methods like MoCo, SimCLR, BYOL and SwAV have reduced the gap with supervised methods. These results have been achieved in a control environment, that is the highly curated ImageNet dataset. However, the premise of self-supervised learning is that it can learn from any random image an...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	222,811
1211.6166	Tracking and Quantifying Censorship on a Chinese Microblogging Site	We present measurements and analysis of censorship on Weibo, a popular microblogging site in China. Since we were limited in the rate at which we could download posts, we identified users likely to participate in sensitive topics and recursively followed their social contacts. We also leveraged new natural language pro...	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	19,958
1507.00695	A new framework for dynamical models on multiplex networks	Many complex systems have natural representations as multi-layer networks. While these formulations retain more information than standard single-layer network models, there is not yet a fully developed theory for computing network metrics and statistics on these objects. We introduce a family of models of multiplex pro...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	44,782
1901.09658	Identifying influential nodes based on fuzzy local dimension in complex networks	How to identify influential nodes in complex networks is an important aspect in the study of complex network. In this paper, a novel fuzzy local dimension (FLD) is proposed to rank the influential nodes in complex networks, where a node with high fuzzy local dimension has high influential ability. This proposed method ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	119,804
2009.09943	NeuroDiff: Scalable Differential Verification of Neural Networks using Fine-Grained Approximation	As neural networks make their way into safety-critical systems, where misbehavior can lead to catastrophes, there is a growing interest in certifying the equivalence of two structurally similar neural networks. For example, compression techniques are often used in practice for deploying trained neural networks on compu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	196,753
2110.10367	Constructions and Applications of Perfect Difference Matrices and Perfect Difference Families	Perfect difference families (PDFs for short) are important both in theoretical and in applications. Perfect difference matrices (PDMs for short) and the equivalent structure had been extensively studied and used to construct perfect difference families, radar array and related codes. The necessary condition for the exi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	262,129
1207.0145	Massively Parallel Sort-Merge Joins in Main Memory Multi-Core Database Systems	Two emerging hardware trends will dominate the database system technology in the near future: increasing main memory capacities of several TB per server and massively parallel multi-core processing. Many algorithmic and control techniques in current database technology were devised for disk-based systems where I/O domi...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	17,139
2110.09004	NYU-VPR: Long-Term Visual Place Recognition Benchmark with View Direction and Data Anonymization Influences	Visual place recognition (VPR) is critical in not only localization and mapping for autonomous driving vehicles, but also in assistive navigation for the visually impaired population. To enable a long-term VPR system on a large scale, several challenges need to be addressed. First, different applications could require ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	261,643
2303.15318	Closed-Loop Koopman Operator Approximation	This paper proposes a method to identify a Koopman model of a feedback-controlled system given a known controller. The Koopman operator allows a nonlinear system to be rewritten as an infinite-dimensional linear system by viewing it in terms of an infinite set of lifting functions. A finite-dimensional approximation of...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	354,448
1908.05751	Examining the Use of Temporal-Difference Incremental Delta-Bar-Delta for Real-World Predictive Knowledge Architectures	Predictions and predictive knowledge have seen recent success in improving not only robot control but also other applications ranging from industrial process control to rehabilitation. A property that makes these predictive approaches well suited for robotics is that they can be learned online and incrementally through...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	141,798
1708.08987	Deep Learning for Medical Image Analysis	This report describes my research activities in the Hasso Plattner Institute and summarizes my Ph.D. plan and several novels, end-to-end trainable approaches for analyzing medical images using deep learning algorithm. In this report, as an example, we explore different novel methods based on deep learning for brain abn...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	79,707
cs/0501028	An Empirical Study of MDL Model Selection with Infinite Parametric Complexity	Parametric complexity is a central concept in MDL model selection. In practice it often turns out to be infinite, even for quite simple models such as the Poisson and Geometric families. In such cases, MDL model selection as based on NML and Bayesian inference based on Jeffreys' prior can not be used. Several ways to r...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	538,488
2402.14976	Unsupervised Domain Adaptation within Deep Foundation Latent Spaces	The vision transformer-based foundation models, such as ViT or Dino-V2, are aimed at solving problems with little or no finetuning of features. Using a setting of prototypical networks, we analyse to what extent such foundation models can solve unsupervised domain adaptation without finetuning over the source or target...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	431,934
2401.04114	Timeline-based Process Discovery	A key concern of automatic process discovery is to provide insights into performance aspects of business processes. Waiting times are of particular importance in this context. For that reason, it is surprising that current techniques for automatic process discovery generate directly-follows graphs and comparable proces...	true	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	420,327
0910.2240	Repeated Auctions with Learning for Spectrum Access in Cognitive Radio Networks	In this paper, spectrum access in cognitive radio networks is modeled as a repeated auction game subject to monitoring and entry costs. For secondary users, sensing costs are incurred as the result of primary users' activity. Furthermore, each secondary user pays the cost of transmissions upon successful bidding for a ...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	4,718
2406.14762	Regularized Distribution Matching Distillation for One-step Unpaired Image-to-Image Translation	Diffusion distillation methods aim to compress the diffusion models into efficient one-step generators while trying to preserve quality. Among them, Distribution Matching Distillation (DMD) offers a suitable framework for training general-form one-step generators, applicable beyond unconditional generation. In this wor...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	466,452
2206.05730	Object Occlusion of Adding New Categories in Objection Detection	Building instance detection models that are data efficient and can handle rare object categories is an important challenge in computer vision. But data collection methods and metrics are lack of research towards real scenarios application using neural network. Here, we perform a systematic study of the Object Occlusion...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	302,114
2305.01655	Predicting blood pressure under circumstances of missing data: An analysis of missing data patterns and imputation methods using NHANES	The World Health Organization defines cardio-vascular disease (CVD) as "a group of disorders of the heart and blood vessels," including coronary heart disease and stroke (WHO 21). CVD is affected by "intermediate risk factors" such as raised blood pressure, raised blood glucose, raised blood lipids, and obesity. These ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	361,757
1607.08635	A 58.6mW Real-Time Programmable Object Detector with Multi-Scale Multi-Object Support Using Deformable Parts Model on 1920x1080 Video at 30fps	This paper presents a programmable, energy-efficient and real-time object detection accelerator using deformable parts models (DPM), with 2x higher accuracy than traditional rigid body models. With 8 deformable parts detection, three methods are used to address the high computational complexity: classification pruning ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	59,179
2308.06974	A One Stop 3D Target Reconstruction and multilevel Segmentation Method	3D object reconstruction and multilevel segmentation are fundamental to computer vision research. Existing algorithms usually perform 3D scene reconstruction and target objects segmentation independently, and the performance is not fully guaranteed due to the challenge of the 3D segmentation. Here we propose an open-so...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	385,351
2103.05774	A principled approach for weighted multilayer network aggregation	A multilayer network depicts different types of interactions among the same set of nodes. For example, protease networks consist of five to seven layers, where different layers represent distinct types of experimentally confirmed molecule interactions among proteins. In a multilayer protease network, the co-expression ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	224,083
2206.07652	Two-stage Human Activity Recognition on Microcontrollers with Decision Trees and CNNs	Human Activity Recognition (HAR) has become an increasingly popular task for embedded devices such as smartwatches. Most HAR systems for ultra-low power devices are based on classic Machine Learning (ML) models, whereas Deep Learning (DL), although reaching state-of-the-art accuracy, is less popular due to its high ene...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	302,824
2211.06934	TorchOpt: An Efficient Library for Differentiable Optimization	Recent years have witnessed the booming of various differentiable optimization algorithms. These algorithms exhibit different execution patterns, and their execution needs massive computational resources that go beyond a single CPU and GPU. Existing differentiable optimization libraries, however, cannot support efficie...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	330,077
2303.07184	Traffic Prediction with Transfer Learning: A Mutual Information-based Approach	In modern traffic management, one of the most essential yet challenging tasks is accurately and timely predicting traffic. It has been well investigated and examined that deep learning-based Spatio-temporal models have an edge when exploiting Spatio-temporal relationships in traffic data. Typically, data-driven models ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	351,156
2104.00086	An Online Survey on the Perception of Mediated Social Touch Interaction and Device Design	Social touch is essential for our social interactions, communication, and well-being. It has been shown to reduce anxiety and loneliness; and is a key channel to transmit emotions for which words are not sufficient, such as love, sympathy, reassurance, etc. However, direct physical contact is not always possible due to...	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	227,870
2201.10252	DocEnTr: An End-to-End Document Image Enhancement Transformer	Document images can be affected by many degradation scenarios, which cause recognition and processing difficulties. In this age of digitization, it is important to denoise them for proper usage. To address this challenge, we present a new encoder-decoder architecture based on vision transformers to enhance both machine...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	276,927
1806.09445	A Unified Model with Structured Output for Fashion Images Classification	A picture is worth a thousand words. Albeit a clich\'e, for the fashion industry, an image of a clothing piece allows one to perceive its category (e.g., dress), sub-category (e.g., day dress) and properties (e.g., white colour with floral patterns). The seasonal nature of the fashion industry creates a highly dynamic ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	101,354
2404.15501	Killkan: The Automatic Speech Recognition Dataset for Kichwa with Morphosyntactic Information	This paper presents Killkan, the first dataset for automatic speech recognition (ASR) in the Kichwa language, an indigenous language of Ecuador. Kichwa is an extremely low-resource endangered language, and there have been no resources before Killkan for Kichwa to be incorporated in applications of natural language proc...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	449,118
2408.07857	An Exploratory Case Study of Query Plan Representations	In database systems, a query plan is a series of concrete internal steps to execute a query. Multiple testing approaches utilize query plans for finding bugs. However, query plans are represented in a database-specific manner, so implementing these testing approaches requires a non-trivial effort, hindering their adopt...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	480,749
2310.14587	Large Search Model: Redefining Search Stack in the Era of LLMs	Modern search engines are built on a stack of different components, including query understanding, retrieval, multi-stage ranking, and question answering, among others. These components are often optimized and deployed independently. In this paper, we introduce a novel conceptual framework called large search model, wh...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	401,931
2408.07285	DDIM Redux: Mathematical Foundation and Some Extension	This note provides a critical review of the mathematical concepts underlying the generalized diffusion denoising implicit model (gDDIM) and the exponential integrator (EI) scheme. We present enhanced mathematical results, including an exact expression for the reverse trajectory in the probability flow ODE and an exact ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	480,526
2011.03303	Deep coastal sea elements forecasting using U-Net based models	The supply and demand of energy is influenced by meteorological conditions. The relevance of accurate weather forecasts increases as the demand for renewable energy sources increases. The energy providers and policy makers require weather information to make informed choices and establish optimal plans according to the...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	205,207
2405.20248	Image-to-Joint Inverse Kinematic of a Supportive Continuum Arm Using Deep Learning	In this work, a deep learning-based technique is used to study the image-to-joint inverse kinematics of a tendon-driven supportive continuum arm. An eye-off-hand configuration is considered by mounting a camera at a fixed pose with respect to the inertial frame attached at the arm base. This camera captures an image fo...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	459,258
2409.14195	The Imperative of Conversation Analysis in the Era of LLMs: A Survey of Tasks, Techniques, and Trends	In the era of large language models (LLMs), a vast amount of conversation logs will be accumulated thanks to the rapid development trend of language UI. Conversation Analysis (CA) strives to uncover and analyze critical information from conversation data, streamlining manual processes and supporting business insights a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	490,366
2206.10573	H&E-based Computational Biomarker Enables Universal EGFR Screening for Lung Adenocarcinoma	Lung cancer is the leading cause of cancer death worldwide, with lung adenocarcinoma being the most prevalent form of lung cancer. EGFR positive lung adenocarcinomas have been shown to have high response rates to TKI therapy, underlying the essential nature of molecular testing for lung cancers. Despite current guideli...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	303,957
2106.05611	Context-Free TextSpotter for Real-Time and Mobile End-to-End Text Detection and Recognition	In the deployment of scene-text spotting systems on mobile platforms, lightweight models with low computation are preferable. In concept, end-to-end (E2E) text spotting is suitable for such purposes because it performs text detection and recognition in a single model. However, current state-of-the-art E2E methods rely ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	240,164
2104.10263	StateCensusLaws.org: A Web Application for Consuming and Annotating Legal Discourse Learning	In this work, we create a web application to highlight the output of NLP models trained to parse and label discourse segments in law text. Our system is built primarily with journalists and legal interpreters in mind, and we focus on state-level law that uses U.S. Census population numbers to allocate resources and org...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	231,512
1807.02401	Learning a Representation Map for Robot Navigation using Deep Variational Autoencoder	The aim of this work is to use Variational Autoencoder (VAE) to learn a representation of an indoor environment that can be used for robot navigation. We use images extracted from a video, in which a camera takes a tour around a house, for training the VAE model with a 4 dimensional latent space. After the model is tra...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	102,262
2304.09093	Improving Items and Contexts Understanding with Descriptive Graph for Conversational Recommendation	State-of-the-art methods on conversational recommender systems (CRS) leverage external knowledge to enhance both items' and contextual words' representations to achieve high quality recommendations and responses generation. However, the representations of the items and words are usually modeled in two separated semanti...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	358,935
2101.03253	Adaptive Learning in Two-Player Stackelberg Games with Application to Network Security	We study a two-player Stackelberg game with incomplete information such that the follower's strategy belongs to a known family of parameterized functions with an unknown parameter vector. We design an adaptive learning approach to simultaneously estimate the unknown parameter and minimize the leader's cost, based on ad...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	214,867
2101.09142	A Study of Continuous Vector Representationsfor Theorem Proving	Applying machine learning to mathematical terms and formulas requires a suitable representation of formulas that is adequate for AI methods. In this paper, we develop an encoding that allows for logical properties to be preserved and is additionally reversible. This means that the tree shape of a formula including all ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	216,513
2306.16660	Real-Time Fully Unsupervised Domain Adaptation for Lane Detection in Autonomous Driving	While deep neural networks are being utilized heavily for autonomous driving, they need to be adapted to new unseen environmental conditions for which they were not trained. We focus on a safety critical application of lane detection, and propose a lightweight, fully unsupervised, real-time adaptation approach that onl...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	376,439
2206.10720	Predicting Team Performance with Spatial Temporal Graph Convolutional Networks	This paper presents a new approach for predicting team performance from the behavioral traces of a set of agents. This spatiotemporal forecasting problem is very relevant to sports analytics challenges such as coaching and opponent modeling. We demonstrate that our proposed model, Spatial Temporal Graph Convolutional N...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	304,010
2208.13138	ClusTR: Exploring Efficient Self-attention via Clustering for Vision Transformers	Although Transformers have successfully transitioned from their language modelling origins to image-based applications, their quadratic computational complexity remains a challenge, particularly for dense prediction. In this paper we propose a content-based sparse attention method, as an alternative to dense self-atten...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	314,966
2007.11230	MetAL: Active Semi-Supervised Learning on Graphs via Meta Learning	The objective of active learning (AL) is to train classification models with less number of labeled instances by selecting only the most informative instances for labeling. The AL algorithms designed for other data types such as images and text do not perform well on graph-structured data. Although a few heuristics-bas...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	188,500
1511.03225	Label Efficient Learning by Exploiting Multi-class Output Codes	We present a new perspective on the popular multi-class algorithmic techniques of one-vs-all and error correcting output codes. Rather than studying the behavior of these techniques for supervised learning, we establish a connection between the success of these methods and the existence of label-efficient learning proc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	48,731
1703.06868	Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization	Gatys et al. recently introduced a neural algorithm that renders a content image in the style of another image, achieving so-called style transfer. However, their framework requires a slow iterative optimization process, which limits its practical application. Fast approximations with feed-forward neural networks have ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	70,291
0908.3670	Randomized Scheduling Algorithm for Queueing Networks	There has recently been considerable interest in design of low-complexity, myopic, distributed and stable scheduling policies for constrained queueing network models that arise in the context of emerging communication networks. Here, we consider two representative models. One, a model for the collection of wireless nod...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	4,340
2011.11906	Spatiotemporal Imaging with Diffeomorphic Optimal Transportation	We propose a variational model with diffeomorphic optimal transportation for joint image reconstruction and motion estimation. The proposed model is a production of assembling the Wasserstein distance with the Benamou--Brenier formula in optimal transportation and the flow of diffeomorphisms involved in large deformati...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	207,987
2402.11352	Unified Capacity Results for Free-Space Optical Communication Systems Over Gamma-Gamma Atmospheric Turbulence Channels	Transmit power control, as in the mobile wireless channels, can enable a robust and spectrally efficient communication through atmospheric turbulence in terrestrial free-space optical (FSO) channels. With optical bandwidths in excess of several GHz and eye safety regulations limiting the transmit optical power, the per...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	430,349
2312.16611	Learning from small data sets: Patch-based regularizers in inverse problems for image reconstruction	The solution of inverse problems is of fundamental interest in medical and astronomical imaging, geophysics as well as engineering and life sciences. Recent advances were made by using methods from machine learning, in particular deep neural networks. Most of these methods require a huge amount of (paired) data and com...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	418,452
1901.03601	Advanced Rich Transcription System for Estonian Speech	This paper describes the current TT\"U speech transcription system for Estonian speech. The system is designed to handle semi-spontaneous speech, such as broadcast conversations, lecture recordings and interviews recorded in diverse acoustic conditions. The system is based on the Kaldi toolkit. Multi-condition training...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	118,440
2306.15444	Limited-Memory Greedy Quasi-Newton Method with Non-asymptotic Superlinear Convergence Rate	Non-asymptotic convergence analysis of quasi-Newton methods has gained attention with a landmark result establishing an explicit local superlinear rate of O$((1/\sqrt{t})^t)$. The methods that obtain this rate, however, exhibit a well-known drawback: they require the storage of the previous Hessian approximation matrix...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	376,024
2302.10523	I2V: Towards Texture-Aware Self-Supervised Blind Denoising using Self-Residual Learning for Real-World Images	Although the advances of self-supervised blind denoising are significantly superior to conventional approaches without clean supervision in synthetic noise scenarios, it shows poor quality in real-world images due to spatially correlated noise corruption. Recently, pixel-shuffle downsampling (PD) has been proposed to e...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	346,842
2204.04998	Team \'UFAL at CMCL 2022 Shared Task: Figuring out the correct recipe for predicting Eye-Tracking features using Pretrained Language Models	Eye-Tracking data is a very useful source of information to study cognition and especially language comprehension in humans. In this paper, we describe our systems for the CMCL 2022 shared task on predicting eye-tracking information. We describe our experiments with pretrained models like BERT and XLM and the different...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	290,875
2501.14701	NLP-based assessment of prescription appropriateness from Italian referrals	Objective: This study proposes a Natural Language Processing pipeline to evaluate prescription appropriateness in Italian referrals, where reasons for prescriptions are recorded only as free text, complicating automated comparisons with guidelines. The pipeline aims to derive, for the first time, a comprehensive summar...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	527,222
2003.12786	Robust Output Regulation: Optimization-Based Synthesis and Event-Triggered Implementation	We investigate the problem of practical output regulation, i.e., to design a controller that brings the system output in the vicinity of a desired target value while keeping the other variables bounded. We consider uncertain systems that are possibly nonlinear and the uncertainty of their linear parts is modeled elemen...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	170,010
1903.02532	An Efficient Production Process for Extracting Salivary Glands from Mosquitoes	Malaria is the one of the leading causes of morbidity and mortality in many developing countries. The development of a highly effective and readily deployable vaccine represents a major goal for world health. There has been recent progress in developing a clinically effective vaccine manufactured using Plasmodium falci...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	123,516
2210.16314	Hierarchical Automatic Power Plane Generation with Genetic Optimization and Multilayer Perceptron	We present an automatic multilayer power plane generation method to accelerate the design of printed circuit boards (PCB). In PCB design, while automatic solvers have been developed to predict important indicators such as the IR-drop, power integrity, and signal integrity, the generation of the power plane itself still...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	327,296
2004.10884	Microscopy Image Restoration using Deep Learning on W2S	We leverage deep learning techniques to jointly denoise and super-resolve biomedical images acquired with fluorescence microscopy. We develop a deep learning algorithm based on the networks and method described in the recent W2S paper to solve a joint denoising and super-resolution problem. Specifically, we address the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	173,746
2410.18798	Distill Visual Chart Reasoning Ability from LLMs to MLLMs	Solving complex chart Q&A tasks requires advanced visual reasoning abilities in multimodal large language models (MLLMs). Recent studies highlight that these abilities consist of two main parts: recognizing key information from visual inputs and conducting reasoning over it. Thus, a promising approach to enhance MLLMs ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	502,033
1206.3362	An Improved WBF Algorithm for Higher-Speed Decoding of LDPC Codes	Due to the speed limitation of the conventional bit-chosen strategy in the existing weighted bit flipping algorithms, a high-speed LDPC decoder cannot be realized. To solve this problem, we propose a fast weighted bit flipping (FWBF) algorithm. Specifically, based on the stochastic error bitmap of the received vector, ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	16,560
1810.09043	Patient Subtyping with Disease Progression and Irregular Observation Trajectories	Patient subtyping based on temporal observations can lead to significantly nuanced subtyping that acknowledges the dynamic characteristics of diseases. Existing methods for subtyping trajectories treat the evolution of clinical observations as a homogeneous process or employ data available at regular intervals. In real...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	110,969
2502.08470	Numerical Schemes for Signature Kernels	Signature kernels have emerged as a powerful tool within kernel methods for sequential data. In the paper "The Signature Kernel is the solution of a Goursat PDE", the authors identify a kernel trick that demonstrates that, for continuously differentiable paths, the signature kernel satisfies a Goursat problem for a hyp...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	533,025
1912.02084	Mining Domain Knowledge: Improved Framework towards Automatically Standardizing Anatomical Structure Nomenclature in Radiotherapy	The automatic standardization of nomenclature for anatomical structures in radiotherapy (RT) clinical data is a critical prerequisite for data curation and data-driven research in the era of big data and artificial intelligence, but it is currently an unmet need. Existing methods either cannot handle cross-institutiona...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	156,252
2212.12984	MC-Nonlocal-PINNs: handling nonlocal operators in PINNs via Monte Carlo sampling	We propose, Monte Carlo Nonlocal physics-informed neural networks (MC-Nonlocal-PINNs), which is a generalization of MC-fPINNs in \cite{guo2022monte}, for solving general nonlocal models such as integral equations and nonlocal PDEs. Similar as in MC-fPINNs, our MC-Nonlocal-PINNs handle the nonlocal operators in a Monte ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	338,189
2203.01326	Precise Stock Price Prediction for Optimized Portfolio Design Using an LSTM Model	Accurate prediction of future prices of stocks is a difficult task to perform. Even more challenging is to design an optimized portfolio of stocks with the identification of proper weights of allocation to achieve the optimized values of return and risk. We present optimized portfolios based on the seven sectors of the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	283,342
2203.06768	Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse	As machine learning models are increasingly being employed to make consequential decisions in real-world settings, it becomes critical to ensure that individuals who are adversely impacted (e.g., loan denied) by the predictions of these models are provided with a means for recourse. While several approaches have been p...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	285,218
2412.05074	LoFi: Vision-Aided Label Generator for Wi-Fi Localization and Tracking	Data-driven Wi-Fi localization and tracking have shown great promise due to their lower reliance on specialized hardware compared to model-based methods. However, most existing data collection techniques provide only coarse-grained ground truth or a limited number of labeled points, significantly hindering the advancem...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	514,679
2110.00745	End-to-End Complex-Valued Multidilated Convolutional Neural Network for Joint Acoustic Echo Cancellation and Noise Suppression	Echo and noise suppression is an integral part of a full-duplex communication system. Many recent acoustic echo cancellation (AEC) systems rely on a separate adaptive filtering module for linear echo suppression and a neural module for residual echo suppression. However, not only do adaptive filtering modules require c...	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	258,516
2304.00740	Inspecting and Editing Knowledge Representations in Language Models	Neural language models (LMs) represent facts about the world described by text. Sometimes these facts derive from training data (in most LMs, a representation of the word "banana" encodes the fact that bananas are fruits). Sometimes facts derive from input text itself (a representation of the sentence "I poured out the...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	355,794
2003.01974	Flow Computation in Temporal Interaction Networks	Temporal interaction networks capture the history of activities between entities along a timeline. At each interaction, some quantity of data (money, information, kbytes, etc.) flows from one vertex of the network to another. Flow-based analysis can reveal important information. For instance, financial intelligent unit...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	166,826
2112.03245	GAM Changer: Editing Generalized Additive Models with Interactive Visualization	Recent strides in interpretable machine learning (ML) research reveal that models exploit undesirable patterns in the data to make predictions, which potentially causes harms in deployment. However, it is unclear how we can fix these models. We present our ongoing work, GAM Changer, an open-source interactive system to...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	270,132
2405.00213	Block-As-Domain Adaptation for Workload Prediction from fNIRS Data	Functional near-infrared spectroscopy (fNIRS) is a non-intrusive way to measure cortical hemodynamic activity. Predicting cognitive workload from fNIRS data has taken on a diffuse set of methods. To be applicable in real-world settings, models are needed, which can perform well across different sessions as well as diff...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	450,830
2405.17925	A real/fast-time simulator for impact assessment of spoofing & jamming attacks on GNSS receivers	In aviation, the impact of threats is becoming increasingly significant, particularly for global navigation satellite system (GNSS). Two relevant GNSS threats are represented by jamming and spoofing. In order to evaluate the technological solutions to counter GNSS attacks, such attacks should be assessed by means of a ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	458,191
1808.03405	End-to-end Active Object Tracking and Its Real-world Deployment via Reinforcement Learning	We study active object tracking, where a tracker takes visual observations (i.e., frame sequences) as input and produces the corresponding camera control signals as output (e.g., move forward, turn left, etc.). Conventional methods tackle tracking and camera control tasks separately, and the resulting system is difficu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	104,931
1608.05461	We Can "See" You via Wi-Fi - WiFi Action Recognition via Vision-based Methods	Recently, Wi-Fi has caught tremendous attention for its ubiquity, and, motivated by Wi-Fi's low cost and privacy preservation, researchers have been putting lots of investigation into its potential on action recognition and even person identification. In this paper, we offer an comprehensive overview on these two topic...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	59,977
1812.01429	Automatic salt deposits segmentation: A deep learning approach	One of the most important applications of seismic reflection is the hydrocarbon exploration which is closely related to salt deposits analysis. This problem is very important even nowadays due to it's non-linear nature. Taking into account the recent developments in deep learning networks TGS-NOPEC Geophysical Company ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	115,517
1904.12958	Predictive Situation Awareness for Ebola Virus Disease using a Collective Intelligence Multi-Model Integration Platform: Bayes Cloud	The humanity has been facing a plethora of challenges associated with infectious diseases, which kill more than 6 million people a year. Although continuous efforts have been applied to relieve the potential damages from such misfortunate events, it is unquestionable that there are many persisting challenges yet to ove...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	129,257
1611.02431	Distributed recovery of jointly sparse signals under communication constraints	The problem of the distributed recovery of jointly sparse signals has attracted much attention recently. Let us assume that the nodes of a network observe different sparse signals with common support; starting from linear, compressed measurements, and exploiting network communication, each node aims at reconstructing t...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	63,564
2310.02611	Analyzing and Improving Optimal-Transport-based Adversarial Networks	Optimal Transport (OT) problem aims to find a transport plan that bridges two distributions while minimizing a given cost function. OT theory has been widely utilized in generative modeling. In the beginning, OT distance has been used as a measure for assessing the distance between data and generated distributions. Rec...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	396,926
2401.13460	Multi-Agent Diagnostics for Robustness via Illuminated Diversity	In the rapidly advancing field of multi-agent systems, ensuring robustness in unfamiliar and adversarial settings is crucial. Notwithstanding their outstanding performance in familiar environments, these systems often falter in new situations due to overfitting during the training phase. This is especially pronounced i...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	423,735
1610.04056	Estimation of linear operators from scattered impulse responses	We provide a new estimator of integral operators with smooth kernels, obtained from a set of scattered and noisy impulse responses. The proposed approach relies on the formalism of smoothing in reproducing kernel Hilbert spaces and on the choice of an appropriate regularization term that takes the smoothness of the ope...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	62,335
2411.09929	Autonomous Robotic Pepper Harvesting: Imitation Learning in Unstructured Agricultural Environments	Automating tasks in outdoor agricultural fields poses significant challenges due to environmental variability, unstructured terrain, and diverse crop characteristics. We present a robotic system for autonomous pepper harvesting designed to operate in these unprotected, complex settings. Utilizing a custom handheld shea...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	508,422
2111.10188	HMS-OS: Improving the Human Mental Search Optimisation Algorithm by Grouping in both Search and Objective Space	The human mental search (HMS) algorithm is a relatively recent population-based metaheuristic algorithm, which has shown competitive performance in solving complex optimisation problems. It is based on three main operators: mental search, grouping, and movement. In the original HMS algorithm, a clustering algorithm is ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	267,235
2207.11478	Overloaded Pilot Assignment with Pilot Decontamination for Cell-Free Systems	The pilot contamination in cell-free massive multiple-input-multiple-output (CF-mMIMO) must be addressed for accommodating a large number of users. In previous works, we have investigated a decontamination method called subspace projection (SP). The SP separates interference from co-pilot users by using the orthogonali...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	309,654
2210.17409	Deep Model Reassembly	In this paper, we explore a novel knowledge-transfer task, termed as Deep Model Reassembly (DeRy), for general-purpose model reuse. Given a collection of heterogeneous models pre-trained from distinct sources and with diverse architectures, the goal of DeRy, as its name implies, is to first dissect each model into dist...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	327,677
1908.05077	Fog Computing Systems: State of the Art, Research Issues and Future Trends, with a Focus on Resilience	Many future innovative computing services will use Fog Computing Systems (FCS), integrated with Internet of Things (IoT) resources. These new services, built on the convergence of several distinct technologies, need to fulfil time-sensitive functions, provide variable levels of integration with their environment, and i...	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	true	141,636
2409.10931	Frontier Shepherding: A Bio-Mimetic Multi-robot Framework for Large-Scale Exploration	Efficient exploration of large-scale environments remains a critical challenge in robotics, with applications ranging from environmental monitoring to search and rescue operations. This article proposes a bio-mimetic multi-robot framework, \textit{Frontier Shepherding (FroShe)}, for large-scale exploration. The present...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	488,937

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