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
2501.17965	Variational Combinatorial Sequential Monte Carlo for Bayesian Phylogenetics in Hyperbolic Space	Hyperbolic space naturally encodes hierarchical structures such as phylogenies (binary trees), where inward-bending geodesics reflect paths through least common ancestors, and the exponential growth of neighborhoods mirrors the super-exponential scaling of topologies. This scaling challenge limits the efficiency of Euc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	528,517
1403.3148	Heat kernel based community detection	The heat kernel is a particular type of graph diffusion that, like the much-used personalized PageRank diffusion, is useful in identifying a community nearby a starting seed node. We present the first deterministic, local algorithm to compute this diffusion and use that algorithm to study the communities that it produc...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	31,547
2110.13633	Optimal non-pharmaceutical intervention policy for Covid-19 epidemic via neuroevolution algorithm	National responses to the Covid-19 pandemic varied markedly across countries, from business-as-usual to complete shutdowns. Policies aimed at disrupting the viral transmission cycle and preventing the healthcare system from being overwhelmed, simultaneously exact an economic toll. We developed a intervention policy mod...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	263,260
2104.02827	Efficient state and parameter estimation for high-dimensional nonlinear system identification with application to MEG brain network modeling	System identification poses a significant bottleneck to characterizing and controlling complex systems. This challenge is greatest when both the system states and parameters are not directly accessible leading to a dual-estimation problem. Current approaches to such problems are limited in their ability to scale with m...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	228,863
1501.02921	ACO-OFDM-Specified Recoverable Upper Clipping With Efficient Detection for Optical Wireless Communications	The high peak-to-average-power ratio (PAPR) of orthogonal frequency-division multiplexing (OFDM) degrades the performance in optical wireless communication systems. This paper proposes a modified asymmetrically clipped optical OFDM (ACOOFDM) with low PAPR via introducing a recoverable upper-clipping (RoC) procedure. Al...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,228
2403.19783	AlloyBERT: Alloy Property Prediction with Large Language Models	The pursuit of novel alloys tailored to specific requirements poses significant challenges for researchers in the field. This underscores the importance of developing predictive techniques for essential physical properties of alloys based on their chemical composition and processing parameters. This study introduces Al...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	442,467
1704.08509	No More Discrimination: Cross City Adaptation of Road Scene Segmenters	Despite the recent success of deep-learning based semantic segmentation, deploying a pre-trained road scene segmenter to a city whose images are not presented in the training set would not achieve satisfactory performance due to dataset biases. Instead of collecting a large number of annotated images of each city of in...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	72,533
2407.03070	Federated Learning for Zero-Day Attack Detection in 5G and Beyond V2X Networks	Deploying Connected and Automated Vehicles (CAVs) on top of 5G and Beyond networks (5GB) makes them vulnerable to increasing vectors of security and privacy attacks. In this context, a wide range of advanced machine/deep learning based solutions have been designed to accurately detect security attacks. Specifically, su...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	470,010
2010.13015	Towards Interaction Detection Using Topological Analysis on Neural Networks	Detecting statistical interactions between input features is a crucial and challenging task. Recent advances demonstrate that it is possible to extract learned interactions from trained neural networks. It has also been observed that, in neural networks, any interacting features must follow a strongly weighted connecti...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	202,965
2003.09208	Diagnosis of Diabetic Retinopathy in Ethiopia: Before the Deep Learning based Automation	Introducing automated Diabetic Retinopathy (DR) diagnosis into Ethiopia is still a challenging task, despite recent reports that present trained Deep Learning (DL) based DR classifiers surpassing manual graders. This is mainly because of the expensive cost of conventional retinal imaging devices used in DL based classi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	168,987
1407.8022	The Gaussian Channel with Noisy Feedback: Near-Capacity Performance via Simple Interaction	Consider a pair of terminals connected by two independent additive white Gaussian noise channels, and limited by individual power constraints. The first terminal would like to reliably send information to the second terminal, within a given error probability. We construct an explicit interactive scheme consisting of on...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	34,996
1709.07487	Computing the Unique Information	Given a pair of predictor variables and a response variable, how much information do the predictors have about the response, and how is this information distributed between unique, redundant, and synergistic components? Recent work has proposed to quantify the unique component of the decomposition as the minimum value ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	81,283
2402.05399	CURE: Simulation-Augmented Auto-Tuning in Robotics	Robotic systems are typically composed of various subsystems, such as localization and navigation, each encompassing numerous configurable components (e.g., selecting different planning algorithms). Once an algorithm has been selected for a component, its associated configuration options must be set to the appropriate ...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	427,845
2107.13136	Insights from Generative Modeling for Neural Video Compression	While recent machine learning research has revealed connections between deep generative models such as VAEs and rate-distortion losses used in learned compression, most of this work has focused on images. In a similar spirit, we view recently proposed neural video coding algorithms through the lens of deep autoregressi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	248,107
2309.11688	LLM Guided Inductive Inference for Solving Compositional Problems	While large language models (LLMs) have demonstrated impressive performance in question-answering tasks, their performance is limited when the questions require knowledge that is not included in the model's training data and can only be acquired through direct observation or interaction with the real world. Existing me...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	393,500
2310.16167	iNVS: Repurposing Diffusion Inpainters for Novel View Synthesis	We present a method for generating consistent novel views from a single source image. Our approach focuses on maximizing the reuse of visible pixels from the source image. To achieve this, we use a monocular depth estimator that transfers visible pixels from the source view to the target view. Starting from a pre-train...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	402,607
2204.12818	Autonomous Vehicle Calibration via Linear Optimization	In navigation activities, kinematic parameters of a mobile vehicle play a significant role. Odometry is most commonly used for dead reckoning. However, the unrestricted accumulation of errors is a disadvantage using this method. As a result, it is necessary to calibrate odometry parameters to minimize the error accumul...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	293,617
1910.04953	Scene-level Pose Estimation for Multiple Instances of Densely Packed Objects	This paper introduces key machine learning operations that allow the realization of robust, joint 6D pose estimation of multiple instances of objects either densely packed or in unstructured piles from RGB-D data. The first objective is to learn semantic and instance-boundary detectors without manual labeling. An adver...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	148,920
2112.00534	Empirical evaluation of shallow and deep learning classifiers for Arabic sentiment analysis	This work presents a detailed comparison of the performance of deep learning models such as convolutional neural networks (CNN), long short-term memory (LSTM), gated recurrent units (GRU), their hybrids, and a selection of shallow learning classifiers for sentiment analysis of Arabic reviews. Additionally, the comparis...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	269,164
2407.08055	Estimation and Control of Motor Core Temperature with Online Learning of Thermal Model Parameters: Application to Musculoskeletal Humanoids	The estimation and management of motor temperature are important for the continuous movements of robots. In this study, we propose an online learning method of thermal model parameters of motors for an accurate estimation of motor core temperature. Also, we propose a management method of motor core temperature using th...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	471,989
2404.01103	Second-Order Newton-Based Extremum Seeking for Multivariable Static Maps	A second-order Newton-based extremum seeking (SONES) algorithm is presented to estimate directional inflection points for multivariable static maps. The design extends the first-order Newton-based extremum seeking algorithm that drives the system toward its peak point. This work provides perturbation matrices to estima...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	443,251
2111.06494	DPLL(MAPF): an Integration of Multi-Agent Path Finding and SAT Solving Technologies	In multi-agent path finding (MAPF), the task is to find non-conflicting paths for multiple agents from their initial positions to given individual goal positions. MAPF represents a classical artificial intelligence problem often addressed by heuristic-search. An important alternative to search-based techniques is compi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	266,090
2407.18961	MMAU: A Holistic Benchmark of Agent Capabilities Across Diverse Domains	Recent advances in large language models (LLMs) have increased the demand for comprehensive benchmarks to evaluate their capabilities as human-like agents. Existing benchmarks, while useful, often focus on specific application scenarios, emphasizing task completion but failing to dissect the underlying skills that driv...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	476,593
1209.6151	Face Alignment Using Active Shape Model And Support Vector Machine	The Active Shape Model (ASM) is one of the most popular local texture models for face alignment. It applies in many fields such as locating facial features in the image, face synthesis, etc. However, the experimental results show that the accuracy of the classical ASM for some applications is not high. This paper sugge...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	18,793
2007.06849	Additively Homomorphical Encryption based Deep Neural Network for Asymmetrically Collaborative Machine Learning	The financial sector presents many opportunities to apply various machine learning techniques. Centralized machine learning creates a constraint which limits further applications in finance sectors. Data privacy is a fundamental challenge for a variety of finance and insurance applications that account on learning a mo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	187,149
2403.07185	Uncertainty in Graph Neural Networks: A Survey	Graph Neural Networks (GNNs) have been extensively used in various real-world applications. However, the predictive uncertainty of GNNs stemming from diverse sources such as inherent randomness in data and model training errors can lead to unstable and erroneous predictions. Therefore, identifying, quantifying, and uti...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	436,765
0711.2116	A numerical approach for 3D manufacturing tolerances synthesis	Making a product conform to the functional requirements indicated by the customer suppose to be able to manage the manufacturing process chosen to realise the parts. A simulation step is generally performed to verify that the expected generated deviations fit with these requirements. It is then necessary to assess the ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	899
2207.03398	Diagnosing and Remedying Shot Sensitivity with Cosine Few-Shot Learners	Few-shot recognition involves training an image classifier to distinguish novel concepts at test time using few examples (shot). Existing approaches generally assume that the shot number at test time is known in advance. This is not realistic, and the performance of a popular and foundational method has been shown to s...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	306,829
2203.16117	SIT: A Bionic and Non-Linear Neuron for Spiking Neural Network	Spiking Neural Networks (SNNs) have piqued researchers' interest because of their capacity to process temporal information and low power consumption. However, current state-of-the-art methods limited their biological plausibility and performance because their neurons are generally built on the simple Leaky-Integrate-an...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	288,663
2404.03778	Flattening the Parent Bias: Hierarchical Semantic Segmentation in the Poincar\'e Ball	Hierarchy is a natural representation of semantic taxonomies, including the ones routinely used in image segmentation. Indeed, recent work on semantic segmentation reports improved accuracy from supervised training leveraging hierarchical label structures. Encouraged by these results, we revisit the fundamental assumpt...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	444,401
0810.4059	Network Coding-based Protection Strategies Against a Single Link Failure in Optical Networks	In this paper we develop network protection strategies against a single link failure in optical networks. The motivation behind this work is the fact that $%70$ of all available links in an optical network suffers from a single link failure. In the proposed protection strategies, denoted NPS-I and NPS-II, we deploy net...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	2,545
1711.00812	Channel masking for multivariate time series shapelets	Time series shapelets are discriminative sub-sequences and their similarity to time series can be used for time series classification. Initial shapelet extraction algorithms searched shapelets by complete enumeration of all possible data sub-sequences. Research on shapelets for univariate time series proposed a mechani...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	83,783
2102.12731	Improving Approximate Optimal Transport Distances using Quantization	Optimal transport (OT) is a popular tool in machine learning to compare probability measures geometrically, but it comes with substantial computational burden. Linear programming algorithms for computing OT distances scale cubically in the size of the input, making OT impractical in the large-sample regime. We introduc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	221,831
1606.04991	A Class of Parallel Doubly Stochastic Algorithms for Large-Scale Learning	We consider learning problems over training sets in which both, the number of training examples and the dimension of the feature vectors, are large. To solve these problems we propose the random parallel stochastic algorithm (RAPSA). We call the algorithm random parallel because it utilizes multiple parallel processors...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	57,337
1708.04725	Hypotheses generation using link prediction in a bipartite graph	The large volume of scientific publications is likely to have hidden knowledge that can be used for suggesting new research topics. We propose an automatic method that is helpful for generating research hypotheses in the field of physics using the massive number of physics journal publications. We convert the text data...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	79,006
1707.08401	Detecting and classifying lesions in mammograms with Deep Learning	In the last two decades Computer Aided Diagnostics (CAD) systems were developed to help radiologists analyze screening mammograms. The benefits of current CAD technologies appear to be contradictory and they should be improved to be ultimately considered useful. Since 2012 deep convolutional neural networks (CNN) have ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	77,828
2312.00081	Synthesize, Diagnose, and Optimize: Towards Fine-Grained Vision-Language Understanding	Vision language models (VLM) have demonstrated remarkable performance across various downstream tasks. However, understanding fine-grained visual-linguistic concepts, such as attributes and inter-object relationships, remains a significant challenge. While several benchmarks aim to evaluate VLMs in finer granularity, t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	411,898
2209.05889	Investigating Bias with a Synthetic Data Generator: Empirical Evidence and Philosophical Interpretation	Machine learning applications are becoming increasingly pervasive in our society. Since these decision-making systems rely on data-driven learning, risk is that they will systematically spread the bias embedded in data. In this paper, we propose to analyze biases by introducing a framework for generating synthetic data...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	317,235
2106.02287	Dutch Named Entity Recognition and De-identification Methods for the Human Resource Domain	The human resource (HR) domain contains various types of privacy-sensitive textual data, such as e-mail correspondence and performance appraisal. Doing research on these documents brings several challenges, one of them anonymisation. In this paper, we evaluate the current Dutch text de-identification methods for the HR...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	238,809
1910.09217	Decoupling Representation and Classifier for Long-Tailed Recognition	The long-tail distribution of the visual world poses great challenges for deep learning based classification models on how to handle the class imbalance problem. Existing solutions usually involve class-balancing strategies, e.g., by loss re-weighting, data re-sampling, or transfer learning from head- to tail-classes, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	150,113
1210.0930	Optimality of Received Energy in Decision Fusion over Rayleigh Fading Diversity MAC with Non-Identical Sensors	Received-energy test for non-coherent decision fusion over a Rayleigh fading multiple access channel (MAC) without diversity was recently shown to be optimum in the case of conditionally mutually independent and identically distributed (i.i.d.) sensor decisions under specific conditions [1], [2]. Here, we provide a two...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	18,914
2402.14396	Quantum Circuit Optimization with AlphaTensor	A key challenge in realizing fault-tolerant quantum computers is circuit optimization. Focusing on the most expensive gates in fault-tolerant quantum computation (namely, the T gates), we address the problem of T-count optimization, i.e., minimizing the number of T gates that are needed to implement a given circuit. To...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	431,666
2209.09498	NBD-GAP: Non-Blind Image Deblurring Without Clean Target Images	In recent years, deep neural network-based restoration methods have achieved state-of-the-art results in various image deblurring tasks. However, one major drawback of deep learning-based deblurring networks is that large amounts of blurry-clean image pairs are required for training to achieve good performance. Moreove...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	318,537
2110.04535	ZSpeedL -- Evaluating the Performance of Zero-Shot Learning Methods using Low-Power Devices	The recognition of unseen objects from a semantic representation or textual description, usually denoted as zero-shot learning, is more prone to be used in real-world scenarios when compared to traditional object recognition. Nevertheless, no work has evaluated the feasibility of deploying zero-shot learning approaches...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	259,935
1501.04920	Regroupement s\'emantique de d\'efinitions en espagnol	This article focuses on the description and evaluation of a new unsupervised learning method of clustering of definitions in Spanish according to their semantic. Textual Energy was used as a clustering measure, and we study an adaptation of the Precision and Recall to evaluate our method.	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	39,436
2310.19507	Analysing Multi-Agent Systems using 1-safe Petri Nets	In the modelling and analysis of large, real systems, the main problem in their efficient processing is the size of the global model. One of the popular approaches that address this issue is the decomposition of such global model into much smaller submodels and interaction between them. In this paper we discuss the tra...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	404,014
2412.18149	Dense-Face: Personalized Face Generation Model via Dense Annotation Prediction	The text-to-image (T2I) personalization diffusion model can generate images of the novel concept based on the user input text caption. However, existing T2I personalized methods either require test-time fine-tuning or fail to generate images that align well with the given text caption. In this work, we propose a new T2...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	520,284
1902.07891	Towards Real-time Eyeblink Detection in The Wild:Dataset,Theory and Practices	Effective and real-time eyeblink detection is of wide-range applications, such as deception detection, drive fatigue detection, face anti-spoofing, etc. Although numerous of efforts have already been paid, most of them focus on addressing the eyeblink detection problem under the constrained indoor conditions with the r...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	122,083
2004.14036	Insights on Training Neural Networks for QUBO Tasks	Current hardware limitations restrict the potential when solving quadratic unconstrained binary optimization (QUBO) problems via the quantum approximate optimization algorithm (QAOA) or quantum annealing (QA). Thus, we consider training neural networks in this context. We first discuss QUBO problems that originate from...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	174,760
2408.04628	LogogramNLP: Comparing Visual and Textual Representations of Ancient Logographic Writing Systems for NLP	Standard natural language processing (NLP) pipelines operate on symbolic representations of language, which typically consist of sequences of discrete tokens. However, creating an analogous representation for ancient logographic writing systems is an extremely labor intensive process that requires expert knowledge. At ...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	479,451
1603.01869	Physical Layer Security for Massive MIMO Systems Impaired by Phase Noise	In this paper, we investigate the impact of phase noise on the secrecy performance of downlink massive MIMO systems in the presence of a passive multiple-antenna eavesdropper. Thereby, for the base station (BS) and the legitimate users, the effect of multiplicative phase noise is taken into account, whereas the eavesdr...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	52,947
1104.4153	Learning invariant features through local space contraction	We present in this paper a novel approach for training deterministic auto-encoders. We show that by adding a well chosen penalty term to the classical reconstruction cost function, we can achieve results that equal or surpass those attained by other regularized auto-encoders as well as denoising auto-encoders on a rang...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	10,060
2206.07994	Joint Class-Affinity Loss Correction for Robust Medical Image Segmentation with Noisy Labels	Noisy labels collected with limited annotation cost prevent medical image segmentation algorithms from learning precise semantic correlations. Previous segmentation arts of learning with noisy labels merely perform a pixel-wise manner to preserve semantics, such as pixel-wise label correction, but neglect the pair-wise...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	302,961
2212.10007	CoCoMIC: Code Completion By Jointly Modeling In-file and Cross-file Context	While pre-trained language models (LM) for code have achieved great success in code completion, they generate code conditioned only on the contents within the file, i.e., in-file context, but ignore the rich semantics in other files within the same project, i.e., cross-file context, a critical source of information tha...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	337,298
2405.00527	ChatBI: Towards Natural Language to Complex Business Intelligence SQL	The Natural Language to SQL (NL2SQL) technology provides non-expert users who are unfamiliar with databases the opportunity to use SQL for data analysis.Converting Natural Language to Business Intelligence (NL2BI) is a popular practical scenario for NL2SQL in actual production systems. Compared to NL2SQL, NL2BI introdu...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	450,957
1806.02371	Adversarial Attack on Graph Structured Data	Deep learning on graph structures has shown exciting results in various applications. However, few attentions have been paid to the robustness of such models, in contrast to numerous research work for image or text adversarial attack and defense. In this paper, we focus on the adversarial attacks that fool the model by...	false	false	false	true	false	false	true	false	false	false	false	false	true	false	false	false	false	false	99,761
2004.09927	TTNet: Real-time temporal and spatial video analysis of table tennis	We present a neural network TTNet aimed at real-time processing of high-resolution table tennis videos, providing both temporal (events spotting) and spatial (ball detection and semantic segmentation) data. This approach gives core information for reasoning score updates by an auto-referee system. We also publish a m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	173,491
2209.10367	Electromagnetic Field Exposure Avoidance thanks to Non-Intended User Equipment and RIS	On the one hand, there is a growing demand for high throughput which can be satisfied thanks to the deployment of new networks using massive multiple-input multiple-output (MIMO) and beamforming. On the other hand, in some countries or cities, there is a demand for arbitrarily low electromagnetic field exposure (EMFE) ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	318,838
2306.05012	Sequence-to-Sequence Model with Transformer-based Attention Mechanism and Temporal Pooling for Non-Intrusive Load Monitoring	This paper presents a novel Sequence-to-Sequence (Seq2Seq) model based on a transformer-based attention mechanism and temporal pooling for Non-Intrusive Load Monitoring (NILM) of smart buildings. The paper aims to improve the accuracy of NILM by using a deep learning-based method. The proposed method uses a Seq2Seq mod...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	372,012
2206.06014	Exploring and Exploiting Hubness Priors for High-Quality GAN Latent Sampling	Despite the extensive studies on Generative Adversarial Networks (GANs), how to reliably sample high-quality images from their latent spaces remains an under-explored topic. In this paper, we propose a novel GAN latent sampling method by exploring and exploiting the hubness priors of GAN latent distributions. Our key i...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	302,226
2005.11450	Fine-Grain Few-Shot Vision via Domain Knowledge as Hyperspherical Priors	Prototypical networks have been shown to perform well at few-shot learning tasks in computer vision. Yet these networks struggle when classes are very similar to each other (fine-grain classification) and currently have no way of taking into account prior knowledge (through the use of tabular data). Using a spherical l...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	178,476
2103.16604	VSS: A Storage System for Video Analytics [Technical Report]	We present a new video storage system (VSS) designed to decouple high-level video operations from the low-level details required to store and efficiently retrieve video data. VSS is designed to be the storage subsystem of a video data management system (VDBMS) and is responsible for: (1) transparently and automatically...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	227,637
1106.5714	Non-parametric change-point detection using string matching algorithms	Given the output of a data source taking values in a finite alphabet, we wish to detect change-points, that is times when the statistical properties of the source change. Motivated by ideas of match lengths in information theory, we introduce a novel non-parametric estimator which we call CRECHE (CRossings Enumeration ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	11,050
2408.03349	Toward Smart Scheduling in Tapis	The Tapis framework provides APIs for automating job execution on remote resources, including HPC clusters and servers running in the cloud. Tapis can simplify the interaction with remote cyberinfrastructure (CI), but the current services require users to specify the exact configuration of a job to run, including the s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	478,982
2304.14298	Instance Segmentation in the Dark	Existing instance segmentation techniques are primarily tailored for high-visibility inputs, but their performance significantly deteriorates in extremely low-light environments. In this work, we take a deep look at instance segmentation in the dark and introduce several techniques that substantially boost the low-ligh...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	360,888
2012.00830	MRI Images Analysis Method for Early Stage Alzheimer's Disease Detection	Alzheimer's disease is a neurogenerative disease that alters memories, cognitive functions leading to death. Early diagnosis of the disease, by detection of the preliminary stage, called Mild Cognitive Impairment (MCI), remains a challenging issue. In this respect, we introduce, in this paper, a powerful classification...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	209,245
2209.04999	Experimental Study on The Effect of Multi-step Deep Reinforcement Learning in POMDPs	Deep Reinforcement Learning (DRL) has made tremendous advances in both simulated and real-world robot control tasks in recent years. This is particularly the case for tasks that can be carefully engineered with a full state representation, and which can then be formulated as a Markov Decision Process (MDP). However, ap...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	316,957
2202.06650	Out of Thin Air: Is Zero-Shot Cross-Lingual Keyword Detection Better Than Unsupervised?	Keyword extraction is the task of retrieving words that are essential to the content of a given document. Researchers proposed various approaches to tackle this problem. At the top-most level, approaches are divided into ones that require training - supervised and ones that do not - unsupervised. In this study, we are ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	280,297
2402.08360	Visual Question Answering Instruction: Unlocking Multimodal Large Language Model To Domain-Specific Visual Multitasks	Having revolutionized natural language processing (NLP) applications, large language models (LLMs) are expanding into the realm of multimodal inputs. Owing to their ability to interpret images, multimodal LLMs (MLLMs) have been primarily used for vision-language tasks. Currently, MLLMs have not yet been extended for do...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	429,072
2405.17657	Robust Perception and Navigation of Autonomous Surface Vehicles in Challenging Environments	Research on coastal regions traditionally involves methods like manual sampling, monitoring buoys, and remote sensing, but these methods face challenges in spatially and temporally diverse regions of interest. Autonomous surface vehicles (ASVs) with artificial intelligence (AI) are being explored, and recognized by the...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	458,043
1505.01753	Weighted Gaussian entropy and determinant inequalities	We produce a series of results extending information-theoretical inequalities (discussed by Dembo--Cover--Thomas in 1989-1991) to a weighted version of entropy. The resulting inequalities involve the Gaussian weighted entropy; they imply a number of new relations for determinants of positive-definite matrices.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	42,879
1907.04361	Estimating Pedestrian Moving State Based on Single 2D Body Pose	The Crossing or Not-Crossing (C/NC) problem is important to autonomous vehicles (AVs) for safe vehicle/pedestrian interactions. However, this problem setup often ignores pedestrians walking along the direction of the vehicles' movement (LONG). To enhance the AVs' awareness of pedestrians behavior, we make the first ste...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	138,086
2502.04847	HumanDiT: Pose-Guided Diffusion Transformer for Long-form Human Motion Video Generation	Human motion video generation has advanced significantly, while existing methods still struggle with accurately rendering detailed body parts like hands and faces, especially in long sequences and intricate motions. Current approaches also rely on fixed resolution and struggle to maintain visual consistency. To address...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	531,341
1906.08229	Mathematical modeling of a Cosserat method in finite-strain holonomic plasticity	This article deals with the mathematical derivation and the validation over benchmark examples of a numerical method for the solution of a finite-strain holonomic (rate-independent) Cosserat plasticity problem for materials, possibly with microstructure. Two improvements are made in contrast to earlier approaches: Firs...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	135,809
2208.01838	Re-Attention Transformer for Weakly Supervised Object Localization	Weakly supervised object localization is a challenging task which aims to localize objects with coarse annotations such as image categories. Existing deep network approaches are mainly based on class activation map, which focuses on highlighting discriminative local region while ignoring the full object. In addition, t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	311,288
2502.12716	Soft Arm-Motor Thrust Characterization for a Pneumatically Actuated Soft Morphing Quadrotor	In this work, an experimental characterization of the configuration space of a soft, pneumatically actuated morphing quadrotor is presented, with a focus on precise thrust characterization of its flexible arms, considering the effect of downwash. Unlike traditional quadrotors, the soft drone has pneumatically actuated ...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	535,021
2111.05139	Human-in-the-Loop Disinformation Detection: Stance, Sentiment, or Something Else?	Both politics and pandemics have recently provided ample motivation for the development of machine learning-enabled disinformation (a.k.a. fake news) detection algorithms. Existing literature has focused primarily on the fully-automated case, but the resulting techniques cannot reliably detect disinformation on the var...	false	false	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	265,706
2104.03904	Social Big Data: An Overview and Applications	The emergence of online social media services has made a qualitative leap and brought profound changes to various aspects of human, cultural, intellectual, and social life. These significant Big data tributaries have further transformed the businesses processes by establishing convergent and transparent dialogues betwe...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	229,218
0907.1814	Bayesian Query-Focused Summarization	We present BayeSum (for ``Bayesian summarization''), a model for sentence extraction in query-focused summarization. BayeSum leverages the common case in which multiple documents are relevant to a single query. Using these documents as reinforcement for query terms, BayeSum is not afflicted by the paucity of informatio...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	4,076
0810.2513	The Impact of Mobility on Gossip Algorithms	The influence of node mobility on the convergence time of averaging gossip algorithms in networks is studied. It is shown that a small number of fully mobile nodes can yield a significant decrease in convergence time. A method is developed for deriving lower bounds on the convergence time by merging nodes according to ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	2,501
2309.07350	Curriculum-based Sensing Reduction in Simulation to Real-World Transfer for In-hand Manipulation	Simulation to Real-World Transfer allows affordable and fast training of learning-based robots for manipulation tasks using Deep Reinforcement Learning methods. Currently, Sim2Real uses Asymmetric Actor-Critic approaches to reduce the rich idealized features in simulation to the accessible ones in the real world. Howev...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	391,741
1804.08669	Ocean Plume Tracking with Unmanned Surface Vessels: Algorithms and Experiments	Pollution plume monitoring using autonomous vehicles is important due to the adverse effect of pollution plumes on the environment and associated monetary losses. Using the advection-diffusion plume dispersion model, we present a control law design to track dynamic concentration level curves. We also present a gradient...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	95,812
1805.03333	A Sample Path Measure of Causal Influence	We present a sample path dependent measure of causal influence between two time series. The proposed measure is a random variable whose expected sum is the directed information. A realization of the proposed measure may be used to identify the specific patterns in the data that yield a greater flow of information from ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	97,029
2406.07690	Active Sidestick Control Integration for Enhanced Aircraft Flight Envelope Protection	The design of Envelope and Pilot-Induced Oscillation (PIO) Protection Features, and Failure Cases detection and prevention using Active Control Sidestick (ACS) is a challenging task. While helping the pilot to respect the envelope limitations also in failure scenarios and, therefore, increasing mission effectiveness, t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	463,162
2410.23586	Multi-Robot Pursuit in Parameterized Formation via Imitation Learning	This paper studies the problem of multi-robot pursuit of how to coordinate a group of defending robots to capture a faster attacker before it enters a protected area. Such operation for defending robots is challenging due to the unknown avoidance strategy and higher speed of the attacker, coupled with the limited commu...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	504,092
2209.06967	A novel illumination condition varied image dataset-Food Vision Dataset (FVD) for fair and reliable consumer acceptability predictions from food	Recent advances in artificial intelligence promote a wide range of computer vision applications in many different domains. Digital cameras, acting as human eyes, can perceive fundamental object properties, such as shapes and colors, and can be further used for conducting high-level tasks, such as image classification, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	317,567
1901.09473	An End-to-End Solution for Effectively Demoting Watermarked Images in Image Search	We propose an end-to-end solution, from watermark feature generation to metric design, for effectively demoting watermarked images surfed by a real world image search engine. We use a few fundamental techniques to obtain effective watermark features of images in the image search index, and utilize the signals in a comm...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	119,757
2008.04465	Safe and Effective Picking Paths in Clutter given Discrete Distributions of Object Poses	Picking an item in the presence of other objects can be challenging as it involves occlusions and partial views. Given object models, one approach is to perform object pose estimation and use the most likely candidate pose per object to pick the target without collisions. This approach, however, ignores the uncertainty...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	191,231
2406.06949	Triple-domain Feature Learning with Frequency-aware Memory Enhancement for Moving Infrared Small Target Detection	As a sub-field of object detection, moving infrared small target detection presents significant challenges due to tiny target sizes and low contrast against backgrounds. Currently-existing methods primarily rely on the features extracted only from spatio-temporal domain. Frequency domain has hardly been concerned yet, ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	462,831
1605.03344	Go-ICP: A Globally Optimal Solution to 3D ICP Point-Set Registration	The Iterative Closest Point (ICP) algorithm is one of the most widely used methods for point-set registration. However, being based on local iterative optimization, ICP is known to be susceptible to local minima. Its performance critically relies on the quality of the initialization and only local optimality is guarant...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	55,738
1707.06487	A Nonlinear Kernel Support Matrix Machine for Matrix Learning	In many problems of supervised tensor learning (STL), real world data such as face images or MRI scans are naturally represented as matrices, which are also called as second order tensors. Most existing classifiers based on tensor representation, such as support tensor machine (STM) need to solve iteratively which occu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	77,434
2502.04475	Augmented Conditioning Is Enough For Effective Training Image Generation	Image generation abilities of text-to-image diffusion models have significantly advanced, yielding highly photo-realistic images from descriptive text and increasing the viability of leveraging synthetic images to train computer vision models. To serve as effective training data, generated images must be highly realist...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	531,170
2309.11178	Relational Expressions for Data Transformation and Computation	Separate programming models for data transformation (declarative) and computation (procedural) impact programmer ergonomics, code reusability and database efficiency. To eliminate the necessity for two models or paradigms, we propose a small but high-leverage innovation: the introduction of complete relations into the ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	393,317
2412.06165	Conservative Contextual Bandits: Beyond Linear Representations	Conservative Contextual Bandits (CCBs) address safety in sequential decision making by requiring that an agent's policy, along with minimizing regret, also satisfies a safety constraint: the performance is not worse than a baseline policy (e.g., the policy that the company has in production) by more than $(1+\alpha)$ f...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	515,122
2202.07425	Algebraic function based Banach space valued ordinary and fractional neural network approximations	Here we research the univariate quantitative approximation, ordinary and fractional, of Banach space valued continuous functions on a compact interval or all the real line by quasi-interpolation Banach space valued neural network operators. These approximations are derived by establishing Jackson type inequalities invo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	280,544
0705.0760	Equivalence of LP Relaxation and Max-Product for Weighted Matching in General Graphs	Max-product belief propagation is a local, iterative algorithm to find the mode/MAP estimate of a probability distribution. While it has been successfully employed in a wide variety of applications, there are relatively few theoretical guarantees of convergence and correctness for general loopy graphs that may have man...	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	true	160
2201.04439	Real-Time Style Modelling of Human Locomotion via Feature-Wise Transformations and Local Motion Phases	Controlling the manner in which a character moves in a real-time animation system is a challenging task with useful applications. Existing style transfer systems require access to a reference content motion clip, however, in real-time systems the future motion content is unknown and liable to change with user input. In...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	true	275,103
1901.09203	ACNN: a Full Resolution DCNN for Medical Image Segmentation	Deep Convolutional Neural Networks (DCNNs) are used extensively in medical image segmentation and hence 3D navigation for robot-assisted Minimally Invasive Surgeries (MISs). However, current DCNNs usually use down sampling layers for increasing the receptive field and gaining abstract semantic information. These down s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	119,676
2111.04823	Cascaded Multilingual Audio-Visual Learning from Videos	In this paper, we explore self-supervised audio-visual models that learn from instructional videos. Prior work has shown that these models can relate spoken words and sounds to visual content after training on a large-scale dataset of videos, but they were only trained and evaluated on videos in English. To learn multi...	false	false	true	false	false	false	false	false	true	false	false	true	false	false	false	false	false	true	265,603
2012.12413	Towards Histopathological Stain Invariance by Unsupervised Domain Augmentation using Generative Adversarial Networks	The application of supervised deep learning methods in digital pathology is limited due to their sensitivity to domain shift. Digital Pathology is an area prone to high variability due to many sources, including the common practice of evaluating several consecutive tissue sections stained with different staining protoc...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	212,922

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