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
1207.3142	Color Constancy based on Image Similarity via Bilayer Sparse Coding	Computational color constancy is a very important topic in computer vision and has attracted many researchers' attention. Recently, lots of research has shown the effects of high level visual content information for illumination estimation. However, all of these existing methods are essentially combinational strategies...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	17,448
1706.08707	PSK Precoding in Multi-User MISO Systems	We consider the downlink scenario of multiuser multiple-input-single-output (MU-MISO) communication systems with constant envelope (CE) signals emitted from each antenna. This results in energy efficient power amplifiers (PAs). We propose a holistic CE precoding scheme based on the symbol-wise minimum squared error (SM...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	76,038
1711.04457	Word, Subword or Character? An Empirical Study of Granularity in Chinese-English NMT	Neural machine translation (NMT), a new approach to machine translation, has been proved to outperform conventional statistical machine translation (SMT) across a variety of language pairs. Translation is an open-vocabulary problem, but most existing NMT systems operate with a fixed vocabulary, which causes the incapab...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	84,397
1611.05722	GENESIM: genetic extraction of a single, interpretable model	Models obtained by decision tree induction techniques excel in being interpretable.However, they can be prone to overfitting, which results in a low predictive performance. Ensemble techniques are able to achieve a higher accuracy. However, this comes at a cost of losing interpretability of the resulting model. This ma...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	64,063
2212.01159	Clustering individuals based on multivariate EMA time-series data	In the field of psychopathology, Ecological Momentary Assessment (EMA) methodological advancements have offered new opportunities to collect time-intensive, repeated and intra-individual measurements. This way, a large amount of data has become available, providing the means for further exploring mental disorders. Cons...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	334,327
2306.07933	Understanding Telecom Language Through Large Language Models	The recent progress of artificial intelligence (AI) opens up new frontiers in the possibility of automating many tasks involved in Telecom networks design, implementation, and deployment. This has been further pushed forward with the evolution of generative artificial intelligence (AI), including the emergence of large...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	373,201
2402.13930	Enhancing Reinforcement Learning Agents with Local Guides	This paper addresses the problem of integrating local guide policies into a Reinforcement Learning agent. For this, we show how to adapt existing algorithms to this setting before introducing a novel algorithm based on a noisy policy-switching procedure. This approach builds on a proper Approximate Policy Evaluation (A...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	431,467
2312.01543	Torso-Based Control Interface for Standing Mobility-Assistive Devices	Wheelchairs and mobility devices have transformed our bodies into cybernic systems, enhancing our well-being by enabling individuals with reduced mobility to regain freedom. Notwithstanding, current interfaces of control primarily rely on hand operation, therefore constraining the user from performing functional activi...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	412,481
1804.05705	And Now for Something Completely Different: Visual Novelty in an Online Network of Designers	Novelty is a key ingredient of innovation but quantifying it is difficult. This is especially true for visual work like graphic design. Using designs shared on an online social network of professional digital designers, we measure visual novelty using statistical learning methods to compare an images features with thos...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	95,131
2408.00751	A Policy-Gradient Approach to Solving Imperfect-Information Games with Iterate Convergence	Policy gradient methods have become a staple of any single-agent reinforcement learning toolbox, due to their combination of desirable properties: iterate convergence, efficient use of stochastic trajectory feedback, and theoretically-sound avoidance of importance sampling corrections. In multi-agent imperfect-informat...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	477,957
2411.07567	Uncertainty-Aware Test-Time Adaptation for Inverse Consistent Diffeomorphic Lung Image Registration	Diffeomorphic deformable image registration ensures smooth invertible transformations across inspiratory and expiratory chest CT scans. Yet, in practice, deep learning-based diffeomorphic methods struggle to capture large deformations between inspiratory and expiratory volumes, and therefore lack inverse consistency. E...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	507,586
1606.07578	Regression Trees and Random forest based feature selection for malaria risk exposure prediction	This paper deals with prediction of anopheles number, the main vector of malaria risk, using environmental and climate variables. The variables selection is based on an automatic machine learning method using regression trees, and random forests combined with stratified two levels cross validation. The minimum threshol...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	57,754
2206.00994	A new fluid-based strategy for the connection of non-matching lattice materials	We present a new algorithm for the design of the connection region between different lattice materials. We solve a Stokes-type topology optimization problem on a narrow morphing region to smoothly connect two different unit cells. The proposed procedure turns out to be effective and provides a local re-design of the ma...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	300,321
2407.03426	Multi-Task Decision-Making for Multi-User 360 Video Processing over Wireless Networks	We study a multi-task decision-making problem for 360 video processing in a wireless multi-user virtual reality (VR) system that includes an edge computing unit (ECU) to deliver 360 videos to VR users and offer computing assistance for decoding/rendering of video frames. However, this comes at the expense of increased ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	470,149
2502.06924	XAMBA: Enabling Efficient State Space Models on Resource-Constrained Neural Processing Units	State-Space Models (SSMs) have emerged as efficient alternatives to transformers for sequential data tasks, offering linear or near-linear scalability with sequence length, making them ideal for long-sequence applications in NLP, vision, and edge AI, including real-time transcription, translation, and contextual search...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	532,355
2410.11741	POLO -- Point-based, multi-class animal detection	Automated wildlife surveys based on drone imagery and object detection technology are a powerful and increasingly popular tool in conservation biology. Most detectors require training images with annotated bounding boxes, which are tedious, expensive, and not always unambiguous to create. To reduce the annotation load ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	498,696
1906.00651	Probabilistic Noise2Void: Unsupervised Content-Aware Denoising	Today, Convolutional Neural Networks (CNNs) are the leading method for image denoising. They are traditionally trained on pairs of images, which are often hard to obtain for practical applications. This motivates self-supervised training methods such as Noise2Void~(N2V) that operate on single noisy images. Self-supervi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	133,472
2304.06715	Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance	Interpretability methods are valuable only if their explanations faithfully describe the explained model. In this work, we consider neural networks whose predictions are invariant under a specific symmetry group. This includes popular architectures, ranging from convolutional to graph neural networks. Any explanation t...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	358,075
2202.13305	Private Location Sharing for Decentralized Routing services	Data-driven methodologies offer many exciting upsides, but they also introduce new challenges, particularly in the realm of user privacy. Specifically, the way data is collected can pose privacy risks to end users. In many routing services, a single entity (e.g., the routing service provider) collects and manages user ...	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	282,554
2104.05345	Dual-Octave Convolution for Accelerated Parallel MR Image Reconstruction	Magnetic resonance (MR) image acquisition is an inherently prolonged process, whose acceleration by obtaining multiple undersampled images simultaneously through parallel imaging has always been the subject of research. In this paper, we propose the Dual-Octave Convolution (Dual-OctConv), which is capable of learning m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	229,692
1702.00372	Visual Saliency Prediction Using a Mixture of Deep Neural Networks	Visual saliency models have recently begun to incorporate deep learning to achieve predictive capacity much greater than previous unsupervised methods. However, most existing models predict saliency using local mechanisms limited to the receptive field of the network. We propose a model that incorporates global scene s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	67,650
1707.09100	MixedPeds: Pedestrian Detection in Unannotated Videos using Synthetically Generated Human-agents for Training	We present a new method for training pedestrian detectors on an unannotated set of images. We produce a mixed reality dataset that is composed of real-world background images and synthetically generated static human-agents. Our approach is general, robust, and makes no other assumptions about the unannotated dataset re...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	77,950
2105.02337	Non-asymptotic analysis and inference for an outlyingness induced winsorized mean	Robust estimation of a mean vector, a topic regarded as obsolete in the traditional robust statistics community, has recently surged in machine learning literature in the last decade. The latest focus is on the sub-Gaussian performance and computability of the estimators in a non-asymptotic setting. Numerous traditiona...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	233,785
2108.12016	DeepFlow: Abnormal Traffic Flow Detection Using Siamese Networks	Nowadays, many cities are equipped with surveillance systems and traffic control centers to monitor vehicular traffic for road safety and efficiency. The monitoring process is mostly done manually which is inefficient and expensive. In recent years, several data-driven solutions have been proposed in the literature to ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	252,367
2005.03853	Project and Forget: Solving Large-Scale Metric Constrained Problems	Given a set of dissimilarity measurements amongst data points, determining what metric representation is most "consistent" with the input measurements or the metric that best captures the relevant geometric features of the data is a key step in many machine learning algorithms. Existing methods are restricted to specif...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	176,281
1610.07930	Active User Authentication for Smartphones: A Challenge Data Set and Benchmark Results	In this paper, automated user verification techniques for smartphones are investigated. A unique non-commercial dataset, the University of Maryland Active Authentication Dataset 02 (UMDAA-02) for multi-modal user authentication research is introduced. This paper focuses on three sensors - front camera, touch sensor and...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	62,863
2301.03164	Cursive Caption Text Detection in Videos	Textual content appearing in videos represents an interesting index for semantic retrieval of videos (from archives), generation of alerts (live streams) as well as high level applications like opinion mining and content summarization. One of the key components of such systems is the detection of textual content in vid...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	339,719
2005.04869	Towards a Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control	Micro- and smart grids (MSG) play an important role both for integrating renewable energy sources in conventional electricity grids and for providing power supply in remote areas. Modern MSGs are largely driven by power electronic converters due to their high efficiency and flexibility. Nevertheless, controlling MSGs i...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	176,584
2012.12439	Analysis of co-authorship networks among Brazilian graduate programs in computer science	The growth and popularization of platforms on scientific production have been the subject of several studies, producing relevant analyses of coauthorship behavior among groups of researchers. Researchers and their scientific productions can be analyzed as coauthorship social networks, so researchers are linked through ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	212,931
2407.05717	A New Framework for Nonlinear Kalman Filters	The Kalman filter (KF) is a state estimation algorithm that optimally combines system knowledge and measurements to minimize the mean squared error of the estimated states. While KF was initially designed for linear systems, numerous extensions of it, such as extended Kalman filter (EKF), unscented Kalman filter (UKF),...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	471,104
2408.02462	An investigation into the causes of race bias in AI-based cine CMR segmentation	Artificial intelligence (AI) methods are being used increasingly for the automated segmentation of cine cardiac magnetic resonance (CMR) imaging. However, these methods have been shown to be subject to race bias, i.e. they exhibit different levels of performance for different races depending on the (im)balance of the d...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	478,649
2412.08484	ConvMesh: Reimagining Mesh Quality Through Convex Optimization	Mesh generation has become a critical topic in recent years, forming the foundation of all 3D objects used across various applications, such as virtual reality, gaming, and 3D printing. With advancements in computational resources and machine learning, neural networks have emerged as powerful tools for generating high-...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	516,105
1805.07816	Towards Understanding Limitations of Pixel Discretization Against Adversarial Attacks	Wide adoption of artificial neural networks in various domains has led to an increasing interest in defending adversarial attacks against them. Preprocessing defense methods such as pixel discretization are particularly attractive in practice due to their simplicity, low computational overhead, and applicability to var...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	true	false	false	97,947
2410.06169	Treat Visual Tokens as Text? But Your MLLM Only Needs Fewer Efforts to See	By treating visual tokens from visual encoders as text tokens, Multimodal Large Language Models (MLLMs) have achieved remarkable progress across diverse visual understanding tasks, leveraging the robust architectures of Large Language Models (LLMs). However, as token counts grow, the quadratic scaling of computation in...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	496,076
2208.09055	On the Accuracy of the One-step UKF and the Two-step UKF	The most accurate version of the unscented Kalman filter (UKF) involves the construction of two ensembles. To reduce computational cost, however, UKF is often implemented without the second ensemble. This simplification comes at a price, however, since, for linear systems, the one-step variation of the two-step UKF doe...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	313,574
2304.05800	Proximity Forest 2.0: A new effective and scalable similarity-based classifier for time series	Time series classification (TSC) is a challenging task due to the diversity of types of feature that may be relevant for different classification tasks, including trends, variance, frequency, magnitude, and various patterns. To address this challenge, several alternative classes of approach have been developed, includi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	357,745
1905.09481	Constrained Design of Deep Iris Networks	Despite the promise of recent deep neural networks in the iris recognition setting, there are vital properties of the classic IrisCode which are almost unable to be achieved with current deep iris networks: the compactness of model and the small number of computing operations (FLOPs). This paper re-models the iris netw...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	131,742
1306.4947	Machine Teaching for Bayesian Learners in the Exponential Family	What if there is a teacher who knows the learning goal and wants to design good training data for a machine learner? We propose an optimal teaching framework aimed at learners who employ Bayesian models. Our framework is expressed as an optimization problem over teaching examples that balance the future loss of the lea...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	25,355
1906.07527	Impoved RPN for Single Targets Detection based on the Anchor Mask Net	Common target detection is usually based on single frame images, which is vulnerable to affected by the similar targets in the image and not applicable to video images. In this paper , anchor mask is proposed to add the prior knowledge for target detection and an anchor mask net is designed to impove the RPN performanc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	135,617
2411.09924	A Polarization Image Dehazing Method Based on the Principle of Physical Diffusion	Computer vision is increasingly used in areas such as unmanned vehicles, surveillance systems and remote sensing. However, in foggy scenarios, image degradation leads to loss of target details, which seriously affects the accuracy and effectiveness of these vision tasks. Polarized light, due to the fact that its electr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	508,420
2206.08882	Edge-Aided Sensor Data Sharing in Vehicular Communication Networks	Sensor data sharing in vehicular networks can significantly improve the range and accuracy of environmental perception for connected automated vehicles. Different concepts and schemes for dissemination and fusion of sensor data have been developed. It is common to these schemes that measurement errors of the sensors im...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	303,335
2304.09546	Sensitivity estimation for differentially private query processing	Differential privacy has become a popular privacy-preserving method in data analysis, query processing, and machine learning, which adds noise to the query result to avoid leaking privacy. Sensitivity, or the maximum impact of deleting or inserting a tuple on query results, determines the amount of noise added. Computi...	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	359,090
1312.6875	Refinement of the random coding bound	An improved pre-factor for the random coding bound is proved. Specifically, for channels with critical rate not equal to capacity, if a regularity condition is satisfied (resp. not satisfied), then for any $\epsilon >0$ a pre-factor of $O(N^{-\frac{1}{2}\left( 1 - \epsilon + \bar{\rho}^\ast_R \right)})$ (resp. $O(N^{-\...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	29,413
2111.01676	Towards Text-based Phishing Detection	This paper reports on an experiment into text-based phishing detection using readily available resources and without the use of semantics. The developed algorithm is a modified version of previously published work that works with the same tools. The results obtained in recognizing phishing emails are considerably bette...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	264,627
1705.10194	Adaptive Classification for Prediction Under a Budget	We propose a novel adaptive approximation approach for test-time resource-constrained prediction. Given an input instance at test-time, a gating function identifies a prediction model for the input among a collection of models. Our objective is to minimize overall average cost without sacrificing accuracy. We learn gat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	74,349
2212.07477	Guiding continuous operator learning through Physics-based boundary constraints	Boundary conditions (BCs) are important groups of physics-enforced constraints that are necessary for solutions of Partial Differential Equations (PDEs) to satisfy at specific spatial locations. These constraints carry important physical meaning, and guarantee the existence and the uniqueness of the PDE solution. Curre...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	336,408
2410.03987	Mamba Capsule Routing Towards Part-Whole Relational Camouflaged Object Detection	The part-whole relational property endowed by Capsule Networks (CapsNets) has been known successful for camouflaged object detection due to its segmentation integrity. However, the previous Expectation Maximization (EM) capsule routing algorithm with heavy computation and large parameters obstructs this trend. The prim...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	495,077
2304.05801	Metrics for network comparison using egonet feature distribution	Identifying networks with similar characteristics in a given ensemble, or detecting pattern discontinuities in a temporal sequence of networks, are two examples of tasks that require an effective metric capable of quantifying network (dis)similarity. Here we propose a method based on a global portrait of graph properti...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	357,746
1911.00036	Deep learning assessment of breast terminal duct lobular unit involution: towards automated prediction of breast cancer risk	Terminal ductal lobular unit (TDLU) involution is the regression of milk-producing structures in the breast. Women with less TDLU involution are more likely to develop breast cancer. A major bottleneck in studying TDLU involution in large cohort studies is the need for labor-intensive manual assessment of TDLUs. We dev...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	151,709
2410.15509	Exploring Curriculum Learning for Vision-Language Tasks: A Study on Small-Scale Multimodal Training	For specialized domains, there is often not a wealth of data with which to train large machine learning models. In such limited data / compute settings, various methods exist aiming to $\textit{do more with less}$, such as finetuning from a pretrained model, modulating difficulty levels as data are presented to a model...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	500,579
2303.14420	Human Preference Score: Better Aligning Text-to-Image Models with Human Preference	Recent years have witnessed a rapid growth of deep generative models, with text-to-image models gaining significant attention from the public. However, existing models often generate images that do not align well with human preferences, such as awkward combinations of limbs and facial expressions. To address this issue...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	354,086
2408.01080	FCDFusion: a Fast, Low Color Deviation Method for Fusing Visible and Infrared Image Pairs	Visible and infrared image fusion (VIF) aims to combine information from visible and infrared images into a single fused image. Previous VIF methods usually employ a color space transformation to keep the hue and saturation from the original visible image. However, for fast VIF methods, this operation accounts for the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	478,095
2501.07498	Computing Safety Margins of Parameterized Nonlinear Systems for Vulnerability Assessment via Trajectory Sensitivities	Physical systems experience nonlinear disturbances which have the potential to disrupt desired behavior. For a particular disturbance, whether or not the system recovers from the disturbance to a desired stable equilibrium point depends on system parameter values, which are typically uncertain and time-varying. Therefo...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	524,416
2310.03878	Automatic and Human-AI Interactive Text Generation	In this tutorial, we focus on text-to-text generation, a class of natural language generation (NLG) tasks, that takes a piece of text as input and then generates a revision that is improved according to some specific criteria (e.g., readability or linguistic styles), while largely retaining the original meaning and the...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	397,450
2010.03806	Flipping the Perspective in Contact Tracing	We introduce a fundamentally different paradigm for contact tracing: for each positive case, do not only ask direct contacts to quarantine; instead, tell everyone how many relationships away the disease just struck (so, "2" is a close physical contact of a close physical contact). This new approach, which has already b...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	199,537
2105.07906	Distributionally Robust Chance-Constrained Flexibility Planning for Integrated Energy System	Inflexible combined heat and power (CHP) plants and uncertain wind power production result in excess power in distribution networks, which leads to inverse power flow challenging grid operations. Power-to-X facilities such as electrolysers and electric boilers can offer extra flexibility to the integrated energy system...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	235,593
2306.05810	Explaining Reinforcement Learning with Shapley Values	For reinforcement learning systems to be widely adopted, their users must understand and trust them. We present a theoretical analysis of explaining reinforcement learning using Shapley values, following a principled approach from game theory for identifying the contribution of individual players to the outcome of a co...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	372,347
2401.00908	DocLLM: A layout-aware generative language model for multimodal document understanding	Enterprise documents such as forms, invoices, receipts, reports, contracts, and other similar records, often carry rich semantics at the intersection of textual and spatial modalities. The visual cues offered by their complex layouts play a crucial role in comprehending these documents effectively. In this paper, we pr...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	419,153
1602.06916	Sparse Linear Regression via Generalized Orthogonal Least-Squares	Sparse linear regression, which entails finding a sparse solution to an underdetermined system of linear equations, can formally be expressed as an $l_0$-constrained least-squares problem. The Orthogonal Least-Squares (OLS) algorithm sequentially selects the features (i.e., columns of the coefficient matrix) to greedil...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	52,442
1608.06716	A Novel Approach for Shot Boundary Detection in Videos	This paper presents a novel approach for video shot boundary detection. The proposed approach is based on split and merge concept. A fisher linear discriminant criterion is used to guide the process of both splitting and merging. For the purpose of capturing the between class and within class scatter we employ 2D2 FLD ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	60,151
1712.04363	Simulated Autonomous Driving on Realistic Road Networks using Deep Reinforcement Learning	Using Deep Reinforcement Learning (DRL) can be a promising approach to handle various tasks in the field of (simulated) autonomous driving. However, recent publications mainly consider learning in unusual driving environments. This paper presents Driving School for Autonomous Agents (DSA^2), a software for validating D...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	86,595
2207.12485	3D Shape Sequence of Human Comparison and Classification using Current and Varifolds	In this paper we address the task of the comparison and the classification of 3D shape sequences of human. The non-linear dynamics of the human motion and the changing of the surface parametrization over the time make this task very challenging. To tackle this issue, we propose to embed the 3D shape sequences in an inf...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	310,013
1701.08492	On Zero Error Capacity of Nearest Neighbor Error Channels with Multilevel Alphabet	This paper studies the zero error capacity of the Nearest Neighbor Error (NNE) channels with a multilevel alphabet. In the NNE channels, a transmitted symbol is a $d$-tuple of elements in $\{0,1,2,\dots, n-1 \}$. It is assumed that only one element error to a nearest neighbor element in a transmitted symbol can occur. ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	67,479
2307.15990	Ultrasound Image Reconstruction with Denoising Diffusion Restoration Models	Ultrasound image reconstruction can be approximately cast as a linear inverse problem that has traditionally been solved with penalized optimization using the $l_1$ or $l_2$ norm, or wavelet-based terms. However, such regularization functions often struggle to balance the sparsity and the smoothness. A promising altern...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	382,439
2409.10463	Kolmogorov-Arnold Networks in Low-Data Regimes: A Comparative Study with Multilayer Perceptrons	Multilayer Perceptrons (MLPs) have long been a cornerstone in deep learning, known for their capacity to model complex relationships. Recently, Kolmogorov-Arnold Networks (KANs) have emerged as a compelling alternative, utilizing highly flexible learnable activation functions directly on network edges, a departure from...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	488,749
2301.09188	Discovering the Traces of Disinformation on Instagram in the Internet Archive	Disinformation, which is fabricated, misleading content spread with the intent to deceive others, is accumulating substantial engagements and reaching a vast audience on Instagram. However, the temporary nature of the platform and the security guidelines that remove malicious content make studying this disinformation a...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	341,427
2203.13641	StretchBEV: Stretching Future Instance Prediction Spatially and Temporally	In self-driving, predicting future in terms of location and motion of all the agents around the vehicle is a crucial requirement for planning. Recently, a new joint formulation of perception and prediction has emerged by fusing rich sensory information perceived from multiple cameras into a compact bird's-eye view repr...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	287,708
1511.04435	A Survey on Dynamic Analysis of the Costas Loop	This survey is devoted to the dynamic analysis of the Costas loop. In particular the acquisition process is analyzed in great detail. Acquision is most conventiently described by a number of frequency and time parameters such as lock-in range, lock-in time, pull-in range, pull-in time, and hold-in range. While for the ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	48,890
2305.07233	Dual Forgetting Operators in the Context of Weakest Sufficient and Strongest Necessary Conditions	Forgetting is an important concept in knowledge representation and automated reasoning with widespread applications across a number of disciplines. A standard forgetting operator, characterized in [Lin and Reiter'94] in terms of model-theoretic semantics and primarily focusing on the propositional case, opened up a new...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	363,818
2002.09044	A Road Map to Strong Intelligence	I wrote this paper because technology can really improve people's lives. With it, we can live longer in a healthy body, save time through increased efficiency and automation, and make better decisions. To get to the next level, we need to start looking at intelligence from a much broader perspective, and promote intern...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	164,942
2412.08536	SenCLIP: Enhancing zero-shot land-use mapping for Sentinel-2 with ground-level prompting	Pre-trained vision-language models (VLMs), such as CLIP, demonstrate impressive zero-shot classification capabilities with free-form prompts and even show some generalization in specialized domains. However, their performance on satellite imagery is limited due to the underrepresentation of such data in their training ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	516,131
2211.09622	AlphaSnake: Policy Iteration on a Nondeterministic NP-hard Markov Decision Process	Reinforcement learning has recently been used to approach well-known NP-hard combinatorial problems in graph theory. Among these problems, Hamiltonian cycle problems are exceptionally difficult to analyze, even when restricted to individual instances of structurally complex graphs. In this paper, we use Monte Carlo Tre...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	331,031
1802.02398	Super-resolution of spatiotemporal event-stream image captured by the asynchronous temporal contrast vision sensor	Super-resolution (SR) is a useful technology to generate a high-resolution (HR) visual output from the low-resolution (LR) visual inputs overcoming the physical limitations of the cameras. However, SR has not been applied to enhance the resolution of spatiotemporal event-stream images captured by the frame-free dynamic...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	89,767
2202.01781	Predicting the impact of urban change in pedestrian and road safety	Increased interaction between and among pedestrians and vehicles in the crowded urban environments of today gives rise to a negative side-effect: a growth in traffic accidents, with pedestrians being the most vulnerable elements. Recent work has shown that Convolutional Neural Networks are able to accurately predict ac...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	278,583
1206.6438	Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain Adaptation	We study the problem of unsupervised domain adaptation, which aims to adapt classifiers trained on a labeled source domain to an unlabeled target domain. Many existing approaches first learn domain-invariant features and then construct classifiers with them. We propose a novel approach that jointly learn the both. Spec...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	16,973
1810.04738	Probabilistic Clustering Using Maximal Matrix Norm Couplings	In this paper, we present a local information theoretic approach to explicitly learn probabilistic clustering of a discrete random variable. Our formulation yields a convex maximization problem for which it is NP-hard to find the global optimum. In order to algorithmically solve this optimization problem, we propose tw...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	110,097
2306.03024	PokemonChat: Auditing ChatGPT for Pok\'emon Universe Knowledge	The recently released ChatGPT model demonstrates unprecedented capabilities in zero-shot question-answering. In this work, we probe ChatGPT for its conversational understanding and introduce a conversational framework (protocol) that can be adopted in future studies. The Pok\'emon universe serves as an ideal testing gr...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	371,159
1911.07923	Cluster-wise Unsupervised Hashing for Cross-Modal Similarity Search	Large-scale cross-modal hashing similarity retrieval has attracted more and more attention in modern search applications such as search engines and autopilot, showing great superiority in computation and storage. However, current unsupervised cross-modal hashing methods still have some limitations: (1)many methods rela...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	154,007
2406.03398	Methods for Class-Imbalanced Learning with Support Vector Machines: A Review and an Empirical Evaluation	This paper presents a review on methods for class-imbalanced learning with the Support Vector Machine (SVM) and its variants. We first explain the structure of SVM and its variants and discuss their inefficiency in learning with class-imbalanced data sets. We introduce a hierarchical categorization of SVM-based models ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	461,220
2208.11056	Enhancement Encoding: A Novel Imbalanced Classification Approach via Encoding the Training Labels	Class imbalance, which is also called long-tailed distribution, is a common problem in classification tasks based on machine learning. If it happens, the minority data will be overwhelmed by the majority, which presents quite a challenge for data science. To address the class imbalance problem, researchers have propose...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	314,295
2005.12147	NENET: An Edge Learnable Network for Link Prediction in Scene Text	Text detection in scenes based on deep neural networks have shown promising results. Instead of using word bounding box regression, recent state-of-the-art methods have started focusing on character bounding box and pixel-level prediction. This necessitates the need to link adjacent characters, which we propose in this...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	178,656
1110.6591	On some quasigroup cryptographical primitives	We propose modifications of known quasigroup based stream ciphers. Systems of orthogonal n-ary groupoids are used.	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	12,819
1903.12266	Generative Adversarial Networks: recent developments	In traditional generative modeling, good data representation is very often a base for a good machine learning model. It can be linked to good representations encoding more explanatory factors that are hidden in the original data. With the invention of Generative Adversarial Networks (GANs), a subclass of generative mod...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	125,676
1912.02811	Clone Swarms: Learning to Predict and Control Multi-Robot Systems by Imitation	In this paper, we propose SwarmNet -- a neural network architecture that can learn to predict and imitate the behavior of an observed swarm of agents in a centralized manner. Tested on artificially generated swarm motion data, the network achieves high levels of prediction accuracy and imitation authenticity. We compar...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	false	false	156,444
cond-mat/0601573	Amorphous packings of hard spheres in large space dimension	In a recent paper (cond-mat/0506445) we derived an expression for the replicated free energy of a liquid of hard spheres based on the HNC free energy functional. An approximate equation of state for the glass and an estimate of the random close packing density were obtained in d=3. Here we show that the HNC approximati...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	536,972
2109.07048	ARCH: Efficient Adversarial Regularized Training with Caching	Adversarial regularization can improve model generalization in many natural language processing tasks. However, conventional approaches are computationally expensive since they need to generate a perturbation for each sample in each epoch. We propose a new adversarial regularization method ARCH (adversarial regularizat...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	255,363
2211.12004	Contextual Bandits in a Survey Experiment on Charitable Giving: Within-Experiment Outcomes versus Policy Learning	We design and implement an adaptive experiment (a ``contextual bandit'') to learn a targeted treatment assignment policy, where the goal is to use a participant's survey responses to determine which charity to expose them to in a donation solicitation. The design balances two competing objectives: optimizing the outcom...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	331,956
2305.17957	Improving Confidence in Evolutionary Mine Scheduling via Uncertainty Discounting	Mine planning is a complex task that involves many uncertainties. During early stage feasibility, available mineral resources can only be estimated based on limited sampling of ore grades from sparse drilling, leading to large uncertainty in under-sampled parts of the deposit. Planning the extraction schedule of ore ov...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	368,812
2302.01791	DilateFormer: Multi-Scale Dilated Transformer for Visual Recognition	As a de facto solution, the vanilla Vision Transformers (ViTs) are encouraged to model long-range dependencies between arbitrary image patches while the global attended receptive field leads to quadratic computational cost. Another branch of Vision Transformers exploits local attention inspired by CNNs, which only mode...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	343,744
2206.07231	Resilience and Energy-Awareness in Constraint-Driven-Controlled Multi-Robot Systems	In the context of constraint-driven control of multi-robot systems, in this paper, we propose an optimization-based framework that is able to ensure resilience and energy-awareness of teams of robots. The approach is based on a novel, frame-theoretic, measure of resilience which allows us to analyze and enforce resilie...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	302,648
2011.02043	Deep-Learning-Aided Path Planning and Map Construction for Expediting Indoor Mapping	The problem of autonomous indoor mapping is addressed. The goal is to minimize the time to achieve a predefined percentage of exposure with some desired level of certainty. The use of a pre-trained generative deep neural network, acting as a map predictor, in both the path planning and the map construction is proposed ...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	204,795
2407.14054	PointRegGPT: Boosting 3D Point Cloud Registration using Generative Point-Cloud Pairs for Training	Data plays a crucial role in training learning-based methods for 3D point cloud registration. However, the real-world dataset is expensive to build, while rendering-based synthetic data suffers from domain gaps. In this work, we present PointRegGPT, boosting 3D point cloud registration using generative point-cloud pair...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	474,624
2403.12042	Exploring Pre-trained Text-to-Video Diffusion Models for Referring Video Object Segmentation	In this paper, we explore the visual representations produced from a pre-trained text-to-video (T2V) diffusion model for video understanding tasks. We hypothesize that the latent representation learned from a pretrained generative T2V model encapsulates rich semantics and coherent temporal correspondences, thereby natu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	439,000
2410.12036	Deep Optimal Sensor Placement for Black Box Stochastic Simulations	Selecting cost-effective optimal sensor configurations for subsequent inference of parameters in black-box stochastic systems faces significant computational barriers. We propose a novel and robust approach, modelling the joint distribution over input parameters and solution with a joint energy-based model, trained on ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	498,822
2402.19218	Memory-Augmented Generative Adversarial Transformers	Conversational AI systems that rely on Large Language Models, like Transformers, have difficulty interweaving external data (like facts) with the language they generate. Vanilla Transformer architectures are not designed for answering factual questions with high accuracy. This paper investigates a possible route for ad...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	433,719
2003.06729	NoiseRank: Unsupervised Label Noise Reduction with Dependence Models	Label noise is increasingly prevalent in datasets acquired from noisy channels. Existing approaches that detect and remove label noise generally rely on some form of supervision, which is not scalable and error-prone. In this paper, we propose NoiseRank, for unsupervised label noise reduction using Markov Random Fields...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	168,206
2410.03578	A Practical Concatenated Coding Scheme for Noisy Shuffling Channels with Coset-based Indexing	Noisy shuffling channels capture the main characteristics of DNA storage systems where distinct segments of data are received out of order, after being corrupted by substitution errors. For realistic schemes with short-length segments, practical indexing and channel coding strategies are required to restore the order a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	494,860
2006.11462	Transporting Robotic Swarms via Mean-Field Feedback Control	With the rapid development of AI and robotics, transporting a large swarm of networked robots has foreseeable applications in the near future. Existing research in swarm robotics has mainly followed a bottom-up philosophy with predefined local coordination and control rules. However, it is arduous to verify the global ...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	183,244
2303.09453	Knowledge Discovery from Atomic Structures using Feature Importances	Molecular-level understanding of the interactions between the constituents of an atomic structure is essential for designing novel materials in various applications. This need goes beyond the basic knowledge of the number and types of atoms, their chemical composition, and the character of the chemical interactions. Th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	352,049
2102.04040	LightSpeech: Lightweight and Fast Text to Speech with Neural Architecture Search	Text to speech (TTS) has been broadly used to synthesize natural and intelligible speech in different scenarios. Deploying TTS in various end devices such as mobile phones or embedded devices requires extremely small memory usage and inference latency. While non-autoregressive TTS models such as FastSpeech have achieve...	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	218,973

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