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
1812.09504	On asymptotic characterization of destabilizing switching signals for switched linear systems	This paper deals with classes of (de)stabilizing switching signals for switched systems. Most of the available conditions for stability of switched systems are sufficient in nature, and consequently, their violation does not conclude instability of a switched system. The study of instability is, however, important for ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	117,166
2302.06246	Incremental Consistent Updating of Incomplete Databases	Efficient consistency maintenance of incomplete and dynamic real-life databases is a quality label for further data analysis. In prior work, we tackled the generic problem of database updating in the presence of tuple generating constraints from a theoretical viewpoint. The current paper considers the usability of our ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	345,340
2403.09439	3D-SceneDreamer: Text-Driven 3D-Consistent Scene Generation	Text-driven 3D scene generation techniques have made rapid progress in recent years. Their success is mainly attributed to using existing generative models to iteratively perform image warping and inpainting to generate 3D scenes. However, these methods heavily rely on the outputs of existing models, leading to error a...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	437,767
2412.06871	Predicting Subway Passenger Flows under Incident Situation with Causality	In the context of rail transit operations, real-time passenger flow prediction is essential; however, most models primarily focus on normal conditions, with limited research addressing incident situations. There are several intrinsic challenges associated with prediction during incidents, such as a lack of interpretabi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	515,433
2306.09486	FedMultimodal: A Benchmark For Multimodal Federated Learning	Over the past few years, Federated Learning (FL) has become an emerging machine learning technique to tackle data privacy challenges through collaborative training. In the Federated Learning algorithm, the clients submit a locally trained model, and the server aggregates these parameters until convergence. Despite sign...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	373,851
2301.10008	Few-shot Font Generation by Learning Style Difference and Similarity	Few-shot font generation (FFG) aims to preserve the underlying global structure of the original character while generating target fonts by referring to a few samples. It has been applied to font library creation, a personalized signature, and other scenarios. Existing FFG methods explicitly disentangle content and styl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	341,669
2010.11153	Cascaded Models With Cyclic Feedback For Direct Speech Translation	Direct speech translation describes a scenario where only speech inputs and corresponding translations are available. Such data are notoriously limited. We present a technique that allows cascades of automatic speech recognition (ASR) and machine translation (MT) to exploit in-domain direct speech translation data in a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	202,141
1909.12146	DISCOMAN: Dataset of Indoor SCenes for Odometry, Mapping And Navigation	We present a novel dataset for training and benchmarking semantic SLAM methods. The dataset consists of 200 long sequences, each one containing 3000-5000 data frames. We generate the sequences using realistic home layouts. For that we sample trajectories that simulate motions of a simple home robot, and then render the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	147,038
1705.06894	Practical Algorithms for Best-K Identification in Multi-Armed Bandits	In the Best-$K$ identification problem (Best-$K$-Arm), we are given $N$ stochastic bandit arms with unknown reward distributions. Our goal is to identify the $K$ arms with the largest means with high confidence, by drawing samples from the arms adaptively. This problem is motivated by various practical applications and...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	73,700
1805.05429	An efficient structural attack on NIST submission DAGS	We present an efficient key recovery attack on code based encryption schemes using some quasi-dyadic alternant codes with extension degree 2. This attack permits to break the proposal DAGS recently submitted to NIST.	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	97,422
2409.06518	Questioning Internal Knowledge Structure of Large Language Models Through the Lens of the Olympic Games	Large language models (LLMs) have become a dominant approach in natural language processing, yet their internal knowledge structures remain largely unexplored. In this paper, we analyze the internal knowledge structures of LLMs using historical medal tallies from the Olympic Games. We task the models with providing the...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	487,152
1208.4895	Broadcast Gossip Algorithms for Consensus on Strongly Connected Digraphs	We study a general framework for broadcast gossip algorithms which use companion variables to solve the average consensus problem. Each node maintains an initial state and a companion variable. Iterative updates are performed asynchronously whereby one random node broadcasts its current state and companion variable and...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	18,235
2208.10993	Application of federated learning techniques for arrhythmia classification using 12-lead ECG signals	Artificial Intelligence-based (AI) analysis of large, curated medical datasets is promising for providing early detection, faster diagnosis, and more effective treatment using low-power Electrocardiography (ECG) monitoring devices information. However, accessing sensitive medical data from diverse sources is highly res...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	314,275
2404.19028	Adaptive Regulated Sparsity Promoting Approach for Data-Driven Modeling and Control of Grid-Connected Solar Photovoltaic Generation	This paper aims to introduce a new statistical learning technique based on sparsity promoting for data-driven modeling and control of solar photovoltaic (PV) systems. Compared with conventional sparse regression techniques that might introduce computational complexities when the number of candidate functions increases,...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	450,476
2312.15796	GenCast: Diffusion-based ensemble forecasting for medium-range weather	Weather forecasts are fundamentally uncertain, so predicting the range of probable weather scenarios is crucial for important decisions, from warning the public about hazardous weather, to planning renewable energy use. Here, we introduce GenCast, a probabilistic weather model with greater skill and speed than the top ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	418,132
1605.09038	Quickest Sequence Phase Detection	A phase detection sequence is a length-$n$ cyclic sequence, such that the location of any length-$k$ contiguous subsequence can be determined from a noisy observation of that subsequence. In this paper, we derive bounds on the minimal possible $k$ in the limit of $n\to\infty$, and describe some sequence constructions. ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	56,511
2207.08898	Benchmarking Machine Learning Robustness in Covid-19 Genome Sequence Classification	The rapid spread of the COVID-19 pandemic has resulted in an unprecedented amount of sequence data of the SARS-CoV-2 genome -- millions of sequences and counting. This amount of data, while being orders of magnitude beyond the capacity of traditional approaches to understanding the diversity, dynamics, and evolution of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	308,722
2106.11266	PHYSFRAME: Type Checking Physical Frames of Reference for Robotic Systems	A robotic system continuously measures its own motions and the external world during operation. Such measurements are with respect to some frame of reference, i.e., a coordinate system. A nontrivial robotic system has a large number of different frames and data have to be translated back-and-forth from a frame to anoth...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	242,336
2309.11981	Rethinking the Evaluating Framework for Natural Language Understanding in AI Systems: Language Acquisition as a Core for Future Metrics	In the burgeoning field of artificial intelligence (AI), the unprecedented progress of large language models (LLMs) in natural language processing (NLP) offers an opportunity to revisit the entire approach of traditional metrics of machine intelligence, both in form and content. As the realm of machine cognitive evalua...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	393,614
2201.00288	Community Search: A Meta-Learning Approach	Community Search (CS) is one of the fundamental graph analysis tasks, which is a building block of various real applications. Given any query nodes, CS aims to find cohesive subgraphs that query nodes belong to. Recently, a large number of CS algorithms are designed. These algorithms adopt predefined subgraph patterns ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	273,920
1910.04462	Flow-based Alignment Approaches for Probability Measures in Different Spaces	Gromov-Wasserstein (GW) is a powerful tool to compare probability measures whose supports are in different metric spaces. GW suffers however from a computational drawback since it requires to solve a complex non-convex quadratic program. We consider in this work a specific family of cost metrics, namely \textit{tree me...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	148,775
1709.00939	DR-RNN: A deep residual recurrent neural network for model reduction	We introduce a deep residual recurrent neural network (DR-RNN) as an efficient model reduction technique for nonlinear dynamical systems. The developed DR-RNN is inspired by the iterative steps of line search methods in finding the residual minimiser of numerically discretized differential equations. We formulate this ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	79,997
1904.05760	Scalarizing Functions in Bayesian Multiobjective Optimization	Scalarizing functions have been widely used to convert a multiobjective optimization problem into a single objective optimization problem. However, their use in solving (computationally) expensive multi- and many-objective optimization problems in Bayesian multiobjective optimization is scarce. Scalarizing functions ca...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	127,404
2106.08600	Federated Semi-supervised Medical Image Classification via Inter-client Relation Matching	Federated learning (FL) has emerged with increasing popularity to collaborate distributed medical institutions for training deep networks. However, despite existing FL algorithms only allow the supervised training setting, most hospitals in realistic usually cannot afford the intricate data labeling due to absence of b...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	241,352
1903.00258	Crowding in humans is unlike that in convolutional neural networks	Object recognition is a primary function of the human visual system. It has recently been claimed that the highly successful ability to recognise objects in a set of emergent computer vision systems---Deep Convolutional Neural Networks (DCNNs)---can form a useful guide to recognition in humans. To test this assertion, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	122,984
1811.00928	Foundations of Comparison-Based Hierarchical Clustering	We address the classical problem of hierarchical clustering, but in a framework where one does not have access to a representation of the objects or their pairwise similarities. Instead, we assume that only a set of comparisons between objects is available, that is, statements of the form "objects $i$ and $j$ are more ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	112,226
2401.14829	UMBRELLA: A One-stop Shop Bridging the Gap from Lab to Real-World IoT Experimentation	UMBRELLA is an open, large-scale IoT ecosystem deployed across South Gloucestershire, UK. It is intended to accelerate innovation across multiple technology domains. UMBRELLA is built to bridge the gap between existing specialised testbeds and address holistically real-world technological challenges in a System-of-Syst...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	424,232
2408.09972	Edge-Cloud Collaborative Motion Planning for Autonomous Driving with Large Language Models	Integrating large language models (LLMs) into autonomous driving enhances personalization and adaptability in open-world scenarios. However, traditional edge computing models still face significant challenges in processing complex driving data, particularly regarding real-time performance and system efficiency. To addr...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	481,670
2211.01234	Uncertainty-Aware DNN for Multi-Modal Camera Localization	Camera localization, i.e., camera pose regression, represents an important task in computer vision since it has many practical applications such as in the context of intelligent vehicles and their localization. Having reliable estimates of the regression uncertainties is also important, as it would allow us to catch da...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	328,150
1408.3154	User Profile Relationships using String Similarity Metrics in Social Networks	This article reviews the problem of degree of closeness and interaction level in a social network by ranking users based on similarity score. This similarity is measured on the basis of social, geographic, educational, professional, shared interests, pages liked, mutual interested groups or communities and mutual frien...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	35,352
1804.02967	HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentation	Recently, dense connections have attracted substantial attention in computer vision because they facilitate gradient flow and implicit deep supervision during training. Particularly, DenseNet, which connects each layer to every other layer in a feed-forward fashion, has shown impressive performances in natural image cl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	94,532
2201.10324	Addressing the Intra-class Mode Collapse Problem using Adaptive Input Image Normalization in GAN-based X-ray Images	Biomedical image datasets can be imbalanced due to the rarity of targeted diseases. Generative Adversarial Networks play a key role in addressing this imbalance by enabling the generation of synthetic images to augment datasets. It is important to generate synthetic images that incorporate a diverse range of features t...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	276,952
1910.08978	Attention Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images	Incorporating human domain knowledge for breast tumor diagnosis is challenging, since shape, boundary, curvature, intensity, or other common medical priors vary significantly across patients and cannot be employed. This work proposes a new approach for integrating visual saliency into a deep learning model for breast t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	150,036
2405.03613	Dual Relation Mining Network for Zero-Shot Learning	Zero-shot learning (ZSL) aims to recognize novel classes through transferring shared semantic knowledge (e.g., attributes) from seen classes to unseen classes. Recently, attention-based methods have exhibited significant progress which align visual features and attributes via a spatial attention mechanism. However, the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	452,241
2404.13528	SmartMem: Layout Transformation Elimination and Adaptation for Efficient DNN Execution on Mobile	This work is motivated by recent developments in Deep Neural Networks, particularly the Transformer architectures underlying applications such as ChatGPT, and the need for performing inference on mobile devices. Focusing on emerging transformers (specifically the ones with computationally efficient Swin-like architectu...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	448,332
2110.11191	Generative Adversarial Graph Convolutional Networks for Human Action Synthesis	Synthesising the spatial and temporal dynamics of the human body skeleton remains a challenging task, not only in terms of the quality of the generated shapes, but also of their diversity, particularly to synthesise realistic body movements of a specific action (action conditioning). In this paper, we propose Kinetic-G...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	262,389
2109.06168	Generatively Augmented Neural Network Watchdog for Image Classification Networks	The identification of out-of-distribution data is vital to the deployment of classification networks. For example, a generic neural network that has been trained to differentiate between images of dogs and cats can only classify an input as either a dog or a cat. If a picture of a car or a kumquat were to be supplied t...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	255,074
2409.03354	Few-Shot Continual Learning for Activity Recognition in Classroom Surveillance Images	The application of activity recognition in the "AI + Education" field is gaining increasing attention. However, current work mainly focuses on the recognition of activities in manually captured videos and a limited number of activity types, with little attention given to recognizing activities in surveillance images fr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	486,016
2403.12381	Explainable AutoML (xAutoML) with adaptive modeling for yield enhancement in semiconductor smart manufacturing	Enhancing yield is recognized as a paramount driver to reducing production costs in semiconductor smart manufacturing. However, optimizing and ensuring high yield rates is a highly complex and technical challenge, especially while maintaining reliable yield diagnosis and prognosis, and this shall require understanding ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	439,144
2005.11335	Single-Agent Optimization Through Policy Iteration Using Monte-Carlo Tree Search	The combination of Monte-Carlo Tree Search (MCTS) and deep reinforcement learning is state-of-the-art in two-player perfect-information games. In this paper, we describe a search algorithm that uses a variant of MCTS which we enhanced by 1) a novel action value normalization mechanism for games with potentially unbound...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	178,442
2111.14426	Improving traffic sign recognition by active search	We describe an iterative active-learning algorithm to recognise rare traffic signs. A standard ResNet is trained on a training set containing only a single sample of the rare class. We demonstrate that by sorting the samples of a large, unlabeled set by the estimated probability of belonging to the rare class, we can e...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	268,596
2110.04953	Compact CNN Models for On-device Ocular-based User Recognition in Mobile Devices	A number of studies have demonstrated the efficacy of deep learning convolutional neural network (CNN) models for ocular-based user recognition in mobile devices. However, these high-performing networks have enormous space and computational complexity due to the millions of parameters and computations involved. These r...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	260,100
2311.12225	HandSight: DeCAF & Improved Fisher Vectors to Classify Clothing Color and Texture with a Finger-Mounted Camera	We demonstrate the use of DeCAF and Improved Fisher Vector image features to classify clothing texture. The issue of choosing clothes is a problem for the blind every day. This work attempts to solve the issue with a finger-mounted camera and state-of-the-art classification algorithms. To evaluate our solution, we coll...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	409,246
2204.00800	Introduction to the Artificial Intelligence that can be applied to the Network Automation Journey	The computer network world is changing and the NetDevOps approach has brought the dynamics of applications and systems into the field of communication infrastructure. Businesses are changing and businesses are faced with difficulties related to the diversity of hardware and software that make up those infrastructures. ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	289,391
2209.02329	Multimodal contrastive learning for remote sensing tasks	Self-supervised methods have shown tremendous success in the field of computer vision, including applications in remote sensing and medical imaging. Most popular contrastive-loss based methods like SimCLR, MoCo, MoCo-v2 use multiple views of the same image by applying contrived augmentations on the image to create posi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	316,170
2406.02044	QROA: A Black-Box Query-Response Optimization Attack on LLMs	Large Language Models (LLMs) have surged in popularity in recent months, yet they possess concerning capabilities for generating harmful content when manipulated. This study introduces the Query-Response Optimization Attack (QROA), an optimization-based strategy designed to exploit LLMs through a black-box, query-only ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	460,588
2209.08343	Data Efficient Visual Place Recognition Using Extremely JPEG-Compressed Images	Visual Place Recognition (VPR) is the ability of a robotic platform to correctly interpret visual stimuli from its on-board cameras in order to determine whether it is currently located in a previously visited place, despite different viewpoint, illumination and appearance changes. JPEG is a widely used image compressi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	318,089
2007.15386	ResNet After All? Neural ODEs and Their Numerical Solution	A key appeal of the recently proposed Neural Ordinary Differential Equation (ODE) framework is that it seems to provide a continuous-time extension of discrete residual neural networks. As we show herein, though, trained Neural ODE models actually depend on the specific numerical method used during training. If the tra...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	189,657
2303.17137	Online Camera-to-ground Calibration for Autonomous Driving	Online camera-to-ground calibration is to generate a non-rigid body transformation between the camera and the road surface in a real-time manner. Existing solutions utilize static calibration, suffering from environmental variations such as tire pressure changes, vehicle loading volume variations, and road surface dive...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	355,117
2305.11984	OL-Transformer: A Fast and Universal Surrogate Simulator for Optical Multilayer Thin Film Structures	Deep learning-based methods have recently been established as fast and accurate surrogate simulators for optical multilayer thin film structures. However, existing methods only work for limited types of structures with different material arrangements, preventing their applications towards diverse and universal structur...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	365,783
2410.12209	Global Censored Quantile Random Forest	In recent years, censored quantile regression has enjoyed an increasing popularity for survival analysis while many existing works rely on linearity assumptions. In this work, we propose a Global Censored Quantile Random Forest (GCQRF) for predicting a conditional quantile process on data subject to right censoring, a ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	498,906
2004.07767	Sliding Window Polar Codes	We propose a novel coupling technique for the design of polar codes of length N, making them decodable through a sliding window of size M < N. This feature allows to reduce the computational complexity of the decoder, an important possibility in wireless communication downlink scenarios. Our approach is based on the de...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	172,868
1905.07443	AutoDispNet: Improving Disparity Estimation With AutoML	Much research work in computer vision is being spent on optimizing existing network architectures to obtain a few more percentage points on benchmarks. Recent AutoML approaches promise to relieve us from this effort. However, they are mainly designed for comparatively small-scale classification tasks. In this work, we ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	131,230
2412.02801	Optimization of Transformer heart disease prediction model based on particle swarm optimization algorithm	Aiming at the latest particle swarm optimization algorithm, this paper proposes an improved Transformer model to improve the accuracy of heart disease prediction and provide a new algorithm idea. We first use three mainstream machine learning classification algorithms - decision tree, random forest and XGBoost, and the...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	513,682
1705.01877	Semi-supervised model-based clustering with controlled clusters leakage	In this paper, we focus on finding clusters in partially categorized data sets. We propose a semi-supervised version of Gaussian mixture model, called C3L, which retrieves natural subgroups of given categories. In contrast to other semi-supervised models, C3L is parametrized by user-defined leakage level, which control...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	72,897
2211.11936	One Eye is All You Need: Lightweight Ensembles for Gaze Estimation with Single Encoders	Gaze estimation has grown rapidly in accuracy in recent years. However, these models often fail to take advantage of different computer vision (CV) algorithms and techniques (such as small ResNet and Inception networks and ensemble models) that have been shown to improve results for other CV problems. Additionally, mos...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	331,921
2207.01791	A deep cascade of ensemble of dual domain networks with gradient-based T1 assistance and perceptual refinement for fast MRI reconstruction	Deep learning networks have shown promising results in fast magnetic resonance imaging (MRI) reconstruction. In our work, we develop deep networks to further improve the quantitative and the perceptual quality of reconstruction. To begin with, we propose reconsynergynet (RSN), a network that combines the complementary ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	306,294
2312.11001	A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables	Most existing causal discovery methods rely on the assumption of no latent confounders, limiting their applicability in solving real-life problems. In this paper, we introduce a novel, versatile framework for causal discovery that accommodates the presence of causally-related hidden variables almost everywhere in the c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	416,409
2411.14390	Persistent Homology for Structural Characterization in Disordered Systems	We propose a unified framework based on persistent homology (PH) to characterize both local and global structures in disordered systems. It can simultaneously generate local and global descriptors using the same algorithm and data structure, and has shown to be highly effective and interpretable in predicting particle ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	510,139
2410.16677	The Neuromorphic Analog Electronic Nose	Rapid detection of gas concentration is important in different domains like gas leakage monitoring, pollution control, and so on, for the prevention of health hazards. Out of different types of gas sensors, Metal oxide (MOx) sensors are extensively used in such applications because of their portability, low cost, and h...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	501,137
2002.03281	PointHop++: A Lightweight Learning Model on Point Sets for 3D Classification	The PointHop method was recently proposed by Zhang et al. for 3D point cloud classification with unsupervised feature extraction. It has an extremely low training complexity while achieving state-of-the-art classification performance. In this work, we improve the PointHop method furthermore in two aspects: 1) reducing ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	163,212
2409.04018	Towards Energy-Efficiency by Navigating the Trilemma of Energy, Latency, and Accuracy	Extended Reality (XR) enables immersive experiences through untethered headsets but suffers from stringent battery and resource constraints. Energy-efficient design is crucial to ensure both longevity and high performance in XR devices. However, latency and accuracy are often prioritized over energy, leading to a gap i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	486,264
2402.13503	Multiple-Error-Correcting Codes for Analog Computing on Resistive Crossbars	Error-correcting codes over the real field are studied which can locate outlying computational errors when performing approximate computing of real vector--matrix multiplication on resistive crossbars. Prior work has concentrated on locating a single outlying error and, in this work, several classes of codes are presen...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	431,277
2206.01312	Optimization of Energy-Constrained IRS-NOMA Using a Complex Circle Manifold Approach	This work investigates the performance of intelligent reflective surfaces (IRSs) assisted uplink non-orthogonal multiple access (NOMA) in energy-constrained networks. Specifically, we formulate and solve two optimization problems; the first aims at minimizing the sum of users' transmit power, while the second targets m...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	300,423
2307.08019	A Multi-model and Multi-scenario Assessment of the Impact of Climate Change on the Heating and Cooling Load Components of an Archetypical Residential Room in Major Indian Cities	Residential heating and cooling currently account for approximately 7% of electricity consumption of India. A warming climate will increase residential cooling requirements, while heating needs will decrease which is an alarming consequence for India, which has predominantly cooling requirements. Thus, to reduce the en...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	379,638
0801.1282	LDPC Codes Which Can Correct Three Errors Under Iterative Decoding	In this paper, we provide necessary and sufficient conditions for a column-weight-three LDPC code to correct three errors when decoded using Gallager A algorithm. We then provide a construction technique which results in a code satisfying the above conditions. We also provide numerical assessment of code performance vi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	1,144
2010.16097	Target Word Masking for Location Metonymy Resolution	Existing metonymy resolution approaches rely on features extracted from external resources like dictionaries and hand-crafted lexical resources. In this paper, we propose an end-to-end word-level classification approach based only on BERT, without dependencies on taggers, parsers, curated dictionaries of place names, o...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	203,968
2110.03477	InfoSeg: Unsupervised Semantic Image Segmentation with Mutual Information Maximization	We propose a novel method for unsupervised semantic image segmentation based on mutual information maximization between local and global high-level image features. The core idea of our work is to leverage recent progress in self-supervised image representation learning. Representation learning methods compute a single ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	259,516
1904.08587	Creative Procedural-Knowledge Extraction From Web Design Tutorials	Complex design tasks often require performing diverse actions in a specific order. To (semi-)autonomously accomplish these tasks, applications need to understand and learn a wide range of design procedures, i.e., Creative Procedural-Knowledge (CPK). Prior knowledge base construction and mining have not typically addres...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	128,120
2208.04229	Choose, not Hoard: Information-to-Model Matching for Artificial Intelligence in O-RAN	Open Radio Access Network (O-RAN) is an emerging paradigm, whereby virtualized network infrastructure elements from different vendors communicate via open, standardized interfaces. A key element therein is the RAN Intelligent Controller (RIC), an Artificial Intelligence (AI)-based controller. Traditionally, all data av...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	312,038
2403.16059	Manifold Regularization Classification Model Based On Improved Diffusion Map	Manifold regularization model is a semi-supervised learning model that leverages the geometric structure of a dataset, comprising a small number of labeled samples and a large number of unlabeled samples, to generate classifiers. However, the original manifold norm limits the performance of models to local regions. To ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	440,856
2011.03615	Single and Multi-Agent Deep Reinforcement Learning for AI-Enabled Wireless Networks: A Tutorial	Deep Reinforcement Learning (DRL) has recently witnessed significant advances that have led to multiple successes in solving sequential decision-making problems in various domains, particularly in wireless communications. The future sixth-generation (6G) networks are expected to provide scalable, low-latency, ultra-rel...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	205,289
1404.1674	Channel Assignment With Access Contention Resolution for Cognitive Radio Networks	In this paper, we consider the channel assignment problem for cognitive radio networks with hardware-constrained secondary users (SUs). In particular, we assume that SUs exploit spectrum holes on a set of channels where each SU can use at most one available channel for communication. We present the optimal brute-force ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	32,139
2001.05840	Multi-Layer Content Interaction Through Quaternion Product For Visual Question Answering	Multi-modality fusion technologies have greatly improved the performance of neural network-based Video Description/Caption, Visual Question Answering (VQA) and Audio Visual Scene-aware Dialog (AVSD) over the recent years. Most previous approaches only explore the last layers of multiple layer feature fusion while omitt...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	160,649
2010.07449	Intuitive sequence matching algorithm applied to a sip-and-puff control interface for robotic assistive devices	This paper presents the development and preliminary validation of a control interface based on a sequence matching algorithm. An important challenge in the field of assistive technology is for users to control high dimensionality devices (e.g., assistive robot with several degrees of freedom, or computer) with low dime...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	200,817
1406.3663	Analysis of networking characteristics of different personality types	The MBTI personality test and a personal facebook network were used in order to gain some insights on the relationship of social network centrality and path length measures and different personality types. Although the personality classification data were scarce, there were some intuitive quantitative results supportin...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	33,862
2011.04260	Robust Visual Tracking via Statistical Positive Sample Generation and Gradient Aware Learning	In recent years, Convolutional Neural Network (CNN) based trackers have achieved state-of-the-art performance on multiple benchmark datasets. Most of these trackers train a binary classifier to distinguish the target from its background. However, they suffer from two limitations. Firstly, these trackers cannot effectiv...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	205,528
2205.00793	Ultra-Reliable Low-Latency Millimeter-Wave Communications with Sliding Window Network Coding	Ultra-reliability and low-latency are pivotal requirements of the new 6th generation of communication systems (xURLLC). Over the past years, to increase throughput, adaptive active antennas were introduced in advanced wireless communications, specifically in the domain of millimeter-wave (mmWave). Consequently, new low...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	294,375
2005.09927	Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection	This paper presents a novel 3D object detection framework that processes LiDAR data directly on its native representation: range images. Benefiting from the compactness of range images, 2D convolutions can efficiently process dense LiDAR data of a scene. To overcome scale sensitivity in this perspective view, a novel r...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	178,040
2206.13723	Prescribed-Time Synchronization of Multiweighted and Directed Complex Networks	In this note, we study the prescribed-time (PT) synchronization of multiweighted and directed complex networks (MWDCNs) via pinning control. Unlike finite-time and fixed-time synchronization, the time for synchronization can be preset as needed, which is independent of initial values and parameters like coupling streng...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	305,061
1908.09893	Coarse Correlation in Extensive-Form Games	Coarse correlation models strategic interactions of rational agents complemented by a correlation device, that is a mediator that can recommend behavior but not enforce it. Despite being a classical concept in the theory of normal-form games for more than forty years, not much is known about the merits of coarse correl...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	true	142,958
2102.06514	Large-Scale Representation Learning on Graphs via Bootstrapping	Self-supervised learning provides a promising path towards eliminating the need for costly label information in representation learning on graphs. However, to achieve state-of-the-art performance, methods often need large numbers of negative examples and rely on complex augmentations. This can be prohibitively expensiv...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	219,771
2410.08491	A Systematic Review of Edge Case Detection in Automated Driving: Methods, Challenges and Future Directions	The rapid development of automated vehicles (AVs) promises to revolutionize transportation by enhancing safety and efficiency. However, ensuring their reliability in diverse real-world conditions remains a significant challenge, particularly due to rare and unexpected situations known as edge cases. Although numerous a...	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	false	false	497,141
2311.08393	MVSA-Net: Multi-View State-Action Recognition for Robust and Deployable Trajectory Generation	The learn-from-observation (LfO) paradigm is a human-inspired mode for a robot to learn to perform a task simply by watching it being performed. LfO can facilitate robot integration on factory floors by minimizing disruption and reducing tedious programming. A key component of the LfO pipeline is a transformation of th...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	407,710
2206.02911	Inverse Boundary Value and Optimal Control Problems on Graphs: A Neural and Numerical Synthesis	A general setup for deterministic system identification problems on graphs with Dirichlet and Neumann boundary conditions is introduced. When control nodes are available along the boundary, we apply a discretize-then-optimize method to estimate an optimal control. A key piece in the present architecture is our boundary...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	301,073
2107.00593	Disaggregated Interventions to Reduce Inequality	A significant body of research in the data sciences considers unfair discrimination against social categories such as race or gender that could occur or be amplified as a result of algorithmic decisions. Simultaneously, real-world disparities continue to exist, even before algorithmic decisions are made. In this work, ...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	244,206
2501.18650	Constructing Cell-type Taxonomy by Optimal Transport with Relaxed Marginal Constraints	The rapid emergence of single-cell data has facilitated the study of many different biological conditions at the cellular level. Cluster analysis has been widely applied to identify cell types, capturing the essential patterns of the original data in a much more concise form. One challenge in the cluster analysis of ce...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	528,801
2211.12075	Greedy based Value Representation for Optimal Coordination in Multi-agent Reinforcement Learning	Due to the representation limitation of the joint Q value function, multi-agent reinforcement learning methods with linear value decomposition (LVD) or monotonic value decomposition (MVD) suffer from relative overgeneralization. As a result, they can not ensure optimal consistency (i.e., the correspondence between indi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	331,983
1107.1066	Families of twisted tensor product codes	Using geometric properties of the variety $\cV_{r,t}$, the image under the Grassmannian map of a Desarguesian $(t-1)$-spread of $\PG(rt-1,q)$, we introduce error correcting codes related to the twisted tensor product construction, producing several families of constacyclic codes. We exactly determine the parameters of ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	11,167
2407.09057	PersonificationNet: Making customized subject act like a person	Recently customized generation has significant potential, which uses as few as 3-5 user-provided images to train a model to synthesize new images of a specified subject. Though subsequent applications enhance the flexibility and diversity of customized generation, fine-grained control over the given subject acting like...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	472,437
2301.06657	Free Lunch for Generating Effective Outlier Supervision	When deployed in practical applications, computer vision systems will encounter numerous unexpected images (\emph{{i.e.}}, out-of-distribution data). Due to the potentially raised safety risks, these aforementioned unseen data should be carefully identified and handled. Generally, existing approaches in dealing with ou...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	340,700
2106.08554	iBatch: Saving Ethereum Fees via Secure and Cost-Effective Batching of Smart-Contract Invocations	This paper presents iBatch, a middleware system running on top of an operational Ethereum network to enable secure batching of smart-contract invocations against an untrusted relay server off-chain. iBatch does so at a low overhead by validating the server's batched invocations in smart contracts without additional sta...	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	241,332
2410.22029	Are VLMs Really Blind	Vision Language Models excel in handling a wide range of complex tasks, including Optical Character Recognition (OCR), Visual Question Answering (VQA), and advanced geometric reasoning. However, these models fail to perform well on low-level basic visual tasks which are especially easy for humans. Our goal in this work...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	503,472
1711.02290	Intelligent Collision Management in Dynamic Environments for Human-Centered Robots	In this context, a major focus of this thesis is on unintentional collisions, where a straight goal is to eliminate injury from users and passerby's via realtime sensing and control systems. A less obvious focus is to combine collision response with tools from motion planning in order to produce intelligent safety beha...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	84,037
1908.07121	Customizing Student Networks From Heterogeneous Teachers via Adaptive Knowledge Amalgamation	A massive number of well-trained deep networks have been released by developers online. These networks may focus on different tasks and in many cases are optimized for different datasets. In this paper, we study how to exploit such heterogeneous pre-trained networks, known as teachers, so as to train a customized stude...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	142,214
1901.02153	Audio Captcha Recognition Using RastaPLP Features by SVM	Nowadays, CAPTCHAs are computer generated tests that human can pass but current computer systems can not. They have common usage in various web services in order to be able to detect a human from computer programs autonomously. In this way, owners can protect their web services from bots. In addition to visual CAPTCHAs...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	118,138
2105.10966	Automatic Product Ontology Extraction from Textual Reviews	Ontologies have proven beneficial in different settings that make use of textual reviews. However, manually constructing ontologies is a laborious and time-consuming process in need of automation. We propose a novel methodology for automatically extracting ontologies, in the form of meronomies, from product reviews, us...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	236,559
2103.01755	An Exploratory Study of Log Placement Recommendation in an Enterprise System	Logging is a development practice that plays an important role in the operations and monitoring of complex systems. Developers place log statements in the source code and use log data to understand how the system behaves in production. Unfortunately, anticipating where to log during development is challenging. Previous...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	222,735
2401.15820	Knowledge-Aware Neuron Interpretation for Scene Classification	Although neural models have achieved remarkable performance, they still encounter doubts due to the intransparency. To this end, model prediction explanation is attracting more and more attentions. However, current methods rarely incorporate external knowledge and still suffer from three limitations: (1) Neglecting con...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	424,598
2410.20722	Interpretable Image Classification with Adaptive Prototype-based Vision Transformers	We present ProtoViT, a method for interpretable image classification combining deep learning and case-based reasoning. This method classifies an image by comparing it to a set of learned prototypes, providing explanations of the form ``this looks like that.'' In our model, a prototype consists of \textit{parts}, which ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	502,932

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