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
2104.12108	On the Achievable Sum-rate of the RIS-aided MIMO Broadcast Channel	Reconfigurable intelligent surfaces (RISs) represent a new technology that can shape the radio wave propagation and thus offers a great variety of possible performance and implementation gains. Motivated by this, we investigate the achievable sum-rate optimization in a broadcast channel (BC) that is equipped with an RI...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	232,118
2310.07723	Equitable and Fair Performance Evaluation of Whale Optimization Algorithm	It is essential that all algorithms are exhaustively, somewhat, and intelligently evaluated. Nonetheless, evaluating the effectiveness of optimization algorithms equitably and fairly is not an easy process for various reasons. Choosing and initializing essential parameters, such as the size issues of the search area fo...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	399,095
2209.05899	A Meta-level Analysis of Online Anomaly Detectors	Real-time detection of anomalies in streaming data is receiving increasing attention as it allows us to raise alerts, predict faults, and detect intrusions or threats across industries. Yet, little attention has been given to compare the effectiveness and efficiency of anomaly detectors for streaming data (i.e., of onl...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	317,236
1905.04624	Diversification Across Mining Pools: Optimal Mining Strategies under PoW	Mining is a central operation of all proof-of-work (PoW) based cryptocurrencies. The vast majority of miners today participate in "mining pools" instead of "solo mining" in order to lower risk and achieve a more steady income. However, this rise of participation in mining pools negatively affects the decentralization l...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	130,517
2008.10129	Predicting Helpfulness of Online Reviews	E-commerce dominates a large part of the world's economy with many websites dedicated to online selling products. The vast majority of e-commerce websites provide their customers with the ability to express their opinions about the products/services they purchase. These feedback in the form of reviews represent a rich ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	192,920
2402.12490	Towards Cross-Domain Continual Learning	Continual learning is a process that involves training learning agents to sequentially master a stream of tasks or classes without revisiting past data. The challenge lies in leveraging previously acquired knowledge to learn new tasks efficiently, while avoiding catastrophic forgetting. Existing methods primarily focus...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	430,863
1911.07394	Strategy Synthesis for Surveillance-Evasion Games with Learning-Enabled Visibility Optimization	This paper studies a two-player game with a quantitative surveillance requirement on an adversarial target moving in a discrete state space and a secondary objective to maximize short-term visibility of the environment. We impose the surveillance requirement as a temporal logic constraint.We then use a greedy approach ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	153,830
2410.08611	Conjugated Semantic Pool Improves OOD Detection with Pre-trained Vision-Language Models	A straightforward pipeline for zero-shot out-of-distribution (OOD) detection involves selecting potential OOD labels from an extensive semantic pool and then leveraging a pre-trained vision-language model to perform classification on both in-distribution (ID) and OOD labels. In this paper, we theorize that enhancing pe...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	497,193
2401.12901	Secure Spatial Signal Design for ISAC in a Cell-Free MIMO Network	In this paper, we study a cell-free multiple-input multiple-output network equipped with integrated sensing and communication (ISAC) access points (APs). The distributed APs are used to jointly serve the communication needs of user equipments (UEs) while sensing a target, assumed to be an eavesdropper (Eve). To increas...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	423,531
2403.06433	Fine-Grained Pillar Feature Encoding Via Spatio-Temporal Virtual Grid for 3D Object Detection	Developing high-performance, real-time architectures for LiDAR-based 3D object detectors is essential for the successful commercialization of autonomous vehicles. Pillar-based methods stand out as a practical choice for onboard deployment due to their computational efficiency. However, despite their efficiency, these m...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	436,451
1803.00446	Inferring Missing Categorical Information in Noisy and Sparse Web Markup	Embedded markup of Web pages has seen widespread adoption throughout the past years driven by standards such as RDFa and Microdata and initiatives such as schema.org, where recent studies show an adoption by 39% of all Web pages already in 2016. While this constitutes an important information source for tasks such as W...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	91,682
1604.06715	Parameterized Compilation Lower Bounds for Restricted CNF-formulas	We show unconditional parameterized lower bounds in the area of knowledge compilation, more specifically on the size of circuits in decomposable negation normal form (DNNF) that encode CNF-formulas restricted by several graph width measures. In particular, we show that - there are CNF formulas of size $n$ and modular...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	54,979
1909.02762	Effective Search of Logical Forms for Weakly Supervised Knowledge-Based Question Answering	Many algorithms for Knowledge-Based Question Answering (KBQA) depend on semantic parsing, which translates a question to its logical form. When only weak supervision is provided, it is usually necessary to search valid logical forms for model training. However, a complex question typically involves a huge search space,...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	144,278
1502.05156	Assessing the effectiveness of real-world network simplification	Many real-world networks are large, complex and thus hard to understand, analyze or visualize. The data about networks is not always complete, their structure may be hidden or they change quickly over time. Therefore, understanding how incomplete system differs from complete one is crucial. In this paper, we study the ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	40,344
2401.08407	Cross-Domain Few-Shot Segmentation via Iterative Support-Query Correspondence Mining	Cross-Domain Few-Shot Segmentation (CD-FSS) poses the challenge of segmenting novel categories from a distinct domain using only limited exemplars. In this paper, we undertake a comprehensive study of CD-FSS and uncover two crucial insights: (i) the necessity of a fine-tuning stage to effectively transfer the learned m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	421,876
2403.02451	Views Are My Own, but Also Yours: Benchmarking Theory of Mind Using Common Ground	Evaluating the theory of mind (ToM) capabilities of language models (LMs) has recently received a great deal of attention. However, many existing benchmarks rely on synthetic data, which risks misaligning the resulting experiments with human behavior. We introduce the first ToM dataset based on naturally occurring spok...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	434,807
2410.14758	Mitigating Embedding Collapse in Diffusion Models for Categorical Data	Latent diffusion models have enabled continuous-state diffusion models to handle a variety of datasets, including categorical data. However, most methods rely on fixed pretrained embeddings, limiting the benefits of joint training with the diffusion model. While jointly learning the embedding (via reconstruction loss) ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	500,197
2410.23641	Recovering Complete Actions for Cross-dataset Skeleton Action Recognition	Despite huge progress in skeleton-based action recognition, its generalizability to different domains remains a challenging issue. In this paper, to solve the skeleton action generalization problem, we present a recover-and-resample augmentation framework based on a novel complete action prior. We observe that human da...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	504,119
2106.12755	Control of a Mixed Autonomy Signalised Urban Intersection: An Action-Delayed Reinforcement Learning Approach	We consider a mixed autonomy scenario where the traffic intersection controller decides whether the traffic light will be green or red at each lane for multiple traffic-light blocks. The objective of the traffic intersection controller is to minimize the queue length at each lane and maximize the outflow of vehicles ov...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	242,832
1210.8436	Optimal size, freshness and time-frame for voice search vocabulary	In this paper, we investigate how to optimize the vocabulary for a voice search language model. The metric we optimize over is the out-of-vocabulary (OoV) rate since it is a strong indicator of user experience. In a departure from the usual way of measuring OoV rates, web search logs allow us to compute the per-session...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	19,499
2007.10595	Video Super-resolution with Temporal Group Attention	Video super-resolution, which aims at producing a high-resolution video from its corresponding low-resolution version, has recently drawn increasing attention. In this work, we propose a novel method that can effectively incorporate temporal information in a hierarchical way. The input sequence is divided into several ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	188,318
1204.3074	Time-Critical Influence Maximization in Social Networks with Time-Delayed Diffusion Process	Influence maximization is a problem of finding a small set of highly influential users, also known as seeds, in a social network such that the spread of influence under certain propagation models is maximized. In this paper, we consider time-critical influence maximization, in which one wants to maximize influence spre...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	15,460
1711.01815	Profile Matching Across Unstructured Online Social Networks: Threats and Countermeasures	In this work, we propose a profile matching (or deanonymization) attack for unstructured online social networks (OSNs) in which similarity in graphical structure cannot be used for profile matching. We consider different attributes that are publicly shared by users. Such attributes include both obvious identifiers such...	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	83,960
1501.07867	Multi-task Image Classification via Collaborative, Hierarchical Spike-and-Slab Priors	Promising results have been achieved in image classification problems by exploiting the discriminative power of sparse representations for classification (SRC). Recently, it has been shown that the use of \emph{class-specific} spike-and-slab priors in conjunction with the class-specific dictionaries from SRC is particu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	39,747
2406.11635	GRID-FAST: A Grid-based Intersection Detection for Fast Semantic Topometric Mapping	This article introduces a novel approach to constructing a topometric map that allows for efficient navigation and decision-making in mobile robotics applications. The method generates the topometric map from a 2D grid-based map. The topometric map segments areas of the input map into different structural-semantic clas...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	464,974
2204.08265	Configuration-Aware Safe Control for Mobile Robotic Arm with Control Barrier Functions	Collision avoidance is a widely investigated topic in robotic applications. When applying collision avoidance techniques to a mobile robot, how to deal with the spatial structure of the robot still remains a challenge. In this paper, we design a configuration-aware safe control law by solving a Quadratic Programming (Q...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	292,023
2411.12168	Sketch-guided Cage-based 3D Gaussian Splatting Deformation	3D Gaussian Splatting (GS) is one of the most promising novel 3D representations that has received great interest in computer graphics and computer vision. While various systems have introduced editing capabilities for 3D GS, such as those guided by text prompts, fine-grained control over deformation remains an open ch...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	509,318
2210.04992	Extracting or Guessing? Improving Faithfulness of Event Temporal Relation Extraction	In this paper, we seek to improve the faithfulness of TempRel extraction models from two perspectives. The first perspective is to extract genuinely based on contextual description. To achieve this, we propose to conduct counterfactual analysis to attenuate the effects of two significant types of training biases: the e...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	322,652
2307.05104	A Deep Dive into Perturbations as Evaluation Technique for Time Series XAI	Explainable Artificial Intelligence (XAI) has gained significant attention recently as the demand for transparency and interpretability of machine learning models has increased. In particular, XAI for time series data has become increasingly important in finance, healthcare, and climate science. However, evaluating the...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	378,625
1801.07446	Double-Stage Delay Multiply and Sum Beamforming Algorithm: Application to Linear-Array Photoacoustic Imaging	Photoacoustic imaging (PAI) is an emerging medical imaging modality capable of providing high spatial resolution of Ultrasound (US) imaging and high contrast of optical imaging. Delay-and-Sum (DAS) is the most common beamforming algorithm in PAI. However, using DAS beamformer leads to low resolution images and consider...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	88,792
2012.04194	Unsupervised Label Refinement Improves Dataless Text Classification	Dataless text classification is capable of classifying documents into previously unseen labels by assigning a score to any document paired with a label description. While promising, it crucially relies on accurate descriptions of the label set for each downstream task. This reliance causes dataless classifiers to be hi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	210,374
2309.12325	FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare	Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. In recent years, concerns have been raised about the technical, clinical, ethical and legal risks associated with medical AI. To increase rea...	false	false	false	false	true	false	true	false	false	false	false	true	false	true	false	false	false	false	393,755
2101.11289	Steady-State Model of VSC based FACTS Devices using Flexible Holomorphic Embedding: (SSSC and IPFC)	For proper planning, operation, control, and protection of the power system, the development of a suitable steady-state mathematical model of FACTS devices is a key issue. The Fast and Flexible Holomorphic Embedding (FFHE) method converges faster and provides the flexibility to use any state as an initial guess. But to...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	217,225
2410.17267	Zero-Shot Vision-and-Language Navigation with Collision Mitigation in Continuous Environment	We propose the zero-shot Vision-and-Language Navigation with Collision Mitigation (VLN-CM), which takes these considerations. VLN-CM is composed of four modules and predicts the direction and distance of the next movement at each step. We utilize large foundation models for each modules. To select the direction, we use...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	501,394
2201.09425	Post-processing of Differentially Private Data: A Fairness Perspective	Post-processing immunity is a fundamental property of differential privacy: it enables arbitrary data-independent transformations to differentially private outputs without affecting their privacy guarantees. Post-processing is routinely applied in data-release applications, including census data, which are then used to...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	276,672
2105.05207	Rethinking of Radar's Role: A Camera-Radar Dataset and Systematic Annotator via Coordinate Alignment	Radar has long been a common sensor on autonomous vehicles for obstacle ranging and speed estimation. However, as a robust sensor to all-weather conditions, radar's capability has not been well-exploited, compared with camera or LiDAR. Instead of just serving as a supplementary sensor, radar's rich information hidden i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	234,746
2211.12184	Leveraging Memory Effects and Gradient Information in Consensus-Based Optimization: On Global Convergence in Mean-Field Law	In this paper we study consensus-based optimization (CBO), a versatile, flexible and customizable optimization method suitable for performing nonconvex and nonsmooth global optimizations in high dimensions. CBO is a multi-particle metaheuristic, which is effective in various applications and at the same time amenable t...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	332,026
2407.05174	Synthetic Data Aided Federated Learning Using Foundation Models	In heterogeneous scenarios where the data distribution amongst the Federated Learning (FL) participants is Non-Independent and Identically distributed (Non-IID), FL suffers from the well known problem of data heterogeneity. This leads the performance of FL to be significantly degraded, as the global model tends to stru...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	470,852
2304.12076	Customized Load Profiles Synthesis for Electricity Customers Based on Conditional Diffusion Models	Customers' load profiles are critical resources to support data analytics applications in modern power systems. However, there are usually insufficient historical load profiles for data analysis, due to the collection cost and data privacy issues. To address such data shortage problems, load profiles synthesis is an ef...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	360,076
1809.03118	A Deep Reinforced Sequence-to-Set Model for Multi-Label Text Classification	Multi-label text classification (MLTC) aims to assign multiple labels to each sample in the dataset. The labels usually have internal correlations. However, traditional methods tend to ignore the correlations between labels. In order to capture the correlations between labels, the sequence-to-sequence (Seq2Seq) model v...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	107,237
1907.04651	Incrementally Learning Functions of the Return	Temporal difference methods enable efficient estimation of value functions in reinforcement learning in an incremental fashion, and are of broader interest because they correspond learning as observed in biological systems. Standard value functions correspond to the expected value of a sum of discounted returns. While ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	138,163
2101.04506	UFA-FUSE: A novel deep supervised and hybrid model for multi-focus image fusion	Traditional and deep learning-based fusion methods generated the intermediate decision map to obtain the fusion image through a series of post-processing procedures. However, the fusion results generated by these methods are easy to lose some source image details or results in artifacts. Inspired by the image reconstru...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	215,166
1707.09662	Adaptive Delivery in Caching Networks	The problem of content delivery in caching networks is investigated for scenarios where multiple users request identical files. Redundant user demands are likely when the file popularity distribution is highly non-uniform or the user demands are positively correlated. An adaptive method is proposed for the delivery of ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	78,044
2204.07742	DRFLM: Distributionally Robust Federated Learning with Inter-client Noise via Local Mixup	Recently, federated learning has emerged as a promising approach for training a global model using data from multiple organizations without leaking their raw data. Nevertheless, directly applying federated learning to real-world tasks faces two challenges: (1) heterogeneity in the data among different organizations; an...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	291,828
2306.13544	Manifold Contrastive Learning with Variational Lie Group Operators	Self-supervised learning of deep neural networks has become a prevalent paradigm for learning representations that transfer to a variety of downstream tasks. Similar to proposed models of the ventral stream of biological vision, it is observed that these networks lead to a separation of category manifolds in the repres...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	375,313
1806.06407	An Improved Text Sentiment Classification Model Using TF-IDF and Next Word Negation	With the rapid growth of Text sentiment analysis, the demand for automatic classification of electronic documents has increased by leaps and bound. The paradigm of text classification or text mining has been the subject of many research works in recent time. In this paper we propose a technique for text sentiment class...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	100,695
2007.08233	Radial basis function kernel optimization for Support Vector Machine classifiers	Support Vector Machines (SVMs) are still one of the most popular and precise classifiers. The Radial Basis Function (RBF) kernel has been used in SVMs to separate among classes with considerable success. However, there is an intrinsic dependence on the initial value of the kernel hyperparameter. In this work, we propos...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	187,569
2401.16687	Revisiting Gradient Pruning: A Dual Realization for Defending against Gradient Attacks	Collaborative learning (CL) is a distributed learning framework that aims to protect user privacy by allowing users to jointly train a model by sharing their gradient updates only. However, gradient inversion attacks (GIAs), which recover users' training data from shared gradients, impose severe privacy threats to CL. ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	424,936
2406.14680	Dravidian language family through Universal Dependencies lens	The Universal Dependencies (UD) project aims to create a cross-linguistically consistent dependency annotation for multiple languages, to facilitate multilingual NLP. It currently supports 114 languages. Dravidian languages are spoken by over 200 million people across the word, and yet there are only two languages from...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	466,411
2411.11405	Extended Neural Contractive Dynamical Systems: On Multiple Tasks and Riemannian Safety Regions	Stability guarantees are crucial when ensuring that a fully autonomous robot does not take undesirable or potentially harmful actions. We recently proposed the Neural Contractive Dynamical Systems (NCDS), which is a neural network architecture that guarantees contractive stability. With this, learning-from-demonstratio...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	509,041
2308.01741	Supply chain emission estimation using large language models	Large enterprises face a crucial imperative to achieve the Sustainable Development Goals (SDGs), especially goal 13, which focuses on combating climate change and its impacts. To mitigate the effects of climate change, reducing enterprise Scope 3 (supply chain emissions) is vital, as it accounts for more than 90\% of t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	383,347
2403.10236	A Fixed-Point Approach to Unified Prompt-Based Counting	Existing class-agnostic counting models typically rely on a single type of prompt, e.g., box annotations. This paper aims to establish a comprehensive prompt-based counting framework capable of generating density maps for concerned objects indicated by various prompt types, such as box, point, and text. To achieve this...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	438,111
2409.01247	Conversational Complexity for Assessing Risk in Large Language Models	Large Language Models (LLMs) present a dual-use dilemma: they enable beneficial applications while harboring potential for harm, particularly through conversational interactions. Despite various safeguards, advanced LLMs remain vulnerable. A watershed case in early 2023 involved journalist Kevin Roose's extended dialog...	false	false	false	false	true	false	false	false	true	true	false	false	false	false	false	false	false	false	485,272
1708.05947	Golden Angle Modulation	Quadrature amplitude modulation (QAM) exhibits a shaping-loss of $\pi \mathrm{e}/6$, ($\approx1.53$ dB) compared to the AWGN Shannon capacity. With inspiration gained from special (leaf, flower petal, and seed) packing arrangements (spiral phyllotaxis) found among plants, a novel, shape-versatile, circular symmetric, m...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	79,235
2210.01680	New Machine Learning Techniques for Simulation-Based Inference: InferoStatic Nets, Kernel Score Estimation, and Kernel Likelihood Ratio Estimation	We propose an intuitive, machine-learning approach to multiparameter inference, dubbed the InferoStatic Networks (ISN) method, to model the score and likelihood ratio estimators in cases when the probability density can be sampled but not computed directly. The ISN uses a backend neural network that models a scalar fun...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	321,349
2305.13498	Parameter estimation from an Ornstein-Uhlenbeck process with measurement noise	This article aims to investigate the impact of noise on parameter fitting for an Ornstein-Uhlenbeck process, focusing on the effects of multiplicative and thermal noise on the accuracy of signal separation. To address these issues, we propose algorithms and methods that can effectively distinguish between thermal and m...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	366,521
2011.05364	Learning ODE Models with Qualitative Structure Using Gaussian Processes	Recent advances in learning techniques have enabled the modelling of dynamical systems for scientific and engineering applications directly from data. However, in many contexts explicit data collection is expensive and learning algorithms must be data-efficient to be feasible. This suggests using additional qualitative...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	205,887
1209.2894	Layered Subspace Codes for Network Coding	Subspace codes were introduced by K\"otter and Kschischang for error control in random linear network coding. In this paper, a layered type of subspace codes is considered, which can be viewed as a superposition of multiple component subspace codes. Exploiting the layered structure, we develop two decoding algorithms f...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	18,545
2411.14642	VQalAttent: a Transparent Speech Generation Pipeline based on Transformer-learned VQ-VAE Latent Space	Generating high-quality speech efficiently remains a key challenge for generative models in speech synthesis. This paper introduces VQalAttent, a lightweight model designed to generate fake speech with tunable performance and interpretability. Leveraging the AudioMNIST dataset, consisting of human utterances of decimal...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	510,258
2111.15323	The signature and cusp geometry of hyperbolic knots	We introduce a new real-valued invariant called the natural slope of a hyperbolic knot in the 3-sphere, which is defined in terms of its cusp geometry. We show that twice the knot signature and the natural slope differ by at most a constant times the hyperbolic volume divided by the cube of the injectivity radius. This...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	268,890
2203.17219	SimVQA: Exploring Simulated Environments for Visual Question Answering	Existing work on VQA explores data augmentation to achieve better generalization by perturbing the images in the dataset or modifying the existing questions and answers. While these methods exhibit good performance, the diversity of the questions and answers are constrained by the available image set. In this work we e...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	289,072
2306.03400	G-CAME: Gaussian-Class Activation Mapping Explainer for Object Detectors	Nowadays, deep neural networks for object detection in images are very prevalent. However, due to the complexity of these networks, users find it hard to understand why these objects are detected by models. We proposed Gaussian Class Activation Mapping Explainer (G-CAME), which generates a saliency map as the explanati...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	371,307
2102.09375	Hierarchical Similarity Learning for Language-based Product Image Retrieval	This paper aims for the language-based product image retrieval task. The majority of previous works have made significant progress by designing network structure, similarity measurement, and loss function. However, they typically perform vision-text matching at certain granularity regardless of the intrinsic multiple g...	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	true	220,753
2109.07652	American Twitter Users Revealed Social Determinants-related Oral Health Disparities amid the COVID-19 Pandemic	Objectives: To assess self-reported population oral health conditions amid COVID-19 pandemic using user reports on Twitter. Method and Material: We collected oral health-related tweets during the COVID-19 pandemic from 9,104 Twitter users across 26 states (with sufficient samples) in the United States between November ...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	255,599
2001.04663	Effects of annotation granularity in deep learning models for histopathological images	Pathological is crucial to cancer diagnosis. Usually, Pathologists draw their conclusion based on observed cell and tissue structure on histology slides. Rapid development in machine learning, especially deep learning have established robust and accurate classifiers. They are being used to analyze histopathological sli...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	160,313
1804.00540	A Systematic Review of Automated Grammar Checking in English Language	Grammar checking is the task of detection and correction of grammatical errors in the text. English is the dominating language in the field of science and technology. Therefore, the non-native English speakers must be able to use correct English grammar while reading, writing or speaking. This generates the need of aut...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	94,065
2010.05484	Multiparty Motion Coordination: From Choreographies to Robotics Programs	We present a programming model and typing discipline for complex multi-robot coordination programming. Our model encompasses both synchronisation through message passing and continuous-time dynamic motion primitives in physical space. We specify \emph{continuous-time motion primitives} in an assume-guarantee logic that...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	200,152
2407.13431	Improving Out-of-Distribution Generalization of Trajectory Prediction for Autonomous Driving via Polynomial Representations	Robustness against Out-of-Distribution (OoD) samples is a key performance indicator of a trajectory prediction model. However, the development and ranking of state-of-the-art (SotA) models are driven by their In-Distribution (ID) performance on individual competition datasets. We present an OoD testing protocol that ho...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	474,377
1210.6334	Resilient Source Coding	This paper provides a source coding theorem for multi-dimensional information signals when, at a given instant, the distribution associated with one arbitrary component of the signal to be compressed is not known and a side information is available at the destination. This new framework appears to be both of informatio...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	19,359
1312.4640	A Review of Temporal Aspects of Hand Gesture Analysis Applied to Discourse Analysis and Natural Conversation	Lately, there has been an increasing interest in hand gesture analysis systems. Recent works have employed pattern recognition techniques and have focused on the development of systems with more natural user interfaces. These systems may use gestures to control interfaces or recognize sign language gestures, which can ...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	29,161
2405.19746	DenseSeg: Joint Learning for Semantic Segmentation and Landmark Detection Using Dense Image-to-Shape Representation	Purpose: Semantic segmentation and landmark detection are fundamental tasks of medical image processing, facilitating further analysis of anatomical objects. Although deep learning-based pixel-wise classification has set a new-state-of-the-art for segmentation, it falls short in landmark detection, a strength of shape-...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	459,044
2411.03114	Investigating the Applicability of a Snapshot Computed Tomography Imaging Spectrometer for the Prediction of Brix and pH of Grapes	In this paper, a recently developed snapshot hyperspectral imaging (HSI) system based on Computed Tomography Imaging Spectroscopy (CTIS) is utilized to determine Brix and pH values in Sheegene 20 table grapes through Partial Least Squares Regression (PLSR) modeling. The performance of the CTIS system is compared with t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	505,794
2206.03680	Improving Evaluation of Debiasing in Image Classification	Image classifiers often rely overly on peripheral attributes that have a strong correlation with the target class (i.e., dataset bias) when making predictions. Due to the dataset bias, the model correctly classifies data samples including bias attributes (i.e., bias-aligned samples) while failing to correctly predict t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	301,370
2408.13945	Personalized Topology-Informed 12-Lead ECG Electrode Localization from Incomplete Cardiac MRIs for Efficient Cardiac Digital Twins	Cardiac digital twins (CDTs) offer personalized \textit{in-silico} cardiac representations for the inference of multi-scale properties tied to cardiac mechanisms. The creation of CDTs requires precise information about the electrode position on the torso, especially for the personalized electrocardiogram (ECG) calibrat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	483,356
2410.13099	Adversarial Neural Networks in Medical Imaging Advancements and Challenges in Semantic Segmentation	Recent advancements in artificial intelligence (AI) have precipitated a paradigm shift in medical imaging, particularly revolutionizing the domain of brain imaging. This paper systematically investigates the integration of deep learning -- a principal branch of AI -- into the semantic segmentation of brain images. Sema...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	499,368
2405.19793	PDDLEGO: Iterative Planning in Textual Environments	Planning in textual environments have been shown to be a long-standing challenge even for current models. A recent, promising line of work uses LLMs to generate a formal representation of the environment that can be solved by a symbolic planner. However, existing methods rely on a fully-observed environment where all e...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	459,068
2405.15423	Lost in the Averages: A New Specific Setup to Evaluate Membership Inference Attacks Against Machine Learning Models	Membership Inference Attacks (MIAs) are widely used to evaluate the propensity of a machine learning (ML) model to memorize an individual record and the privacy risk releasing the model poses. MIAs are commonly evaluated similarly to ML models: the MIA is performed on a test set of models trained on datasets unseen dur...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	456,923
2109.01246	Two Shifts for Crop Mapping: Leveraging Aggregate Crop Statistics to Improve Satellite-based Maps in New Regions	Crop type mapping at the field level is critical for a variety of applications in agricultural monitoring, and satellite imagery is becoming an increasingly abundant and useful raw input from which to create crop type maps. Still, in many regions crop type mapping with satellite data remains constrained by a scarcity o...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	253,379
2307.12157	Identifying contributors to supply chain outcomes in a multi-echelon setting: a decentralised approach	Organisations often struggle to identify the causes of change in metrics such as product quality and delivery duration. This task becomes increasingly challenging when the cause lies outside of company borders in multi-echelon supply chains that are only partially observable. Although traditional supply chain managemen...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	381,160
2404.19168	PEVA-Net: Prompt-Enhanced View Aggregation Network for Zero/Few-Shot Multi-View 3D Shape Recognition	Large vision-language models have impressively promote the performance of 2D visual recognition under zero/few-shot scenarios. In this paper, we focus on exploiting the large vision-language model, i.e., CLIP, to address zero/few-shot 3D shape recognition based on multi-view representations. The key challenge for both ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	450,529
2403.04369	From Graph to Word Bag: Introducing Domain Knowledge to Confusing Charge Prediction	Confusing charge prediction is a challenging task in legal AI, which involves predicting confusing charges based on fact descriptions. While existing charge prediction methods have shown impressive performance, they face significant challenges when dealing with confusing charges, such as Snatch and Robbery. In the lega...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	435,572
1607.01436	A Generalized Framework on Beamformer Design and CSI Acquisition for Single-Carrier Massive MIMO Systems in Millimeter Wave Channels	In this paper, we establish a general framework on the reduced dimensional channel state information (CSI) estimation and pre-beamformer design for frequency-selective massive multiple-input multiple-output MIMO systems employing single-carrier (SC) modulation in time division duplex (TDD) mode by exploiting the joint ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	58,222
2206.13646	On bounds for norms of reparameterized ReLU artificial neural network parameters: sums of fractional powers of the Lipschitz norm control the network parameter vector	It is an elementary fact in the scientific literature that the Lipschitz norm of the realization function of a feedforward fully-connected rectified linear unit (ReLU) artificial neural network (ANN) can, up to a multiplicative constant, be bounded from above by sums of powers of the norm of the ANN parameter vector. R...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	305,037
2208.06807	Semi-Supervised Video Inpainting with Cycle Consistency Constraints	Deep learning-based video inpainting has yielded promising results and gained increasing attention from researchers. Generally, these methods usually assume that the corrupted region masks of each frame are known and easily obtained. However, the annotation of these masks are labor-intensive and expensive, which limits...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	312,831
2309.09011	Optimal Initialization Strategies for Range-Only Trajectory Estimation	Range-only (RO) pose estimation involves determining a robot's pose over time by measuring the distance between multiple devices on the robot, known as tags, and devices installed in the environment, known as anchors. The nonconvex nature of the range measurement model results in a cost function with possible local min...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	392,433
2106.11280	The Arm-Swing Is Discriminative in Video Gait Recognition for Athlete Re-Identification	In this paper we evaluate running gait as an attribute for video person re-identification in a long-distance running event. We show that running gait recognition achieves competitive performance compared to appearance-based approaches in the cross-camera retrieval task and that gait and appearance features are compleme...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	242,339
2502.11177	The Mirage of Model Editing: Revisiting Evaluation in the Wild	Despite near-perfect results in artificial evaluations, the effectiveness of model editing in real-world applications remains unexplored. To bridge this gap, we propose to study model editing in question answering (QA) by establishing a rigorous evaluation practice to assess the effectiveness of editing methods in corr...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	534,235
2311.13293	The Influence of Neural Networks on Hydropower Plant Management in Agriculture: Addressing Challenges and Exploring Untapped Opportunities	Hydropower plants are crucial for stable renewable energy and serve as vital water sources for sustainable agriculture. However, it is essential to assess the current water management practices associated with hydropower plant management software. A key concern is the potential conflict between electricity generation a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	409,697
2206.05018	Going Beyond the Cookie Theft Picture Test: Detecting Cognitive Impairments using Acoustic Features	Standardized tests play a crucial role in the detection of cognitive impairment. Previous work demonstrated that automatic detection of cognitive impairment is possible using audio data from a standardized picture description task. The presented study goes beyond that, evaluating our methods on data taken from two stan...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	301,861
1705.08623	Deep Rotation Equivariant Network	Recently, learning equivariant representations has attracted considerable research attention. Dieleman et al. introduce four operations which can be inserted into convolutional neural network to learn deep representations equivariant to rotation. However, feature maps should be copied and rotated four times in each lay...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	74,059
1902.02918	Certified Adversarial Robustness via Randomized Smoothing	We show how to turn any classifier that classifies well under Gaussian noise into a new classifier that is certifiably robust to adversarial perturbations under the $\ell_2$ norm. This "randomized smoothing" technique has been proposed recently in the literature, but existing guarantees are loose. We prove a tight robu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	120,975
2002.03042	Bayesian Residual Policy Optimization: Scalable Bayesian Reinforcement Learning with Clairvoyant Experts	Informed and robust decision making in the face of uncertainty is critical for robots that perform physical tasks alongside people. We formulate this as Bayesian Reinforcement Learning over latent Markov Decision Processes (MDPs). While Bayes-optimality is theoretically the gold standard, existing algorithms do not sca...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	163,113
2302.12593	Effect of Lossy Compression Algorithms on Face Image Quality and Recognition	Lossy face image compression can degrade the image quality and the utility for the purpose of face recognition. This work investigates the effect of lossy image compression on a state-of-the-art face recognition model, and on multiple face image quality assessment models. The analysis is conducted over a range of speci...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	347,627
2307.15040	A Sparse Quantized Hopfield Network for Online-Continual Memory	An important difference between brains and deep neural networks is the way they learn. Nervous systems learn online where a stream of noisy data points are presented in a non-independent, identically distributed (non-i.i.d.) way. Further, synaptic plasticity in the brain depends only on information local to synapses. D...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	382,132
1902.06024	CruzAffect at AffCon 2019 Shared Task: A feature-rich approach to characterize happiness	We present our system, CruzAffect, for the CL-Aff Shared Task 2019. CruzAffect consists of several types of robust and efficient models for affective classification tasks. We utilize both traditional classifiers, such as XGBoosted Forest, as well as a deep learning Convolutional Neural Networks (CNN) classifier. We exp...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	121,663
2203.08965	3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation	Medical image segmentation has been so far achieving promising results with Convolutional Neural Networks (CNNs). However, it is arguable that in traditional CNNs, its pooling layer tends to discard important information such as positions. Moreover, CNNs are sensitive to rotation and affine transformation. Capsule netw...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	285,974
1907.06249	Bayesian Synthesis of Probabilistic Programs for Automatic Data Modeling	We present new techniques for automatically constructing probabilistic programs for data analysis, interpretation, and prediction. These techniques work with probabilistic domain-specific data modeling languages that capture key properties of a broad class of data generating processes, using Bayesian inference to synth...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	138,567
1904.11163	A Conditional Adversarial Network for Scene Flow Estimation	The problem of Scene flow estimation in depth videos has been attracting attention of researchers of robot vision, due to its potential application in various areas of robotics. The conventional scene flow methods are difficult to use in reallife applications due to their long computational overhead. We propose a condi...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	128,803
1801.04102	Generative Single Image Reflection Separation	Single image reflection separation is an ill-posed problem since two scenes, a transmitted scene and a reflected scene, need to be inferred from a single observation. To make the problem tractable, in this work we assume that categories of two scenes are known. It allows us to address the problem by generating both sce...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	88,219
2409.17997	Distributed Invariant Unscented Kalman Filter based on Inverse Covariance Intersection with Intermittent Measurements	This paper studies the problem of distributed state estimation (DSE) over sensor networks on matrix Lie groups, which is crucial for applications where system states evolve on Lie groups rather than vector spaces. We propose a diffusion-based distributed invariant Unscented Kalman Filter using the inverse covariance in...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	492,061

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.