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
2403.15704	Gaussian in the Wild: 3D Gaussian Splatting for Unconstrained Image Collections	Novel view synthesis from unconstrained in-the-wild images remains a meaningful but challenging task. The photometric variation and transient occluders in those unconstrained images make it difficult to reconstruct the original scene accurately. Previous approaches tackle the problem by introducing a global appearance ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	440,704
2102.10205	CKNet: A Convolutional Neural Network Based on Koopman Operator for Modeling Latent Dynamics from Pixels	With the development of end-to-end control based on deep learning, it is important to study new system modeling techniques to realize dynamics modeling with high-dimensional inputs. In this paper, a novel Koopman-based deep convolutional network, called CKNet, is proposed to identify latent dynamics from raw pixels. CK...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	221,005
2212.05679	Evolutionary Multitasking with Solution Space Cutting for Point Cloud Registration	Point cloud registration (PCR) is a popular research topic in computer vision. Recently, the registration method in an evolutionary way has received continuous attention because of its robustness to the initial pose and flexibility in objective function design. However, most evolving registration methods cannot tackle ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	335,851
2008.01807	Explainable Predictive Process Monitoring	Predictive Business Process Monitoring is becoming an essential aid for organizations, providing online operational support of their processes. This paper tackles the fundamental problem of equipping predictive business process monitoring with explanation capabilities, so that not only the what but also the why is repo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	190,436
2312.09570	CAGE: Controllable Articulation GEneration	We address the challenge of generating 3D articulated objects in a controllable fashion. Currently, modeling articulated 3D objects is either achieved through laborious manual authoring, or using methods from prior work that are hard to scale and control directly. We leverage the interplay between part shape, connectiv...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	415,789
2201.10106	On the Feasible Region of Efficient Algorithms for Attributed Graph Alignment	Graph alignment aims at finding the vertex correspondence between two correlated graphs, a task that frequently occurs in graph mining applications such as social network analysis. Attributed graph alignment is a variant of graph alignment, in which publicly available side information or attributes are exploited to ass...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	276,880
2403.01731	RISeg: Robot Interactive Object Segmentation via Body Frame-Invariant Features	In order to successfully perform manipulation tasks in new environments, such as grasping, robots must be proficient in segmenting unseen objects from the background and/or other objects. Previous works perform unseen object instance segmentation (UOIS) by training deep neural networks on large-scale data to learn RGB/...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	434,546
1902.09294	Multi-Label Network Classification via Weighted Personalized Factorizations	Multi-label network classification is a well-known task that is being used in a wide variety of web-based and non-web-based domains. It can be formalized as a multi-relational learning task for predicting nodes labels based on their relations within the network. In sparse networks, this prediction task can be very chal...	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	false	122,387
1811.01100	Prior Knowledge Integration for Neural Machine Translation using Posterior Regularization	Although neural machine translation has made significant progress recently, how to integrate multiple overlapping, arbitrary prior knowledge sources remains a challenge. In this work, we propose to use posterior regularization to provide a general framework for integrating prior knowledge into neural machine translatio...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	112,268
2008.05049	Distantly Supervised Relation Extraction in Federated Settings	This paper investigates distantly supervised relation extraction in federated settings. Previous studies focus on distant supervision under the assumption of centralized training, which requires collecting texts from different platforms and storing them on one machine. However, centralized training is challenged by two...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	191,392
2207.00556	Learning to correct spectral methods for simulating turbulent flows	Despite their ubiquity throughout science and engineering, only a handful of partial differential equations (PDEs) have analytical, or closed-form solutions. This motivates a vast amount of classical work on numerical simulation of PDEs and more recently, a whirlwind of research into data-driven techniques leveraging m...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	305,799
2405.01840	An Essay concerning machine understanding	Artificial intelligence systems exhibit many useful capabilities, but they appear to lack understanding. This essay describes how we could go about constructing a machine capable of understanding. As John Locke (1689) pointed out words are signs for ideas, which we can paraphrase as thoughts and concepts. To understand...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	451,532
2311.18054	I Know You Did Not Write That! A Sampling Based Watermarking Method for Identifying Machine Generated Text	Potential harms of Large Language Models such as mass misinformation and plagiarism can be partially mitigated if there exists a reliable way to detect machine generated text. In this paper, we propose a new watermarking method to detect machine-generated texts. Our method embeds a unique pattern within the generated t...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	411,535
1209.1711	Programming Languages for Scientific Computing	Scientific computation is a discipline that combines numerical analysis, physical understanding, algorithm development, and structured programming. Several yottacycles per year on the world's largest computers are spent simulating problems as diverse as weather prediction, the properties of material composites, the beh...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	18,460
1910.10670	Efficient Dynamic WFST Decoding for Personalized Language Models	We propose a two-layer cache mechanism to speed up dynamic WFST decoding with personalized language models. The first layer is a public cache that stores most of the static part of the graph. This is shared globally among all users. A second layer is a private cache that caches the graph that represents the personalize...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	150,549
2306.15903	Diversity is Strength: Mastering Football Full Game with Interactive Reinforcement Learning of Multiple AIs	Training AI with strong and rich strategies in multi-agent environments remains an important research topic in Deep Reinforcement Learning (DRL). The AI's strength is closely related to its diversity of strategies, and this relationship can guide us to train AI with both strong and rich strategies. To prove this point,...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	376,195
2107.06257	Object Tracking and Geo-localization from Street Images	Geo-localizing static objects from street images is challenging but also very important for road asset mapping and autonomous driving. In this paper we present a two-stage framework that detects and geolocalizes traffic signs from low frame rate street videos. Our proposed system uses a modified version of RetinaNet (G...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	246,037
2401.04282	A Fast Graph Search Algorithm with Dynamic Optimization and Reduced Histogram for Discrimination of Binary Classification Problem	This study develops a graph search algorithm to find the optimal discrimination path for the binary classification problem. The objective function is defined as the difference of variations between the true positive (TP) and false positive (FP). It uses the depth first search (DFS) algorithm to find the top-down paths ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	420,379
2006.02141	Efficient Discontinuous Galerkin Scheme for Analyzing Nanostructured Photoconductive Devices	Incorporation of plasmonic nanostructures in the design of photoconductive devices (PCDs) has significantly improved their optical-to-terahertz conversion efficiency. However, this improvement comes at the cost of increased complexity for the design and simulation of these devices. Indeed, accurate and efficient modeli...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	179,965
2205.04769	Reliable Monte Carlo Localization for Mobile Robots	Reliability is a key factor for realizing safety guarantee of full autonomous robot systems. In this paper, we focus on reliability in mobile robot localization. Monte Carlo localization (MCL) is widely used for mobile robot localization. However, it is still difficult to guarantee its safety because there are no metho...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	295,748
1308.6175	Connections Between Construction D and Related Constructions of Lattices	Most practical constructions of lattice codes with high coding gains are multilevel constructions where each level corresponds to an underlying code component. Construction D, Construction D$'$, and Forney's code formula are classical constructions that produce such lattices explicitly from a family of nested binary li...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	26,688
1807.08061	A Line in the Sand: Recommendation or Ad-hoc Retrieval?	The popular approaches to recommendation and ad-hoc retrieval tasks are largely distinct in the literature. In this work, we argue that many recommendation problems can also be cast as ad-hoc retrieval tasks. To demonstrate this, we build a solution for the RecSys 2018 Spotify challenge by combining standard ad-hoc ret...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	103,443
2410.17714	CogSteer: Cognition-Inspired Selective Layer Intervention for Efficiently Steering Large Language Models	Large Language Models (LLMs) achieve remarkable performance through pretraining on extensive data. This enables efficient adaptation to diverse downstream tasks. However, the lack of interpretability in their underlying mechanisms limits the ability to effectively steer LLMs for specific applications. In this work, we ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	501,583
2409.08450	Inter Observer Variability Assessment through Ordered Weighted Belief Divergence Measure in MAGDM Application to the Ensemble Classifier Feature Fusion	A large number of multi-attribute group decisionmaking (MAGDM) have been widely introduced to obtain consensus results. However, most of the methodologies ignore the conflict among the experts opinions and only consider equal or variable priorities of them. Therefore, this study aims to propose an Evidential MAGDM meth...	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	487,909
2305.08673	aUToLights: A Robust Multi-Camera Traffic Light Detection and Tracking System	Following four successful years in the SAE AutoDrive Challenge Series I, the University of Toronto is participating in the Series II competition to develop a Level 4 autonomous passenger vehicle capable of handling various urban driving scenarios by 2025. Accurate detection of traffic lights and correct identification ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	364,363
2412.17228	MatchMiner-AI: An Open-Source Solution for Cancer Clinical Trial Matching	Clinical trials drive improvements in cancer treatments and outcomes. However, most adults with cancer do not participate in trials, and trials often fail to enroll enough patients to answer their scientific questions. Artificial intelligence could accelerate matching of patients to appropriate clinical trials. Here, w...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	519,876
2101.00909	Fair Training of Decision Tree Classifiers	We study the problem of formally verifying individual fairness of decision tree ensembles, as well as training tree models which maximize both accuracy and individual fairness. In our approach, fairness verification and fairness-aware training both rely on a notion of stability of a classification model, which is a var...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	true	214,233
2002.01664	Identification of Indian Languages using Ghost-VLAD pooling	In this work, we propose a new pooling strategy for language identification by considering Indian languages. The idea is to obtain utterance level features for any variable length audio for robust language recognition. We use the GhostVLAD approach to generate an utterance level feature vector for any variable length i...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	162,718
1511.09123	A Short Survey on Data Clustering Algorithms	With rapidly increasing data, clustering algorithms are important tools for data analytics in modern research. They have been successfully applied to a wide range of domains; for instance, bioinformatics, speech recognition, and financial analysis. Formally speaking, given a set of data instances, a clustering algorith...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	49,633
2208.06412	Contrastive Learning for Object Detection	Contrastive learning is commonly used as a method of self-supervised learning with the "anchor" and "positive" being two random augmentations of a given input image, and the "negative" is the set of all other images. However, the requirement of large batch sizes and memory banks has made it difficult and slow to train....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	312,709
2405.10800	Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting	Spatiotemporal time series forecasting plays a key role in a wide range of real-world applications. While significant progress has been made in this area, fully capturing and leveraging spatiotemporal heterogeneity remains a fundamental challenge. Therefore, we propose a novel Heterogeneity-Informed Meta-Parameter Lear...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	454,889
1409.2668	A Crowdsourcing Procedure for the Discovery of Non-Obvious Attributes of Social Image	Research on mid-level image representations has conventionally concentrated relatively obvious attributes and overlooked non-obvious attributes, i.e., characteristics that are not readily observable when images are viewed independently of their context or function. Non-obvious attributes are not necessarily easily name...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	35,930
1511.09099	Position paper: a general framework for applying machine learning techniques in operating room	In this position paper we describe a general framework for applying machine learning and pattern recognition techniques in healthcare. In particular, we are interested in providing an automated tool for monitoring and incrementing the level of awareness in the operating room and for identifying human errors which occur...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	49,627
1904.07994	A Systematic Study of Leveraging Subword Information for Learning Word Representations	The use of subword-level information (e.g., characters, character n-grams, morphemes) has become ubiquitous in modern word representation learning. Its importance is attested especially for morphologically rich languages which generate a large number of rare words. Despite a steadily increasing interest in such subword...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	127,936
1110.2294	Query Driven Visualization of Astronomical Catalogs	Interactive visualization of astronomical catalogs requires novel techniques due to the huge volumes and complex structure of the data produced by existing and upcoming astronomical surveys. The creation as well as the disclosure of the catalogs can be handled by data pulling mechanisms. These prevent unnecessary proce...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	12,581
2311.06281	Efficient Parallelization of a Ubiquitous Sequential Computation	We find a succinct expression for computing the sequence $x_t = a_t x_{t-1} + b_t$ in parallel with two prefix sums, given $t = (1, 2, \dots, n)$, $a_t \in \mathbb{R}^n$, $b_t \in \mathbb{R}^n$, and initial value $x_0 \in \mathbb{R}$. On $n$ parallel processors, the computation of $n$ elements incurs $\mathcal{O}(\log ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	406,881
2306.07743	V-LoL: A Diagnostic Dataset for Visual Logical Learning	Despite the successes of recent developments in visual AI, different shortcomings still exist; from missing exact logical reasoning, to abstract generalization abilities, to understanding complex and noisy scenes. Unfortunately, existing benchmarks, were not designed to capture more than a few of these aspects. Whereas...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	373,132
2409.00388	A method for detecting dead fish on large water surfaces based on improved YOLOv10	Dead fish frequently appear on the water surface due to various factors. If not promptly detected and removed, these dead fish can cause significant issues such as water quality deterioration, ecosystem damage, and disease transmission. Consequently, it is imperative to develop rapid and effective detection methods to ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	484,911
1905.11213	Provable robustness against all adversarial $l_p$-perturbations for $p\geq 1$	In recent years several adversarial attacks and defenses have been proposed. Often seemingly robust models turn out to be non-robust when more sophisticated attacks are used. One way out of this dilemma are provable robustness guarantees. While provably robust models for specific $l_p$-perturbation models have been dev...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	132,361
1907.07237	FAHT: An Adaptive Fairness-aware Decision Tree Classifier	Automated data-driven decision-making systems are ubiquitous across a wide spread of online as well as offline services. These systems, depend on sophisticated learning algorithms and available data, to optimize the service function for decision support assistance. However, there is a growing concern about the accounta...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	138,816
2305.16513	Sliding Window Sum Algorithms for Deep Neural Networks	Sliding window sums are widely used for string indexing, hashing and time series analysis. We have developed a family of the generic vectorized sliding sum algorithms that provide speedup of O(P/w) for window size $w$ and number of processors P. For a sum with a commutative operator the speedup is improved to O(P/log(w...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	368,124
2011.03367	Disentangling 3D Prototypical Networks For Few-Shot Concept Learning	We present neural architectures that disentangle RGB-D images into objects' shapes and styles and a map of the background scene, and explore their applications for few-shot 3D object detection and few-shot concept classification. Our networks incorporate architectural biases that reflect the image formation process, 3D...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	205,227
2310.19055	A Few-Shot Learning Focused Survey on Recent Named Entity Recognition and Relation Classification Methods	Named Entity Recognition (NER) and Relation Classification (RC) are important steps in extracting information from unstructured text and formatting it into a machine-readable format. We present a survey of recent deep learning models that address named entity recognition and relation classification, with focus on few-s...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	403,828
2403.01246	Dual Graph Attention based Disentanglement Multiple Instance Learning for Brain Age Estimation	Deep learning techniques have demonstrated great potential for accurately estimating brain age by analyzing Magnetic Resonance Imaging (MRI) data from healthy individuals. However, current methods for brain age estimation often directly utilize whole input images, overlooking two important considerations: 1) the hetero...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	434,323
1804.01050	Training VAEs Under Structured Residuals	Variational auto-encoders (VAEs) are a popular and powerful deep generative model. Previous works on VAEs have assumed a factorized likelihood model, whereby the output uncertainty of each pixel is assumed to be independent. This approximation is clearly limited as demonstrated by observing a residual image from a VAE ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	94,167
2303.11032	DeID-GPT: Zero-shot Medical Text De-Identification by GPT-4	The digitization of healthcare has facilitated the sharing and re-using of medical data but has also raised concerns about confidentiality and privacy. HIPAA (Health Insurance Portability and Accountability Act) mandates removing re-identifying information before the dissemination of medical records. Thus, effective an...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	352,678
2309.13653	Probabilistic Bounds for Data Storage with Feature Selection and Undersampling	In this paper we consider data storage from a probabilistic point of view and obtain bounds for efficient storage in the presence of feature selection and undersampling, both of which are important from the data science perspective. First, we consider encoding of correlated sources for nonstationary data and obtain a S...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	394,300
2410.09119	$\textit{lucie}$: An Improved Python Package for Loading Datasets from the UCI Machine Learning Repository	The University of California--Irvine (UCI) Machine Learning (ML) Repository (UCIMLR) is consistently cited as one of the most popular dataset repositories, hosting hundreds of high-impact datasets. However, a significant portion, including 28.4% of the top 250, cannot be imported via the $\textit{ucimlrepo}$ package th...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	497,447
2107.01881	Robust Online Convex Optimization in the Presence of Outliers	We consider online convex optimization when a number k of data points are outliers that may be corrupted. We model this by introducing the notion of robust regret, which measures the regret only on rounds that are not outliers. The aim for the learner is to achieve small robust regret, without knowing where the outlier...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	244,631
2309.10773	Semi-supervised Domain Adaptation in Graph Transfer Learning	As a specific case of graph transfer learning, unsupervised domain adaptation on graphs aims for knowledge transfer from label-rich source graphs to unlabeled target graphs. However, graphs with topology and attributes usually have considerable cross-domain disparity and there are numerous real-world scenarios where me...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	393,146
1803.00039	Super-Efficient Spatially Adaptive Contrast Enhancement Algorithm for Superficial Vein Imaging	This paper presents a super-efficient spatially adaptive contrast enhancement algorithm for enhancing infrared (IR) radiation based superficial vein images in real-time. The super-efficiency permits the algorithm to run in consumer-grade handheld devices, which ultimately reduces the cost of vein imaging equipment. The...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	91,572
1810.09113	The Bregman chord divergence	Distances are fundamental primitives whose choice significantly impacts the performances of algorithms in machine learning and signal processing. However selecting the most appropriate distance for a given task is an endeavor. Instead of testing one by one the entries of an ever-expanding dictionary of {\em ad hoc} dis...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	110,990
2407.12055	Integrating Query-aware Segmentation and Cross-Attention for Robust VQA	This paper introduces a method for VizWiz-VQA using LVLM with trainable cross-attention and LoRA finetuning. We train the model with the following conditions: 1) Training with original images. 2) Training with enhanced images using CLIPSeg to highlight or contrast the original image. 3) Training with integrating the ou...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	473,746
1608.03694	Density Matching Reward Learning	In this paper, we focus on the problem of inferring the underlying reward function of an expert given demonstrations, which is often referred to as inverse reinforcement learning (IRL). In particular, we propose a model-free density-based IRL algorithm, named density matching reward learning (DMRL), which does not requ...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	59,712
1905.00479	Shadowed FSO/mmWave Systems with Interference	We investigate the performance of mixed free space optical (FSO)/millimeter-wave (mmWave) relay networks with interference at the destination. The FSO/mmWave channels are assumed to follow Malaga-M/Generalized-K fading models with pointing errors in the FSO link. The H-transform theory, wherein integral transforms invo...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	129,478
2412.08496	Drift-free Visual SLAM using Digital Twins	Globally-consistent localization in urban environments is crucial for autonomous systems such as self-driving vehicles and drones, as well as assistive technologies for visually impaired people. Traditional Visual-Inertial Odometry (VIO) and Visual Simultaneous Localization and Mapping (VSLAM) methods, though adequate ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	516,109
2405.03266	Efficient computation of Katz centrality for very dense networks via negative parameter Katz	Katz centrality (and its limiting case, eigenvector centrality) is a frequently used tool to measure the importance of a node in a network, and to rank the nodes accordingly. One reason for its popularity is that Katz centrality can be computed very efficiently when the network is sparse, i.e., having only $O(n)$ edges...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	452,118
2010.01169	DocuBot : Generating financial reports using natural language interactions	The financial services industry perpetually processes an overwhelming amount of complex data. Digital reports are often created based on tedious manual analysis as well as visualization of the underlying trends and characteristics of data. Often, the accruing costs of human computation errors in creating these reports ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	198,541
2109.00460	From Movement Kinematics to Object Properties: Online Recognition of Human Carefulness	When manipulating objects, humans finely adapt their motions to the characteristics of what they are handling. Thus, an attentive observer can foresee hidden properties of the manipulated object, such as its weight, temperature, and even whether it requires special care in manipulation. This study is a step towards end...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	253,109
2411.16568	J-CaPA : Joint Channel and Pyramid Attention Improves Medical Image Segmentation	Medical image segmentation is crucial for diagnosis and treatment planning. Traditional CNN-based models, like U-Net, have shown promising results but struggle to capture long-range dependencies and global context. To address these limitations, we propose a transformer-based architecture that jointly applies Channel At...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	511,072
2406.15578	Neural Moving Horizon Estimation: A Systematic Literature Review	The neural moving horizon estimator (NMHE) is a relatively new and powerful state estimator that combines the strengths of neural networks (NNs) and model-based state estimation techniques. Various approaches exist for constructing NMHEs, each with its unique advantages and limitations. However, a comprehensive literat...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	466,782
2310.09935	Passivity and Decentralized Stability Conditions for Grid-Forming Converters	We prove that the popular grid-forming control, i.e., dispatchable virtual oscillator control (dVOC), also termed complex droop control, exhibits output-feedback passivity in its large-signal model, featuring an explicit and physically meaningful passivity index. Using this passivity property, we derive decentralized s...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	400,014
1704.03660	Feature Tracking Cardiac Magnetic Resonance via Deep Learning and Spline Optimization	Feature tracking Cardiac Magnetic Resonance (CMR) has recently emerged as an area of interest for quantification of regional cardiac function from balanced, steady state free precession (SSFP) cine sequences. However, currently available techniques lack full automation, limiting reproducibility. We propose a fully auto...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	71,672
2308.03008	Early Detection and Localization of Pancreatic Cancer by Label-Free Tumor Synthesis	Early detection and localization of pancreatic cancer can increase the 5-year survival rate for patients from 8.5% to 20%. Artificial intelligence (AI) can potentially assist radiologists in detecting pancreatic tumors at an early stage. Training AI models require a vast number of annotated examples, but the availabili...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	383,860
2412.03548	Perception Tokens Enhance Visual Reasoning in Multimodal Language Models	Multimodal language models (MLMs) still face challenges in fundamental visual perception tasks where specialized models excel. Tasks requiring reasoning about 3D structures benefit from depth estimation, and reasoning about 2D object instances benefits from object detection. Yet, MLMs can not produce intermediate depth...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	513,997
2207.13644	Using Deep Learning to Detecting Deepfakes	In the recent years, social media has grown to become a major source of information for many online users. This has given rise to the spread of misinformation through deepfakes. Deepfakes are videos or images that replace one persons face with another computer-generated face, often a more recognizable person in society...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	310,358
2011.04349	MAGNeto: An Efficient Deep Learning Method for the Extractive Tags Summarization Problem	In this work, we study a new image annotation task named Extractive Tags Summarization (ETS). The goal is to extract important tags from the context lying in an image and its corresponding tags. We adjust some state-of-the-art deep learning models to utilize both visual and textual information. Our proposed solution co...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	205,558
1312.5578	Multimodal Transitions for Generative Stochastic Networks	Generative Stochastic Networks (GSNs) have been recently introduced as an alternative to traditional probabilistic modeling: instead of parametrizing the data distribution directly, one parametrizes a transition operator for a Markov chain whose stationary distribution is an estimator of the data generating distributio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	29,245
1603.09522	Image Retrieval with a Bayesian Model of Relevance Feedback	A content-based image retrieval system based on multinomial relevance feedback is proposed. The system relies on an interactive search paradigm where at each round a user is presented with k images and selects the one closest to their ideal target. Two approaches, one based on the Dirichlet distribution and one based t...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	53,936
1902.00555	Riconoscimento ortografico per apostrofo ed espressioni polirematiche	The work presents two algorithms of manipulation and comparison between strings whose purpose is the orthographic recognition of the apostrophe and of the compound expressions. The theory supporting general reasoning refers to the basic concept of EditDistance, the improvements that ensure the achievement of the object...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	120,428
2308.06975	Can Knowledge Graphs Simplify Text?	Knowledge Graph (KG)-to-Text Generation has seen recent improvements in generating fluent and informative sentences which describe a given KG. As KGs are widespread across multiple domains and contain important entity-relation information, and as text simplification aims to reduce the complexity of a text while preserv...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	385,352
1906.10366	Software Engineering Practices for Machine Learning	In the last couple of years we have witnessed an enormous increase of machine learning (ML) applications. More and more program functions are no longer written in code, but learnt from a huge amount of data samples using an ML algorithm. However, what is often overlooked is the complexity of managing the resulting ML m...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	136,420
2208.11108	Efficient Attention-free Video Shift Transformers	This paper tackles the problem of efficient video recognition. In this area, video transformers have recently dominated the efficiency (top-1 accuracy vs FLOPs) spectrum. At the same time, there have been some attempts in the image domain which challenge the necessity of the self-attention operation within the transfor...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	314,314
1501.01579	Consensus Labeled Random Finite Set Filtering for Distributed Multi-Object Tracking	This paper addresses distributed multi-object tracking over a network of heterogeneous and geographically dispersed nodes with sensing, communication and processing capabilities. The main contribution is an approach to distributed multi-object estimation based on labeled Random Finite Sets (RFSs) and dynamic Bayesian i...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	39,097
2406.05708	Towards A General-Purpose Motion Planning for Autonomous Vehicles Using Fluid Dynamics	General-purpose motion planners for automated/autonomous vehicles promise to handle the task of motion planning (including tactical decision-making and trajectory generation) for various automated driving functions (ADF) in a diverse range of operational design domains (ODDs). The challenges of designing a general-purp...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	462,258
2006.07911	Loss Rate Forecasting Framework Based on Macroeconomic Changes: Application to US Credit Card Industry	A major part of the balance sheets of the largest US banks consists of credit card portfolios. Hence, managing the charge-off rates is a vital task for the profitability of the credit card industry. Different macroeconomic conditions affect individuals' behavior in paying down their debts. In this paper, we propose an ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	182,003
2201.00075	How do lexical semantics affect translation? An empirical study	Neural machine translation (NMT) systems aim to map text from one language into another. While there are a wide variety of applications of NMT, one of the most important is translation of natural language. A distinguishing factor of natural language is that words are typically ordered according to the rules of the gram...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	273,854
2406.09606	Cross-Modality Program Representation Learning for Electronic Design Automation with High-Level Synthesis	In recent years, domain-specific accelerators (DSAs) have gained popularity for applications such as deep learning and autonomous driving. To facilitate DSA designs, programmers use high-level synthesis (HLS) to compile a high-level description written in C/C++ into a design with low-level hardware description language...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	464,002
1706.05125	Deal or No Deal? End-to-End Learning for Negotiation Dialogues	Much of human dialogue occurs in semi-cooperative settings, where agents with different goals attempt to agree on common decisions. Negotiations require complex communication and reasoning skills, but success is easy to measure, making this an interesting task for AI. We gather a large dataset of human-human negotiatio...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	75,458
2402.01188	Segment Any Change	Visual foundation models have achieved remarkable results in zero-shot image classification and segmentation, but zero-shot change detection remains an open problem. In this paper, we propose the segment any change models (AnyChange), a new type of change detection model that supports zero-shot prediction and generaliz...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	425,905
1705.03148	Deep Spatio-temporal Manifold Network for Action Recognition	Visual data such as videos are often sampled from complex manifold. We propose leveraging the manifold structure to constrain the deep action feature learning, thereby minimizing the intra-class variations in the feature space and alleviating the over-fitting problem. Considering that manifold can be transferred, layer...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	73,126
2202.11295	Continual learning-based probabilistic slow feature analysis for multimode dynamic process monitoring	In this paper, a novel multimode dynamic process monitoring approach is proposed by extending elastic weight consolidation (EWC) to probabilistic slow feature analysis (PSFA) in order to extract multimode slow features for online monitoring. EWC was originally introduced in the setting of machine learning of sequential...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	281,840
2311.04542	FEIR: Quantifying and Reducing Envy and Inferiority for Fair Recommendation of Limited Resources	In settings such as e-recruitment and online dating, recommendation involves distributing limited opportunities, calling for novel approaches to quantify and enforce fairness. We introduce \emph{inferiority}, a novel (un)fairness measure quantifying a user's competitive disadvantage for their recommended items. Inferio...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	406,265
2007.11246	Fragments-Expert: A Graphical User Interface MATLAB Toolbox for Classification of File Fragments	The classification of file fragments of various file formats is an essential task in various applications such as firewalls, intrusion detection systems, anti-viruses, web content filtering, and digital forensics. However, the community lacks a suitable software tool that can integrate major methods for feature extract...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	188,504
1808.07997	Non-asymptotic bounds for percentiles of independent non-identical random variables	This note displays an interesting phenomenon for percentiles of independent but non-identical random variables. Let $X_1,\cdots,X_n$ be independent random variables obeying non-identical continuous distributions and $X^{(1)}\geq \cdots\geq X^{(n)}$ be the corresponding order statistics. For any $p\in(0,1)$, we investig...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	105,851
1908.07307	Investigation of wind pressures on tall building under interference effects using machine learning techniques	Interference effects of tall buildings have attracted numerous studies due to the boom of clusters of tall buildings in megacities. To fully understand the interference effects of buildings, it often requires a substantial amount of wind tunnel tests. Limited wind tunnel tests that only cover part of interference scena...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	142,254
1909.02425	Random Error Sampling-based Recurrent Neural Network Architecture Optimization	Recurrent neural networks are good at solving prediction problems. However, finding a network that suits a problem is quite hard because their performance is strongly affected by their architecture configuration. Automatic architecture optimization methods help to find the most suitable design, but they are not extensi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	144,193
2209.08445	SDFE-LV: A Large-Scale, Multi-Source, and Unconstrained Database for Spotting Dynamic Facial Expressions in Long Videos	In this paper, we present a large-scale, multi-source, and unconstrained database called SDFE-LV for spotting the onset and offset frames of a complete dynamic facial expression from long videos, which is known as the topic of dynamic facial expression spotting (DFES) and a vital prior step for lots of facial expressio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	318,127
2106.12030	A Simple and Practical Approach to Improve Misspellings in OCR Text	The focus of our paper is the identification and correction of non-word errors in OCR text. Such errors may be the result of incorrect insertion, deletion, or substitution of a character, or the transposition of two adjacent characters within a single word. Or, it can be the result of word boundary problems that lead t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	242,589
2401.12708	Deep Neural Network Benchmarks for Selective Classification	With the increasing deployment of machine learning models in many socially sensitive tasks, there is a growing demand for reliable and trustworthy predictions. One way to accomplish these requirements is to allow a model to abstain from making a prediction when there is a high risk of making an error. This requires add...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	423,472
2201.10101	Towards Ubiquitous Sensing and Localization With Reconfigurable Intelligent Surfaces	In future cellular systems, wireless localization and sensing functions will be built-in for specific applications, e.g., navigation, transportation, and healthcare, and to support flexible and seamless connectivity. Driven by this trend, the need rises for fine-resolution sensing solutions and cm-level localization ac...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	276,877
2501.14197	Bi-directional Curriculum Learning for Graph Anomaly Detection: Dual Focus on Homogeneity and Heterogeneity	Graph anomaly detection (GAD) aims to identify nodes from a graph that are significantly different from normal patterns. Most previous studies are model-driven, focusing on enhancing the detection effect by improving the model structure. However, these approaches often treat all nodes equally, neglecting the different ...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	527,021
2103.15581	Supporting verification of news articles with automated search for semantically similar articles	Fake information poses one of the major threats for society in the 21st century. Identifying misinformation has become a key challenge due to the amount of fake news that is published daily. Yet, no approach is established that addresses the dynamics and versatility of fake news editorials. Instead of classifying conte...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	227,270
1604.08568	Towards Temporal Graph Databases	In spite of the extensive literature on graph databases (GDBs), temporal GDBs have not received too much attention so far. Temporal GBDs can capture, for example, the evolution of social networks across time, a relevant topic in data analysis nowadays. In this paper we propose a data model and query language (denoted T...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	55,223
1311.3773	Non-Convex Compressed Sensing Using Partial Support Information	In this paper we address the recovery conditions of weighted $\ell_p$ minimization for signal reconstruction from compressed sensing measurements when partial support information is available. We show that weighted $\ell_p$ minimization with $0<p<1$ is stable and robust under weaker sufficient conditions compared to we...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	28,433
2307.06940	Animate-A-Story: Storytelling with Retrieval-Augmented Video Generation	Generating videos for visual storytelling can be a tedious and complex process that typically requires either live-action filming or graphics animation rendering. To bypass these challenges, our key idea is to utilize the abundance of existing video clips and synthesize a coherent storytelling video by customizing thei...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	379,223
1106.3153	Algorithmic analogies to kamae-Weiss theorem on normal numbers	In this paper we study subsequences of random numbers. In Kamae (1973), selection functions that depend only on coordinates are studied, and their necessary and sufficient condition for the selected sequences to be normal numbers is given. In van Lambalgen (1987), an algorithmic analogy to the theorem is conjectured in...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	10,866
2012.03105	Obstacle avoidance and path finding for mobile robot navigation	This paper investigates different methods to detect obstacles ahead of a robot using a camera in the robot, an aerial camera, and an ultrasound sensor. We also explored various efficient path finding methods for the robot to navigate to the target source. Single and multi-iteration angle-based navigation algorithms wer...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	209,989
1812.04652	Evaluating the Impact of Intensity Normalization on MR Image Synthesis	Image synthesis learns a transformation from the intensity features of an input image to yield a different tissue contrast of the output image. This process has been shown to have application in many medical image analysis tasks including imputation, registration, and segmentation. To carry out synthesis, the intensiti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	116,253
1810.00088	TS-MPC for Autonomous Vehicles including a dynamic TS-MHE-UIO	In this work, a novel approach is presented to solve the problem of tracking trajectories in autonomous vehicles. This approach is based on the use of a cascade control where the external loop solves the position control using a novel Takagi Sugeno - Model Predictive Control (TS-MPC) approach and the internal loop is i...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	109,083

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