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
2103.07279	Patient-specific virtual spine straightening and vertebra inpainting: An automatic framework for osteoplasty planning	Symptomatic spinal vertebral compression fractures (VCFs) often require osteoplasty treatment. A cement-like material is injected into the bone to stabilize the fracture, restore the vertebral body height and alleviate pain. Leakage is a common complication and may occur due to too much cement being injected. In this w...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	224,551
2311.07150	Interaction is all You Need? A Study of Robots Ability to Understand and Execute	This paper aims to address a critical challenge in robotics, which is enabling them to operate seamlessly in human environments through natural language interactions. Our primary focus is to equip robots with the ability to understand and execute complex instructions in coherent dialogs to facilitate intricate task-sol...	false	false	false	false	true	false	false	true	true	false	false	true	false	false	false	false	false	false	407,219
1802.02914	Praaline: Integrating Tools for Speech Corpus Research	This paper presents Praaline, an open-source software system for managing, annotating, analysing and visualising speech corpora. Researchers working with speech corpora are often faced with multiple tools and formats, and they need to work with ever-increasing amounts of data in a collaborative way. Praaline integrates...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	89,860
2403.16110	ByteCard: Enhancing ByteDance's Data Warehouse with Learned Cardinality Estimation	Cardinality estimation is a critical component and a longstanding challenge in modern data warehouses. ByteHouse, ByteDance's cloud-native engine for extensive data analysis in exabyte-scale environments, serves numerous internal decision-making business scenarios. With the increasing demand for ByteHouse, cardinality ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	440,875
2409.13115	Personalized 2D Binary Patient Codes of Tissue Images and Immunogenomic Data Through Multimodal Self-Supervised Fusion	The field of medical diagnostics has witnessed a transformative convergence of artificial intelligence (AI) and healthcare data, offering promising avenues for enhancing patient care and disease comprehension. However, this integration of multimodal data, specifically histopathology whole slide images (WSIs) and geneti...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	489,854
2005.04965	A finite-strain model for incomplete damage in elastoplastic materials	We address a three-dimensional model capable of describing coupled damage and plastic effects in solids at finite strains. Formulated within the variational setting of {\it generalized standard materials}, the constitutive model results from the balance of conservative and dissipative forces. Material response is rate-...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	176,604
2212.09676	Words as Gatekeepers: Measuring Discipline-specific Terms and Meanings in Scholarly Publications	Scholarly text is often laden with jargon, or specialized language that can facilitate efficient in-group communication within fields but hinder understanding for out-groups. In this work, we develop and validate an interpretable approach for measuring scholarly jargon from text. Expanding the scope of prior work which...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	337,189
2308.12604	PromptMRG: Diagnosis-Driven Prompts for Medical Report Generation	Automatic medical report generation (MRG) is of great research value as it has the potential to relieve radiologists from the heavy burden of report writing. Despite recent advancements, accurate MRG remains challenging due to the need for precise clinical understanding and disease identification. Moreover, the imbalan...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	387,606
2112.12812	MDN-VO: Estimating Visual Odometry with Confidence	Visual Odometry (VO) is used in many applications including robotics and autonomous systems. However, traditional approaches based on feature matching are computationally expensive and do not directly address failure cases, instead relying on heuristic methods to detect failure. In this work, we propose a deep learning...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	273,060
2206.11104	OpenXAI: Towards a Transparent Evaluation of Model Explanations	While several types of post hoc explanation methods have been proposed in recent literature, there is very little work on systematically benchmarking these methods. Here, we introduce OpenXAI, a comprehensive and extensible open-source framework for evaluating and benchmarking post hoc explanation methods. OpenXAI comp...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	304,156
2303.10404	MotionTrack: Learning Robust Short-term and Long-term Motions for Multi-Object Tracking	The main challenge of Multi-Object Tracking~(MOT) lies in maintaining a continuous trajectory for each target. Existing methods often learn reliable motion patterns to match the same target between adjacent frames and discriminative appearance features to re-identify the lost targets after a long period. However, the r...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	352,431
2203.07374	Automated fault tree learning from continuous-valued sensor data: a case study on domestic heaters	Many industrial sectors have been collecting big sensor data. With recent technologies for processing big data, companies can exploit this for automatic failure detection and prevention. We propose the first completely automated method for failure analysis, machine-learning fault trees from raw observational data with ...	false	true	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	285,409
2206.00636	A modular architecture for creating multimodal agents	The paper describes a flexible and modular platform to create multimodal interactive agents. The platform operates through an event-bus on which signals and interpretations are posted in a sequence in time. Different sensors and interpretation components can be integrated by defining their input and output as topics, w...	true	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	300,196
2301.11916	Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning	In recent years, pre-trained large language models (LLMs) have demonstrated remarkable efficiency in achieving an inference-time few-shot learning capability known as in-context learning. However, existing literature has highlighted the sensitivity of this capability to the selection of few-shot demonstrations. Current...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	342,318
2303.13037	Universal Linear Intensity Transformations Using Spatially-Incoherent Diffractive Processors	Under spatially-coherent light, a diffractive optical network composed of structured surfaces can be designed to perform any arbitrary complex-valued linear transformation between its input and output fields-of-view (FOVs) if the total number (N) of optimizable phase-only diffractive features is greater than or equal t...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	353,518
2310.06433	Retromorphic Testing: A New Approach to the Test Oracle Problem	A test oracle serves as a criterion or mechanism to assess the correspondence between software output and the anticipated behavior for a given input set. In automated testing, black-box techniques, known for their non-intrusive nature in test oracle construction, are widely used, including notable methodologies like di...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	true	398,577
2203.16897	Multi-Granularity Alignment Domain Adaptation for Object Detection	Domain adaptive object detection is challenging due to distinctive data distribution between source domain and target domain. In this paper, we propose a unified multi-granularity alignment based object detection framework towards domain-invariant feature learning. To this end, we encode the dependencies across differe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	288,967
2205.05168	Deep Graph Clustering via Mutual Information Maximization and Mixture Model	Attributed graph clustering or community detection which learns to cluster the nodes of a graph is a challenging task in graph analysis. In this paper, we introduce a contrastive learning framework for learning clustering-friendly node embedding. Although graph contrastive learning has shown outstanding performance in ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	295,856
2404.16611	Towards Symbiotic SAGIN Through Inter-operator Resource and Service Sharing: Joint Orchestration of User Association and Radio Resources	The space-air-ground integrated network (SAGIN) is a pivotal architecture to support ubiquitous connectivity in the upcoming 6G era. Inter-operator resource and service sharing is a promising way to realize such a huge network, utilizing resources efficiently and reducing construction costs. Given the rationality of op...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	449,558
2106.11612	Uniform-PAC Bounds for Reinforcement Learning with Linear Function Approximation	We study reinforcement learning (RL) with linear function approximation. Existing algorithms for this problem only have high-probability regret and/or Probably Approximately Correct (PAC) sample complexity guarantees, which cannot guarantee the convergence to the optimal policy. In this paper, in order to overcome the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	242,463
2402.08978	Prismatic: Interactive Multi-View Cluster Analysis of Concept Stocks	Financial cluster analysis allows investors to discover investment alternatives and avoid undertaking excessive risks. However, this analytical task faces substantial challenges arising from many pairwise comparisons, the dynamic correlations across time spans, and the ambiguity in deriving implications from business r...	true	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	429,318
1407.6075	Robust Distributed Averaging: When are Potential-Theoretic Strategies Optimal?	We study the interaction between a network designer and an adversary over a dynamical network. The network consists of nodes performing continuous-time distributed averaging. The adversary strategically disconnects a set of links to prevent the nodes from reaching consensus. Meanwhile, the network designer assists the ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	34,828
2408.08089	AgentCourt: Simulating Court with Adversarial Evolvable Lawyer Agents	In this paper, we present a simulation system called AgentCourt that simulates the entire courtroom process. The judge, plaintiff's lawyer, defense lawyer, and other participants are autonomous agents driven by large language models (LLMs). Our core goal is to enable lawyer agents to learn how to argue a case, as well ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	480,854
1502.04156	Towards Biologically Plausible Deep Learning	Neuroscientists have long criticised deep learning algorithms as incompatible with current knowledge of neurobiology. We explore more biologically plausible versions of deep representation learning, focusing here mostly on unsupervised learning but developing a learning mechanism that could account for supervised, unsu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	40,225
2412.06268	Open-Vocabulary High-Resolution 3D (OVHR3D) Data Segmentation and Annotation Framework	In the domain of the U.S. Army modeling and simulation, the availability of high quality annotated 3D data is pivotal to creating virtual environments for training and simulations. Traditional methodologies for 3D semantic and instance segmentation, such as KpConv, RandLA, Mask3D, etc., are designed to train on extensi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	515,182
2412.15260	Analyzing Images of Legal Documents: Toward Multi-Modal LLMs for Access to Justice	Interacting with the legal system and the government requires the assembly and analysis of various pieces of information that can be spread across different (paper) documents, such as forms, certificates and contracts (e.g. leases). This information is required in order to understand one's legal rights, as well as to f...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	true	519,020
2411.05793	A Comprehensive Survey of Time Series Forecasting: Architectural Diversity and Open Challenges	Time series forecasting is a critical task that provides key information for decision-making across various fields. Recently, various fundamental deep learning architectures such as MLPs, CNNs, RNNs, and GNNs have been developed and applied to solve time series forecasting problems. However, the structural limitations ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	506,796
1510.08535	On the Covering Radius of the Second Order Reed-Muller Code of Length 128	In 1981, Schatz proved that the covering radius of the binary Reed-Muller code $RM(2,6)$ is 18. For $RM(2,7)$, we only know that its covering radius is between 40 and 44. In this paper, we prove that the covering radius of the binary Reed-Muller code $RM(2,7)$ is at most 42. Moreover, we give a sufficient and necessary...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	48,296
2207.02194	Data-driven synchronization-avoiding algorithms in the explicit distributed structural analysis of soft tissue	We propose a data-driven framework to increase the computational efficiency of the explicit finite element method in the structural analysis of soft tissue. An encoder-decoder long short-term memory deep neural network is trained based on the data produced by an explicit, distributed finite element solver. We leverage ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	306,435
2305.04066	Semi-Asynchronous Federated Edge Learning Mechanism via Over-the-air Computation	Over-the-air Computation (AirComp) has been demonstrated as an effective transmission scheme to boost the efficiency of federated edge learning (FEEL). However, existing FEEL systems with AirComp scheme often employ traditional synchronous aggregation mechanisms for local model aggregation in each global round, which s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	362,619
1801.05585	Light-weight pixel context encoders for image inpainting	In this work we propose Pixel Content Encoders (PCE), a light-weight image inpainting model, capable of generating novel con-tent for large missing regions in images. Unlike previously presented convolutional neural network based models, our PCE model has an order of magnitude fewer trainable parameters. Moreover, by i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	88,484
2303.06574	Diffusion Models for Non-autoregressive Text Generation: A Survey	Non-autoregressive (NAR) text generation has attracted much attention in the field of natural language processing, which greatly reduces the inference latency but has to sacrifice the generation accuracy. Recently, diffusion models, a class of latent variable generative models, have been introduced into NAR text genera...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	350,906
2310.20039	Radiomics as a measure superior to the Dice similarity coefficient for tumor segmentation performance evaluation	In high-quality radiotherapy delivery, precise segmentation of targets and healthy structures is essential. This study proposes Radiomics features as a superior measure for assessing the segmentation ability of physicians and auto-segmentation tools, in comparison to the widely used Dice Similarity Coefficient (DSC). T...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	404,225
1805.09978	Distributed Cartesian Power Graph Segmentation for Graphon Estimation	We study an extention of total variation denoising over images to over Cartesian power graphs and its applications to estimating non-parametric network models. The power graph fused lasso (PGFL) segments a matrix by exploiting a known graphical structure, $G$, over the rows and columns. Our main results shows that for ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	98,550
1106.0439	Model of communities isolation at hierarchical modular networks	The model of community isolation was extended to the case when individuals are randomly placed at nodes of hierarchical modular networks. It was shown that the average number of blocked nodes (individuals) increases in time as a power function, with the exponent depending on network parameters. The distribution of time...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	10,687
1912.07331	Scalable Group Secret Key Generation over Wireless Channels	In this paper, we consider the problem of secret key generation for multiple parties. Multi-user networks usually require a trusted party to efficiently distribute keys to the legitimate users and this process is a weakness against eavesdroppers. With the help of the physical layer security techniques, users can secure...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	157,579
1302.6844	Belief Induced by the Partial Knowledge of the Probabilities	We construct the belief function that quantifies the agent, beliefs about which event of Q will occurred when he knows that the event is selected by a chance set-up and that the probability function associated to the chance set up is only partially known.	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	22,474
1710.03442	On- and Off-Policy Monotonic Policy Improvement	Monotonic policy improvement and off-policy learning are two main desirable properties for reinforcement learning algorithms. In this paper, by lower bounding the performance difference of two policies, we show that the monotonic policy improvement is guaranteed from on- and off-policy mixture samples. An optimization ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	82,331
2201.04188	Dynamic Price of Parking Service based on Deep Learning	The improvement of air-quality in urban areas is one of the main concerns of public government bodies. This concern emerges from the evidence between the air quality and the public health. Major efforts from government bodies in this area include monitoring and forecasting systems, banning more pollutant motor vehicles...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	275,035
1001.4423	A New Decoding Scheme for Errorless Codes for Overloaded CDMA with Active User Detection	Recently, a new class of binary codes for overloaded CDMA systems are proposed that not only has the ability of errorless communication but also suitable for detecting active users. These codes are called COWDA [1]. In [1], a Maximum Likelihood (ML) decoder is proposed for this class of codes. Although the proposed sch...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	5,521
2001.04346	Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-Based Recommendation	Recently, recommender systems have been able to emit substantially improved recommendations by leveraging user-provided reviews. Existing methods typically merge all reviews of a given user or item into a long document, and then process user and item documents in the same manner. In practice, however, these two sets of...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	160,229
2411.08297	TowerDebias: A Novel Debiasing Method based on the Tower Property	Decision-making processes have increasingly come to rely on sophisticated machine learning tools, raising concerns about the fairness of their predictions with respect to any sensitive groups. The widespread use of commercial black-box machine learning models necessitates careful consideration of their legal and ethica...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	507,837
2403.12399	Dynamic Gradient Influencing for Viral Marketing Using Graph Neural Networks	The problem of maximizing the adoption of a product through viral marketing in social networks has been studied heavily through postulated network models. We present a novel data-driven formulation of the problem. We use Graph Neural Networks (GNNs) to model the adoption of products by utilizing both topological and at...	false	false	false	true	false	false	true	false	false	false	false	false	true	false	false	false	false	false	439,155
1811.08979	An Efficient Approach to Informative Feature Extraction from Multimodal Data	One primary focus in multimodal feature extraction is to find the representations of individual modalities that are maximally correlated. As a well-known measure of dependence, the Hirschfeld-Gebelein-R\'{e}nyi (HGR) maximal correlation becomes an appealing objective because of its operational meaning and desirable pro...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	114,162
2109.06638	Learnable Discrete Wavelet Pooling (LDW-Pooling) For Convolutional Networks	Pooling is a simple but essential layer in modern deep CNN architectures for feature aggregation and extraction. Typical CNN design focuses on the conv layers and activation functions, while leaving the pooling layers with fewer options. We introduce the Learning Discrete Wavelet Pooling (LDW-Pooling) that can be appli...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	255,223
2403.12997	A Multi-Task Oriented Semantic Communication Framework for Autonomous Vehicles	Task-oriented semantic communication is an emerging technology that transmits only the relevant semantics of a message instead of the whole message to achieve a specific task. It reduces latency, compresses the data, and is more robust in low SNR scenarios. This work presents a multi-task-oriented semantic communicatio...	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	true	439,431
2310.07940	Cost-Driven Hardware-Software Co-Optimization of Machine Learning Pipelines	Researchers have long touted a vision of the future enabled by a proliferation of internet-of-things devices, including smart sensors, homes, and cities. Increasingly, embedding intelligence in such devices involves the use of deep neural networks. However, their storage and processing requirements make them prohibitiv...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	399,189
2203.08921	Hybrid Pixel-Unshuffled Network for Lightweight Image Super-Resolution	Convolutional neural network (CNN) has achieved great success on image super-resolution (SR). However, most deep CNN-based SR models take massive computations to obtain high performance. Downsampling features for multi-resolution fusion is an efficient and effective way to improve the performance of visual recognition....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	285,950
2203.05301	Double Constacyclic Codes over Two Finite Commutative Chain Rings	Many kinds of codes which possess two cycle structures over two special finite commutative chain rings, such as ${\Bbb Z}_2{\Bbb Z}_4$-additive cyclic codes and quasi-cyclic codes of fractional index etc., were proved asymptotically good. In this paper we extend the study in two directions: we consider any two finite c...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	284,767
2107.11810	Efficient Large Scale Inlier Voting for Geometric Vision Problems	Outlier rejection and equivalently inlier set optimization is a key ingredient in numerous applications in computer vision such as filtering point-matches in camera pose estimation or plane and normal estimation in point clouds. Several approaches exist, yet at large scale we face a combinatorial explosion of possible ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	247,704
2306.11341	MSVD-Indonesian: A Benchmark for Multimodal Video-Text Tasks in Indonesian	Multimodal learning on video and text data has been receiving growing attention from many researchers in various research tasks, including text-to-video retrieval, video-to-text retrieval, and video captioning. Although many algorithms have been proposed for those challenging tasks, most of them are developed on Englis...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	true	374,562
2003.13865	COVID-CT-Dataset: A CT Scan Dataset about COVID-19	During the outbreak time of COVID-19, computed tomography (CT) is a useful manner for diagnosing COVID-19 patients. Due to privacy issues, publicly available COVID-19 CT datasets are highly difficult to obtain, which hinders the research and development of AI-powered diagnosis methods of COVID-19 based on CTs. To addre...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	170,330
1907.02209	Earthquake Prediction With Artificial Neural Network Method: The Application Of West Anatolian Fault In Turkey	A method that exactly knows the earthquakes beforehand and can generalize them cannot still been developed. However, earthquakes are tried to be predicted through numerous methods. One of these methods, artificial neural networks give appropriate outputs to different patterns by learning the relationship between the de...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	137,558
2403.15675	An active learning model to classify animal species in Hong Kong	Camera traps are used by ecologists globally as an efficient and non-invasive method to monitor animals. While it is time-consuming to manually label the collected images, recent advances in deep learning and computer vision has made it possible to automating this process [1]. A major obstacle to this is the generalisa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	440,686
2206.09348	Nested bandits	In many online decision processes, the optimizing agent is called to choose between large numbers of alternatives with many inherent similarities; in turn, these similarities imply closely correlated losses that may confound standard discrete choice models and bandit algorithms. We study this question in the context of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	303,531
1308.6373	Special Bent and Near-bent Functions	Starting from special near-bent functions in dimension 2t-1 we construct bent functions in dimension 2t having a specific derivative. We deduce new famillies of bent functions	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	26,710
2312.10308	Event-Based Contrastive Learning for Medical Time Series	In clinical practice, one often needs to identify whether a patient is at high risk of adverse outcomes after some key medical event. For example, quantifying the risk of adverse outcomes after an acute cardiovascular event helps healthcare providers identify those patients at the highest risk of poor outcomes; i.e., p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	416,103
1907.06010	The Futility of Bias-Free Learning and Search	Building on the view of machine learning as search, we demonstrate the necessity of bias in learning, quantifying the role of bias (measured relative to a collection of possible datasets, or more generally, information resources) in increasing the probability of success. For a given degree of bias towards a fixed targe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	138,498
1906.02420	Zorro: A Model Agnostic System to Price Consumer Data	Personal data is essential in showing users targeted ads - the economic backbone of the web. Still, there are major inefficiencies in how data is transacted online: (1) users don't decide what information is released nor get paid for this privacy loss; (2) algorithmic advertisers are stuck in inefficient long-term cont...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	134,048
2410.07635	Shift and matching queries for video semantic segmentation	Video segmentation is a popular task, but applying image segmentation models frame-by-frame to videos does not preserve temporal consistency. In this paper, we propose a method to extend a query-based image segmentation model to video using feature shift and query matching. The method uses a query-based architecture, w...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	496,723
2102.09039	Spacewalker: Rapid UI Design Exploration Using Lightweight Markup Enhancement and Crowd Genetic Programming	User interface design is a complex task that involves designers examining a wide range of options. We present Spacewalker, a tool that allows designers to rapidly search a large design space for an optimal web UI with integrated support. Designers first annotate each attribute they want to explore in a typical HTML pag...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	220,651
2410.21194	SoS Certifiability of Subgaussian Distributions and its Algorithmic Applications	We prove that there is a universal constant $C>0$ so that for every $d \in \mathbb N$, every centered subgaussian distribution $\mathcal D$ on $\mathbb R^d$, and every even $p \in \mathbb N$, the $d$-variate polynomial $(Cp)^{p/2} \cdot \\|v\\|_{2}^p - \mathbb E_{X \sim \mathcal D} \langle v,X\rangle^p$ is a sum of squar...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	503,124
2105.03279	Generating abstractive summaries of Lithuanian news articles using a transformer model	In this work, we train the first monolingual Lithuanian transformer model on a relatively large corpus of Lithuanian news articles and compare various output decoding algorithms for abstractive news summarization. We achieve an average ROUGE-2 score 0.163, generated summaries are coherent and look impressive at first g...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	234,099
2311.03989	Learned Causal Method Prediction	For a given causal question, it is important to efficiently decide which causal inference method to use for a given dataset. This is challenging because causal methods typically rely on complex and difficult-to-verify assumptions, and cross-validation is not applicable since ground truth causal quantities are unobserve...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	406,058
2106.05886	Group Equivariant Subsampling	Subsampling is used in convolutional neural networks (CNNs) in the form of pooling or strided convolutions, to reduce the spatial dimensions of feature maps and to allow the receptive fields to grow exponentially with depth. However, it is known that such subsampling operations are not translation equivariant, unlike c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	240,269
2007.05411	AGI Agent Safety by Iteratively Improving the Utility Function	While it is still unclear if agents with Artificial General Intelligence (AGI) could ever be built, we can already use mathematical models to investigate potential safety systems for these agents. We present an AGI safety layer that creates a special dedicated input terminal to support the iterative improvement of an A...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	186,668
1103.5110	Formation of Modularity in a Model of Evolving Networks	Modularity structures are common in various social and biological networks. However, its dynamical origin remains an open question. In this work, we set up a dynamical model describing the evolution of a social network. Based on the observations of real social networks, we introduced a link-creating/deleting strategy a...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	9,764
1404.2343	Wireless Transmission of Video for Biomechanical Analysis	When there is a possibility to wirelessly stream video over a network, a sophisticated computer analysis of the transmitted video is possible. Such process is used in biomechanics when it is important to analyze athletes performance via streaming digital uncompressed video to a computer and then analyzing it using spec...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	32,206
2304.00381	On the Sample Complexity of the Linear Quadratic Gaussian Regulator	In this paper we provide direct data-driven expressions for the Linear Quadratic Regulator (LQR), the Kalman filter, and the Linear Quadratic Gaussian (LQG) controller using a finite dataset of noisy input, state, and output trajectories. We show that our data-driven expressions are consistent, since they converge as t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	355,662
2107.07707	Probabilistic Appearance-Invariant Topometric Localization with New Place Awareness	Probabilistic state-estimation approaches offer a principled foundation for designing localization systems, because they naturally integrate sequences of imperfect motion and exteroceptive sensor data. Recently, probabilistic localization systems utilizing appearance-invariant visual place recognition (VPR) methods as ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	246,501
2309.09039	Microscale 3-D Capacitance Tomography with a CMOS Sensor Array	Electrical capacitance tomography (ECT) is a nonoptical imaging technique in which a map of the interior permittivity of a volume is estimated by making capacitance measurements at its boundary and solving an inverse problem. While previous ECT demonstrations have often been at centimeter scales, ECT is not limited to ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	392,445
2110.05196	Learning and Dynamical Models for Sub-seasonal Climate Forecasting: Comparison and Collaboration	Sub-seasonal climate forecasting (SSF) is the prediction of key climate variables such as temperature and precipitation on the 2-week to 2-month time horizon. Skillful SSF would have substantial societal value in areas such as agricultural productivity, hydrology and water resource management, and emergency planning fo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	260,199
2109.05300	On syntactically similar logic programs and sequential decompositions	Rule-based reasoning is an essential part of human intelligence prominently formalized in artificial intelligence research via logic programs. Describing complex objects as the composition of elementary ones is a common strategy in computer science and science in general. The author has recently introduced the sequenti...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	254,740
1301.5083	Improved Asymptotic Key Rate of the B92 Protocol	We analyze the asymptotic key rate of the single photon B92 protocol by using Renner's security analysis given in 2005. The new analysis shows that the B92 protocol can securely generate key at 6.5% depolarizing rate, while the previous analyses cannot guarantee the secure key generation at 4.2% depolarizing rate.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	21,310
2411.08759	Clutter-Aware Target Detection for ISAC in a Millimeter-Wave Cell-Free Massive MIMO System	In this paper, we investigate the performance of an integrated sensing and communication (ISAC) system within a cell-free massive multiple-input multiple-output (MIMO) system. Each access point (AP) operates in the millimeter-wave (mmWave) frequency band. The APs jointly serve the user equipments (UEs) in the downlink ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	508,007
2106.00196	All-Hex Meshing Strategies For Densely Packed Spheres	We develop an all-hex meshing strategy for the interstitial space in beds of densely packed spheres that is tailored to turbulent flow simulations based on the spectral element method (SEM). The SEM achieves resolution through elevated polynomial order N and requires two to three orders of magnitude fewer elements than...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	238,026
1609.00661	Localization by Fusing a Group of Fingerprints via Multiple Antennas in Indoor Environment	Most existing fingerprints-based indoor localization approaches are based on some single fingerprints, such as received signal strength (RSS), channel impulse response (CIR), and signal subspace. However, the localization accuracy obtained by the single fingerprint approach is rather susceptible to the changing environ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	60,503
1907.09285	ParaFIS:A new online fuzzy inference system based on parallel drift anticipation	This paper proposes a new architecture of incremen-tal fuzzy inference system (also called Evolving Fuzzy System-EFS). In the context of classifying data stream in non stationary environment, concept drifts problems must be addressed. Several studies have shown that EFS can deal with such environment thanks to their hi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	139,322
2407.09519	Putting GPT-4o to the Sword: A Comprehensive Evaluation of Language, Vision, Speech, and Multimodal Proficiency	As large language models (LLMs) continue to advance, evaluating their comprehensive capabilities becomes significant for their application in various fields. This research study comprehensively evaluates the language, vision, speech, and multimodal capabilities of GPT-4o. The study employs standardized exam questions, ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	472,612
2402.16837	Do Large Language Models Latently Perform Multi-Hop Reasoning?	We study whether Large Language Models (LLMs) latently perform multi-hop reasoning with complex prompts such as "The mother of the singer of 'Superstition' is". We look for evidence of a latent reasoning pathway where an LLM (1) latently identifies "the singer of 'Superstition'" as Stevie Wonder, the bridge entity, and...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	432,718
2202.10659	ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Multi-Task Learning Challenges	This paper describes the third Affective Behavior Analysis in-the-wild (ABAW) Competition, held in conjunction with IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2022. The 3rd ABAW Competition is a continuation of the Competitions held at ICCV 2021, IEEE FG 2020 and IEEE CVPR 2017 Con...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	281,609
2006.10281	Variance Reduction via Accelerated Dual Averaging for Finite-Sum Optimization	In this paper, we introduce a simplified and unified method for finite-sum convex optimization, named \emph{Variance Reduction via Accelerated Dual Averaging (VRADA)}. In both general convex and strongly convex settings, VRADA can attain an $O\big(\frac{1}{n}\big)$-accurate solution in $O(n\log\log n)$ number of stocha...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	182,833
2004.00292	Evaluation of Model Selection for Kernel Fragment Recognition in Corn Silage	Model selection when designing deep learning systems for specific use-cases can be a challenging task as many options exist and it can be difficult to know the trade-off between them. Therefore, we investigate a number of state of the art CNN models for the task of measuring kernel fragmentation in harvested corn silag...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	170,585
1708.03704	Deep Incremental Boosting	This paper introduces Deep Incremental Boosting, a new technique derived from AdaBoost, specifically adapted to work with Deep Learning methods, that reduces the required training time and improves generalisation. We draw inspiration from Transfer of Learning approaches to reduce the start-up time to training each incr...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	78,807
2004.02988	Probabilistic Diagnostic Tests for Degradation Problems in Supervised Learning	Several studies point out different causes of performance degradation in supervised machine learning. Problems such as class imbalance, overlapping, small-disjuncts, noisy labels, and sparseness limit accuracy in classification algorithms. Even though a number of approaches either in the form of a methodology or an alg...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	171,398
2311.16707	Full-resolution MLPs Empower Medical Dense Prediction	Dense prediction is a fundamental requirement for many medical vision tasks such as medical image restoration, registration, and segmentation. The most popular vision model, Convolutional Neural Networks (CNNs), has reached bottlenecks due to the intrinsic locality of convolution operations. Recently, transformers have...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	411,022
2204.10018	Path-Specific Objectives for Safer Agent Incentives	We present a general framework for training safe agents whose naive incentives are unsafe. As an example, manipulative or deceptive behaviour can improve rewards but should be avoided. Most approaches fail here: agents maximize expected return by any means necessary. We formally describe settings with 'delicate' parts ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	292,640
2107.13957	Towards Semantic Interoperability in Historical Research: Documenting Research Data and Knowledge with Synthesis	A vast area of research in historical science concerns the documentation and study of artefacts and related evidence. Current practice mostly uses spreadsheets or simple relational databases to organise the information as rows with multiple columns of related attributes. This form offers itself for data analysis and sc...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	248,339
1908.07491	Controversy in Context	With the growing interest in social applications of Natural Language Processing and Computational Argumentation, a natural question is how controversial a given concept is. Prior works relied on Wikipedia's metadata and on content analysis of the articles pertaining to a concept in question. Here we show that the immed...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	142,305
2305.09901	On the Difficulty of Intersection Checking with Polynomial Zonotopes	Polynomial zonotopes, a non-convex set representation, have a wide range of applications from real-time motion planning and control in robotics, to reachability analysis of nonlinear systems and safety shielding in reinforcement learning. Despite this widespread use, a frequently overlooked difficulty associated with p...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	364,821
2008.06599	Wikidata on MARS	Multi-attributed relational structures (MARSs) have been proposed as a formal data model for generalized property graphs, along with multi-attributed rule-based predicate logic (MARPL) as a useful rule-based logic in which to write inference rules over property graphs. Wikidata can be modelled in an extended MARS that ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	191,835
2212.07144	Uncertain Facial Expression Recognition via Multi-task Assisted Correction	Deep models for facial expression recognition achieve high performance by training on large-scale labeled data. However, publicly available datasets contain uncertain facial expressions caused by ambiguous annotations or confusing emotions, which could severely decline the robustness. Previous studies usually follow th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	336,318
1908.06134	Online Feature Selection for Activity Recognition using Reinforcement Learning with Multiple Feedback	Recent advances in both machine learning and Internet-of-Things have attracted attention to automatic Activity Recognition, where users wear a device with sensors and their outputs are mapped to a predefined set of activities. However, few studies have considered the balance between wearable power consumption and activ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	141,916
1109.4668	Robust estimation of latent tree graphical models: Inferring hidden states with inexact parameters	Latent tree graphical models are widely used in computational biology, signal and image processing, and network tomography. Here we design a new efficient, estimation procedure for latent tree models, including Gaussian and discrete, reversible models, that significantly improves on previous sample requirement bounds. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	12,268
2401.17711	Prediction of multitasking performance post-longitudinal tDCS via EEG-based functional connectivity and machine learning methods	Predicting and understanding the changes in cognitive performance, especially after a longitudinal intervention, is a fundamental goal in neuroscience. Longitudinal brain stimulation-based interventions like transcranial direct current stimulation (tDCS) induce short-term changes in the resting membrane potential and i...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	425,294
1512.06992	On the Differential Privacy of Bayesian Inference	We study how to communicate findings of Bayesian inference to third parties, while preserving the strong guarantee of differential privacy. Our main contributions are four different algorithms for private Bayesian inference on proba-bilistic graphical models. These include two mechanisms for adding noise to the Bayesia...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	50,375
2406.06578	SMS Spam Detection and Classification to Combat Abuse in Telephone Networks Using Natural Language Processing	In the modern era, mobile phones have become ubiquitous, and Short Message Service (SMS) has grown to become a multi-million-dollar service due to the widespread adoption of mobile devices and the millions of people who use SMS daily. However, SMS spam has also become a pervasive problem that endangers users' privacy a...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	462,661
1804.06733	NHAD: Neuro-Fuzzy Based Horizontal Anomaly Detection In Online Social Networks	Use of social network is the basic functionality of today's life. With the advent of more and more online social media, the information available and its utilization have come under the threat of several anomalies. Anomalies are the major cause of online frauds which allow information access by unauthorized users as we...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	95,369
1101.1920	Superposition Coding-Based Bounds and Capacity for the Cognitive Z-Interference Channels	This paper considers the cognitive interference channel (CIC) with two transmitters and two receivers, in which the cognitive transmitter non-causally knows the message and codeword of the primary transmitter. We first introduce a discrete memoryless more capable CIC, which is an extension to the more capable broadcast...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	8,769
2102.09382	Recommending Training Set Sizes for Classification	Based on a comprehensive study of 20 established data sets, we recommend training set sizes for any classification data set. We obtain our recommendations by systematically withholding training data and developing models through five different classification methods for each resulting training set. Based on these resul...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	220,758

Subsets and Splits

No community queries yet

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