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
2008.13278	On a plausible concept-wise multipreference semantics and its relations with self-organising maps	Inthispaperwedescribeaconcept-wisemulti-preferencesemantics for description logic which has its root in the preferential approach for modeling defeasible reasoning in knowledge representation. We argue that this proposal, beside satisfying some desired properties, such as KLM postulates, and avoiding the drowning probl...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	193,808
2011.07833	Data-driven stabilization of nonlinear polynomial systems with noisy data	In a recent paper we have shown how to learn controllers for unknown linear systems using finite-sized noisy data by solving linear matrix inequalities. In this note we extend this approach to deal with unknown nonlinear polynomial systems by formulating stability certificates in the form of data-dependent sum of squar...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	206,691
0807.4478	An Image-Based Sensor System for Autonomous Rendez-Vous with Uncooperative Satellites	In this paper are described the image processing algorithms developed by SENER, Ingenieria y Sistemas to cope with the problem of image-based, autonomous rendez-vous (RV) with an orbiting satellite. The methods developed have a direct application in the OLEV (Orbital Life Extension Extension Vehicle) mission. OLEV is a...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	2,127
2404.09308	In My Perspective, In My Hands: Accurate Egocentric 2D Hand Pose and Action Recognition	Action recognition is essential for egocentric video understanding, allowing automatic and continuous monitoring of Activities of Daily Living (ADLs) without user effort. Existing literature focuses on 3D hand pose input, which requires computationally intensive depth estimation networks or wearing an uncomfortable dep...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	446,620
1804.07790	A Mixed Hierarchical Attention based Encoder-Decoder Approach for Standard Table Summarization	Structured data summarization involves generation of natural language summaries from structured input data. In this work, we consider summarizing structured data occurring in the form of tables as they are prevalent across a wide variety of domains. We formulate the standard table summarization problem, which deals wit...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	95,597
2408.03790	Vision-Language Guidance for LiDAR-based Unsupervised 3D Object Detection	Accurate 3D object detection in LiDAR point clouds is crucial for autonomous driving systems. To achieve state-of-the-art performance, the supervised training of detectors requires large amounts of human-annotated data, which is expensive to obtain and restricted to predefined object categories. To mitigate manual labe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	479,150
2404.13909	Physics-informed neural networks with curriculum training for poroelastic flow and deformation processes	Physics-Informed Neural Networks (PINNs) have emerged as a highly active research topic across multiple disciplines in science and engineering, including computational geomechanics. PINNs offer a promising approach in different applications where faster, near real-time or real-time numerical prediction is required. Exa...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	448,496
2305.17280	Improved Instruction Ordering in Recipe-Grounded Conversation	In this paper, we study the task of instructional dialogue and focus on the cooking domain. Analyzing the generated output of the GPT-J model, we reveal that the primary challenge for a recipe-grounded dialog system is how to provide the instructions in the correct order. We hypothesize that this is due to the model's ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	368,499
2005.13857	Deep Reinforcement learning for real autonomous mobile robot navigation in indoor environments	Deep Reinforcement Learning has been successfully applied in various computer games [8]. However, it is still rarely used in real-world applications, especially for the navigation and continuous control of real mobile robots [13]. Previous approaches lack safety and robustness and/or need a structured environment. In t...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	179,121
2104.11557	Knodle: Modular Weakly Supervised Learning with PyTorch	Strategies for improving the training and prediction quality of weakly supervised machine learning models vary in how much they are tailored to a specific task or integrated with a specific model architecture. In this work, we introduce Knodle, a software framework that treats weak data annotations, deep learning model...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	231,948
2501.12215	Automatic selection of the best neural architecture for time series forecasting via multi-objective optimization and Pareto optimality conditions	Time series forecasting plays a pivotal role in a wide range of applications, including weather prediction, healthcare, structural health monitoring, predictive maintenance, energy systems, and financial markets. While models such as LSTM, GRU, Transformers, and State-Space Models (SSMs) have become standard tools in t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	526,210
1907.07962	Interactional and Informational Attention on Twitter	Twitter may be considered as a decentralized social information processing platform whose users constantly receive their followees' information feeds, which they may in turn dispatch to their followers. This decentralization is not devoid of hierarchy and heterogeneity, both in terms of activity and attention. In parti...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	139,006
1711.00793	3D Mobile Localization Using Distance-only Measurements	For a group of cooperating UAVs, localizing each other is often a key task. This paper studies the localization problem for a group of UAVs flying in 3D space with very limited information, i.e., when noisy distance measurements are the only type of inter-agent sensing that is available, and when only one UAV knows a g...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	83,780
2007.11684	Approximation Benefits of Policy Gradient Methods with Aggregated States	Folklore suggests that policy gradient can be more robust to misspecification than its relative, approximate policy iteration. This paper studies the case of state-aggregated representations, where the state space is partitioned and either the policy or value function approximation is held constant over partitions. Thi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	188,603
2009.09609	Weakly Supervised Learning of Nuanced Frames for Analyzing Polarization in News Media	In this paper we suggest a minimally-supervised approach for identifying nuanced frames in news article coverage of politically divisive topics. We suggest to break the broad policy frames suggested by Boydstun et al., 2014 into fine-grained subframes which can capture differences in political ideology in a better way....	false	false	false	false	true	false	true	false	true	false	false	false	false	true	false	false	false	false	196,636
2305.17449	FishEye8K: A Benchmark and Dataset for Fisheye Camera Object Detection	With the advance of AI, road object detection has been a prominent topic in computer vision, mostly using perspective cameras. Fisheye lens provides omnidirectional wide coverage for using fewer cameras to monitor road intersections, however with view distortions. To our knowledge, there is no existing open dataset pre...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	368,599
2103.10550	Gender and Racial Fairness in Depression Research using Social Media	Multiple studies have demonstrated that behavior on internet-based social media platforms can be indicative of an individual's mental health status. The widespread availability of such data has spurred interest in mental health research from a computational lens. While previous research has raised concerns about possib...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	225,490
2501.13935	Low rank matrix completion and realization of graphs: results and problems	The Netflix problem (from machine learning) asks the following. Given a ratings matrix in which each entry $(i,j)$ represents the rating of movie $j$ by customer $i$, if customer $i$ has watched movie $j$, and is otherwise missing, we would like to predict the remaining entries in order to make good recommendations to ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	526,885
2407.11741	Puppeteer Your Robot: Augmented Reality Leader-Follower Teleoperation	High-quality demonstrations are necessary when learning complex and challenging manipulation tasks. In this work, we introduce an approach to puppeteer a robot by controlling a virtual robot in an augmented reality setting. Our system allows for retaining the advantages of being intuitive from a physical leader-followe...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	473,596
2412.07393	CMT: A Memory Compression Method for Continual Knowledge Learning of Large Language Models	Large Language Models (LLMs) need to adapt to the continuous changes in data, tasks, and user preferences. Due to their massive size and the high costs associated with training, LLMs are not suitable for frequent retraining. However, updates are necessary to keep them in sync with rapidly evolving human knowledge. To a...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	515,650
2102.10607	Improved Semantic Segmentation of Tuberculosis-consistent findings in Chest X-rays Using Augmented Training of Modality-specific U-Net Models with Weak Localizations	Deep learning (DL) has drawn tremendous attention in object localization and recognition for both natural and medical images. U-Net segmentation models have demonstrated superior performance compared to conventional handcrafted feature-based methods. Medical image modality-specific DL models are better at transferring ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	221,157
2007.11742	Engineering Reliable Interactions in the Reality-Artificiality Continuum	Milgram's reality-virtuality continuum applies to interaction in the physical space dimension, going from real to virtual. However, interaction has a social dimension as well, that can go from real to artificial depending on the companion with whom the user interacts. In this paper we present our vision of the Reality-...	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	188,622
2411.19149	Counting Stacked Objects from Multi-View Images	Visual object counting is a fundamental computer vision task underpinning numerous real-world applications, from cell counting in biomedicine to traffic and wildlife monitoring. However, existing methods struggle to handle the challenge of stacked 3D objects in which most objects are hidden by those above them. To addr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	512,142
2406.09694	An Efficient Approach to Regression Problems with Tensor Neural Networks	This paper introduces a tensor neural network (TNN) to address nonparametric regression problems, leveraging its distinct sub-network structure to effectively facilitate variable separation and enhance the approximation of complex, high-dimensional functions. The TNN demonstrates superior performance compared to conven...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	464,042
1811.00753	Risk-Stratify: Confident Stratification Of Patients Based On Risk	A clinician desires to use a risk-stratification method that achieves confident risk-stratification - the risk estimates of the different patients reflect the true risks with a high probability. This allows him/her to use these risks to make accurate predictions about prognosis and decisions about screening, treatments...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	112,188
2112.03643	QKSA: Quantum Knowledge Seeking Agent -- resource-optimized reinforcement learning using quantum process tomography	In this research, we extend the universal reinforcement learning (URL) agent models of artificial general intelligence to quantum environments. The utility function of a classical exploratory stochastic Knowledge Seeking Agent, KL-KSA, is generalized to distance measures from quantum information theory on density matri...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	270,290
2010.09577	GANs for learning from very high class conditional noisy labels	We use Generative Adversarial Networks (GANs) to design a class conditional label noise (CCN) robust scheme for binary classification. It first generates a set of correctly labelled data points from noisy labelled data and 0.1% or 1% clean labels such that the generated and true (clean) labelled data distributions are ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	201,599
2002.04862	Convex Density Constraints for Computing Plausible Counterfactual Explanations	The increasing deployment of machine learning as well as legal regulations such as EU's GDPR cause a need for user-friendly explanations of decisions proposed by machine learning models. Counterfactual explanations are considered as one of the most popular techniques to explain a specific decision of a model. While the...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	163,726
2406.09401	MMScan: A Multi-Modal 3D Scene Dataset with Hierarchical Grounded Language Annotations	With the emergence of LLMs and their integration with other data modalities, multi-modal 3D perception attracts more attention due to its connectivity to the physical world and makes rapid progress. However, limited by existing datasets, previous works mainly focus on understanding object properties or inter-object spa...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	463,920
2212.02721	A Novel Deep Reinforcement Learning Based Automated Stock Trading System Using Cascaded LSTM Networks	More and more stock trading strategies are constructed using deep reinforcement learning (DRL) algorithms, but DRL methods originally widely used in the gaming community are not directly adaptable to financial data with low signal-to-noise ratios and unevenness, and thus suffer from performance shortcomings. In this pa...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	334,858
2409.05295	Adaptive Visual Servoing for On-Orbit Servicing	This paper presents an adaptive visual servoing framework for robotic on-orbit servicing (OOS), specifically designed for capturing tumbling satellites. The vision-guided robotic system is capable of selecting optimal control actions in the event of partial or complete vision system failure, particularly in the short t...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	486,715
2211.11752	RHCO: A Relation-aware Heterogeneous Graph Neural Network with Contrastive Learning for Large-scale Graphs	Heterogeneous graph neural networks (HGNNs) have been widely applied in heterogeneous information network tasks, while most HGNNs suffer from poor scalability or weak representation when they are applied to large-scale heterogeneous graphs. To address these problems, we propose a novel Relation-aware Heterogeneous Grap...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	331,864
2202.12530	Banyan: A Scoped Dataflow Engine for Graph Query Service	Graph query services (GQS) are widely used today to interactively answer graph traversal queries on large-scale graph data. Existing graph query engines focus largely on optimizing the latency of a single query. This ignores significant challenges posed by GQS, including fine-grained control and scheduling during query...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	282,278
2205.04765	Hybrid RIS and DMA Assisted Multiuser MIMO Uplink Transmission With Electromagnetic Exposure Constraints	In the fifth-generation and beyond era, reconfigurable intelligent surface (RIS) and dynamic metasurface antennas (DMAs) are emerging metamaterials keeping up with the demand for high-quality wireless communication services, which promote the diversification of portable wireless terminals. However, along with the rapid...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	295,746
2207.02162	Tackling Real-World Autonomous Driving using Deep Reinforcement Learning	In the typical autonomous driving stack, planning and control systems represent two of the most crucial components in which data retrieved by sensors and processed by perception algorithms are used to implement a safe and comfortable self-driving behavior. In particular, the planning module predicts the path the autono...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	306,422
2005.04022	On the Effect of Learned Clauses on Stochastic Local Search	There are two competing paradigms in successful SAT solvers: Conflict-driven clause learning (CDCL) and stochastic local search (SLS). CDCL uses systematic exploration of the search space and has the ability to learn new clauses. SLS examines the neighborhood of the current complete assignment. Unlike CDCL, it lacks th...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	176,333
2004.13470	FU-net: Multi-class Image Segmentation Using Feedback Weighted U-net	In this paper, we present a generic deep convolutional neural network (DCNN) for multi-class image segmentation. It is based on a well-established supervised end-to-end DCNN model, known as U-net. U-net is firstly modified by adding widely used batch normalization and residual block (named as BRU-net) to improve the ef...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	174,561
2109.15044	SPATE-GAN: Improved Generative Modeling of Dynamic Spatio-Temporal Patterns with an Autoregressive Embedding Loss	From ecology to atmospheric sciences, many academic disciplines deal with data characterized by intricate spatio-temporal complexities, the modeling of which often requires specialized approaches. Generative models of these data are of particular interest, as they enable a range of impactful downstream applications lik...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	258,153
2206.04328	Novel projection schemes for graph-based Light Field coding	In Light Field compression, graph-based coding is powerful to exploit signal redundancy along irregular shapes and obtains good energy compaction. However, apart from high time complexity to process high dimensional graphs, their graph construction method is highly sensitive to the accuracy of disparity information bet...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	301,586
2404.08662	FewUser: Few-Shot Social User Geolocation via Contrastive Learning	To address the challenges of scarcity in geotagged data for social user geolocation, we propose FewUser, a novel framework for Few-shot social User geolocation. We incorporate a contrastive learning strategy between users and locations to improve geolocation performance with no or limited training data. FewUser feature...	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	false	446,330
2310.07652	LLM4Vis: Explainable Visualization Recommendation using ChatGPT	Data visualization is a powerful tool for exploring and communicating insights in various domains. To automate visualization choice for datasets, a task known as visualization recommendation has been proposed. Various machine-learning-based approaches have been developed for this purpose, but they often require a large...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	399,056
2110.13188	Simultaneous Perturbation Method for Multi-Task Weight Optimization in One-Shot Meta-Learning	Meta-learning methods aim to build learning algorithms capable of quickly adapting to new tasks in low-data regime. One of the most difficult benchmarks of such algorithms is a one-shot learning problem. In this setting many algorithms face uncertainties associated with limited amount of training samples, which may res...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	263,088
2410.01085	RoTip: A Finger-Shaped Tactile Sensor with Active Rotation Capability	In recent years, advancements in optical tactile sensor technology have primarily centred on enhancing sensing precision and expanding the range of sensing modalities. To meet the requirements for more skilful manipulation, there should be a movement towards making tactile sensors more dynamic. In this paper, we introd...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	493,599
2412.02823	Minimization of Boolean Complexity in In-Context Concept Learning	What factors contribute to the relative success and corresponding difficulties of in-context learning for Large Language Models (LLMs)? Drawing on insights from the literature on human concept learning, we test LLMs on carefully designed concept learning tasks, and show that task performance highly correlates with the ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	513,693
2501.11762	Disentangling stellar atmospheric parameters in astronomical spectra using Generative Adversarial Neural Networks	A method based on Generative Adversaria! Networks (GANs) is developed for disentangling the physical (effective temperature and gravity) and chemical (metallicity, overabundance of a-elements with respect to iron) atmospheric properties in astronomical spectra. Using a projection of the stellar spectra, commonly called...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	526,030
1602.05705	A theory of contemplation	In this paper you can explore the application of some notable Boolean-derived methods, namely the Disjunctive Normal Form representation of logic table expansions, and extend them to a real-valued logic model which is able to utilize quantities on the range [0,1], [-1,1], [a,b], (x,y), (x,y,z), and etc. so as to produc...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	52,287
2208.09632	Adam Can Converge Without Any Modification On Update Rules	Ever since Reddi et al. 2018 pointed out the divergence issue of Adam, many new variants have been designed to obtain convergence. However, vanilla Adam remains exceptionally popular and it works well in practice. Why is there a gap between theory and practice? We point out there is a mismatch between the settings of t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	313,772
2211.03052	Confidence Intervals for Unobserved Events	Consider a finite sample from an unknown distribution over a countable alphabet. Unobserved events are alphabet symbols which do not appear in the sample. Estimating the probabilities of unobserved events is a basic problem in statistics and related fields, which was extensively studied in the context of point estimati...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	328,812
2408.09177	Chinese Metaphor Recognition Using a Multi-stage Prompting Large Language Model	Metaphors are common in everyday language, and the identification and understanding of metaphors are facilitated by models to achieve a better understanding of the text. Metaphors are mainly identified and generated by pre-trained models in existing research, but situations, where tenors or vehicles are not included in...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	481,318
2312.09207	WikiMuTe: A web-sourced dataset of semantic descriptions for music audio	Multi-modal deep learning techniques for matching free-form text with music have shown promising results in the field of Music Information Retrieval (MIR). Prior work is often based on large proprietary data while publicly available datasets are few and small in size. In this study, we present WikiMuTe, a new and open ...	false	false	true	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	415,631
1012.3853	On the CNF encoding of cardinality constraints and beyond	In this report, we propose a quick survey of the currently known techniques for encoding a Boolean cardinality constraint into a CNF formula, and we discuss about the relevance of these encodings. We also propose models to facilitate analysis and design of CNF encodings for Boolean constraints.	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	8,573
2206.11124	A view of mini-batch SGD via generating functions: conditions of convergence, phase transitions, benefit from negative momenta	Mini-batch SGD with momentum is a fundamental algorithm for learning large predictive models. In this paper we develop a new analytic framework to analyze noise-averaged properties of mini-batch SGD for linear models at constant learning rates, momenta and sizes of batches. Our key idea is to consider the dynamics of t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	304,164
1604.04137	Autonomous Scanning for Endomicroscopic Mosaicing and 3D Fusion	Robotic-assisted Minimally Invasive Surgery (RMIS) can benefit from the automation of common, repetitive or well-defined but ergonomically difficult tasks. One such task is the scanning of a pick-up endomicroscopy probe over a complex, undulating tissue surface in order to enhance the effective field-of-view through vi...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	54,598
1909.10120	Field typing for improved recognition on heterogeneous handwritten forms	Offline handwriting recognition has undergone continuous progress over the past decades. However, existing methods are typically benchmarked on free-form text datasets that are biased towards good-quality images and handwriting styles, and homogeneous content. In this paper, we show that state-of-the-art algorithms, em...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	146,451
2302.12769	Probabilistic maps on bistable vibration energy harvesters	This paper analyzes the impact of parametric uncertainties on the dynamics of bistable energy harvesters, focusing on obtaining statistical information about how each parameter's variability affects the energy harvesting process. To model the parametric uncertainties, we use a probability distribution derived from the ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	347,688
2310.09739	AugUndo: Scaling Up Augmentations for Monocular Depth Completion and Estimation	Unsupervised depth completion and estimation methods are trained by minimizing reconstruction error. Block artifacts from resampling, intensity saturation, and occlusions are amongst the many undesirable by-products of common data augmentation schemes that affect image reconstruction quality, and thus the training sign...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	399,920
1904.08495	An Unsupervised Feature Learning Approach to Reduce False Alarm Rate in ICUs	The high rate of false alarms in intensive care units (ICUs) is one of the top challenges of using medical technology in hospitals. These false alarms are often caused by patients' movements, detachment of monitoring sensors, or different sources of noise and interference that impact the collected signals from differen...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	128,081
2308.01249	A Spatially Coupled LDPC Coding Scheme with Scalable Decoders for Space Division Multiplexing	In this paper, we study the application of spatially coupled LDPC codes with sub-block locality for space division multiplexing. We focus on the information exchange between the sub-blocks and compare decoding strategies with respect to the complexity, performance and the information flow.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	383,195
1803.08661	Bayesian Optimization with Expensive Integrands	We propose a Bayesian optimization algorithm for objective functions that are sums or integrals of expensive-to-evaluate functions, allowing noisy evaluations. These objective functions arise in multi-task Bayesian optimization for tuning machine learning hyperparameters, optimization via simulation, and sequential des...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	93,312
1608.03287	Deep vs. shallow networks : An approximation theory perspective	The paper briefy reviews several recent results on hierarchical architectures for learning from examples, that may formally explain the conditions under which Deep Convolutional Neural Networks perform much better in function approximation problems than shallow, one-hidden layer architectures. The paper announces new r...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	59,658
2110.06456	Updating Street Maps using Changes Detected in Satellite Imagery	Accurately maintaining digital street maps is labor-intensive. To address this challenge, much work has studied automatically processing geospatial data sources such as GPS trajectories and satellite images to reduce the cost of maintaining digital maps. An end-to-end map update system would first process geospatial da...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	260,624
2306.05937	Robust Data-driven Prescriptiveness Optimization	The abundance of data has led to the emergence of a variety of optimization techniques that attempt to leverage available side information to provide more anticipative decisions. The wide range of methods and contexts of application have motivated the design of a universal unitless measure of performance known as the c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	372,383
1710.06471	Coded Fourier Transform	We consider the problem of computing the Fourier transform of high-dimensional vectors, distributedly over a cluster of machines consisting of a master node and multiple worker nodes, where the worker nodes can only store and process a fraction of the inputs. We show that by exploiting the algebraic structure of the Fo...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	82,774
2207.09025	Indoor Localization for Personalized Ambient Assisted Living of Multiple Users in Multi-Floor Smart Environments	This paper presents a multifunctional interdisciplinary framework that makes four scientific contributions towards the development of personalized ambient assisted living, with a specific focus to address the different and dynamic needs of the diverse aging population in the future of smart living environments. First, ...	true	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	308,762
1805.04176	A Performance Evaluation of Convolutional Neural Networks for Face Anti Spoofing	In the current era, biometric based access control is becoming more popular due to its simplicity and ease to use by the users. It reduces the manual work of identity recognition and facilitates the automatic processing. The face is one of the most important biometric visual information that can be easily captured with...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	97,186
2312.16510	Structure and Optimization of Parameters for Neural Network Controllers in Automatic Control Systems	The article outlines the methodology of structural and parametric synthesis of neural network controllers for controlling objects with limiters under incomplete information about the controlled object. Artificial neural networks are used to create controllers that are sequentially integrated into a control system with ...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	418,412
2209.10890	EPIC TTS Models: Empirical Pruning Investigations Characterizing Text-To-Speech Models	Neural models are known to be over-parameterized, and recent work has shown that sparse text-to-speech (TTS) models can outperform dense models. Although a plethora of sparse methods has been proposed for other domains, such methods have rarely been applied in TTS. In this work, we seek to answer the question: what are...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	319,006
2501.12976	LiT: Delving into a Simplified Linear Diffusion Transformer for Image Generation	In commonly used sub-quadratic complexity modules, linear attention benefits from simplicity and high parallelism, making it promising for image synthesis tasks. However, the architectural design and learning strategy for linear attention remain underexplored in this field. In this paper, we offer a suite of ready-to-u...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	526,509
2502.14807	FetalCLIP: A Visual-Language Foundation Model for Fetal Ultrasound Image Analysis	Foundation models are becoming increasingly effective in the medical domain, offering pre-trained models on large datasets that can be readily adapted for downstream tasks. Despite progress, fetal ultrasound images remain a challenging domain for foundation models due to their inherent complexity, often requiring subst...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	535,989
1012.1258	Simultaneous Sequential Detection of Multiple Interacting Faults	Single fault sequential change point problems have become important in modeling for various phenomena in large distributed systems, such as sensor networks. But such systems in many situations present multiple interacting faults. For example, individual sensors in a network may fail and detection is performed by compar...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	8,432
1901.02256	Artificial Intelligence and Machine Learning to Predict and Improve Efficiency in Manufacturing Industry	The overall equipment effectiveness (OEE) is a performance measurement metric widely used. Its calculation provides to the managers the possibility to identify the main losses that reduce the machine effectiveness and then take the necessary decisions in order to improve the situation. However, this calculation is done...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	118,160
2211.00881	Unsupervised Syntactically Controlled Paraphrase Generation with Abstract Meaning Representations	Syntactically controlled paraphrase generation has become an emerging research direction in recent years. Most existing approaches require annotated paraphrase pairs for training and are thus costly to extend to new domains. Unsupervised approaches, on the other hand, do not need paraphrase pairs but suffer from relati...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	328,035
2012.05217	Positional Encoding as Spatial Inductive Bias in GANs	SinGAN shows impressive capability in learning internal patch distribution despite its limited effective receptive field. We are interested in knowing how such a translation-invariant convolutional generator could capture the global structure with just a spatially i.i.d. input. In this work, taking SinGAN and StyleGAN2...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	210,714
2501.07423	An Investigation into Seasonal Variations in Energy Forecasting for Student Residences	This research provides an in-depth evaluation of various machine learning models for energy forecasting, focusing on the unique challenges of seasonal variations in student residential settings. The study assesses the performance of baseline models, such as LSTM and GRU, alongside state-of-the-art forecasting methods, ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	524,390
1203.5255	Post-Editing Error Correction Algorithm for Speech Recognition using Bing Spelling Suggestion	ASR short for Automatic Speech Recognition is the process of converting a spoken speech into text that can be manipulated by a computer. Although ASR has several applications, it is still erroneous and imprecise especially if used in a harsh surrounding wherein the input speech is of low quality. This paper proposes a ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	15,096
2306.00551	Enhancing Programming eTextbooks with ChatGPT Generated Counterfactual-Thinking-Inspired Questions	Digital textbooks have become an integral part of everyday learning tasks. In this work, we consider the use of digital textbooks for programming classes. Generally, students struggle with utilizing textbooks on programming to the maximum, with a possible reason being that the example programs provided as illustration ...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	370,059
2412.15209	PRIMA: Multi-Image Vision-Language Models for Reasoning Segmentation	Despite significant advancements in Large Vision-Language Models (LVLMs), existing pixel-grounding models operate on single-image settings, limiting their ability to perform detailed, fine-grained comparisons across multiple images. Conversely, current multi-image understanding models lack pixel-level grounding. Our wo...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	518,983
2311.01107	GREEMA: Proposal and Experimental Verification of Growing Robot by Eating Environmental MAterial for Landslide Disaster	In areas that are inaccessible to humans, such as the lunar surface and landslide sites, there is a need for multiple autonomous mobile robot systems that can replace human workers. In particular, at landslide sites such as river channel blockages, robots are required to remove water and sediment from the site as soon ...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	404,919
2005.04157	Hybrid 2-stage Imperialist Competitive Algorithm with Ant Colony Optimization for Solving Multi-Depot Vehicle Routing Problem	The Multi-Depot Vehicle Routing Problem (MDVRP) is a real-world model of the simplistic Vehicle Routing Problem (VRP) that considers how to satisfy multiple customer demands from numerous depots. This paper introduces a hybrid 2-stage approach based on two population-based algorithms - Ant Colony Optimization (ACO) tha...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	176,375
2407.06540	General and Task-Oriented Video Segmentation	We present GvSeg, a general video segmentation framework for addressing four different video segmentation tasks (i.e., instance, semantic, panoptic, and exemplar-guided) while maintaining an identical architectural design. Currently, there is a trend towards developing general video segmentation solutions that can be a...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	471,434
2210.12964	Non-Contrastive Learning-based Behavioural Biometrics for Smart IoT Devices	Behaviour biometrics are being explored as a viable alternative to overcome the limitations of traditional authentication methods such as passwords and static biometrics. Also, they are being considered as a viable authentication method for IoT devices such as smart headsets with AR/VR capabilities, wearables, and erab...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	325,993
2109.06513	Exploring Prompt-based Few-shot Learning for Grounded Dialog Generation	Dialog models can be greatly strengthened through grounding on various external information, but grounded dialog corpora are usually not naturally accessible. In this work, we focus on the few-shot learning for grounded dialog generation (GDG). We first propose a simple prompting method for GDG tasks, where different c...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	255,178
2206.00807	Applied Federated Learning: Architectural Design for Robust and Efficient Learning in Privacy Aware Settings	The classical machine learning paradigm requires the aggregation of user data in a central location where machine learning practitioners can preprocess data, calculate features, tune models and evaluate performance. The advantage of this approach includes leveraging high performance hardware (such as GPUs) and the abil...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	300,262
1906.08656	Stochastic One-Sided Full-Information Bandit	In this paper, we study the stochastic version of the one-sided full information bandit problem, where we have $K$ arms $[K] = \{1, 2, \ldots, K\}$, and playing arm $i$ would gain reward from an unknown distribution for arm $i$ while obtaining reward feedback for all arms $j \ge i$. One-sided full information bandit ca...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	135,934
2401.08328	Un-Mixing Test-Time Normalization Statistics: Combatting Label Temporal Correlation	Recent test-time adaptation methods heavily rely on nuanced adjustments of batch normalization (BN) parameters. However, one critical assumption often goes overlooked: that of independently and identically distributed (i.i.d.) test batches with respect to unknown labels. This oversight leads to skewed BN statistics and...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	421,849
2501.19205	RIGNO: A Graph-based framework for robust and accurate operator learning for PDEs on arbitrary domains	Learning the solution operators of PDEs on arbitrary domains is challenging due to the diversity of possible domain shapes, in addition to the often intricate underlying physics. We propose an end-to-end graph neural network (GNN) based neural operator to learn PDE solution operators from data on point clouds in arbitr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	529,058
2408.08058	Navigating Data Scarcity using Foundation Models: A Benchmark of Few-Shot and Zero-Shot Learning Approaches in Medical Imaging	Data scarcity is a major limiting factor for applying modern machine learning techniques to clinical tasks. Although sufficient data exists for some well-studied medical tasks, there remains a long tail of clinically relevant tasks with poor data availability. Recently, numerous foundation models have demonstrated high...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	480,836
1007.1069	On the instantaneous frequency of Gaussian stochastic processes	This paper concerns the instantaneous frequency (IF) of continuous-time, zero-mean, complex-valued, proper, mean-square differentiable nonstationary Gaussian stochastic processes. We compute the probability density function for the IF for fixed time, which extends a result known for wide-sense stationary processes to n...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	7,011
1707.04771	Original Loop-closure Detection Algorithm for Monocular vSLAM	Vision-based simultaneous localization and mapping (vSLAM) is a well-established problem in mobile robotics and monocular vSLAM is one of the most challenging variations of that problem nowadays. In this work we study one of the core post-processing optimization mechanisms in vSLAM, e.g. loop-closure detection. We anal...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	77,096
2206.05182	Human-AI Interaction Design in Machine Teaching	Machine Teaching (MT) is an interactive process where a human and a machine interact with the goal of training a machine learning model (ML) for a specified task. The human teacher communicates their task expertise and the machine student gathers the required data and knowledge to produce an ML model. MT systems are de...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	301,916
2301.09799	LDMIC: Learning-based Distributed Multi-view Image Coding	Multi-view image compression plays a critical role in 3D-related applications. Existing methods adopt a predictive coding architecture, which requires joint encoding to compress the corresponding disparity as well as residual information. This demands collaboration among cameras and enforces the epipolar geometric cons...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	true	341,608
1608.01072	Fuzzy c-Shape: A new algorithm for clustering finite time series waveforms	The existence of large volumes of time series data in many applications has motivated data miners to investigate specialized methods for mining time series data. Clustering is a popular data mining method due to its powerful exploratory nature and its usefulness as a preprocessing step for other data mining techniques....	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	59,382
2303.01237	FlowFormer++: Masked Cost Volume Autoencoding for Pretraining Optical Flow Estimation	FlowFormer introduces a transformer architecture into optical flow estimation and achieves state-of-the-art performance. The core component of FlowFormer is the transformer-based cost-volume encoder. Inspired by the recent success of masked autoencoding (MAE) pretraining in unleashing transformers' capacity of encoding...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	348,886
0810.2133	Diversity-Multiplexing Tradeoff of the Half-Duplex Relay Channel	We show that the diversity-multiplexing tradeoff of a half-duplex single-relay channel with identically distributed Rayleigh fading channel gains meets the 2 by 1 MISO bound. We generalize the result to the case when there are N non-interfering relays and show that the diversity-multiplexing tradeoff is equal to the N ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	2,491
2401.06086	XGBoost Learning of Dynamic Wager Placement for In-Play Betting on an Agent-Based Model of a Sports Betting Exchange	We present first results from the use of XGBoost, a highly effective machine learning (ML) method, within the Bristol Betting Exchange (BBE), an open-source agent-based model (ABM) designed to simulate a contemporary sports-betting exchange with in-play betting during track-racing events such as horse races. We use the...	false	true	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	421,009
1503.04475	Simulation of Genetic Algorithm: Traffic Light Efficiency	Traffic is a problem in many urban areas worldwide. Traffic flow is dictated by certain devices such as traffic lights. The traffic lights signal when each lane is able to pass through the intersection. Often, static schedules interfere with ideal traffic flow. The purpose of this project was to find a way to make inte...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	41,163
2110.00493	Preconditioned Plug-and-Play ADMM with Locally Adjustable Denoiser for Image Restoration	Plug-and-Play optimization recently emerged as a powerful technique for solving inverse problems by plugging a denoiser into a classical optimization algorithm. The denoiser accounts for the regularization and therefore implicitly determines the prior knowledge on the data, hence replacing typical handcrafted priors. I...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	258,409
2310.18511	3DCoMPaT$^{++}$: An improved Large-scale 3D Vision Dataset for Compositional Recognition	In this work, we present 3DCoMPaT$^{++}$, a multimodal 2D/3D dataset with 160 million rendered views of more than 10 million stylized 3D shapes carefully annotated at the part-instance level, alongside matching RGB point clouds, 3D textured meshes, depth maps, and segmentation masks. 3DCoMPaT$^{++}$ covers 41 shape cat...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	403,572
1506.00011	Group Symmetries of Complementary Code Matrices	We characterize group symmetries of poly-phase complementary code matrices (CCMs), which we use to classify CCMs in terms of their equivalence classes. We also present classification results for CCMs of dimension $N\times 4$ where $N=2,3,4,5,6$. Finally, we present a new construction to generate quad-phase CCMs from te...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	43,604
1110.3672	Reasoning about Actions with Temporal Answer Sets	In this paper we combine Answer Set Programming (ASP) with Dynamic Linear Time Temporal Logic (DLTL) to define a temporal logic programming language for reasoning about complex actions and infinite computations. DLTL extends propositional temporal logic of linear time with regular programs of propositional dynamic logi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	12,686

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