Split (2)

train · 433k rows

id stringlengths 9 16	title stringlengths 4 278	abstract stringlengths 3 4.08k	cs.HC bool 2 classes	cs.CE bool 2 classes	cs.SD bool 2 classes	cs.SI bool 2 classes	cs.AI bool 2 classes	cs.IR bool 2 classes	cs.LG bool 2 classes	cs.RO bool 2 classes	cs.CL bool 2 classes	cs.IT bool 2 classes	cs.SY bool 2 classes	cs.CV bool 2 classes	cs.CR bool 2 classes	cs.CY bool 2 classes	cs.MA bool 2 classes	cs.NE bool 2 classes	cs.DB bool 2 classes	Other bool 2 classes	__index_level_0__ int64 0 541k
2403.06264	Rational Silence and False Polarization: How Viewpoint Organizations and Recommender Systems Distort the Expression of Public Opinion	AI-based social media platforms has already transformed the nature of economic and social interaction. AI enables the massive scale and highly personalized nature of online information sharing that we now take for granted. Extensive attention has been devoted to the polarization that social media platforms appear to fa...	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	436,370
1907.07485	Multi-Adapter RGBT Tracking	The task of RGBT tracking aims to take the complementary advantages from visible spectrum and thermal infrared data to achieve robust visual tracking, and receives more and more attention in recent years. Existing works focus on modality-specific information integration by introducing modality weights to achieve adapti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	138,886
2208.02512	Scalable Video Coding for Humans and Machines	Video content is watched not only by humans, but increasingly also by machines. For example, machine learning models analyze surveillance video for security and traffic monitoring, search through YouTube videos for inappropriate content, and so on. In this paper, we propose a scalable video coding framework that suppor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	311,493
2110.02645	A Weighted Generalized Coherence Approach for Sensing Matrix Design	As compared to using randomly generated sensing matrices, optimizing the sensing matrix w.r.t. a carefully designed criterion is known to lead to better quality signal recovery given a set of compressive measurements. In this paper, we propose generalizations of the well-known mutual coherence criterion for optimizing ...	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	259,201
1911.06912	Fixed-horizon Active Hypothesis Testing	Two active hypothesis testing problems are formulated. In these problems, the agent can perform a fixed number of experiments and then decide on one of the hypotheses. The agent is also allowed to declare its experiments inconclusive if needed. The first problem is an asymmetric formulation in which the the objective i...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	153,652
2501.05472	The 2nd Place Solution from the 3D Semantic Segmentation Track in the 2024 Waymo Open Dataset Challenge	3D semantic segmentation is one of the most crucial tasks in driving perception. The ability of a learning-based model to accurately perceive dense 3D surroundings often ensures the safe operation of autonomous vehicles. However, existing LiDAR-based 3D semantic segmentation databases consist of sequentially acquired L...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	523,604
2401.03397	Predicting the Skies: A Novel Model for Flight-Level Passenger Traffic Forecasting	Accurate prediction of flight-level passenger traffic is of paramount importance in airline operations, influencing key decisions from pricing to route optimization. This study introduces a novel, multimodal deep learning approach to the challenge of predicting flight-level passenger traffic, yielding substantial accur...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	420,091
2212.01540	Quadcopter Tracking Using Euler-Angle-Free Flatness-Based Control	Quadcopter trajectory tracking control has been extensively investigated and implemented in the past. Available controls mostly use the Euler angle standards to describe the quadcopters rotational kinematics and dynamics. As a result, the same rotation can be translated into different roll, pitch, and yaw angles becaus...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	334,467
1607.02334	Betweenness centrality profiles in trees	Betweenness centrality of a vertex in a graph measures the fraction of shortest paths going through the vertex. This is a basic notion for determining the importance of a vertex in a network. The k-betweenness centrality of a vertex is defined similarly, but only considers shortest paths of length at most k. The sequen...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	58,334
2106.04193	Targeted Active Learning for Bayesian Decision-Making	Active learning is usually applied to acquire labels of informative data points in supervised learning, to maximize accuracy in a sample-efficient way. However, maximizing the accuracy is not the end goal when the results are used for decision-making, for example in personalized medicine or economics. We argue that whe...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	239,628
2409.15303	Disruptive RIS for Enhancing Key Generation and Secret Transmission in Low-Entropy Environments	Key generation, a pillar in physical-layer security (PLS), is the process of the exchanging signals from two legitimate users (Alice and Bob) to extract a common key from the random, common channels. The drawback of extracting keys from wireless channels is the ample dependence on the dynamicity and fluctuations of the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	490,847
2410.14892	Frequency Control and Disturbance Containment Using Grid-Forming Embedded Storage Networks	The paper discusses fast frequency control in bulk power systems using embedded networks of grid-forming energy storage resources. Differing from their traditional roles of regulating reserves, the storage resources in this work operate as fast-acting grid assets shaping transient dynamics. The storage resources in the...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	500,252
1303.4695	NetLogo Implementation of an Evacuation Scenario	The problem of evacuating crowded closed spaces, such as discotheques, public exhibition pavilions or concert houses, has become increasingly important and gained attention both from practitioners and from public authorities. A simulation implementation using NetLogo, an agent-based simulation framework that permits th...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	23,027
2311.05988	Vision Big Bird: Random Sparsification for Full Attention	Recently, Transformers have shown promising performance in various vision tasks. However, the high costs of global self-attention remain challenging for Transformers, especially for high-resolution vision tasks. Inspired by one of the most successful transformers-based models for NLP: Big Bird, we propose a novel spars...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	406,781
1304.3082	Reasoning With Uncertain Knowledge	A model of knowledge representation is described in which propositional facts and the relationships among them can be supported by other facts. The set of knowledge which can be supported is called the set of cognitive units, each having associated descriptions of their explicit and implicit support structures, summari...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	23,798
2106.08462	Multi-Resolution Continuous Normalizing Flows	Recent work has shown that Neural Ordinary Differential Equations (ODEs) can serve as generative models of images using the perspective of Continuous Normalizing Flows (CNFs). Such models offer exact likelihood calculation, and invertible generation/density estimation. In this work we introduce a Multi-Resolution varia...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	241,300
1403.3369	Controlling Recurrent Neural Networks by Conceptors	The human brain is a dynamical system whose extremely complex sensor-driven neural processes give rise to conceptual, logical cognition. Understanding the interplay between nonlinear neural dynamics and concept-level cognition remains a major scientific challenge. Here I propose a mechanism of neurodynamical organizati...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	31,566
2010.12916	Modeling and Optimization Trade-off in Meta-learning	By searching for shared inductive biases across tasks, meta-learning promises to accelerate learning on novel tasks, but with the cost of solving a complex bilevel optimization problem. We introduce and rigorously define the trade-off between accurate modeling and optimization ease in meta-learning. At one end, classic...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	202,929
2106.11118	SODA10M: A Large-Scale 2D Self/Semi-Supervised Object Detection Dataset for Autonomous Driving	Aiming at facilitating a real-world, ever-evolving and scalable autonomous driving system, we present a large-scale dataset for standardizing the evaluation of different self-supervised and semi-supervised approaches by learning from raw data, which is the first and largest dataset to date. Existing autonomous driving ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	242,282
2101.04632	Context Matters: Self-Attention for Sign Language Recognition	This paper proposes an attentional network for the task of Continuous Sign Language Recognition. The proposed approach exploits co-independent streams of data to model the sign language modalities. These different channels of information can share a complex temporal structure between each other. For that reason, we app...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	215,192
1905.08389	Time-varying Autoregression with Low Rank Tensors	We present a windowed technique to learn parsimonious time-varying autoregressive models from multivariate timeseries. This unsupervised method uncovers interpretable spatiotemporal structure in data via non-smooth and non-convex optimization. In each time window, we assume the data follow a linear model parameterized ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	131,458
2407.15463	Integrated Access and Backhaul (IAB) in Low Altitude Platforms	In this paper, we explore the problem of utilizing Integrated Access and Backhaul (IAB) technology in Non-Terrestrial Networks (NTN), with a particular focus on aerial access networks. We consider an Uncrewed Aerial Vehicle (UAV)-based wireless network comprised of two layers of UAVs: (a) a lower layer consisting a num...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	475,197
2110.13624	Technology Fitness Landscape for Design Innovation: A Deep Neural Embedding Approach Based on Patent Data	Technology is essential to innovation and economic prosperity. Understanding technological changes can guide innovators to find new directions of design innovation and thus make breakthroughs. In this work, we construct a technology fitness landscape via deep neural embeddings of patent data. The landscape consists of ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	263,254
2406.17907	Delta-V-Optimal Centralized Guidance Strategy For Under-actuated N-Satellite Formations	This paper addresses the computation of Delta-V-optimal, safe, relative orbit reconfigurations for satellite formations in a centralized fashion. The formations under consideration comprise an uncontrolled chief spacecraft flying with an arbitrary number, N, of deputy satellites, where each deputy is equipped with a si...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	467,786
2403.16353	Energy-Efficient Hybrid Beamforming with Dynamic On-off Control for Integrated Sensing, Communications, and Powering	This paper investigates the energy-efficient hybrid beamforming design for a multi-functional integrated sensing, communications, and powering (ISCAP) system. In this system, a base station (BS) with a hybrid analog-digital (HAD) architecture sends unified wireless signals to communicate with multiple information recei...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	440,990
2307.07713	Data-Driven Optimal Control of Tethered Space Robot Deployment with Learning Based Koopman Operator	To avoid complex constraints of the traditional nonlinear method for tethered space robot (TSR) deployment, this paper proposes a data-driven optimal control framework with an improved deep learning based Koopman operator that could be applied to complex environments. In consideration of TSR's nonlinearity, its finite ...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	379,518
2405.13791	Multi-Type Point Cloud Autoencoder: A Complete Equivariant Embedding for Molecule Conformation and Pose	The point cloud is a flexible representation for a wide variety of data types, and is a particularly natural fit for the 3D conformations of molecules. Extant molecule embedding/representation schemes typically focus on internal degrees of freedom, ignoring the global 3D orientation. For tasks that depend on knowledge ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	456,082
2001.07608	Analytic Properties of Trackable Weak Models	We present several new results on the feasibility of inferring the hidden states in strongly-connected trackable weak models. Here, a weak model is a directed graph in which each node is assigned a set of colors which may be emitted when that node is visited. A hypothesis is a node sequence which is consistent with a g...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	161,080
2207.05060	Differentiable Physics Simulations with Contacts: Do They Have Correct Gradients w.r.t. Position, Velocity and Control?	In recent years, an increasing amount of work has focused on differentiable physics simulation and has produced a set of open source projects such as Tiny Differentiable Simulator, Nimble Physics, diffTaichi, Brax, Warp, Dojo and DiffCoSim. By making physics simulations end-to-end differentiable, we can perform gradien...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	307,410
2412.07573	Subtopic-aware View Sampling and Temporal Aggregation for Long-form Document Matching	Long-form document matching aims to judge the relevance between two documents and has been applied to various scenarios. Most existing works utilize hierarchical or long context models to process documents, which achieve coarse understanding but may ignore details. Some researchers construct a document view with simila...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	515,717
2412.12565	PBVS 2024 Solution: Self-Supervised Learning and Sampling Strategies for SAR Classification in Extreme Long-Tail Distribution	The Multimodal Learning Workshop (PBVS 2024) aims to improve the performance of automatic target recognition (ATR) systems by leveraging both Synthetic Aperture Radar (SAR) data, which is difficult to interpret but remains unaffected by weather conditions and visible light, and Electro-Optical (EO) data for simultaneou...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	517,926
2312.12121	Towards Learning-Based Gyrocompassing	Inertial navigation systems (INS) are widely used in both manned and autonomous platforms. One of the most critical tasks prior to their operation is to accurately determine their initial alignment while stationary, as it forms the cornerstone for the entire INS operational trajectory. While low-performance acceleromet...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	416,850
1805.11706	Supervised Policy Update for Deep Reinforcement Learning	We propose a new sample-efficient methodology, called Supervised Policy Update (SPU), for deep reinforcement learning. Starting with data generated by the current policy, SPU formulates and solves a constrained optimization problem in the non-parameterized proximal policy space. Using supervised regression, it then con...	false	false	false	false	true	false	true	true	false	false	true	false	false	false	false	false	false	false	98,980
1606.00623	Spectrally-Precoded OFDM for 5G Wideband Operation in Fragmented sub-6GHz Spectrum	We consider spectrally-precoded OFDM waveforms for 5G wideband transmission in sub-6GHz band. In this densely packed spectrum, a low out-of-band (OOB) waveform is a critical 5G component to achieve the promised high spectral efficiency. By precoding data symbols before OFDM modulation, it is possible to achieve extreme...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	56,690
2206.02144	Product safety idioms: a method for building causal Bayesian networks for product safety and risk assessment	Idioms are small, reusable Bayesian network (BN) fragments that represent generic types of uncertain reasoning. This paper shows how idioms can be used to build causal BNs for product safety and risk assessment that use a combination of data and knowledge. We show that the specific product safety idioms that we introdu...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	300,767
2012.11243	Get It Scored Using AutoSAS -- An Automated System for Scoring Short Answers	In the era of MOOCs, online exams are taken by millions of candidates, where scoring short answers is an integral part. It becomes intractable to evaluate them by human graders. Thus, a generic automated system capable of grading these responses should be designed and deployed. In this paper, we present a fast, scalabl...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	212,584
2006.07235	SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)	We present the results and main findings of SemEval-2020 Task 12 on Multilingual Offensive Language Identification in Social Media (OffensEval 2020). The task involves three subtasks corresponding to the hierarchical taxonomy of the OLID schema (Zampieri et al., 2019a) from OffensEval 2019. The task featured five langu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	181,731
2401.06354	Initial Analysis of Data-Driven Haptic Search for the Smart Suction Cup	Suction cups offer a useful gripping solution, particularly in industrial robotics and warehouse applications. Vision-based grasp algorithms, like Dex-Net, show promise but struggle to accurately perceive dark or reflective objects, sub-resolution features, and occlusions, resulting in suction cup grip failures. In our...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	421,128
2403.16694	Design and Performance of Resonant Beam Communications -- Part II: Mobile Scenario	This two-part paper focuses on the system design and performance analysis for a point-to-point resonant beam communication (RBCom) system under both the quasi-static and mobile scenarios. Part I of this paper proposes a synchronization-based information transmission scheme and derives the capacity upper and lower bound...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	441,157
2203.14849	Safe Active Learning for Multi-Output Gaussian Processes	Multi-output regression problems are commonly encountered in science and engineering. In particular, multi-output Gaussian processes have been emerged as a promising tool for modeling these complex systems since they can exploit the inherent correlations and provide reliable uncertainty estimates. In many applications,...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	288,152
2210.02636	Geodesic Graph Neural Network for Efficient Graph Representation Learning	Graph Neural Networks (GNNs) have recently been applied to graph learning tasks and achieved state-of-the-art (SOTA) results. However, many competitive methods run GNNs multiple times with subgraph extraction and customized labeling to capture information that is hard for normal GNNs to learn. Such operations are time-...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	321,721
2009.01030	Privacy Leakage of SIFT Features via Deep Generative Model based Image Reconstruction	Many practical applications, e.g., content based image retrieval and object recognition, heavily rely on the local features extracted from the query image. As these local features are usually exposed to untrustworthy parties, the privacy leakage problem of image local features has received increasing attention in recen...	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	194,202
2408.00783	Data-driven Verification of DNNs for Object Recognition	The paper proposes a new testing approach for Deep Neural Networks (DNN) using gradient-free optimization to find perturbation chains that successfully falsify the tested DNN, going beyond existing grid-based or combinatorial testing. Applying it to an image segmentation task of detecting railway tracks in images, we d...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	477,982
2309.11414	EDMP: Ensemble-of-costs-guided Diffusion for Motion Planning	Classical motion planning for robotic manipulation includes a set of general algorithms that aim to minimize a scene-specific cost of executing a given plan. This approach offers remarkable adaptability, as they can be directly used off-the-shelf for any new scene without needing specific training datasets. However, wi...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	393,399
2302.14015	CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design	We formalize the problem of contextual optimization through the lens of Bayesian experimental design and propose CO-BED -- a general, model-agnostic framework for designing contextual experiments using information-theoretic principles. After formulating a suitable information-based objective, we employ black-box variat...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	348,125
2307.06630	Image Transformation Sequence Retrieval with General Reinforcement Learning	In this work, the novel Image Transformation Sequence Retrieval (ITSR) task is presented, in which a model must retrieve the sequence of transformations between two given images that act as source and target, respectively. Given certain characteristics of the challenge such as the multiplicity of a correct sequence or ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	379,129
1911.02524	A Spoken Dialogue System for Spatial Question Answering in a Physical Blocks World	The blocks world is a classic toy domain that has long been used to build and test spatial reasoning systems. Despite its relative simplicity, tackling this domain in its full complexity requires the agent to exhibit a rich set of functional capabilities, ranging from vision to natural language understanding. There is ...	true	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	152,383
2305.05803	Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation	Weakly supervised semantic segmentation (WSSS) aims to bypass the need for laborious pixel-level annotation by using only image-level annotation. Most existing methods rely on Class Activation Maps (CAM) to derive pixel-level pseudo-labels and use them to train a fully supervised semantic segmentation model. Although t...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	363,284
2502.01375	Compact Rule-Based Classifier Learning via Gradient Descent	Rule-based models play a crucial role in scenarios that require transparency and accountable decision-making. However, they primarily consist of discrete parameters and structures, which presents challenges for scalability and optimization. In this work, we introduce a new rule-based classifier trained using gradient d...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	529,827
2205.08249	Learnable Optimal Sequential Grouping for Video Scene Detection	Video scene detection is the task of dividing videos into temporal semantic chapters. This is an important preliminary step before attempting to analyze heterogeneous video content. Recently, Optimal Sequential Grouping (OSG) was proposed as a powerful unsupervised solution to solve a formulation of the video scene det...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	296,867
2305.04522	Event Knowledge Incorporation with Posterior Regularization for Event-Centric Question Answering	We propose a simple yet effective strategy to incorporate event knowledge extracted from event trigger annotations via posterior regularization to improve the event reasoning capability of mainstream question-answering (QA) models for event-centric QA. In particular, we define event-related knowledge constraints based ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	362,803
2004.07982	Analytical Factors for Describing the Control Ability of Linear Discrete-time Systems	In this paper, the analytical volume computations of the zonotopes generated by the matrix pair with $n$ different or repeated real eigenvalues are discussed firstly, and then by deconstructing the volume computing equations, 3 classes of the shape factors are constructed. These analytical volume and shape factors can ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	172,922
1810.11787	A Hitchhiker's Guide On Distributed Training of Deep Neural Networks	Deep learning has led to tremendous advancements in the field of Artificial Intelligence. One caveat however is the substantial amount of compute needed to train these deep learning models. Training a benchmark dataset like ImageNet on a single machine with a modern GPU can take upto a week, distributing training on mu...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	111,597
1504.00657	Eliciting Disease Data from Wikipedia Articles	Traditional disease surveillance systems suffer from several disadvantages, including reporting lags and antiquated technology, that have caused a movement towards internet-based disease surveillance systems. Internet systems are particularly attractive for disease outbreaks because they can provide data in near real-t...	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	false	false	41,721
2209.07714	Variational quantum algorithm for measurement extraction from the Navier-Stokes, Einstein, Maxwell, B-type, Lin-Tsien, Camassa-Holm, DSW, H-S, KdV-B, non-homogeneous KdV, generalized KdV, KdV, translational KdV, sKdV, B-L and Airy equations	Classical-quantum hybrid algorithms have recently garnered significant attention, which are characterized by combining quantum and classical computing protocols to obtain readout from quantum circuits of interest. Recent progress due to Lubasch et al in a 2019 paper provides readout for solutions to the Schrodinger and...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	317,859
2203.08029	Optimal dispatch schedule for a fast EV charging station with account to supplementary battery health degradation	This paper investigates the usage of battery storage systems in a fast charging station (FCS) for participation in energy markets and charging electrical vehicles (EVs) simultaneously. In particular, we focus on optimizing the scheduling strategies to reduce the overall operational cost of the system over its lifetime ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	285,648
1911.01106	Singular points detection with semantic segmentation networks	Singular points detection is one of the most classical and important problem in the field of fingerprint recognition. However, current detection rates of singular points are still unsatisfactory, especially for low-quality fingerprints. Compared with traditional image processing-based detection methods, methods based o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	152,018
1905.08910	A Neural-Symbolic Architecture for Inverse Graphics Improved by Lifelong Meta-Learning	We follow the idea of formulating vision as inverse graphics and propose a new type of element for this task, a neural-symbolic capsule. It is capable of de-rendering a scene into semantic information feed-forward, as well as rendering it feed-backward. An initial set of capsules for graphical primitives is obtained fr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	131,605
2310.02930	Small-Disturbance Input-to-State Stability of Perturbed Gradient Flows: Applications to LQR Problem	This paper studies the effect of perturbations on the gradient flow of a general nonlinear programming problem, where the perturbation may arise from inaccurate gradient estimation in the setting of data-driven optimization. Under suitable conditions on the objective function, the perturbed gradient flow is shown to be...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	397,046
2410.14738	Advancements In Heart Disease Prediction: A Machine Learning Approach For Early Detection And Risk Assessment	The primary aim of this paper is to comprehend, assess, and analyze the role, relevance, and efficiency of machine learning models in predicting heart disease risks using clinical data. While the importance of heart disease risk prediction cannot be overstated, the application of machine learning (ML) in identifying an...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	500,181
2003.06917	End-to-End Velocity Estimation For Autonomous Racing	Velocity estimation plays a central role in driverless vehicles, but standard and affordable methods struggle to cope with extreme scenarios like aggressive maneuvers due to the presence of high sideslip. To solve this, autonomous race cars are usually equipped with expensive external velocity sensors. In this paper, w...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	168,265
1411.2328	Modeling Word Relatedness in Latent Dirichlet Allocation	Standard LDA model suffers the problem that the topic assignment of each word is independent and word correlation hence is neglected. To address this problem, in this paper, we propose a model called Word Related Latent Dirichlet Allocation (WR-LDA) by incorporating word correlation into LDA topic models. This leads to...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	37,403
1806.07916	RSDD-Time: Temporal Annotation of Self-Reported Mental Health Diagnoses	Self-reported diagnosis statements have been widely employed in studying language related to mental health in social media. However, existing research has largely ignored the temporality of mental health diagnoses. In this work, we introduce RSDD-Time: a new dataset of 598 manually annotated self-reported depression di...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	101,046
1811.01174	Nonparallel Emotional Speech Conversion	We propose a nonparallel data-driven emotional speech conversion method. It enables the transfer of emotion-related characteristics of a speech signal while preserving the speaker's identity and linguistic content. Most existing approaches require parallel data and time alignment, which is not available in most real ap...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	112,293
1303.0058	A Cooperative MARC Scheme Using Analogue Network Coding to Achieve Second-Order Diversity	A multiple access relay channel (MARC) is considered in which an analogue-like network coding is implemented in the relay node. This analogue coding is a simple addition of the received signals at the relay node. Using "nulling detection" structure employed in V-BLAST receiver, we propose a detection scheme in the dest...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	22,525
2311.04378	Watermarks in the Sand: Impossibility of Strong Watermarking for Generative Models	Watermarking generative models consists of planting a statistical signal (watermark) in a model's output so that it can be later verified that the output was generated by the given model. A strong watermarking scheme satisfies the property that a computationally bounded attacker cannot erase the watermark without causi...	false	false	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	406,201
2405.15964	A hierarchical Bayesian model for syntactic priming	The effect of syntactic priming exhibits three well-documented empirical properties: the lexical boost, the inverse frequency effect, and the asymmetrical decay. We aim to show how these three empirical phenomena can be reconciled in a general learning framework, the hierarchical Bayesian model (HBM). The model represe...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	457,183
2401.01522	LORE++: Logical Location Regression Network for Table Structure Recognition with Pre-training	Table structure recognition (TSR) aims at extracting tables in images into machine-understandable formats. Recent methods solve this problem by predicting the adjacency relations of detected cell boxes or learning to directly generate the corresponding markup sequences from the table images. However, existing approache...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	419,389
cs/0006021	Compiling Language Models from a Linguistically Motivated Unification Grammar	Systems now exist which are able to compile unification grammars into language models that can be included in a speech recognizer, but it is so far unclear whether non-trivial linguistically principled grammars can be used for this purpose. We describe a series of experiments which investigate the question empirically,...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	537,130
1802.00176	Perceptual Compressive Sensing	Compressive sensing (CS) works to acquire measurements at sub-Nyquist rate and recover the scene images. Existing CS methods always recover the scene images in pixel level. This causes the smoothness of recovered images and lack of structure information, especially at a low measurement rate. To overcome this drawback, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	89,363
1905.04360	Kesten-McKay law for random subensembles of Paley equiangular tight frames	We apply the method of moments to prove a recent conjecture of Haikin, Zamir and Gavish (2017) concerning the distribution of the singular values of random subensembles of Paley equiangular tight frames. Our analysis applies more generally to real equiangular tight frames of redundancy 2, and we suspect similar ideas w...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	130,436
1602.03725	A Versatile Scene Model with Differentiable Visibility Applied to Generative Pose Estimation	Generative reconstruction methods compute the 3D configuration (such as pose and/or geometry) of a shape by optimizing the overlap of the projected 3D shape model with images. Proper handling of occlusions is a big challenge, since the visibility function that indicates if a surface point is seen from a camera can ofte...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	52,044
2409.17981	BlinkTrack: Feature Tracking over 100 FPS via Events and Images	Feature tracking is crucial for, structure from motion (SFM), simultaneous localization and mapping (SLAM), object tracking and various computer vision tasks. Event cameras, known for their high temporal resolution and ability to capture asynchronous changes, have gained significant attention for their potential in fea...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	492,049
2408.04556	BA-LoRA: Bias-Alleviating Low-Rank Adaptation to Mitigate Catastrophic Inheritance in Large Language Models	Large language models (LLMs) have demonstrated remarkable proficiency across various natural language processing (NLP) tasks. However, adapting LLMs to downstream applications requires computationally intensive and memory-demanding fine-tuning procedures. To alleviate these burdens, parameter-efficient fine-tuning (PEF...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	479,425
1810.00122	A Quantitative Analysis of the Effect of Batch Normalization on Gradient Descent	Despite its empirical success and recent theoretical progress, there generally lacks a quantitative analysis of the effect of batch normalization (BN) on the convergence and stability of gradient descent. In this paper, we provide such an analysis on the simple problem of ordinary least squares (OLS). Since precise dyn...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	109,097
1204.1276	Distribution-Dependent Sample Complexity of Large Margin Learning	We obtain a tight distribution-specific characterization of the sample complexity of large-margin classification with L2 regularization: We introduce the margin-adapted dimension, which is a simple function of the second order statistics of the data distribution, and show distribution-specific upper and lower bounds on...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	15,305
2106.08596	Temporal Convolution Networks with Positional Encoding for Evoked Expression Estimation	This paper presents an approach for Evoked Expressions from Videos (EEV) challenge, which aims to predict evoked facial expressions from video. We take advantage of pre-trained models on large-scale datasets in computer vision and audio signals to extract the deep representation of timestamps in the video. A temporal c...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	241,348
1307.0193	A Sampling Algebra for Aggregate Estimation	As of 2005, sampling has been incorporated in all major database systems. While efficient sampling techniques are realizable, determining the accuracy of an estimate obtained from the sample is still an unresolved problem. In this paper, we present a theoretical framework that allows an elegant treatment of the problem...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	25,530
2406.15571	Texture Feature Analysis for Classification of Early-Stage Prostate Cancer in mpMRI	Magnetic resonance imaging (MRI) has become a crucial tool in the diagnosis and staging of prostate cancer, owing to its superior tissue contrast. However, it also creates large volumes of data that must be assessed by trained experts, a time-consuming and laborious task. This has prompted the development of machine le...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	466,779
1905.04611	Data description and retrieval using periods represented by uncertain time intervals	Time periods are frequently used to specify time in metadata and retrieval. However, it is not easy to describe and retrieve information about periods, because the temporal ranges represented by periods are often ambiguous. This is because these temporal ranges do not have fixed beginning and end points. To solve this ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	130,514
1912.00342	Machines Getting with the Program: Understanding Intent Arguments of Non-Canonical Directives	Modern dialog managers face the challenge of having to fulfill human-level conversational skills as part of common user expectations, including but not limited to discourse with no clear objective. Along with these requirements, agents are expected to extrapolate intent from the user's dialogue even when subjected to n...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	155,739
1807.03537	Soft-TTL: Time-Varying Fractional Caching	Standard Time-to-Live (TTL) cache management prescribes the storage of entire files, or possibly fractions thereof, for a given amount of time after a request. As a generalization of this approach, this work proposes the storage of a time-varying, diminishing, fraction of a requested file. Accordingly, the cache progre...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	102,552
2005.07776	Efficient Federated Learning over Multiple Access Channel with Differential Privacy Constraints	In this paper, the problem of federated learning (FL) through digital communication between clients and a parameter server (PS) over a multiple access channel (MAC), also subject to differential privacy (DP) constraints, is studied. More precisely, we consider the setting in which clients in a centralized network are p...	false	false	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	true	177,375
2111.08330	Bayesian Optimization for Cascade-type Multi-stage Processes	Complex processes in science and engineering are often formulated as multistage decision-making problems. In this paper, we consider a type of multistage decision-making process called a cascade process. A cascade process is a multistage process in which the output of one stage is used as an input for the subsequent st...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	266,651
2108.00596	GTNet:Guided Transformer Network for Detecting Human-Object Interactions	The human-object interaction (HOI) detection task refers to localizing humans, localizing objects, and predicting the interactions between each human-object pair. HOI is considered one of the fundamental steps in truly understanding complex visual scenes. For detecting HOI, it is important to utilize relative spatial c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	248,765
2406.18055	Filtering Reconfigurable Intelligent Computational Surface for RF Spectrum Purification	The increasing demand for communication is degrading the electromagnetic (EM) transmission environment due to severe EM interference, significantly reducing the efficiency of the radio frequency (RF) spectrum. Metasurfaces, a promising technology for controlling desired EM waves, have recently received significant atte...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	467,854
2409.19414	Sequential Signal Mixing Aggregation for Message Passing Graph Neural Networks	Message Passing Graph Neural Networks (MPGNNs) have emerged as the preferred method for modeling complex interactions across diverse graph entities. While the theory of such models is well understood, their aggregation module has not received sufficient attention. Sum-based aggregators have solid theoretical foundation...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	492,665
2305.12584	Sparse Representer Theorems for Learning in Reproducing Kernel Banach Spaces	Sparsity of a learning solution is a desirable feature in machine learning. Certain reproducing kernel Banach spaces (RKBSs) are appropriate hypothesis spaces for sparse learning methods. The goal of this paper is to understand what kind of RKBSs can promote sparsity for learning solutions. We consider two typical lear...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	366,074
1902.05978	GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction	In the past few years, a lot of work has been done towards reconstructing the 3D facial structure from single images by capitalizing on the power of Deep Convolutional Neural Networks (DCNNs). In the most recent works, differentiable renderers were employed in order to learn the relationship between the facial identity...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	121,649
2210.02159	Differentiable Mathematical Programming for Object-Centric Representation Learning	We propose topology-aware feature partitioning into $k$ disjoint partitions for given scene features as a method for object-centric representation learning. To this end, we propose to use minimum $s$-$t$ graph cuts as a partitioning method which is represented as a linear program. The method is topologically aware sinc...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	321,546
1310.8467	Reinforcement Learning Framework for Opportunistic Routing in WSNs	Routing packets opportunistically is an essential part of multihop ad hoc wireless sensor networks. The existing routing techniques are not adaptive opportunistic. In this paper we have proposed an adaptive opportunistic routing scheme that routes packets opportunistically in order to ensure that packet loss is avoided...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	28,106
2002.10376	The Two Regimes of Deep Network Training	Learning rate schedule has a major impact on the performance of deep learning models. Still, the choice of a schedule is often heuristical. We aim to develop a precise understanding of the effects of different learning rate schedules and the appropriate way to select them. To this end, we isolate two distinct phases of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	165,384
2104.11014	Network Space Search for Pareto-Efficient Spaces	Network spaces have been known as a critical factor in both handcrafted network designs or defining search spaces for Neural Architecture Search (NAS). However, an effective space involves tremendous prior knowledge and/or manual effort, and additional constraints are required to discover efficiency-aware architectures...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	231,789
0906.2635	Bayesian History Reconstruction of Complex Human Gene Clusters on a Phylogeny	Clusters of genes that have evolved by repeated segmental duplication present difficult challenges throughout genomic analysis, from sequence assembly to functional analysis. Improved understanding of these clusters is of utmost importance, since they have been shown to be the source of evolutionary innovation, and hav...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	3,881
1908.05959	Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learning	Supervised learning algorithms trained on medical images will often fail to generalize across changes in acquisition parameters. Recent work in domain adaptation addresses this challenge and successfully leverages labeled data in a source domain to perform well on an unlabeled target domain. Inspired by recent work in ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	141,868
1703.05260	InScript: Narrative texts annotated with script information	This paper presents the InScript corpus (Narrative Texts Instantiating Script structure). InScript is a corpus of 1,000 stories centered around 10 different scenarios. Verbs and noun phrases are annotated with event and participant types, respectively. Additionally, the text is annotated with coreference information. T...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	70,047
1902.00197	Adaptive Monte Carlo Multiple Testing via Multi-Armed Bandits	Monte Carlo (MC) permutation test is considered the gold standard for statistical hypothesis testing, especially when standard parametric assumptions are not clear or likely to fail. However, in modern data science settings where a large number of hypothesis tests need to be performed simultaneously, it is rarely used ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	120,355
2405.13341	Wealth inequality and utility: Effect evaluation of redistribution and consumption morals using macro-econophysical coupled approach	Reducing wealth inequality and increasing utility are critical issues. This study reveals the effects of redistribution and consumption morals on wealth inequality and utility. To this end, we present a novel approach that couples the dynamic model of capital, consumption, and utility in macroeconomics with the interac...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	455,899
2501.01557	Click-Calib: A Robust Extrinsic Calibration Method for Surround-View Systems	Surround-View System (SVS) is an essential component in Advanced Driver Assistance System (ADAS) and requires precise calibrations. However, conventional offline extrinsic calibration methods are cumbersome and time-consuming as they rely heavily on physical patterns. Additionally, these methods primarily focus on shor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	522,117
1705.07364	Stabilizing Adversarial Nets With Prediction Methods	Adversarial neural networks solve many important problems in data science, but are notoriously difficult to train. These difficulties come from the fact that optimal weights for adversarial nets correspond to saddle points, and not minimizers, of the loss function. The alternating stochastic gradient methods typically ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	73,820

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