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
1803.10914	Adversarial Binary Coding for Efficient Person Re-identification	Person re-identification (ReID) aims at matching persons across different views/scenes. In addition to accuracy, the matching efficiency has received more and more attention because of demanding applications using large-scale data. Several binary coding based methods have been proposed for efficient ReID, which either ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	93,788
1312.1147	Optimality of Operator-Like Wavelets for Representing Sparse AR(1) Processes	It is known that the Karhunen-Lo\`{e}ve transform (KLT) of Gaussian first-order auto-regressive (AR(1)) processes results in sinusoidal basis functions. The same sinusoidal bases come out of the independent-component analysis (ICA) and actually correspond to processes with completely independent samples. In this paper,...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	28,844
0712.0042	On the Mutual Information Distribution of OFDM-Based Spatial Multiplexing: Exact Variance and Outage Approximation	This paper considers the distribution of the mutual information of frequency-selective spatially-uncorrelated Rayleigh fading MIMO channels. Results are presented for OFDM-based spatial multiplexing. New exact closed-form expressions are derived for the variance of the mutual information. In contrast to previous result...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	980
2206.07247	Fair Ranking as Fair Division: Impact-Based Individual Fairness in Ranking	Rankings have become the primary interface in two-sided online markets. Many have noted that the rankings not only affect the satisfaction of the users (e.g., customers, listeners, employers, travelers), but that the position in the ranking allocates exposure -- and thus economic opportunity -- to the ranked items (e.g...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	302,659
2005.09068	Soft, Round, High Resolution Tactile Fingertip Sensors for Dexterous Robotic Manipulation	High resolution tactile sensors are often bulky and have shape profiles that make them awkward for use in manipulation. This becomes important when using such sensors as fingertips for dexterous multi-fingered hands, where boxy or planar fingertips limit the available set of smooth manipulation strategies. High resolut...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	177,803
2304.08058	One-Class SVM on siamese neural network latent space for Unsupervised Anomaly Detection on brain MRI White Matter Hyperintensities	Anomaly detection remains a challenging task in neuroimaging when little to no supervision is available and when lesions can be very small or with subtle contrast. Patch-based representation learning has shown powerful representation capacities when applied to industrial or medical imaging and outlier detection methods...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	358,575
1306.2863	Random Drift Particle Swarm Optimization	The random drift particle swarm optimization (RDPSO) algorithm, inspired by the free electron model in metal conductors placed in an external electric field, is presented, systematically analyzed and empirically studied in this paper. The free electron model considers that electrons have both a thermal and a drift moti...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	25,161
2008.06310	Improving Smart Conference Participation through Socially-Aware Recommendation	This research addresses recommending presentation sessions at smart conferences to participants. We propose a venue recommendation algorithm, Socially-Aware Recommendation of Venues and Environments (SARVE). SARVE computes correlation and social characteristic information of conference participants. In order to model a...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	191,769
1808.05325	Electronic properties of binary compounds with high fidelity and high throughput	We present example applications of an approach to high-throughput first-principles calculations of the electronic properties of materials implemented within the Exabyte.io platform. We deploy computational techniques based on the Density Functional Theory with both Generalized Gradient Approximation (GGA) and Hybrid Sc...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	105,324
2412.04867	MANTA: A Large-Scale Multi-View and Visual-Text Anomaly Detection Dataset for Tiny Objects	We present MANTA, a visual-text anomaly detection dataset for tiny objects. The visual component comprises over 137.3K images across 38 object categories spanning five typical domains, of which 8.6K images are labeled as anomalous with pixel-level annotations. Each image is captured from five distinct viewpoints to ens...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	514,606
2102.00046	Recovery of Power Flow to Critical Infrastructures using Mode-dependent Droop-based Inverters	Recovery of power flow to critical infrastructures, after grid failure, is a crucial need arising in scenarios that are increasingly becoming more frequent. This article proposes a power transition and recovery strategy by proposing a mode-dependent droop control-based inverters. The control strategy of inverters achie...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	217,649
2403.05870	Channel Estimation for Stacked Intelligent Metasurface-Assisted Wireless Networks	Emerging technologies, such as holographic multiple-input multiple-output (HMIMO) and stacked intelligent metasurface (SIM), are driving the development of wireless communication systems. Specifically, the SIM is physically constructed by stacking multiple layers of metasurfaces and has an architecture similar to an ar...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	436,195
1302.4974	A Theoretical Framework for Context-Sensitive Temporal Probability Model Construction with Application to Plan Projection	We define a context-sensitive temporal probability logic for representing classes of discrete-time temporal Bayesian networks. Context constraints allow inference to be focused on only the relevant portions of the probabilistic knowledge. We provide a declarative semantics for our language. We present a Bayesian networ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	22,248
cs/0607062	Get out the vote: Determining support or opposition from Congressional floor-debate transcripts	We investigate whether one can determine from the transcripts of U.S. Congressional floor debates whether the speeches represent support of or opposition to proposed legislation. To address this problem, we exploit the fact that these speeches occur as part of a discussion; this allows us to use sources of information ...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	539,582
2311.06038	2D Image head pose estimation via latent space regression under occlusion settings	Head orientation is a challenging Computer Vision problem that has been extensively researched having a wide variety of applications. However, current state-of-the-art systems still underperform in the presence of occlusions and are unreliable for many task applications in such scenarios. This work proposes a novel dee...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	406,794
2406.16213	Provable Statistical Rates for Consistency Diffusion Models	Diffusion models have revolutionized various application domains, including computer vision and audio generation. Despite the state-of-the-art performance, diffusion models are known for their slow sample generation due to the extensive number of steps involved. In response, consistency models have been developed to me...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	467,041
1807.07752	Twitter Sentiment Analysis System	Social media is increasingly used by humans to express their feelings and opinions in the form of short text messages. Detecting sentiments in the text has a wide range of applications including identifying anxiety or depression of individuals and measuring well-being or mood of a community. Sentiments can be expressed...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	103,372
1904.02147	Learning Shared Encoding Representation for End-to-End Speech Recognition Models	In this work, we learn a shared encoding representation for a multi-task neural network model optimized with connectionist temporal classification (CTC) and conventional framewise cross-entropy training criteria. Our experiments show that the multi-task training not only tackles the complexity of optimizing CTC models ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	126,340
1010.1584	High-SIR Transmission Capacity of Wireless Networks with General Fading and Node Distribution	In many wireless systems, interference is the main performance-limiting factor, and is primarily dictated by the locations of concurrent transmitters. In many earlier works, the locations of the transmitters is often modeled as a Poisson point process for analytical tractability. While analytically convenient, the PPP ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	7,830
1511.02429	A Micro-foundation of Social Capital in Evolving Social Networks	A social network confers benefits and advantages on individuals (and on groups), the literature refers to these advantages as social capital. This paper presents a micro-founded mathematical model of the evolution of a social network and of the social capital of individuals within the network. The evolution of the netw...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	48,633
2202.12297	Embedded Ensembles: Infinite Width Limit and Operating Regimes	A memory efficient approach to ensembling neural networks is to share most weights among the ensembled models by means of a single reference network. We refer to this strategy as Embedded Ensembling (EE); its particular examples are BatchEnsembles and Monte-Carlo dropout ensembles. In this paper we perform a systematic...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	282,183
1804.06034	Set-membership NLMS algorithm based on bias-compensated and regression noise variance estimation for noisy inputs	The bias-compensated set-membership normalised LMS (BCSMNLMS) algorithm is proposed based on the concept of set-membership filtering, which incorporates the bias-compensation technique to mitigate the negative effect of noisy inputs. Moreover, an efficient regression noise variance estimation method is developed by tak...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	95,214
2105.10315	Online Statistical Inference for Parameters Estimation with Linear-Equality Constraints	Stochastic gradient descent (SGD) and projected stochastic gradient descent (PSGD) are scalable algorithms to compute model parameters in unconstrained and constrained optimization problems. In comparison with SGD, PSGD forces its iterative values into the constrained parameter space via projection. From a statistical ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	236,352
1010.1911	On a Low-Rate TLDPC Code Ensemble and the Necessary Condition on the Linear Minimum Distance for Sparse-Graph Codes	This paper addresses the issue of design of low-rate sparse-graph codes with linear minimum distance in the blocklength. First, we define a necessary condition which needs to be satisfied when the linear minimum distance is to be ensured. The condition is formulated in terms of degree-1 and degree-2 variable nodes and ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	7,852
1107.4730	Empirical analysis of collective human behavior for extraordinary events in blogosphere	To uncover underlying mechanism of collective human dynamics, we survey more than 1.8 billion blog entries and observe the statistical properties of word appearances. We focus on words that show dynamic growth and decay with a tendency to diverge on a certain day. After careful pretreatment and fitting method, we found...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	11,429
1906.00080	Gmail Smart Compose: Real-Time Assisted Writing	In this paper, we present Smart Compose, a novel system for generating interactive, real-time suggestions in Gmail that assists users in writing mails by reducing repetitive typing. In the design and deployment of such a large-scale and complicated system, we faced several challenges including model selection, performa...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	133,254
2401.09945	HGAttack: Transferable Heterogeneous Graph Adversarial Attack	Heterogeneous Graph Neural Networks (HGNNs) are increasingly recognized for their performance in areas like the web and e-commerce, where resilience against adversarial attacks is crucial. However, existing adversarial attack methods, which are primarily designed for homogeneous graphs, fall short when applied to HGNNs...	false	false	false	false	false	true	true	false	false	false	false	false	true	false	false	false	false	false	422,435
1703.01382	Multi-Scale Wavelet Domain Residual Learning for Limited-Angle CT Reconstruction	Limited-angle computed tomography (CT) is often used in clinical applications such as C-arm CT for interventional imaging. However, CT images from limited angles suffers from heavy artifacts due to incomplete projection data. Existing iterative methods require extensive calculations but can not deliver satisfactory res...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	69,350
2408.05452	EV-MGDispNet: Motion-Guided Event-Based Stereo Disparity Estimation Network with Left-Right Consistency	Event cameras have the potential to revolutionize the field of robot vision, particularly in areas like stereo disparity estimation, owing to their high temporal resolution and high dynamic range. Many studies use deep learning for event camera stereo disparity estimation. However, these methods fail to fully exploit t...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	479,793
2206.13703	Kwame for Science: An AI Teaching Assistant Based on Sentence-BERT for Science Education in West Africa	Africa has a high student-to-teacher ratio which limits students' access to teachers. Consequently, students struggle to get answers to their questions. In this work, we extended Kwame, our previous AI teaching assistant, adapted it for science education, and deployed it as a web app. Kwame for Science answers question...	true	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	305,053
2202.10566	Efficient Massive Machine Type Communication (mMTC) via AMP	We propose efficient and low-complexity multiuser detection (MUD) algorithms for Gaussian multiple access channel (G-MAC) for short-packet transmission in massive machine type communications. To do so, we first formulate the G-MAC MUD problem as a sparse signal recovery problem and obtain the exact and approximate join...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	281,568
2104.01350	Generation of Gradient-Preserving Images allowing HOG Feature Extraction	In this paper, we propose a method for generating visually protected images, referred to as gradient-preserving images. The protected images allow us to directly extract Histogram-of-Oriented-Gradients (HOG) features for privacy-preserving machine learning. In an experiment, HOG features extracted from gradient-preserv...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	228,313
2301.05908	An Order-Complexity Model for Aesthetic Quality Assessment of Symbolic Homophony Music Scores	Computational aesthetics evaluation has made great achievements in the field of visual arts, but the research work on music still needs to be explored. Although the existing work of music generation is very substantial, the quality of music score generated by AI is relatively poor compared with that created by human co...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	340,490
2108.04035	Mixture of Linear Models Co-supervised by Deep Neural Networks	Deep neural network (DNN) models have achieved phenomenal success for applications in many domains, ranging from academic research in science and engineering to industry and business. The modeling power of DNN is believed to have come from the complexity and over-parameterization of the model, which on the other hand h...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	249,870
2407.09887	OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling	Large language models (LLMs) have exhibited their problem-solving abilities in mathematical reasoning. Solving realistic optimization (OPT) problems in application scenarios requires advanced and applied mathematics ability. However, current OPT benchmarks that merely solve linear programming are far from complex reali...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	472,758
2111.02265	SERC: Syntactic and Semantic Sequence based Event Relation Classification	Temporal and causal relations play an important role in determining the dependencies between events. Classifying the temporal and causal relations between events has many applications, such as generating event timelines, event summarization, textual entailment and question answering. Temporal and causal relations are c...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	264,816
2001.06744	Dual Stochastic Natural Gradient Descent and convergence of interior half-space gradient approximations	The multinomial logistic regression (MLR) model is widely used in statistics and machine learning. Stochastic gradient descent (SGD) is the most common approach for determining the parameters of a MLR model in big data scenarios. However, SGD has slow sub-linear rates of convergence. A way to improve these rates of con...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	160,874
1902.08970	Secret Key Capacity For Multipleaccess Channel With Public Feedback	We consider the generation of a secret key (SK) by the inputs and the output of a secure multipleaccess channel (MAC) that additionally have access to a noiseless public communication channel. Under specific restrictions on the protocols, we derive various upper bounds on the rate of such SKs. Specifically, if the publ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	122,309
2201.05230	NLP in Human Rights Research -- Extracting Knowledge Graphs About Police and Army Units and Their Commanders	In this working paper we explore the use of an NLP system to assist the work of Security Force Monitor (SFM). SFM creates data about the organizational structure, command personnel and operations of police, army and other security forces, which assists human rights researchers, journalists and litigators in their work ...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	275,322
2311.12887	Optimal, and approximately optimal, quantum strategies for $\mathrm{XOR}^{*}$ and $\mathrm{FFL}$ games	We analyze optimal, and approximately optimal, quantum strategies for a variety of non-local XOR games. Building upon previous arguments due to Ostrev in 2016, which characterized approximately optimal, and optimal, strategies that players Alice and Bob can adopt for maximizing a linear functional to win non-local game...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	409,540
2402.04268	ProtAgents: Protein discovery via large language model multi-agent collaborations combining physics and machine learning	Designing de novo proteins beyond those found in nature holds significant promise for advancements in both scientific and engineering applications. Current methodologies for protein design often rely on AI-based models, such as surrogate models that address end-to-end problems by linking protein structure to material p...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	427,384
2205.15404	Gator: Customizable Channel Pruning of Neural Networks with Gating	The rise of neural network (NN) applications has prompted an increased interest in compression, with a particular focus on channel pruning, which does not require any additional hardware. Most pruning methods employ either single-layer operations or global schemes to determine which channels to remove followed by fine-...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	299,707
2104.07308	Spectral MVIR: Joint Reconstruction of 3D Shape and Spectral Reflectance	Reconstructing an object's high-quality 3D shape with inherent spectral reflectance property, beyond typical device-dependent RGB albedos, opens the door to applications requiring a high-fidelity 3D model in terms of both geometry and photometry. In this paper, we propose a novel Multi-View Inverse Rendering (MVIR) met...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	230,376
2307.03330	On the convexity of static output feedback control synthesis for systems with lossless nonlinearities	Computing a stabilizing static output-feedback (SOF) controller is an NP-hard problem, in general. Yet, these controllers have amassed popularity in recent years because of their practical use in feedback control applications, such as fluid flow control and sensor/actuator selection. The inherent difficulty of synthesi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	377,995
2204.09893	MAP-SNN: Mapping Spike Activities with Multiplicity, Adaptability, and Plasticity into Bio-Plausible Spiking Neural Networks	Spiking Neural Network (SNN) is considered more biologically realistic and power-efficient as it imitates the fundamental mechanism of the human brain. Recently, backpropagation (BP) based SNN learning algorithms that utilize deep learning frameworks have achieved good performance. However, bio-interpretability is part...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	292,600
2402.00825	Resolution invariant deep operator network for PDEs with complex geometries	Neural operators (NO) are discretization invariant deep learning methods with functional output and can approximate any continuous operator. NO have demonstrated the superiority of solving partial differential equations (PDEs) over other deep learning methods. However, the spatial domain of its input function needs to ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	425,737
2405.12399	Diffusion for World Modeling: Visual Details Matter in Atari	World models constitute a promising approach for training reinforcement learning agents in a safe and sample-efficient manner. Recent world models predominantly operate on sequences of discrete latent variables to model environment dynamics. However, this compression into a compact discrete representation may ignore vi...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	455,504
2403.18133	AE SemRL: Learning Semantic Association Rules with Autoencoders	Association Rule Mining (ARM) is the task of learning associations among data features in the form of logical rules. Mining association rules from high-dimensional numerical data, for example, time series data from a large number of sensors in a smart environment, is a computationally intensive task. In this study, we ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	441,777
2111.08951	Exploring Student Representation For Neural Cognitive Diagnosis	Cognitive diagnosis, the goal of which is to obtain the proficiency level of students on specific knowledge concepts, is an fundamental task in smart educational systems. Previous works usually represent each student as a trainable knowledge proficiency vector, which cannot capture the relations of concepts and the bas...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	266,861
2306.17626	Design of Induction Machines using Reinforcement Learning	The design of induction machine is a challenging task due to different electromagnetic and thermal constraints. Quick estimation of machine's dimensions is important in the sales tool to provide quick quotations to customers based on specific requirements. The key part of this process is to select different design para...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	376,767
1909.12436	Autonomous Control of a Tendon-driven Robotic Limb with Elastic Elements Reveals that Added Elasticity can Enhance Learning	Passive elastic elements can contribute to stability, energetic efficiency, and impact absorption in both biological and robotic systems. They also add dynamical complexity which makes them more challenging to model and control. The impact of this added complexity to autonomous learning has not been thoroughly explored...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	147,126
1805.01128	Local Critic Training of Deep Neural Networks	This paper proposes a novel approach to train deep neural networks by unlocking the layer-wise dependency of backpropagation training. The approach employs additional modules called local critic networks besides the main network model to be trained, which are used to obtain error gradients without complete feedforward ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	96,593
2405.01740	The Psychosocial Impacts of Generative AI Harms	The rapid emergence of generative Language Models (LMs) has led to growing concern about the impacts that their unexamined adoption may have on the social well-being of diverse user groups. Meanwhile, LMs are increasingly being adopted in K-20 schools and one-on-one student settings with minimal investigation of potent...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	451,485
2309.05813	Design and Validation of a Metallic Reflectarray for Communications at True Terahertz Frequencies	Wireless communications in the terahertz band (0.1-10 THz) is a promising and key wireless technology enabling ultra-high data rate communication over multi-gigahertz-wide bandwidths, thus fulfilling the demand for denser networks. The complex propagation environment at such high frequencies introduces several challeng...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	391,200
1709.10371	Multi-Kernel Polar Codes: Proof of Polarization and Error Exponents	In this paper, we investigate a novel family of polar codes based on multi-kernel constructions, proving that this construction actually polarizes. To this end, we derive a new and more general proof of polarization, which gives sufficient conditions for kernels to polarize. Finally, we derive the convergence rate of t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	81,768
1608.08782	Training Deep Spiking Neural Networks using Backpropagation	Deep spiking neural networks (SNNs) hold great potential for improving the latency and energy efficiency of deep neural networks through event-based computation. However, training such networks is difficult due to the non-differentiable nature of asynchronous spike events. In this paper, we introduce a novel technique,...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	60,396
2407.10252	Nullpointer at CheckThat! 2024: Identifying Subjectivity from Multilingual Text Sequence	This study addresses a binary classification task to determine whether a text sequence, either a sentence or paragraph, is subjective or objective. The task spans five languages: Arabic, Bulgarian, English, German, and Italian, along with a multilingual category. Our approach involved several key techniques. Initially,...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	472,905
2501.07373	Dynami-CAL GraphNet: A Physics-Informed Graph Neural Network Conserving Linear and Angular Momentum for Dynamical Systems	Accurate, interpretable, and real-time modeling of multi-body dynamical systems is essential for predicting behaviors and inferring physical properties in natural and engineered environments. Traditional physics-based models face scalability challenges and are computationally demanding, while data-driven approaches lik...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	524,375
1210.3853	Transceiver Design For SC-FDE Based MIMO Relay Systems	In this paper, we propose a joint transceiver design for single-carrier frequency-domain equalization (SC-FDE) based multiple-input multiple-output (MIMO) relay systems. To this end, we first derive the optimal minimum mean-squared error linear and decision-feedback frequency-domain equalization filters at the destinat...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	19,106
2412.11813	Designing Semi-Structured Pruning of Graph Convolutional Networks for Skeleton-based Recognition	Deep neural networks (DNNs) are nowadays witnessing a major success in solving many pattern recognition tasks including skeleton-based classification. The deployment of DNNs on edge-devices, endowed with limited time and memory resources, requires designing lightweight and efficient variants of these networks. Pruning ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	517,594
2211.16490	Coder Reviewer Reranking for Code Generation	Sampling diverse programs from a code language model and reranking with model likelihood is a popular method for code generation but it is prone to preferring degenerate solutions. Inspired by collaborative programming, we propose Coder-Reviewer reranking. We augment Coder language models from past work, which generate...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	333,647
2407.03917	Timestep-Aware Correction for Quantized Diffusion Models	Diffusion models have marked a significant breakthrough in the synthesis of semantically coherent images. However, their extensive noise estimation networks and the iterative generation process limit their wider application, particularly on resource-constrained platforms like mobile devices. Existing post-training quan...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	470,345
1703.06912	Application of backpropagation neural networks to both stages of fingerprinting based WIPS	We propose a scheme to employ backpropagation neural networks (BPNNs) for both stages of fingerprinting-based indoor positioning using WLAN/WiFi signal strengths (FWIPS): radio map construction during the offline stage, and localization during the online stage. Given a training radio map (TRM), i.e., a set of coordinat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	70,297
2209.12731	Machine Learning for Improved Gas Network Models in Coordinated Energy Systems	The current energy transition promotes the convergence of operation between the power and natural gas systems. In that direction, it becomes paramount to improve the modeling of non-convex natural gas flow dynamics within the coordinated power and gas dispatch. In this work, we propose a neural-network-constrained opti...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	319,636
2003.04387	Spine intervertebral disc labeling using a fully convolutional redundant counting model	Labeling intervertebral discs is relevant as it notably enables clinicians to understand the relationship between a patient's symptoms (pain, paralysis) and the exact level of spinal cord injury. However manually labeling those discs is a tedious and user-biased task which would benefit from automated methods. While so...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	167,542
2412.02140	SparseGrasp: Robotic Grasping via 3D Semantic Gaussian Splatting from Sparse Multi-View RGB Images	Language-guided robotic grasping is a rapidly advancing field where robots are instructed using human language to grasp specific objects. However, existing methods often depend on dense camera views and struggle to quickly update scenes, limiting their effectiveness in changeable environments. In contrast, we propose...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	513,400
1901.03097	Optimal Channel Estimation for Reciprocity-Based Backscattering with a Full-Duplex MIMO Reader	Backscatter communication (BSC) technology can enable ubiquitous deployment of low-cost sustainable wireless devices. In this work we investigate the efficacy of a full-duplex multiple-input-multiple-output (MIMO) reader for enhancing the limited communication range of monostatic BSC systems. As this performance is str...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	118,340
2405.12236	Fully Distributed Fog Load Balancing with Multi-Agent Reinforcement Learning	Real-time Internet of Things (IoT) applications require real-time support to handle the ever-growing demand for computing resources to process IoT workloads. Fog Computing provides high availability of such resources in a distributed manner. However, these resources must be efficiently managed to distribute unpredictab...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	true	455,452
1712.01643	Discriminant Projection Representation-based Classification for Vision Recognition	Representation-based classification methods such as sparse representation-based classification (SRC) and linear regression classification (LRC) have attracted a lot of attentions. In order to obtain the better representation, a novel method called projection representation-based classification (PRC) is proposed for ima...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	86,137
2305.04885	Decentralized Vehicle Coordination and Lane Switching without Switching of Controllers	This paper proposes a controller for safe lane change manoeuvres of autonomous vehicles using high-order control barrier and Lyapunov functions. The inputs are calculated using a quadratic program (CLF-CBF-QP) which admits short calculation times. The controller allows for adaptive cruise control, lane following, lane ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	362,940
1410.5209	Distributed Methods for High-dimensional and Large-scale Tensor Factorization	Given a high-dimensional large-scale tensor, how can we decompose it into latent factors? Can we process it on commodity computers with limited memory? These questions are closely related to recommender systems, which have modeled rating data not as a matrix but as a tensor to utilize contextual information such as tim...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	true	36,885
2104.10851	Continuous Learning and Adaptation with Membrane Potential and Activation Threshold Homeostasis	Most classical (non-spiking) neural network models disregard internal neuron dynamics and treat neurons as simple input integrators. However, biological neurons have an internal state governed by complex dynamics that plays a crucial role in learning, adaptation and the overall network activity and behaviour. This pape...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	231,738
1911.03154	A General Framework for Adaptation of Neural Machine Translation to Simultaneous Translation	Despite the success of neural machine translation (NMT), simultaneous neural machine translation (SNMT), the task of translating in real time before a full sentence has been observed, remains challenging due to the syntactic structure difference and simultaneity requirements. In this paper, we propose a general framewo...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	152,569
2012.15543	Discovering Dialog Structure Graph for Open-Domain Dialog Generation	Learning interpretable dialog structure from human-human dialogs yields basic insights into the structure of conversation, and also provides background knowledge to facilitate dialog generation. In this paper, we conduct unsupervised discovery of dialog structure from chitchat corpora, and then leverage it to facilitat...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	213,829
2310.05553	Regulation and NLP (RegNLP): Taming Large Language Models	The scientific innovation in Natural Language Processing (NLP) and more broadly in artificial intelligence (AI) is at its fastest pace to date. As large language models (LLMs) unleash a new era of automation, important debates emerge regarding the benefits and risks of their development, deployment and use. Currently, ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	398,203
2409.04934	Maximizing Relation Extraction Potential: A Data-Centric Study to Unveil Challenges and Opportunities	Relation extraction is a Natural Language Processing task that aims to extract relationships from textual data. It is a critical step for information extraction. Due to its wide-scale applicability, research in relation extraction has rapidly scaled to using highly advanced neural networks. Despite their computational ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	486,566
2210.00359	Counter-Adversarial Learning with Inverse Unscented Kalman Filter	In counter-adversarial systems, to infer the strategy of an intelligent adversarial agent, the defender agent needs to cognitively sense the information that the adversary has gathered about the latter. Prior works on the problem employ linear Gaussian state-space models and solve this inverse cognition problem by desi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	320,836
1801.05135	Stabilizing Unstable Periodic Orbits with Delayed Feedback Control in Act-and-Wait Fashion	A delayed feedback control framework for stabilizing unstable periodic orbits of linear periodic time-varying systems is proposed. In this framework, act-and-wait approach is utilized for switching a delayed feedback controller on and off alternately at every integer multiples of the period of the system. By analyzing ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	88,401
1906.10225	Compound Probabilistic Context-Free Grammars for Grammar Induction	We study a formalization of the grammar induction problem that models sentences as being generated by a compound probabilistic context-free grammar. In contrast to traditional formulations which learn a single stochastic grammar, our grammar's rule probabilities are modulated by a per-sentence continuous latent variabl...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	136,385
2108.08569	Large-scale Offshore Wind Farm Electrical Collector System Planning: A Mixed-Integer Linear Programming Approach	In this paper, we propose a planning method for large-scale offshore wind farm (OWF) electrical collector system (ECS) based on mixed integer linear programming, in which the sizing and siting of offshore substations and the lines between wind turbines (WTs) are optimized. We found out that the problem is similar to po...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	251,299
2101.01292	GeCo: Quality Counterfactual Explanations in Real Time	Machine learning is increasingly applied in high-stakes decision making that directly affect people's lives, and this leads to an increased demand for systems to explain their decisions. Explanations often take the form of counterfactuals, which consists of conveying to the end user what she/he needs to change in order...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	214,325
2408.06693	DC3DO: Diffusion Classifier for 3D Objects	Inspired by Geoffrey Hinton emphasis on generative modeling, To recognize shapes, first learn to generate them, we explore the use of 3D diffusion models for object classification. Leveraging the density estimates from these models, our approach, the Diffusion Classifier for 3D Objects (DC3DO), enables zero-shot classi...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	480,303
2412.03069	TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation	We present TokenFlow, a novel unified image tokenizer that bridges the long-standing gap between multimodal understanding and generation. Prior research attempt to employ a single reconstruction-targeted Vector Quantization (VQ) encoder for unifying these two tasks. We observe that understanding and generation require ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	513,801
2006.16011	Intrinsic Autoencoders for Joint Neural Rendering and Intrinsic Image Decomposition	Neural rendering techniques promise efficient photo-realistic image synthesis while at the same time providing rich control over scene parameters by learning the physical image formation process. While several supervised methods have been proposed for this task, acquiring a dataset of images with accurately aligned 3D ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	184,688
2308.13996	Improve in-situ life prediction and classification performance by capturing both the present state and evolution rate of battery aging	This study develops a methodology by capturing both the battery aging state and degradation rate for improved life prediction performance. The aging state is indicated by six physical features of an equivalent circuit model that are extracted from the voltage relaxation data. And the degradation rate is captured by two...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	388,140
1712.04432	Integrated Model, Batch and Domain Parallelism in Training Neural Networks	We propose a new integrated method of exploiting model, batch and domain parallelism for the training of deep neural networks (DNNs) on large distributed-memory computers using minibatch stochastic gradient descent (SGD). Our goal is to find an efficient parallelization strategy for a fixed batch size using $P$ process...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	86,606
1105.5419	Strong Secrecy from Channel Resolvability	We analyze physical-layer security based on the premise that the coding mechanism for secrecy over noisy channels is tied to the notion of channel resolvability. Instead of considering capacity-based constructions, which associate to each message a sub-code that operates just below the capacity of the eavesdropper's ch...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	10,513
1510.02983	OmniGraph: Rich Representation and Graph Kernel Learning	OmniGraph, a novel representation to support a range of NLP classification tasks, integrates lexical items, syntactic dependencies and frame semantic parses into graphs. Feature engineering is folded into the learning through convolution graph kernel learning to explore different extents of the graph. A high-dimensiona...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	47,790
1802.08483	GPU Implementation and Optimization of a Flexible MAP Decoder for Synchronization Correction	In this paper we present an optimized parallel implementation of a flexible MAP decoder for synchronization error correcting codes, supporting a very wide range of code sizes and channel conditions. On mid-range GPUs we demonstrate decoding speedups of more than two orders of magnitude over a CPU implementation of the ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	91,115
2110.07057	High-throughput Phenotyping of Nematode Cysts	The beet cyst nematode (BCN) Heterodera schachtii is a plant pest responsible for crop loss on a global scale. Here, we introduce a high-throughput system based on computer vision that allows quantifying BCN infestation and characterizing nematode cysts through phenotyping. After recording microscopic images of soil ex...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	260,845
1812.11894	Accurate, Data-Efficient, Unconstrained Text Recognition with Convolutional Neural Networks	Unconstrained text recognition is an important computer vision task, featuring a wide variety of different sub-tasks, each with its own set of challenges. One of the biggest promises of deep neural networks has been the convergence and automation of feature extractors from input raw signals, allowing for the highest po...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	117,647
2105.00637	ISTR: End-to-End Instance Segmentation with Transformers	End-to-end paradigms significantly improve the accuracy of various deep-learning-based computer vision models. To this end, tasks like object detection have been upgraded by replacing non-end-to-end components, such as removing non-maximum suppression by training with a set loss based on bipartite matching. However, su...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	233,281
2310.16412	FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness for Semi-Supervised Learning	Semi-Supervised Learning (SSL) has been an effective way to leverage abundant unlabeled data with extremely scarce labeled data. However, most SSL methods are commonly based on instance-wise consistency between different data transformations. Therefore, the label guidance on labeled data is hard to be propagated to unl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	402,723
2403.14652	MemeCraft: Contextual and Stance-Driven Multimodal Meme Generation	Online memes have emerged as powerful digital cultural artifacts in the age of social media, offering not only humor but also platforms for political discourse, social critique, and information dissemination. Their extensive reach and influence in shaping online communities' sentiments make them invaluable tools for ca...	false	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	true	440,179
2101.03882	Transient Stability Analysis of Power Grids with Admissible and Maximal Robust Positively Invariant Sets	The energy transition is causing many stability-related challenges for power systems. Transient stability refers to the ability of a power grid's bus angles to retain synchronism after the occurrence of a major fault. In this paper a set-based approach is presented to assess the transient stability of power systems. Th...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	215,016
2311.11570	Decoupled DETR For Few-shot Object Detection	Few-shot object detection (FSOD), an efficient method for addressing the severe data-hungry problem, has been extensively discussed. Current works have significantly advanced the problem in terms of model and data. However, the overall performance of most FSOD methods still does not fulfill the desired accuracy. In thi...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	408,997
2210.05833	Parameter estimation of the homodyned K distribution based on neural networks and trainable fractional-order moments	Homodyned K (HK) distribution has been widely used to describe the scattering phenomena arising in various research fields, such as ultrasound imaging or optics. In this work, we propose a machine learning based approach to the estimation of the HK distribution parameters. We develop neural networks that can estimate t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	323,017
2407.18998	Towards a Cyber Information Ontology	This paper introduces a set of terms that are intended to act as an interface between cyber ontologies (like a file system ontology or a data fusion ontology) and top- and mid-level ontologies, specifically Basic Formal Ontology and the Common Core Ontologies. These terms center on what makes cyberinformation managemen...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	476,609
2405.01975	Introducing a microstructure-embedded autoencoder approach for reconstructing high-resolution solution field data from a reduced parametric space	In this study, we develop a novel multi-fidelity deep learning approach that transforms low-fidelity solution maps into high-fidelity ones by incorporating parametric space information into a standard autoencoder architecture. This method's integration of parametric space information significantly reduces the need for ...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	451,577
2401.12711	When Redundancy Matters: Machine Teaching of Representations	In traditional machine teaching, a teacher wants to teach a concept to a learner, by means of a finite set of examples, the witness set. But concepts can have many equivalent representations. This redundancy strongly affects the search space, to the extent that teacher and learner may not be able to easily determine th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	423,473

Subsets and Splits

No community queries yet

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