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
2204.12511	PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions	Cross-entropy loss and focal loss are the most common choices when training deep neural networks for classification problems. Generally speaking, however, a good loss function can take on much more flexible forms, and should be tailored for different tasks and datasets. Motivated by how functions can be approximated vi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	293,498
2010.04565	Table Structure Recognition using Top-Down and Bottom-Up Cues	Tables are information-rich structured objects in document images. While significant work has been done in localizing tables as graphic objects in document images, only limited attempts exist on table structure recognition. Most existing literature on structure recognition depends on extraction of meta-features from th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	199,791
2210.06313	The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers	This paper studies the curious phenomenon for machine learning models with Transformer architectures that their activation maps are sparse. By activation map we refer to the intermediate output of the multi-layer perceptrons (MLPs) after a ReLU activation function, and by sparse we mean that on average very few entries...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	323,227
2212.01348	Predict-and-Critic: Accelerated End-to-End Predictive Control for Cloud Computing through Reinforcement Learning	Cloud computing holds the promise of reduced costs through economies of scale. To realize this promise, cloud computing vendors typically solve sequential resource allocation problems, where customer workloads are packed on shared hardware. Virtual machines (VM) form the foundation of modern cloud computing as they hel...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	334,393
2108.11985	Simulating progressive intramural damage leading to aortic dissection using an operator-regression neural network	Aortic dissection progresses via delamination of the medial layer of the wall. Notwithstanding the complexity of this process, insight has been gleaned by studying in vitro and in silico the progression of dissection driven by quasi-static pressurization of the intramural space by fluid injection, which demonstrates th...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	252,355
1703.07394	Deep Learning for Explicitly Modeling Optimization Landscapes	In all but the most trivial optimization problems, the structure of the solutions exhibit complex interdependencies between the input parameters. Decades of research with stochastic search techniques has shown the benefit of explicitly modeling the interactions between sets of parameters and the overall quality of the ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	70,388
1901.10879	Span Model for Open Information Extraction on Accurate Corpus	Open information extraction (Open IE) is a challenging task especially due to its brittle data basis. Most of Open IE systems have to be trained on automatically built corpus and evaluated on inaccurate test set. In this work, we first alleviate this difficulty from both sides of training and test sets. For the former,...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	120,127
2405.01102	Less is More: on the Over-Globalizing Problem in Graph Transformers	Graph Transformer, due to its global attention mechanism, has emerged as a new tool in dealing with graph-structured data. It is well recognized that the global attention mechanism considers a wider receptive field in a fully connected graph, leading many to believe that useful information can be extracted from all the...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	451,221
2102.06315	Segmentation-Renormalized Deep Feature Modulation for Unpaired Image Harmonization	Deep networks are now ubiquitous in large-scale multi-center imaging studies. However, the direct aggregation of images across sites is contraindicated for downstream statistical and deep learning-based image analysis due to inconsistent contrast, resolution, and noise. To this end, in the absence of paired data, varia...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	219,712
2210.14303	WaveBound: Dynamic Error Bounds for Stable Time Series Forecasting	Time series forecasting has become a critical task due to its high practicality in real-world applications such as traffic, energy consumption, economics and finance, and disease analysis. Recent deep-learning-based approaches have shown remarkable success in time series forecasting. Nonetheless, due to the dynamics of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	326,488
2201.02584	Elephant-Human Conflict Mitigation: An Autonomous UAV Approach	Elephant-human conflict (EHC) is one of the major problems in most African and Asian countries. As humans overutilize natural resources for their development, elephants' living area continues to decrease; this leads elephants to invade the human living area and raid crops more frequently, costing millions of dollars an...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	274,582
2409.10524	3CSim: CARLA Corner Case Simulation for Control Assessment in Autonomous Driving	We present the CARLA corner case simulation (3CSim) for evaluating autonomous driving (AD) systems within the CARLA simulator. This framework is designed to address the limitations of traditional AD model training by focusing on non-standard, rare, and cognitively challenging scenarios. These corner cases are crucial f...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	488,774
2010.07343	Causal Multi-Level Fairness	Algorithmic systems are known to impact marginalized groups severely, and more so, if all sources of bias are not considered. While work in algorithmic fairness to-date has primarily focused on addressing discrimination due to individually linked attributes, social science research elucidates how some properties we lin...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	200,772
1810.11347	Generating equilibrium molecules with deep neural networks	Discovery of atomistic systems with desirable properties is a major challenge in chemistry and material science. Here we introduce a novel, autoregressive, convolutional deep neural network architecture that generates molecular equilibrium structures by sequentially placing atoms in three-dimensional space. The model e...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	111,477
2402.18651	Quantifying Human Priors over Social and Navigation Networks	Human knowledge is largely implicit and relational -- do we have a friend in common? can I walk from here to there? In this work, we leverage the combinatorial structure of graphs to quantify human priors over such relational data. Our experiments focus on two domains that have been continuously relevant over evolution...	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	false	false	433,506
2311.17091	Beyond Sole Strength: Customized Ensembles for Generalized Vision-Language Models	Fine-tuning pre-trained vision-language models (VLMs), e.g., CLIP, for the open-world generalization has gained increasing popularity due to its practical value. However, performance advancements are limited when relying solely on intricate algorithmic designs for a single model, even one exhibiting strong performance,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	411,160
2112.11340	Transferable End-to-end Room Layout Estimation via Implicit Encoding	We study the problem of estimating room layouts from a single panorama image. Most former works have two stages: feature extraction and parametric model fitting. Here we propose an end-to-end method that directly predicts parametric layouts from an input panorama image. It exploits an implicit encoding procedure that e...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	272,679
2411.03025	DA-MoE: Addressing Depth-Sensitivity in Graph-Level Analysis through Mixture of Experts	Graph neural networks (GNNs) are gaining popularity for processing graph-structured data. In real-world scenarios, graph data within the same dataset can vary significantly in scale. This variability leads to depth-sensitivity, where the optimal depth of GNN layers depends on the scale of the graph data. Empirically, f...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	505,765
1012.2782	Symmetry invariance for adapting biological systems	We study in this paper certain properties of the responses of dynamical systems to external inputs. The motivation arises from molecular systems biology. and, in particular, the recent discovery of an important transient property, related to Weber's law in psychophysics: "fold-change detection" in adapting systems, the...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	8,527
1509.07449	Structural Vulnerability of Power Grids to Disasters: Bounds, Adversarial Attacks and Reinforcement	Natural Disasters like hurricanes, floods or earthquakes can damage power grid devices and create cascading blackouts and islands. The nature of failure propagation and extent of damage is dependent on the structural features of the grid, which is different from that of random networks. This paper analyzes the structur...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	47,259
0908.0175	BGP Route Analysis and Management Systems	The Border Gateway Protocol (BGP) is an important component in today's IP network infrastructure. As the main routing protocol of the Internet, clear understanding of its dynamics is crucial for configuring, diagnosing and debugging Internet routing problems. Despite the increase in the services that BGP provide such a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	4,200
2208.00593	Long Short-Term Preference Modeling for Continuous-Time Sequential Recommendation	Modeling the evolution of user preference is essential in recommender systems. Recently, dynamic graph-based methods have been studied and achieved SOTA for recommendation, majority of which focus on user's stable long-term preference. However, in real-world scenario, user's short-term preference evolves over time dyna...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	310,904
1410.4598	TiQuant: Software for tissue analysis, quantification and surface reconstruction	Motivation: TiQuant is a modular software tool for efficient quantification of biological tissues based on volume data obtained by biomedical image modalities. It includes a number of versatile image and volume processing chains tailored to the analysis of different tissue types which have been experimentally verified....	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	36,822
1702.07971	Seeing What Is Not There: Learning Context to Determine Where Objects Are Missing	Most of computer vision focuses on what is in an image. We propose to train a standalone object-centric context representation to perform the opposite task: seeing what is not there. Given an image, our context model can predict where objects should exist, even when no object instances are present. Combined with object...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	68,882
2108.07909	A comparative study of universal quantum computing models: towards a physical unification	Quantum computing has been a fascinating research field in quantum physics. Recent progresses motivate us to study in depth the universal quantum computing models (UQCM), which lie at the foundation of quantum computing and have tight connections with fundamental physics. Although being developed decades ago, a physica...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	251,056
2308.04322	Domain Adaptive Person Search via GAN-based Scene Synthesis for Cross-scene Videos	Person search has recently been a challenging task in the computer vision domain, which aims to search specific pedestrians from real cameras.Nevertheless, most surveillance videos comprise only a handful of images of each pedestrian, which often feature identical backgrounds and clothing. Hence, it is difficult to lea...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	384,369
1605.04805	Achievable information rates of ambient backscatter communications	Ambient backscatter is an intriguing wireless communication paradigm that allows small devices to compute and communicate by using only the power they harvest from radio-frequency (RF) signals in the air. Ambient backscattering devices reflect existing RF signals emitted by legacy communications systems, such as digita...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	55,918
1707.01836	Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks	We develop an algorithm which exceeds the performance of board certified cardiologists in detecting a wide range of heart arrhythmias from electrocardiograms recorded with a single-lead wearable monitor. We build a dataset with more than 500 times the number of unique patients than previously studied corpora. On this d...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	76,604
2102.13337	Neural Generalization of Multiple Kernel Learning	Multiple Kernel Learning is a conventional way to learn the kernel function in kernel-based methods. MKL algorithms enhance the performance of kernel methods. However, these methods have a lower complexity compared to deep learning models and are inferior to these models in terms of recognition accuracy. Deep learning ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	222,029
2004.05013	Estimating Individual Treatment Effects through Causal Populations Identification	Estimating the Individual Treatment Effect from observational data, defined as the difference between outcomes with and without treatment or intervention, while observing just one of both, is a challenging problems in causal learning. In this paper, we formulate this problem as an inference from hidden variables and en...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	172,068
2303.17597	Robo3D: Towards Robust and Reliable 3D Perception against Corruptions	The robustness of 3D perception systems under natural corruptions from environments and sensors is pivotal for safety-critical applications. Existing large-scale 3D perception datasets often contain data that are meticulously cleaned. Such configurations, however, cannot reflect the reliability of perception models dur...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	355,269
1505.03093	A new Level-set based Protocol for Accurate Bone Segmentation from CT Imaging	In this work it is proposed a medical image segmentation pipeline for accurate bone segmentation from CT imaging. It is a two-step methodology, with a pre-segmentation step and a segmentation refinement step. First, the user performs a rough segmenting of the desired region of interest. Next, a fully automatic refineme...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	43,042
2405.04378	Splat-MOVER: Multi-Stage, Open-Vocabulary Robotic Manipulation via Editable Gaussian Splatting	We present Splat-MOVER, a modular robotics stack for open-vocabulary robotic manipulation, which leverages the editability of Gaussian Splatting (GSplat) scene representations to enable multi-stage manipulation tasks. Splat-MOVER consists of: (i) ASK-Splat, a GSplat representation that distills semantic and grasp affor...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	452,552
1907.09643	Highlight Every Step: Knowledge Distillation via Collaborative Teaching	High storage and computational costs obstruct deep neural networks to be deployed on resource-constrained devices. Knowledge distillation aims to train a compact student network by transferring knowledge from a larger pre-trained teacher model. However, most existing methods on knowledge distillation ignore the valuabl...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	139,425
1702.03507	Sense-and-Predict: Opportunistic MAC Based on Spatial Interference Correlation for Cognitive Radio Networks	Opportunity detection at secondary transmitters (TXs) is a key technique enabling cognitive radio (CR) networks. Such detection however cannot guarantee reliable communication at secondary receivers (RXs), especially when their association distance is long. To cope with the issue, this paper proposes a novel MAC called...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	68,147
2406.06458	Evaluating the Retrieval Component in LLM-Based Question Answering Systems	Question answering systems (QA) utilizing Large Language Models (LLMs) heavily depend on the retrieval component to provide them with domain-specific information and reduce the risk of generating inaccurate responses or hallucinations. Although the evaluation of retrievers dates back to the early research in Informatio...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	462,584
2410.03496	Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases	Interest is rising in Physics-Informed Neural Networks (PINNs) as a mesh-free alternative to traditional numerical solvers for partial differential equations (PDEs). However, PINNs often struggle to learn high-frequency and multi-scale target solutions. To tackle this problem, we first study a strong Boundary Condition...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	494,812
2305.10825	DiffUTE: Universal Text Editing Diffusion Model	Diffusion model based language-guided image editing has achieved great success recently. However, existing state-of-the-art diffusion models struggle with rendering correct text and text style during generation. To tackle this problem, we propose a universal self-supervised text editing diffusion model (DiffUTE), which...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	365,244
2305.08226	NLP-based Cross-Layer 5G Vulnerabilities Detection via Fuzzing Generated Run-Time Profiling	The effectiveness and efficiency of 5G software stack vulnerability and unintended behavior detection are essential for 5G assurance, especially for its applications in critical infrastructures. Scalability and automation are the main challenges in testing approaches and cybersecurity research. In this paper, we propos...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	364,205
1503.08393	SLOPE is Adaptive to Unknown Sparsity and Asymptotically Minimax	We consider high-dimensional sparse regression problems in which we observe $y = X \beta + z$, where $X$ is an $n \times p$ design matrix and $z$ is an $n$-dimensional vector of independent Gaussian errors, each with variance $\sigma^2$. Our focus is on the recently introduced SLOPE estimator ((Bogdan et al., 2014)), w...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	41,583
2201.01183	Multi-physics inverse homogenization for the design of innovative cellular materials: application to thermo-mechanical problems	We present a new algorithm to design lightweight cellular materials with required properties in a multi-physics context. In particular, we focus on a thermo-mechanical setting, by promoting the design of unit cells characterized both by an isotropic and an anisotropic behaviour with respect to mechanical and thermal re...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	274,173
1901.10072	On the negation of a Dempster-Shafer belief structure based on maximum uncertainty allocation	Probability theory and Dempster-Shafer theory are two germane theories to represent and handle uncertain information. Recent study suggested a transformation to obtain the negation of a probability distribution based on the maximum entropy. Correspondingly, determining the negation of a belief structure, however, is st...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	119,917
2206.14777	System-level Simulation of Reconfigurable Intelligent Surface assisted Wireless Communications System	Reconfigurable intelligent surface (RIS) is an emerging technique employing metasurface to reflect the signal from the source node to the destination node. By smartly reconfiguring the electromagnetic (EM) properties of the metasurface and adjusting the EM parameters of the reflected radio waves, RIS can turn the uncon...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	305,394
2203.16148	Applying Model Checking to Highly-Configurable Safety Critical Software: The SPS-PPS PLC Program	An important aspect of many particle accelerators is the constant evolution and frequent configuration changes that are needed to perform the experiments they are designed for. This often leads to the design of configurable software that can absorb these changes and perform the required control and protection actions. ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	288,671
2007.01350	Uncertainty Prediction for Deep Sequential Regression Using Meta Models	Generating high quality uncertainty estimates for sequential regression, particularly deep recurrent networks, remains a challenging and open problem. Existing approaches often make restrictive assumptions (such as stationarity) yet still perform poorly in practice, particularly in presence of real world non-stationary...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	185,397
2004.00827	Approximate Selection with Guarantees using Proxies	Due to the falling costs of data acquisition and storage, researchers and industry analysts often want to find all instances of rare events in large datasets. For instance, scientists can cheaply capture thousands of hours of video, but are limited by the need to manually inspect long videos to identify relevant object...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	170,750
2410.19105	Conditional diffusions for neural posterior estimation	Neural posterior estimation (NPE), a simulation-based computational approach for Bayesian inference, has shown great success in situations where posteriors are intractable or likelihood functions are treated as "black boxes." Existing NPE methods typically rely on normalizing flows, which transform a base distributions...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	502,158
2410.14916	Cooperation and Fairness in Multi-Agent Reinforcement Learning	Multi-agent systems are trained to maximize shared cost objectives, which typically reflect system-level efficiency. However, in the resource-constrained environments of mobility and transportation systems, efficiency may be achieved at the expense of fairness -- certain agents may incur significantly greater costs or ...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	true	false	false	false	500,262
2010.16298	Learning Vision-based Reactive Policies for Obstacle Avoidance	In this paper, we address the problem of vision-based obstacle avoidance for robotic manipulators. This topic poses challenges for both perception and motion generation. While most work in the field aims at improving one of those aspects, we provide a unified framework for approaching this problem. The main goal of thi...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	204,028
2308.11507	Unsupervised Prototype Adapter for Vision-Language Models	Recently, large-scale pre-trained vision-language models (e.g. CLIP and ALIGN) have demonstrated remarkable effectiveness in acquiring transferable visual representations. To leverage the valuable knowledge encoded within these models for downstream tasks, several fine-tuning approaches, including prompt tuning methods...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	387,166
2010.10836	ReSCo-CC: Unsupervised Identification of Key Disinformation Sentences	Disinformation is often presented in long textual articles, especially when it relates to domains such as health, often seen in relation to COVID-19. These articles are typically observed to have a number of trustworthy sentences among which core disinformation sentences are scattered. In this paper, we propose a novel...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	202,021
1806.08991	Leveraging Implicit Spatial Information in Global Features for Image Retrieval	Most image retrieval methods use global features that aggregate local distinctive patterns into a single representation. However, the aggregation process destroys the relative spatial information by considering orderless sets of local descriptors. We propose to integrate relative spatial information into the aggregatio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	101,266
2101.02463	Decision Support System for an Intelligent Operator of Utility Tunnel Boring Machines	In tunnel construction projects, delays induce high costs. Thus, tunnel boring machines (TBM) operators aim for fast advance rates, without safety compromise, a difficult mission in uncertain ground environments. Finding the optimal control parameters based on the TBM sensors' measurements remains an open research ques...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	214,633
2202.01875	Rethinking Explainability as a Dialogue: A Practitioner's Perspective	As practitioners increasingly deploy machine learning models in critical domains such as health care, finance, and policy, it becomes vital to ensure that domain experts function effectively alongside these models. Explainability is one way to bridge the gap between human decision-makers and machine learning models. Ho...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	278,615
2210.11773	SimANS: Simple Ambiguous Negatives Sampling for Dense Text Retrieval	Sampling proper negatives from a large document pool is vital to effectively train a dense retrieval model. However, existing negative sampling strategies suffer from the uninformative or false negative problem. In this work, we empirically show that according to the measured relevance scores, the negatives ranked arou...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	325,448
1704.01745	How to Make an Image More Memorable? A Deep Style Transfer Approach	Recent works have shown that it is possible to automatically predict intrinsic image properties like memorability. In this paper, we take a step forward addressing the question: "Can we make an image more memorable?". Methods for automatically increasing image memorability would have an impact in many application field...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	71,317
2307.13869	Number Theoretic Accelerated Learning of Physics-Informed Neural Networks	Physics-informed neural networks solve partial differential equations by training neural networks. Since this method approximates infinite-dimensional PDE solutions with finite collocation points, minimizing discretization errors by selecting suitable points is essential for accelerating the learning process. Inspired ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	381,724
2012.02807	Learning summary features of time series for likelihood free inference	There has been an increasing interest from the scientific community in using likelihood-free inference (LFI) to determine which parameters of a given simulator model could best describe a set of experimental data. Despite exciting recent results and a wide range of possible applications, an important bottleneck of LFI ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	209,884
0911.5708	Learning in a Large Function Space: Privacy-Preserving Mechanisms for SVM Learning	Several recent studies in privacy-preserving learning have considered the trade-off between utility or risk and the level of differential privacy guaranteed by mechanisms for statistical query processing. In this paper we study this trade-off in private Support Vector Machine (SVM) learning. We present two efficient me...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	true	false	5,054
2305.02881	Trainability barriers and opportunities in quantum generative modeling	Quantum generative models, in providing inherently efficient sampling strategies, show promise for achieving a near-term advantage on quantum hardware. Nonetheless, important questions remain regarding their scalability. In this work, we investigate the barriers to the trainability of quantum generative models posed by...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	362,201
2211.13337	Multi-Environment Pretraining Enables Transfer to Action Limited Datasets	Using massive datasets to train large-scale models has emerged as a dominant approach for broad generalization in natural language and vision applications. In reinforcement learning, however, a key challenge is that available data of sequential decision making is often not annotated with actions - for example, videos o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	332,442
1411.5172	Learning nonparametric differential equations with operator-valued kernels and gradient matching	Modeling dynamical systems with ordinary differential equations implies a mechanistic view of the process underlying the dynamics. However in many cases, this knowledge is not available. To overcome this issue, we introduce a general framework for nonparametric ODE models using penalized regression in Reproducing Kerne...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	37,708
2207.08134	Editing Out-of-domain GAN Inversion via Differential Activations	Despite the demonstrated editing capacity in the latent space of a pretrained GAN model, inverting real-world images is stuck in a dilemma that the reconstruction cannot be faithful to the original input. The main reason for this is that the distributions between training and real-world data are misaligned, and because...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	308,467
1901.09066	Visualizing Semantic Structures of Sequential Data by Learning Temporal Dependencies	While conventional methods for sequential learning focus on interaction between consecutive inputs, we suggest a new method which captures composite semantic flows with variable-length dependencies. In addition, the semantic structures within given sequential data can be interpreted by visualizing temporal dependencies...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	119,635
1904.12385	Machine Learning in the Air	Thanks to the recent advances in processing speed and data acquisition and storage, machine learning (ML) is penetrating every facet of our lives, and transforming research in many areas in a fundamental manner. Wireless communications is another success story -- ubiquitous in our lives, from handheld devices to wearab...	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	true	129,100
1907.09427	A Systematic Mapping Study on Testing of Machine Learning Programs	We aim to conduct a systematic mapping in the area of testing ML programs. We identify, analyze and classify the existing literature to provide an overview of the area. We followed well-established guidelines of systematic mapping to develop a systematic protocol to identify and review the existing literature. We formu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	139,355
2502.06049	LM2: Large Memory Models	This paper introduces the Large Memory Model (LM2), a decoder-only Transformer architecture enhanced with an auxiliary memory module that aims to address the limitations of standard Transformers in multi-step reasoning, relational argumentation, and synthesizing information distributed over long contexts. The proposed ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	531,898
2408.00106	WAS: Dataset and Methods for Artistic Text Segmentation	Accurate text segmentation results are crucial for text-related generative tasks, such as text image generation, text editing, text removal, and text style transfer. Recently, some scene text segmentation methods have made significant progress in segmenting regular text. However, these methods perform poorly in scenari...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	477,704
2404.04234	player2vec: A Language Modeling Approach to Understand Player Behavior in Games	Methods for learning latent user representations from historical behavior logs have gained traction for recommendation tasks in e-commerce, content streaming, and other settings. However, this area still remains relatively underexplored in video and mobile gaming contexts. In this work, we present a novel method for ov...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	444,555
1902.07708	A Stability Analysis for the Acceleration-based Robust Position Control of Robot Manipulators via Disturbance Observer	This paper proposes a new nonlinear stability analysis for the acceleration-based robust position control of robot manipulators by using Disturbance Observer (DOb). It is shown that if the nominal inertia matrix is properly tuned in the design of DOb, then the position error asymptotically goes to zero in regulation co...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	122,043
2404.19065	HELPER-X: A Unified Instructable Embodied Agent to Tackle Four Interactive Vision-Language Domains with Memory-Augmented Language Models	Recent research on instructable agents has used memory-augmented Large Language Models (LLMs) as task planners, a technique that retrieves language-program examples relevant to the input instruction and uses them as in-context examples in the LLM prompt to improve the performance of the LLM in inferring the correct act...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	450,488
1309.3439	Measuring the similarity of PML documents with RFID-based sensors	The Electronic Product Code (EPC) Network is an important part of the Internet of Things. The Physical Mark-Up Language (PML) is to represent and de-scribe data related to objects in EPC Network. The PML documents of each component to exchange data in EPC Network system are XML documents based on PML Core schema. For m...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	27,020
2310.01188	Quantifying the Plausibility of Context Reliance in Neural Machine Translation	Establishing whether language models can use contextual information in a human-plausible way is important to ensure their trustworthiness in real-world settings. However, the questions of when and which parts of the context affect model generations are typically tackled separately, with current plausibility evaluations...	true	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	396,314
2311.17012	Counter-terrorism in cyber-physical spaces: Best practices and technologies from the state of the art	Context: The demand for protection and security of physical spaces and urban areas increased with the escalation of terroristic attacks in recent years. We envision with the proposed cyber-physical systems and spaces, a city that would indeed become a smarter urbanistic object, proactively providing alerts and being pr...	false	false	false	false	false	false	false	false	false	true	false	false	true	true	false	false	false	true	411,121
2303.13641	No Love Among Haters: Negative Interactions Reduce Hate Community Engagement	While online hate groups pose significant risks to the health of online platforms and safety of marginalized groups, little is known about what causes users to become active in hate groups and the effect of social interactions on furthering their engagement. We address this gap by first developing tools to find hate co...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	353,762
1301.2260	Confidence Inference in Bayesian Networks	We present two sampling algorithms for probabilistic confidence inference in Bayesian networks. These two algorithms (we call them AIS-BN-mu and AIS-BN-sigma algorithms) guarantee that estimates of posterior probabilities are with a given probability within a desired precision bound. Our algorithms are based on recent ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	20,936
1901.01977	Accelerating Goal-Directed Reinforcement Learning by Model Characterization	We propose a hybrid approach aimed at improving the sample efficiency in goal-directed reinforcement learning. We do this via a two-step mechanism where firstly, we approximate a model from Model-Free reinforcement learning. Then, we leverage this approximate model along with a notion of reachability using Mean First P...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	118,090
2102.12029	Theoretical Understandings of Product Embedding for E-commerce Machine Learning	Product embeddings have been heavily investigated in the past few years, serving as the cornerstone for a broad range of machine learning applications in e-commerce. Despite the empirical success of product embeddings, little is known on how and why they work from the theoretical standpoint. Analogous results from the ...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	221,586
1810.06913	How to share a cake with a secret agent	In this note we study a problem of fair division in the absence of full information. We give an algorithm which solves the following problem: n $\ge$ 2 persons want to cut a cake into n shares so that each person will get at least 1/n of the cake for his or her own measure, furthermore the preferences of one person are...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	110,532
2302.06727	Deep Learning Predicts Prevalent and Incident Parkinson's Disease From UK Biobank Fundus Imaging	Parkinson's disease is the world's fastest-growing neurological disorder. Research to elucidate the mechanisms of Parkinson's disease and automate diagnostics would greatly improve the treatment of patients with Parkinson's disease. Current diagnostic methods are expensive and have limited availability. Considering the...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	345,508
2106.10938	A Game-Theoretic Taxonomy of Visual Concepts in DNNs	In this paper, we rethink how a DNN encodes visual concepts of different complexities from a new perspective, i.e. the game-theoretic multi-order interactions between pixels in an image. Beyond the categorical taxonomy of objects and the cognitive taxonomy of textures and shapes, we provide a new taxonomy of visual con...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	242,220
1611.06527	Robust Regularized Least-Squares Beamforming Approach to Signal Estimation	In this paper, we address the problem of robust adaptive beamforming of signals received by a linear array. The challenge associated with the beamforming problem is twofold. Firstly, the process requires the inversion of the usually ill-conditioned covariance matrix of the received signals. Secondly, the steering vecto...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	64,206
2304.09061	A Scalable Framework for Automatic Playlist Continuation on Music Streaming Services	Music streaming services often aim to recommend songs for users to extend the playlists they have created on these services. However, extending playlists while preserving their musical characteristics and matching user preferences remains a challenging task, commonly referred to as Automatic Playlist Continuation (APC)...	false	false	true	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	358,920
1909.04572	Deep MR Brain Image Super-Resolution Using Spatio-Structural Priors	High resolution Magnetic Resonance (MR) images are desired for accurate diagnostics. In practice, image resolution is restricted by factors like hardware and processing constraints. Recently, deep learning methods have been shown to produce compelling state-of-the-art results for image enhancement/super-resolution. Pay...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	144,843
2106.10698	Plant Disease Detection Using Image Processing and Machine Learning	One of the important and tedious task in agricultural practices is the detection of the disease on crops. It requires huge time as well as skilled labor. This paper proposes a smart and efficient technique for detection of crop disease which uses computer vision and machine learning techniques. The proposed system is a...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	242,122
2501.16616	Few-Shot Optimized Framework for Hallucination Detection in Resource-Limited NLP Systems	Hallucination detection in text generation remains an ongoing struggle for natural language processing (NLP) systems, frequently resulting in unreliable outputs in applications such as machine translation and definition modeling. Existing methods struggle with data scarcity and the limitations of unlabeled datasets, as...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	528,032
1905.13464	Effective writing style imitation via combinatorial paraphrasing	Stylometry can be used to profile or deanonymize authors against their will based on writing style. Style transfer provides a defence. Current techniques typically use either encoder-decoder architectures or rule-based algorithms. Crucially, style transfer must reliably retain original semantic content to be actually d...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	133,142
2112.04839	Design and Implementation of Real-Time Localization System (RTLS) based on UWB and TDoA Algorithm	Nowadays, accurate localization plays an essential role in many fields, like target tracking and path planning. The challenges of indoor localization include inadequate localization accuracy, unreasonable anchor deployment in complex scenarios, lack of stability, and high cost. So the universal positioning technologies...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	270,659
2201.13256	Proximal Denoiser for Convergent Plug-and-Play Optimization with Nonconvex Regularization	Plug-and-Play (PnP) methods solve ill-posed inverse problems through iterative proximal algorithms by replacing a proximal operator by a denoising operation. When applied with deep neural network denoisers, these methods have shown state-of-the-art visual performance for image restoration problems. However, their theor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	277,927
math/0309120	An invariant of finitary codes with finite expected square root coding length	Let $p$ and $q$ be probability vectors with the same entropy $h$. Denote by $B(p)$ the Bernoulli shift indexed by $\Z$ with marginal distribution $p$. Suppose that $\phi$ is a measure preserving homomorphism from $B(p)$ to $B(q)$. We prove that if the coding length of $\phi$ has a finite 1/2 moment, then $\sigma_p^2=\s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	540,667
1910.08288	Hierarchical Attentive Knowledge Graph Embedding for Personalized Recommendation	Knowledge graphs (KGs) have proven to be effective for high-quality recommendation, where the connectivities between users and items provide rich and complementary information to user-item interactions. Most existing methods, however, are insufficient to exploit the KGs for capturing user preferences, as they either re...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	149,836
1805.00706	On the Structure of Interlinked Cycle Structures with Interlocked Outer Cycles	For index coding problems with special structure on the side-information graphs called Interlinked Cycle (IC) structures index codes have been proposed in the literature (C. Thapa, L. Ong, and S. Johnson, "Interlinked Cycles for Index Coding: Generalizing Cycles and Cliques", in IEEE Trans. Inf. Theory, vol. 63, no. 6,...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	96,492
1501.07417	An improved rate region for the classical-quantum broadcast channel	We present a new achievable rate region for the two-user binary-input classical-quantum broadcast channel. The result is a generalization of the classical Marton-Gelfand-Pinsker region and is provably larger than the best previously known rate region for classical-quantum broadcast channels. The proof of achievability ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,705
1506.06075	Natural Gas Flow Solutions with Guarantees: A Monotone Operator Theory Approach	We consider balanced flows in a natural gas transmission network and discuss computationally hard problems such as establishing if solution of the underlying nonlinear gas flow equations exists, if it is unique, and finding the solution. Particular topologies, e.g. trees, are known to be easy to solve based on a variat...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	44,377
2209.00989	Deep Learning-based ECG Classification on Raspberry PI using a Tensorflow Lite Model based on PTB-XL Dataset	The number of IoT devices in healthcare is expected to rise sharply due to increased demand since the COVID-19 pandemic. Deep learning and IoT devices are being employed to monitor body vitals and automate anomaly detection in clinical and non-clinical settings. Most of the current technology requires the transmission ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	315,747
2106.07079	Decentralized Inertial Best-Response with Voluntary and Limited Communication in Random Communication Networks	Multiple autonomous agents interact over a random communication network to maximize their individual utility functions which depend on the actions of other agents. We consider decentralized best-response with inertia type algorithms in which agents form beliefs about the future actions of other players based on local i...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	240,763
2010.03743	Visual News: Benchmark and Challenges in News Image Captioning	We propose Visual News Captioner, an entity-aware model for the task of news image captioning. We also introduce Visual News, a large-scale benchmark consisting of more than one million news images along with associated news articles, image captions, author information, and other metadata. Unlike the standard image cap...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	199,512
1601.06057	Topological descriptors for 3D surface analysis	We investigate topological descriptors for 3D surface analysis, i.e. the classification of surfaces according to their geometric fine structure. On a dataset of high-resolution 3D surface reconstructions we compute persistence diagrams for a 2D cubical filtration. In the next step we investigate different topological d...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	51,209
2206.11181	On the Role of Spatial, Spectral, and Temporal Processing for DNN-based Non-linear Multi-channel Speech Enhancement	Employing deep neural networks (DNNs) to directly learn filters for multi-channel speech enhancement has potentially two key advantages over a traditional approach combining a linear spatial filter with an independent tempo-spectral post-filter: 1) non-linear spatial filtering allows to overcome potential restrictions ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	304,186
2309.15275	Efficient Low-rank Backpropagation for Vision Transformer Adaptation	The increasing scale of vision transformers (ViT) has made the efficient fine-tuning of these large models for specific needs a significant challenge in various applications. This issue originates from the computationally demanding matrix multiplications required during the backpropagation process through linear layers...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	394,907

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