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
2304.09088	A Field Test of Bandit Algorithms for Recommendations: Understanding the Validity of Assumptions on Human Preferences in Multi-armed Bandits	Personalized recommender systems suffuse modern life, shaping what media we read and what products we consume. Algorithms powering such systems tend to consist of supervised learning-based heuristics, such as latent factor models with a variety of heuristically chosen prediction targets. Meanwhile, theoretical treatmen...	true	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	358,932
2502.07396	Optimality in importance sampling: a gentle survey	The performance of the Monte Carlo sampling methods relies on the crucial choice of a proposal density. The notion of optimality is fundamental to design suitable adaptive procedures of the proposal density within Monte Carlo schemes. This work is an exhaustive review around the concept of optimality in importance samp...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	532,582
1505.04214	Algorithmic Connections Between Active Learning and Stochastic Convex Optimization	Interesting theoretical associations have been established by recent papers between the fields of active learning and stochastic convex optimization due to the common role of feedback in sequential querying mechanisms. In this paper, we continue this thread in two parts by exploiting these relations for the first time ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	43,163
1607.07515	Single Stage Prediction with Embedded Topic Modeling of Online Reviews for Mobile App Management	Mobile apps are one of the building blocks of the mobile digital economy. A differentiating feature of mobile apps to traditional enterprise software is online reviews, which are available on app marketplaces and represent a valuable source of consumer feedback on the app. We create a supervised topic modeling approach...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	59,031
2112.09568	Nearest neighbor search with compact codes: A decoder perspective	Modern approaches for fast retrieval of similar vectors on billion-scaled datasets rely on compressed-domain approaches such as binary sketches or product quantization. These methods minimize a certain loss, typically the mean squared error or other objective functions tailored to the retrieval problem. In this paper, ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	272,186
2110.07992	BayesAoA: A Bayesian method for Computation Efficient Angle of Arrival Estimation	The angle of Arrival (AoA) estimation is of great interest in modern communication systems. Traditional maximum likelihood-based iterative algorithms are sensitive to initialization and cannot be used online. We propose a Bayesian method to find AoA that is insensitive towards initialization. The proposed method is les...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	261,204
2206.14599	Information geometry of excess and housekeeping entropy production	A nonequilibrium system is characterized by a set of thermodynamic forces and fluxes which give rise to entropy production (EP). We show that these forces and fluxes have an information-geometric structure, which allows us to decompose EP into contributions from different types of forces in general (linear and nonlinea...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	305,337
2311.11065	Enhancing Transformer-Based Segmentation for Breast Cancer Diagnosis using Auto-Augmentation and Search Optimisation Techniques	Breast cancer remains a critical global health challenge, necessitating early and accurate detection for effective treatment. This paper introduces a methodology that combines automated image augmentation selection (RandAugment) with search optimisation strategies (Tree-based Parzen Estimator) to identify optimal value...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	408,779
2203.11471	Ray3D: ray-based 3D human pose estimation for monocular absolute 3D localization	In this paper, we propose a novel monocular ray-based 3D (Ray3D) absolute human pose estimation with calibrated camera. Accurate and generalizable absolute 3D human pose estimation from monocular 2D pose input is an ill-posed problem. To address this challenge, we convert the input from pixel space to 3D normalized ray...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	286,927
1711.02396	Unconstrained Scene Text and Video Text Recognition for Arabic Script	Building robust recognizers for Arabic has always been challenging. We demonstrate the effectiveness of an end-to-end trainable CNN-RNN hybrid architecture in recognizing Arabic text in videos and natural scenes. We outperform previous state-of-the-art on two publicly available video text datasets - ALIF and ACTIV. For...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	84,059
2204.11448	High-Efficiency Lossy Image Coding Through Adaptive Neighborhood Information Aggregation	Questing for learned lossy image coding (LIC) with superior compression performance and computation throughput is challenging. The vital factor behind it is how to intelligently explore Adaptive Neighborhood Information Aggregation (ANIA) in transform and entropy coding modules. To this end, Integrated Convolution and ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	293,156
1601.04126	Engineering Safety in Machine Learning	Machine learning algorithms are increasingly influencing our decisions and interacting with us in all parts of our daily lives. Therefore, just like for power plants, highways, and myriad other engineered sociotechnical systems, we must consider the safety of systems involving machine learning. In this paper, we first ...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	50,985
2201.02352	Degrees of Freedom Analysis of Mechanisms using the New Zebra Crossing Method	Mobility, which is a basic property for a mechanism has to be analyzed to find the degrees of freedom. A quick method for calculation of degrees of freedom in a mechanism is proposed in this work. The mechanism is represented in a way that resembles a zebra crossing. An algorithm is proposed which is used to determine ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	274,518
2407.05197	A Generalized Transformer-based Radio Link Failure Prediction Framework in 5G RANs	Radio link failure (RLF) prediction system in Radio Access Networks (RANs) is critical for ensuring seamless communication and meeting the stringent requirements of high data rates, low latency, and improved reliability in 5G networks. However, weather conditions such as precipitation, humidity, temperature, and wind i...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	470,864
2010.03807	Information Theory Measures via Multidimensional Gaussianization	Information theory is an outstanding framework to measure uncertainty, dependence and relevance in data and systems. It has several desirable properties for real world applications: it naturally deals with multivariate data, it can handle heterogeneous data types, and the measures can be interpreted in physical units. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	199,538
2301.12276	ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts	We introduce ProtoSeg, a novel model for interpretable semantic image segmentation, which constructs its predictions using similar patches from the training set. To achieve accuracy comparable to baseline methods, we adapt the mechanism of prototypical parts and introduce a diversity loss function that increases the va...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	342,469
2004.14281	A Wearable Social Interaction Aid for Children with Autism	With most recent estimates giving an incidence rate of 1 in 68 children in the United States, the autism spectrum disorder (ASD) is a growing public health crisis. Many of these children struggle to make eye contact, recognize facial expressions, and engage in social interactions. Today the standard for treatment of th...	true	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	174,830
2411.06396	A Variance Minimization Approach to Temporal-Difference Learning	Fast-converging algorithms are a contemporary requirement in reinforcement learning. In the context of linear function approximation, the magnitude of the smallest eigenvalue of the key matrix is a major factor reflecting the convergence speed. Traditional value-based RL algorithms focus on minimizing errors. This pape...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	507,097
1912.00477	How to GAN away Detector Effects	LHC analyses directly comparing data and simulated events bear the danger of using first-principle predictions only as a black-box part of event simulation. We show how simulations, for instance, of detector effects can instead be inverted using generative networks. This allows us to reconstruct parton level informatio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	155,785
2208.09123	IAN: Iterated Adaptive Neighborhoods for manifold learning and dimensionality estimation	Invoking the manifold assumption in machine learning requires knowledge of the manifold's geometry and dimension, and theory dictates how many samples are required. However, in applications data are limited, sampling may not be uniform, and manifold properties are unknown and (possibly) non-pure; this implies that neig...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	313,594
1904.09654	Integrating Association Rules with Decision Trees in Object-Relational Databases	Research has provided evidence that associative classification produces more accurate results compared to other classification models. The Classification Based on Association (CBA) is one of the famous Associative Classification algorithms that generates accurate classifiers. However, current association classification...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	128,443
1904.12710	Radio Resource Allocation for Reliable Out-of-coverage V2V Communications	We explore a new approach to radio resource allocation for vehicle-to-vehicle (V2V) communications in case of out-of-coverage areas that are delimited by network infrastructure. By collecting and predicting information such as vehicle velocity, density and message traffic, the network infrastructure ensures reliability...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	129,205
2204.00523	Estimating the Jacobian matrix of an unknown multivariate function from sample values by means of a neural network	We describe, implement and test a novel method for training neural networks to estimate the Jacobian matrix $J$ of an unknown multivariate function $F$. The training set is constructed from finitely many pairs $(x,F(x))$ and it contains no explicit information about $J$. The loss function for backpropagation is based o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	289,290
2110.14010	MisConv: Convolutional Neural Networks for Missing Data	Processing of missing data by modern neural networks, such as CNNs, remains a fundamental, yet unsolved challenge, which naturally arises in many practical applications, like image inpainting or autonomous vehicles and robots. While imputation-based techniques are still one of the most popular solutions, they frequentl...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	263,377
2310.06484	Memory efficient location recommendation through proximity-aware representation	Sequential location recommendation plays a huge role in modern life, which can enhance user experience, bring more profit to businesses and assist in government administration. Although methods for location recommendation have evolved significantly thanks to the development of recommendation systems, there is still lim...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	398,599
2407.12784	AgentPoison: Red-teaming LLM Agents via Poisoning Memory or Knowledge Bases	LLM agents have demonstrated remarkable performance across various applications, primarily due to their advanced capabilities in reasoning, utilizing external knowledge and tools, calling APIs, and executing actions to interact with environments. Current agents typically utilize a memory module or a retrieval-augmented...	false	false	false	false	false	true	true	false	false	false	false	false	true	false	false	false	false	false	474,071
2006.07749	Parametric Bootstrap for Differentially Private Confidence Intervals	The goal of this paper is to develop a practical and general-purpose approach to construct confidence intervals for differentially private parametric estimation. We find that the parametric bootstrap is a simple and effective solution. It cleanly reasons about variability of both the data sample and the randomized priv...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,924
1303.1494	Two Procedures for Compiling Influence Diagrams	Two algorithms are presented for "compiling" influence diagrams into a set of simple decision rules. These decision rules define simple-to-execute, complete, consistent, and near-optimal decision procedures. These compilation algorithms can be used to derive decision procedures for human teams solving time constrained ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	22,709
2305.15077	Contrastive Learning of Sentence Embeddings from Scratch	Contrastive learning has been the dominant approach to train state-of-the-art sentence embeddings. Previous studies have typically learned sentence embeddings either through the use of human-annotated natural language inference (NLI) data or via large-scale unlabeled sentences in an unsupervised manner. However, even i...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	367,440
2001.00116	Exploiting the Sensitivity of $L_2$ Adversarial Examples to Erase-and-Restore	By adding carefully crafted perturbations to input images, adversarial examples (AEs) can be generated to mislead neural-network-based image classifiers. $L_2$ adversarial perturbations by Carlini and Wagner (CW) are among the most effective but difficult-to-detect attacks. While many countermeasures against AEs have b...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	159,135
2202.08533	AISHELL-NER: Named Entity Recognition from Chinese Speech	Named Entity Recognition (NER) from speech is among Spoken Language Understanding (SLU) tasks, aiming to extract semantic information from the speech signal. NER from speech is usually made through a two-step pipeline that consists of (1) processing the audio using an Automatic Speech Recognition (ASR) system and (2) a...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	280,916
2305.18356	RT-kNNS Unbound: Using RT Cores to Accelerate Unrestricted Neighbor Search	The problem of identifying the k-Nearest Neighbors (kNNS) of a point has proven to be very useful both as a standalone application and as a subroutine in larger applications. Given its far-reaching applicability in areas such as machine learning and point clouds, extensive research has gone into leveraging GPU accelera...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	368,980
2310.06948	A Variational Autoencoder Framework for Robust, Physics-Informed Cyberattack Recognition in Industrial Cyber-Physical Systems	Cybersecurity of Industrial Cyber-Physical Systems is drawing significant concerns as data communication increasingly leverages wireless networks. A lot of data-driven methods were develope for detecting cyberattacks, but few are focused on distinguishing them from equipment faults. In this paper, we develop a data-dri...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	398,772
1904.02357	Plan, Write, and Revise: an Interactive System for Open-Domain Story Generation	Story composition is a challenging problem for machines and even for humans. We present a neural narrative generation system that interacts with humans to generate stories. Our system has different levels of human interaction, which enables us to understand at what stage of story-writing human collaboration is most pro...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	126,407
2211.12432	Multi-task Learning for Camera Calibration	For a number of tasks, such as 3D reconstruction, robotic interface, autonomous driving, etc., camera calibration is essential. In this study, we present a unique method for predicting intrinsic (principal point offset and focal length) and extrinsic (baseline, pitch, and translation) properties from a pair of images. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	332,107
2205.14400	Agent-based Simulation of District-based Elections	In district-based elections, electors cast votes in their respective districts. In each district, the party with maximum votes wins the corresponding seat in the governing body. The election result is based on the number of seats won by different parties. In this system, locations of electors across the districts may s...	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	299,350
2409.06535	PoseEmbroider: Towards a 3D, Visual, Semantic-aware Human Pose Representation	Aligning multiple modalities in a latent space, such as images and texts, has shown to produce powerful semantic visual representations, fueling tasks like image captioning, text-to-image generation, or image grounding. In the context of human-centric vision, albeit CLIP-like representations encode most standard human ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	487,162
1902.01349	An Argument-Marker Model for Syntax-Agnostic Proto-Role Labeling	Semantic proto-role labeling (SPRL) is an alternative to semantic role labeling (SRL) that moves beyond a categorical definition of roles, following Dowty's feature-based view of proto-roles. This theory determines agenthood vs. patienthood based on a participant's instantiation of more or less typical agent vs. patien...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	120,631
2501.14232	Learning-Augmented Online Control for Decarbonizing Water Infrastructures	Water infrastructures are essential for drinking water supply, irrigation, fire protection, and other critical applications. However, water pumping systems, which are key to transporting water to the point of use, consume significant amounts of energy and emit millions of tons of greenhouse gases annually. With the wid...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	527,034
2404.08002	ApproxDARTS: Differentiable Neural Architecture Search with Approximate Multipliers	Integrating the principles of approximate computing into the design of hardware-aware deep neural networks (DNN) has led to DNNs implementations showing good output quality and highly optimized hardware parameters such as low latency or inference energy. In this work, we present ApproxDARTS, a neural architecture searc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	446,070
2210.14184	Learning Ability of Interpolating Deep Convolutional Neural Networks	It is frequently observed that overparameterized neural networks generalize well. Regarding such phenomena, existing theoretical work mainly devotes to linear settings or fully-connected neural networks. This paper studies the learning ability of an important family of deep neural networks, deep convolutional neural ne...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	326,452
1212.5250	A genetic algorithm applied to the validation of building thermal models	This paper presents the coupling of a building thermal simulation code with genetic algorithms (GAs). GAs are randomized search algorithms that are based on the mechanisms of natural selection and genetics. We show that this coupling allows the location of defective sub-models of a building thermal model i.e. parts of ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	20,521
1605.00495	Coalition Formability Semantics with Conflict-Eliminable Sets of Arguments	We consider abstract-argumentation-theoretic coalition formability in this work. Taking a model from political alliance among political parties, we will contemplate profitability, and then formability, of a coalition. As is commonly understood, a group forms a coalition with another group for a greater good, the goodne...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	55,352
2010.06087	Contrast and Classify: Training Robust VQA Models	Recent Visual Question Answering (VQA) models have shown impressive performance on the VQA benchmark but remain sensitive to small linguistic variations in input questions. Existing approaches address this by augmenting the dataset with question paraphrases from visual question generation models or adversarial perturba...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	200,360
2203.04762	Autonomous soft hand grasping -- Literature review	Autonomous grasping remains challenging as unlike humans, robots do not possess a sophisticated sensing nor delicate interaction capability with the real environment. Among other efforts that tried to close the gap between them, anthropomorphic robotic hands is the most prominent direction. However, exactly following h...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	284,595
2212.05386	A Hierarchical Approach for Investigating Social Features of a City from Mobile Phone Call Detail Records	Cellphone service-providers continuously collect Call Detail Records (CDR) as a usage log containing spatio-temporal traces of phone users. We proposed a multi-layered hierarchical analytical model for large spatio-temporal datasets and applied that for the progressive exploration of social features of a city, e.g., so...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	335,774
1303.4840	Asynchronous Cellular Operations on Gray Images Extracting Topographic Shape Features and Their Relations	A variety of operations of cellular automata on gray images is presented. All operations are of a wave-front nature finishing in a stable state. They are used to extract shape descripting gray objects robust to a variety of pattern distortions. Topographic terms are used: "lakes", "dales", "dales of dales". It is shown...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	23,038
1505.01802	Optimal Decision-Theoretic Classification Using Non-Decomposable Performance Metrics	We provide a general theoretical analysis of expected out-of-sample utility, also referred to as decision-theoretic classification, for non-decomposable binary classification metrics such as F-measure and Jaccard coefficient. Our key result is that the expected out-of-sample utility for many performance metrics is prov...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	42,882
2410.20202	An Efficient Watermarking Method for Latent Diffusion Models via Low-Rank Adaptation	The rapid proliferation of deep neural networks (DNNs) is driving a surge in model watermarking technologies, as the trained deep models themselves serve as intellectual properties. The core of existing model watermarking techniques involves modifying or tuning the models' weights. However, with the emergence of increa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	502,697
2009.13019	Concentrated Multi-Grained Multi-Attention Network for Video Based Person Re-Identification	Occlusion is still a severe problem in the video-based Re-IDentification (Re-ID) task, which has a great impact on the success rate. The attention mechanism has been proved to be helpful in solving the occlusion problem by a large number of existing methods. However, their attention mechanisms still lack the capability...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	197,610
2211.06377	Two-Step Online Trajectory Planning of a Quadcopter in Indoor Environments with Obstacles	This paper presents a two-step algorithm for online trajectory planning in indoor environments with unknown obstacles. In the first step, sampling-based path planning techniques such as the optimal Rapidly exploring Random Tree (RRT*) algorithm and the Line-of-Sight (LOS) algorithm are employed to generate a collision-...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	329,870
2501.13484	MambaQuant: Quantizing the Mamba Family with Variance Aligned Rotation Methods	Mamba is an efficient sequence model that rivals Transformers and demonstrates significant potential as a foundational architecture for various tasks. Quantization is commonly used in neural networks to reduce model size and computational latency. However, applying quantization to Mamba remains underexplored, and exist...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	526,713
2305.12144	DiffCap: Exploring Continuous Diffusion on Image Captioning	Current image captioning works usually focus on generating descriptions in an autoregressive manner. However, there are limited works that focus on generating descriptions non-autoregressively, which brings more decoding diversity. Inspired by the success of diffusion models on generating natural-looking images, we pro...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	365,861
2312.09750	Attention-Based VR Facial Animation with Visual Mouth Camera Guidance for Immersive Telepresence Avatars	Facial animation in virtual reality environments is essential for applications that necessitate clear visibility of the user's face and the ability to convey emotional signals. In our scenario, we animate the face of an operator who controls a robotic Avatar system. The use of facial animation is particularly valuable ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	415,866
2009.07641	BSN++: Complementary Boundary Regressor with Scale-Balanced Relation Modeling for Temporal Action Proposal Generation	Generating human action proposals in untrimmed videos is an important yet challenging task with wide applications. Current methods often suffer from the noisy boundary locations and the inferior quality of confidence scores used for proposal retrieving. In this paper, we present BSN++, a new framework which exploits co...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	196,002
2302.02283	Recurrence With Correlation Network for Medical Image Registration	We present Recurrence with Correlation Network (RWCNet), a medical image registration network with multi-scale features and a cost volume layer. We demonstrate that these architectural features improve medical image registration accuracy in two image registration datasets prepared for the MICCAI 2022 Learn2Reg Workshop...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	343,937
2208.08034	Deep Reinforcement Learning based Robot Navigation in Dynamic Environments using Occupancy Values of Motion Primitives	This paper presents a Deep Reinforcement Learning based navigation approach in which we define the occupancy observations as heuristic evaluations of motion primitives, rather than using raw sensor data. Our method enables fast mapping of the occupancy data, generated by multi-sensor fusion, into trajectory values in 3...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	313,224
2207.07087	Parameter-Efficient Prompt Tuning Makes Generalized and Calibrated Neural Text Retrievers	Prompt tuning attempts to update few task-specific parameters in pre-trained models. It has achieved comparable performance to fine-tuning of the full parameter set on both language understanding and generation tasks. In this work, we study the problem of prompt tuning for neural text retrievers. We introduce parameter...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	308,099
2211.16994	Continual Learning with Distributed Optimization: Does CoCoA Forget?	We focus on the continual learning problem where the tasks arrive sequentially and the aim is to perform well on the newly arrived task without performance degradation on the previously seen tasks. In contrast to the continual learning literature focusing on the centralized setting, we investigate the distributed estim...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	333,822
2406.17689	Robust Gray Codes Approaching the Optimal Rate	Robust Gray codes were introduced by (Lolck and Pagh, SODA 2024). Informally, a robust Gray code is a (binary) Gray code $\mathcal{G}$ so that, given a noisy version of the encoding $\mathcal{G}(j)$ of an integer $j$, one can recover $\hat{j}$ that is close to $j$ (with high probability over the noise). Such codes have...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	467,680
2404.18209	4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on Relational DBs	Although RDBs store vast amounts of rich, informative data spread across interconnected tables, the progress of predictive machine learning models as applied to such tasks arguably falls well behind advances in other domains such as computer vision or natural language processing. This deficit stems, at least in part, f...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	450,169
2212.10378	Data Curation Alone Can Stabilize In-context Learning	In-context learning (ICL) enables large language models (LLMs) to perform new tasks by prompting them with a sequence of training examples. However, it is known that ICL is very sensitive to the choice of training examples: randomly sampling examples from a training set leads to high variance in performance. In this pa...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	337,431
2107.03299	Big Data Information and Nowcasting: Consumption and Investment from Bank Transactions in Turkey	We use the aggregate information from individual-to-firm and firm-to-firm in Garanti BBVA Bank transactions to mimic domestic private demand. Particularly, we replicate the quarterly national accounts aggregate consumption and investment (gross fixed capital formation) and its bigger components (Machinery and Equipment...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	245,117
2304.12610	Fast Continuous Subgraph Matching over Streaming Graphs via Backtracking Reduction	Streaming graphs are drawing increasing attention in both academic and industrial communities as many graphs in real applications evolve over time. Continuous subgraph matching (shorted as CSM) aims to report the incremental matches of a query graph in such streaming graphs. It involves two major steps, i.e., candidate...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	360,289
2104.12218	Breast Mass Detection with Faster R-CNN: On the Feasibility of Learning from Noisy Annotations	In this work we study the impact of noise on the training of object detection networks for the medical domain, and how it can be mitigated by improving the training procedure. Annotating large medical datasets for training data-hungry deep learning models is expensive and time consuming. Leveraging information that is ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	232,144
2306.14136	Scribble-supervised Cell Segmentation Using Multiscale Contrastive Regularization	Current state-of-the-art supervised deep learning-based segmentation approaches have demonstrated superior performance in medical image segmentation tasks. However, such supervised approaches require fully annotated pixel-level ground-truth labels, which are labor-intensive and time-consuming to acquire. Recently, Scri...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	375,568
1805.08718	Inferring Human Traits From Facebook Statuses	This paper explores the use of language models to predict 20 human traits from users' Facebook status updates. The data was collected by the myPersonality project, and includes user statuses along with their personality, gender, political identification, religion, race, satisfaction with life, IQ, self-disclosure, fair...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	98,236
2209.13019	Fast online ranking with fairness of exposure	As recommender systems become increasingly central for sorting and prioritizing the content available online, they have a growing impact on the opportunities or revenue of their items producers. For instance, they influence which recruiter a resume is recommended to, or to whom and how much a music track, video or news...	false	false	false	false	true	true	true	false	false	false	false	false	false	true	false	false	false	false	319,740
1912.06513	Reducing selfish routing inefficiencies using traffic lights	Traffic congestion games abstract away from the costs of junctions in transport networks, yet, in urban environments, these often impact journey times significantly. In this paper we equip congestion games with traffic lights, modelled as junction-based waiting cycles, therefore enabling more realistic route planning s...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	true	157,367
2404.01901	Learning-based model augmentation with LFRs	Nonlinear system identification (NL-SI) has proven to be effective in obtaining accurate models for highly complex systems. Especially, recent encoder-based methods for artificial neural networks state-space (ANN-SS) models have achieved state-of-the-art performance on various benchmarks, while offering consistency and...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	443,639
2004.11228	Using GAN to Enhance the Accuracy of Indoor Human Activity Recognition	Indoor human activity recognition (HAR) explores the correlation between human body movements and the reflected WiFi signals to classify different activities. By analyzing WiFi signal patterns, especially the dynamics of channel state information (CSI), different activities can be distinguished. Gathering CSI data is e...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	173,854
2401.07331	Rapid Estimation of Left Ventricular Contractility with a Physics-Informed Neural Network Inverse Modeling Approach	Physics-based computer models based on numerical solution of the governing equations generally cannot make rapid predictions, which in turn, limits their applications in the clinic. To address this issue, we developed a physics-informed neural network (PINN) model that encodes the physics of a closed-loop blood circula...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	421,496
2408.02623	YOWOv3: An Efficient and Generalized Framework for Human Action Detection and Recognition	In this paper, we propose a new framework called YOWOv3, which is an improved version of YOWOv2, designed specifically for the task of Human Action Detection and Recognition. This framework is designed to facilitate extensive experimentation with different configurations and supports easy customization of various compo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	478,698
1602.00287	Additive Approximations in High Dimensional Nonparametric Regression via the SALSA	High dimensional nonparametric regression is an inherently difficult problem with known lower bounds depending exponentially in dimension. A popular strategy to alleviate this curse of dimensionality has been to use additive models of \emph{first order}, which model the regression function as a sum of independent funct...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	51,556
2402.14469	Reimagining Anomalies: What If Anomalies Were Normal?	Deep learning-based methods have achieved a breakthrough in image anomaly detection, but their complexity introduces a considerable challenge to understanding why an instance is predicted to be anomalous. We introduce a novel explanation method that generates multiple counterfactual examples for each anomaly, capturing...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	431,700
2101.06779	Few Shot Dialogue State Tracking using Meta-learning	Dialogue State Tracking (DST) forms a core component of automated chatbot based systems designed for specific goals like hotel, taxi reservation, tourist information, etc. With the increasing need to deploy such systems in new domains, solving the problem of zero/few-shot DST has become necessary. There has been a risi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	215,833
2305.19802	Neuro-Causal Factor Analysis	Factor analysis (FA) is a statistical tool for studying how observed variables with some mutual dependences can be expressed as functions of mutually independent unobserved factors, and it is widely applied throughout the psychological, biological, and physical sciences. We revisit this classic method from the comparat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	369,693
1911.13271	Unpaired Image Translation via Adaptive Convolution-based Normalization	Disentangling content and style information of an image has played an important role in recent success in image translation. In this setting, how to inject given style into an input image containing its own content is an important issue, but existing methods followed relatively simple approaches, leaving room for impro...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	155,636
1808.03114	Classifier-Guided Visual Correction of Noisy Labels for Image Classification Tasks	Training data plays an essential role in modern applications of machine learning. However, gathering labeled training data is time-consuming. Therefore, labeling is often outsourced to less experienced users, or completely automated. This can introduce errors, which compromise valuable training data, and lead to subopt...	true	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	104,882
1102.5407	Random Networks with given Rich-club Coefficient	In complex networks it is common to model a network or generate a surrogate network based on the conservation of the network's degree distribution. We provide an alternative network model based on the conservation of connection density within a set of nodes. This density is measure by the rich-club coefficient. We pres...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	9,383
2501.17559	Solving Urban Network Security Games: Learning Platform, Benchmark, and Challenge for AI Research	After the great achievement of solving two-player zero-sum games, more and more AI researchers focus on solving multiplayer games. To facilitate the development of designing efficient learning algorithms for solving multiplayer games, we propose a multiplayer game platform for solving Urban Network Security Games (\tex...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	528,373
2203.09830	Laneformer: Object-aware Row-Column Transformers for Lane Detection	We present Laneformer, a conceptually simple yet powerful transformer-based architecture tailored for lane detection that is a long-standing research topic for visual perception in autonomous driving. The dominant paradigms rely on purely CNN-based architectures which often fail in incorporating relations of long-range...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	286,304
2407.00553	Cooperative Advisory Residual Policies for Congestion Mitigation	Fleets of autonomous vehicles can mitigate traffic congestion through simple actions, thus improving many socioeconomic factors such as commute time and gas costs. However, these approaches are limited in practice as they assume precise control over autonomous vehicle fleets, incur extensive installation costs for a ce...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	468,908
1208.3811	State distributions and minimum relative entropy noise sequences in uncertain stochastic systems: the discrete time case	The paper is concerned with a dissipativity theory and robust performance analysis of discrete-time stochastic systems driven by a statistically uncertain random noise. The uncertainty is quantified by the conditional relative entropy of the actual probability law of the noise with respect to a nominal product measure ...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	18,141
2403.06032	Matrix Concentration Inequalities for Sensor Selection	In this work, we address the problem of sensor selection for state estimation via Kalman filtering. We consider a linear time-invariant (LTI) dynamical system subject to process and measurement noise, where the sensors we use to perform state estimation are randomly drawn according to a sampling with replacement policy...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	436,267
2411.11082	STOP: Spatiotemporal Orthogonal Propagation for Weight-Threshold-Leakage Synergistic Training of Deep Spiking Neural Networks	The prevailing of artificial intelligence-of-things calls for higher energy-efficient edge computing paradigms, such as neuromorphic agents leveraging brain-inspired spiking neural network (SNN) models based on spatiotemporally sparse binary spikes. However, the lack of efficient and high-accuracy deep SNN learning alg...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	508,913
1910.04376	RLCard: A Toolkit for Reinforcement Learning in Card Games	RLCard is an open-source toolkit for reinforcement learning research in card games. It supports various card environments with easy-to-use interfaces, including Blackjack, Leduc Hold'em, Texas Hold'em, UNO, Dou Dizhu and Mahjong. The goal of RLCard is to bridge reinforcement learning and imperfect information games, an...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	148,750
1708.01713	Automatic Question-Answering Using A Deep Similarity Neural Network	Automatic question-answering is a classical problem in natural language processing, which aims at designing systems that can automatically answer a question, in the same way as human does. In this work, we propose a deep learning based model for automatic question-answering. First the questions and answers are embedded...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	78,434
2205.06234	SIBILA: A novel interpretable ensemble of general-purpose machine learning models applied to medical contexts	Personalized medicine remains a major challenge for scientists. The rapid growth of Machine learning and Deep learning has made them a feasible al- ternative for predicting the most appropriate therapy for individual patients. However, the need to develop a custom model for every dataset, the lack of interpretation of ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	296,181
2404.08686	Extractive text summarisation of Privacy Policy documents using machine learning approaches	This work demonstrates two Privacy Policy (PP) summarisation models based on two different clustering algorithms: K-means clustering and Pre-determined Centroid (PDC) clustering. K-means is decided to be used for the first model after an extensive evaluation of ten commonly used clustering algorithms. The summariser mo...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	446,353
2206.06177	Transductive CLIP with Class-Conditional Contrastive Learning	Inspired by the remarkable zero-shot generalization capacity of vision-language pre-trained model, we seek to leverage the supervision from CLIP model to alleviate the burden of data labeling. However, such supervision inevitably contains the label noise, which significantly degrades the discriminative power of the cla...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	302,283
2407.08633	A Novel Framework for Automated Warehouse Layout Generation	Optimizing warehouse layouts is crucial due to its significant impact on efficiency and productivity. We present an AI-driven framework for automated warehouse layout generation. This framework employs constrained beam search to derive optimal layouts within given spatial parameters, adhering to all functional requirem...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	472,239
2303.17968	VDN-NeRF: Resolving Shape-Radiance Ambiguity via View-Dependence Normalization	We propose VDN-NeRF, a method to train neural radiance fields (NeRFs) for better geometry under non-Lambertian surface and dynamic lighting conditions that cause significant variation in the radiance of a point when viewed from different angles. Instead of explicitly modeling the underlying factors that result in the v...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	355,418
1707.03471	Proceedings of the 2017 AdKDD & TargetAd Workshop	Proceedings of the 2017 AdKDD and TargetAd Workshop held in conjunction with the 23rd ACM SIGKDD Conference on Knowledge Discovery and Data Mining Halifax, Nova Scotia, Canada.	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	76,872
2409.14324	Unveiling Narrative Reasoning Limits of Large Language Models with Trope in Movie Synopses	Large language models (LLMs) equipped with chain-of-thoughts (CoT) prompting have shown significant multi-step reasoning capabilities in factual content like mathematics, commonsense, and logic. However, their performance in narrative reasoning, which demands greater abstraction capabilities, remains unexplored. This s...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	490,423
2004.07111	Hand-worn Haptic Interface for Drone Teleoperation	Drone teleoperation is usually accomplished using remote radio controllers, devices that can be hard to master for inexperienced users. Moreover, the limited amount of information fed back to the user about the robot's state, often limited to vision, can represent a bottleneck for operation in several conditions. In th...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	172,692
1812.08338	Quantum computing and the brain: quantum nets, dessins d'enfants and neural networks	In this paper, we will discuss a formal link between neural networks and quantum computing. For that purpose we will present a simple model for the description of the neural network by forming sub-graphs of the whole network with the same or a similar state. We will describe the interaction between these areas by close...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	116,985
2212.13992	Social-Aware Clustered Federated Learning with Customized Privacy Preservation	A key feature of federated learning (FL) is to preserve the data privacy of end users. However, there still exist potential privacy leakage in exchanging gradients under FL. As a result, recent research often explores the differential privacy (DP) approaches to add noises to the computing results to address privacy con...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	338,467
2308.13735	MST-compression: Compressing and Accelerating Binary Neural Networks with Minimum Spanning Tree	Binary neural networks (BNNs) have been widely adopted to reduce the computational cost and memory storage on edge-computing devices by using one-bit representation for activations and weights. However, as neural networks become wider/deeper to improve accuracy and meet practical requirements, the computational burden ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	388,031
1210.5292	Low-Complexity Demodulation for Interleaved OFDMA Downlink System Using Circular Convolution	In this paper, a new low-complexity demodulation scheme is proposed for interleaved orthogonal frequency division multiple access (OFDMA) downlink system with N subcarriers and M users using circular convolution. In the proposed scheme, each user's signal is extracted from the received interleaved OFDMA signal of M use...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	19,268

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