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
2109.02369	Point-Based Neural Rendering with Per-View Optimization	There has recently been great interest in neural rendering methods. Some approaches use 3D geometry reconstructed with Multi-View Stereo (MVS) but cannot recover from the errors of this process, while others directly learn a volumetric neural representation, but suffer from expensive training and inference. We introduc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	253,724
1802.00373	EMG Pattern Classification to Control a Hand Orthosis for Functional Grasp Assistance after Stroke	Wearable orthoses can function both as assistive devices, which allow the user to live independently, and as rehabilitation devices, which allow the user to regain use of an impaired limb. To be fully wearable, such devices must have intuitive controls, and to improve quality of life, the device should enable the user ...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	89,402
1812.10457	Optimal Secure GDoF of Symmetric Gaussian Wiretap Channel with a Helper	We study a symmetric Gaussian wiretap channel with a helper, where a confidential message is sent from a transmitter to a legitimate receiver, in the presence of a helper and an eavesdropper, under a weak notion of secrecy constraint. For this setting, we characterize the optimal secure generalized degrees-of-freedom (...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	117,369
2411.10500	Edge-Only Universal Adversarial Attacks in Distributed Learning	Distributed learning frameworks, which partition neural network models across multiple computing nodes, enhance efficiency in collaborative edge-cloud systems but may also introduce new vulnerabilities. In this work, we explore the feasibility of generating universal adversarial attacks when an attacker has access to t...	false	false	false	false	true	false	false	false	false	false	false	true	true	false	false	false	false	false	508,670
1204.2114	Image-based Vehicle Classification System	Electronic toll collection (ETC) system has been a common trend used for toll collection on toll road nowadays. The implementation of electronic toll collection allows vehicles to travel at low or full speed during the toll payment, which help to avoid the traffic delay at toll road. One of the major components of an e...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	15,385
1908.05657	Non-coherent Detection and Bit Error Rate for an Ambient Backscatter Link in Time-Selective Fading	This paper focuses on the non-coherent detection in ambient backscatter communication, which is highly appealing for systems where the trade-off between signaling overhead and the actual data transmission is very critical. Modeling the time-selective fading channel as a first-order autoregressive (AR) process, we propo...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	141,774
2103.03932	Prosumer Behavior: Decision Making with Bounded Horizon	Most studies of prosumer decision making in the smart grid have focused on single, temporally discrete decisions within the framework of expected utility theory (EUT) and behavioral theories such as prospect theory. In this work, we study prosumer decision making in a more natural, ongoing market situation in which a p...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	223,457
2305.05845	Sketching the Future (STF): Applying Conditional Control Techniques to Text-to-Video Models	The proliferation of video content demands efficient and flexible neural network based approaches for generating new video content. In this paper, we propose a novel approach that combines zero-shot text-to-video generation with ControlNet to improve the output of these models. Our method takes multiple sketched frames...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	363,308
1703.07475	PKU-MMD: A Large Scale Benchmark for Continuous Multi-Modal Human Action Understanding	Despite the fact that many 3D human activity benchmarks being proposed, most existing action datasets focus on the action recognition tasks for the segmented videos. There is a lack of standard large-scale benchmarks, especially for current popular data-hungry deep learning based methods. In this paper, we introduce a ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	70,400
2408.12772	Symmetric masking strategy enhances the performance of Masked Image Modeling	Masked Image Modeling (MIM) is a technique in self-supervised learning that focuses on acquiring detailed visual representations from unlabeled images by estimating the missing pixels in randomly masked sections. It has proven to be a powerful tool for the preliminary training of Vision Transformers (ViTs), yielding im...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	482,870
2407.08148	SCPNet: Unsupervised Cross-modal Homography Estimation via Intra-modal Self-supervised Learning	We propose a novel unsupervised cross-modal homography estimation framework based on intra-modal Self-supervised learning, Correlation, and consistent feature map Projection, namely SCPNet. The concept of intra-modal self-supervised learning is first presented to facilitate the unsupervised cross-modal homography estim...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	472,032
1803.02728	Towards the Creation of a Large Corpus of Synthetically-Identified Clinical Notes	Clinical notes often describe the most important aspects of a patient's physiology and are therefore critical to medical research. However, these notes are typically inaccessible to researchers without prior removal of sensitive protected health information (PHI), a natural language processing (NLP) task referred to as...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	92,115
1510.05569	Estimating the Causal Impact of Recommendation Systems from Observational Data	Recommendation systems are an increasingly prominent part of the web, accounting for up to a third of all traffic on several of the world's most popular sites. Nevertheless, little is known about how much activity such systems actually cause over and above activity that would have occurred via other means (e.g., search...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	48,037
2204.03687	Statistical QoS Analysis of Reconfigurable Intelligent Surface-assisted D2D Communication	This work performs the statistical QoS analysis of a Rician block-fading reconfigurable intelligent surface (RIS)-assisted D2D link in which the transmit node operates under delay QoS constraints. First, we perform mode selection for the D2D link, in which the D2D pair can either communicate directly by relaying data f...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	290,395
2104.03226	Evaluation of Time Series Forecasting Models for Estimation of PM2.5 Levels in Air	Air contamination in urban areas has risen consistently over the past few years. Due to expanding industrialization and increasing concentration of toxic gases in the climate, the air is getting more poisonous step by step at an alarming rate. Since the arrival of the Coronavirus pandemic, it is getting more critical t...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	229,016
2206.00960	SparseDet: Towards End-to-End 3D Object Detection	In this paper, we propose SparseDet for end-to-end 3D object detection from point cloud. Existing works on 3D object detection rely on dense object candidates over all locations in a 3D or 2D grid following the mainstream methods for object detection in 2D images. However, this dense paradigm requires expertise in data...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	300,314
0907.1099	Multi-User Diversity vs. Accurate Channel State Information in MIMO Downlink Channels	In a multiple transmit antenna, single antenna per receiver downlink channel with limited channel state feedback, we consider the following question: given a constraint on the total system-wide feedback load, is it preferable to get low-rate/coarse channel feedback from a large number of receivers or high-rate/high-qua...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	4,055
2108.13101	Densely Semantic Enhancement for Domain Adaptive Region-free Detectors	Unsupervised domain adaptive object detection aims to adapt a well-trained detector from its original source domain with rich labeled data to a new target domain with unlabeled data. Previous works focus on improving the domain adaptability of region-based detectors, e.g., Faster-RCNN, through matching cross-domain ins...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	252,712
2406.18967	Structural Attention: Rethinking Transformer for Unpaired Medical Image Synthesis	Unpaired medical image synthesis aims to provide complementary information for an accurate clinical diagnostics, and address challenges in obtaining aligned multi-modal medical scans. Transformer-based models excel in imaging translation tasks thanks to their ability to capture long-range dependencies. Although effecti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	468,255
1911.09781	Beyond Synthetic Noise: Deep Learning on Controlled Noisy Labels	Performing controlled experiments on noisy data is essential in understanding deep learning across noise levels. Due to the lack of suitable datasets, previous research has only examined deep learning on controlled synthetic label noise, and real-world label noise has never been studied in a controlled setting. This pa...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	154,607
2001.01347	Elastic Bulk Synchronous Parallel Model for Distributed Deep Learning	The bulk synchronous parallel (BSP) is a celebrated synchronization model for general-purpose parallel computing that has successfully been employed for distributed training of machine learning models. A prevalent shortcoming of the BSP is that it requires workers to wait for the straggler at every iteration. To amelio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	159,472
2409.08527	EHC-MM: Embodied Holistic Control for Mobile Manipulation	Mobile manipulation typically entails the base for mobility, the arm for accurate manipulation, and the camera for perception. It is necessary to follow the principle of Distant Mobility, Close Grasping(DMCG) in holistic control. We propose Embodied Holistic Control for Mobile Manipulation(EHC-MM) with the embodied fun...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	487,947
2212.12011	A Method for Crash Prediction and Avoidance Using Hidden Markov Models	In recent years, automotive technology has made a steady progress. In particular, Advanced Driver Assistance System (ADAS) has enabled many safety features in commercial vehicles, for instance, pedestrian detection, lane keeping assist, emergency automatic braking, etc. Although these features provide drivers with a sa...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	337,935
2408.13185	Dual Grid-Forming Converter	This letter proposes a dual model for grid-forming (GFM) controlled converters. The model is inspired from the observation that the structures of the active and reactive power equations of lossy synchronous machine models are almost symmetrical in terms of armature resistance and transient reactance. The proposed devic...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	483,042
1111.0508	Geometric Graph Properties of the Spatial Preferred Attachment model	The spatial preferred attachment (SPA) model is a model for networked information spaces such as domains of the World Wide Web, citation graphs, and on-line social networks. It uses a metric space to model the hidden attributes of the vertices. Thus, vertices are elements of a metric space, and link formation depends o...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	12,879
1507.01839	Dependency-based Convolutional Neural Networks for Sentence Embedding	In sentence modeling and classification, convolutional neural network approaches have recently achieved state-of-the-art results, but all such efforts process word vectors sequentially and neglect long-distance dependencies. To exploit both deep learning and linguistic structures, we propose a tree-based convolutional ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	44,912
2305.09777	BSGAN: A Novel Oversampling Technique for Imbalanced Pattern Recognitions	Class imbalanced problems (CIP) are one of the potential challenges in developing unbiased Machine Learning (ML) models for predictions. CIP occurs when data samples are not equally distributed between the two or multiple classes. Borderline-Synthetic Minority Oversampling Techniques (SMOTE) is one of the approaches th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	364,765
2406.10200	SSTFB: Leveraging self-supervised pretext learning and temporal self-attention with feature branching for real-time video polyp segmentation	Polyps are early cancer indicators, so assessing occurrences of polyps and their removal is critical. They are observed through a colonoscopy screening procedure that generates a stream of video frames. Segmenting polyps in their natural video screening procedure has several challenges, such as the co-existence of imag...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	464,271
2202.00102	Real-Time Facial Expression Recognition using Facial Landmarks and Neural Networks	This paper presents a lightweight algorithm for feature extraction, classification of seven different emotions, and facial expression recognition in a real-time manner based on static images of the human face. In this regard, a Multi-Layer Perceptron (MLP) neural network is trained based on the foregoing algorithm. In ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	278,026
2111.12903	Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation	Consistency learning using input image, feature, or network perturbations has shown remarkable results in semi-supervised semantic segmentation, but this approach can be seriously affected by inaccurate predictions of unlabelled training images. There are two consequences of these inaccurate predictions: 1) the trainin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	268,116
2210.10176	Entity-Focused Dense Passage Retrieval for Outside-Knowledge Visual Question Answering	Most Outside-Knowledge Visual Question Answering (OK-VQA) systems employ a two-stage framework that first retrieves external knowledge given the visual question and then predicts the answer based on the retrieved content. However, the retrieved knowledge is often inadequate. Retrievals are frequently too general and fa...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	324,809
2109.05444	RIS and Cell-Free Massive MIMO: A Marriage For Harsh Propagation Environments	This paper considers Cell-Free Massive Multiple Input Multiple Output (MIMO) systems with the assistance of an RIS for enhancing the system performance. Distributed maximum-ratio combining (MRC) is considered at the access points (APs). We introduce an aggregated channel estimation method that provides sufficient infor...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	254,793
2204.07520	Resource-Aware Distributed Submodular Maximization: A Paradigm for Multi-Robot Decision-Making	Multi-robot decision-making is the process where multiple robots coordinate actions. In this paper, we aim for efficient and effective multi-robot decision-making despite the robots' limited on-board resources and the often resource-demanding complexity of their tasks. We introduce the first algorithm enabling the robo...	false	false	false	false	true	false	false	true	false	false	true	false	false	false	true	false	false	false	291,736
2110.12175	Analysis of Thompson Sampling for Partially Observable Contextual Multi-Armed Bandits	Contextual multi-armed bandits are classical models in reinforcement learning for sequential decision-making associated with individual information. A widely-used policy for bandits is Thompson Sampling, where samples from a data-driven probabilistic belief about unknown parameters are used to select the control action...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	262,739
2303.09012	Exploring the Power of Generative Deep Learning for Image-to-Image Translation and MRI Reconstruction: A Cross-Domain Review	Deep learning has become a prominent computational modeling tool in the areas of computer vision and image processing in recent years. This research comprehensively analyzes the different deep-learning methods used for image-to-image translation and reconstruction in the natural and medical imaging domains. We examine ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	351,863
1504.02762	Image patch analysis of sunspots and active regions. II. Clustering via matrix factorization	Separating active regions that are quiet from potentially eruptive ones is a key issue in Space Weather applications. Traditional classification schemes such as Mount Wilson and McIntosh have been effective in relating an active region large scale magnetic configuration to its ability to produce eruptive events. Howeve...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	41,954
2106.06083	Analyzing Neural Jacobian Methods in Applications of Visual Servoing and Kinematic Control	Designing adaptable control laws that can transfer between different robots is a challenge because of kinematic and dynamic differences, as well as in scenarios where external sensors are used. In this work, we empirically investigate a neural networks ability to approximate the Jacobian matrix for an application in Ca...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	240,346
2011.06822	SHAD3S: A model to Sketch, Shade and Shadow	Hatching is a common method used by artists to accentuate the third dimension of a sketch, and to illuminate the scene. Our system SHAD3S attempts to compete with a human at hatching generic three-dimensional (3D) shapes, and also tries to assist her in a form exploration exercise. The novelty of our approach lies in t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	206,354
1709.00348	Inferring Networked Device Categories from Low-Level Activity Indicators	We study the problem of inferring the type of a networked device in a home network by leveraging low level traffic activity indicators seen at commodity home gateways. We analyze a dataset of detailed device network activity obtained from 240 subscriber homes of a large European ISP and extract a number of traffic and ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	79,888
2011.04872	An Efficient Closed-Form Method for Optimal Hybrid Force-Velocity Control	This paper derives a closed-form method for computing hybrid force-velocity control. The key idea is to maximize the kinematic conditioning of the mechanical system, which includes a robot, free objects, a rigid environment and contact constraints. The method is complete, in that it always produces an optimal/near opti...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	205,728
1512.05665	Probabilistic Programming with Gaussian Process Memoization	Gaussian Processes (GPs) are widely used tools in statistics, machine learning, robotics, computer vision, and scientific computation. However, despite their popularity, they can be difficult to apply; all but the simplest classification or regression applications require specification and inference over complex covari...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	50,248
1605.06190	Modularity in Complex Multilayer Networks with Multiple Aspects: A Static Perspective	Complex systems are usually illustrated by networks which captures the topology of the interactions between the entities. To better understand the roles played by the entities in the system one needs to uncover the underlying community structure of the system. In recent years, systems with interactions that have variou...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	56,096
2405.03851	Querying in Constant Expected Time with Learned Indexes	Learned indexes leverage machine learning models to accelerate query answering in databases, showing impressive practical performance. However, theoretical understanding of these methods remains incomplete. Existing research suggests that learned indexes have superior asymptotic complexity compared to their non-learned...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	452,333
2212.04624	The Hybridization of Branch and Bound with Metaheuristics for Nonconvex Multiobjective Optimization	A hybrid framework combining the branch and bound method with multiobjective evolutionary algorithms is proposed for nonconvex multiobjective optimization. The hybridization exploits the complementary character of the two optimization strategies. A multiobjective evolutionary algorithm is intended for inducing tight lo...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	335,510
2010.02650	If beam search is the answer, what was the question?	Quite surprisingly, exact maximum a posteriori (MAP) decoding of neural language generators frequently leads to low-quality results. Rather, most state-of-the-art results on language generation tasks are attained using beam search despite its overwhelmingly high search error rate. This implies that the MAP objective al...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	199,121
2112.01914	SGM3D: Stereo Guided Monocular 3D Object Detection	Monocular 3D object detection aims to predict the object location, dimension and orientation in 3D space alongside the object category given only a monocular image. It poses a great challenge due to its ill-posed property which is critically lack of depth information in the 2D image plane. While there exist approaches ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	269,670
2108.09637	Graph-Convolutional Deep Learning to Identify Optimized Molecular Configurations	Tackling molecular optimization problems using conventional computational methods is challenging, because the determination of the optimized configuration is known to be an NP-hard problem. Recently, there has been increasing interest in applying different deep-learning techniques to benchmark molecular optimization ta...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	251,666
2008.03324	Fisher Information Field: an Efficient and Differentiable Map for Perception-aware Planning	Considering visual localization accuracy at the planning time gives preference to robot motion that can be better localized and thus has the potential of improving vision-based navigation, especially in visually degraded environments. To integrate the knowledge about localization accuracy in motion planning algorithms,...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	190,861
2305.04213	Robust Image Ordinal Regression with Controllable Image Generation	Image ordinal regression has been mainly studied along the line of exploiting the order of categories. However, the issues of class imbalance and category overlap that are very common in ordinal regression were largely overlooked. As a result, the performance on minority categories is often unsatisfactory. In this pape...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	362,681
2304.12951	Neural Implicit Shape Editing using Boundary Sensitivity	Neural fields are receiving increased attention as a geometric representation due to their ability to compactly store detailed and smooth shapes and easily undergo topological changes. Compared to classic geometry representations, however, neural representations do not allow the user to exert intuitive control over the...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	360,400
2308.11417	ScanNet++: A High-Fidelity Dataset of 3D Indoor Scenes	We present ScanNet++, a large-scale dataset that couples together capture of high-quality and commodity-level geometry and color of indoor scenes. Each scene is captured with a high-end laser scanner at sub-millimeter resolution, along with registered 33-megapixel images from a DSLR camera, and RGB-D streams from an iP...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	387,128
1802.03001	Statistical Learnability of Generalized Additive Models based on Total Variation Regularization	A generalized additive model (GAM, Hastie and Tibshirani (1987)) is a nonparametric model by the sum of univariate functions with respect to each explanatory variable, i.e., $f({\mathbf x}) = \sum f_j(x_j)$, where $x_j\in\mathbb{R}$ is $j$-th component of a sample ${\mathbf x}\in \mathbb{R}^p$. In this paper, we introd...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	89,876
2208.01136	Exploring the GLIDE model for Human Action-effect Prediction	We address the following action-effect prediction task. Given an image depicting an initial state of the world and an action expressed in text, predict an image depicting the state of the world following the action. The prediction should have the same scene context as the input image. We explore the use of the recently...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	311,072
1912.01413	Spatial images from temporal data	Traditional paradigms for imaging rely on the use of a spatial structure, either in the detector (pixels arrays) or in the illumination (patterned light). Removal of the spatial structure in the detector or illumination, i.e., imaging with just a single-point sensor, would require solving a very strongly ill-posed inve...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	156,080
1804.06489	Simplex Queues for Hot-Data Download	In cloud storage systems, hot data is usually replicated over multiple nodes in order to accommodate simultaneous access by multiple users as well as increase the fault tolerance of the system. Recent cloud storage research has proposed using availability codes, which is a special class of erasure codes, as a more stor...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	95,310
2304.09818	What Should Be Balanced in a "Balanced" Face Recognition Dataset?	The issue of demographic disparities in face recognition accuracy has attracted increasing attention in recent years. Various face image datasets have been proposed as 'fair' or 'balanced' to assess the accuracy of face recognition algorithms across demographics. These datasets typically balance the number of identitie...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	359,181
2301.02818	App Review Driven Collaborative Bug Finding	Software development teams generally welcome any effort to expose bugs in their code base. In this work, we build on the hypothesis that mobile apps from the same category (e.g., two web browser apps) may be affected by similar bugs in their evolution process. It is therefore possible to transfer the experience of one ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	339,606
2003.14291	Hurricanes and hashtags: Characterizing online collective attention for natural disasters	We study collective attention paid towards hurricanes through the lens of $n$-grams on Twitter, a social media platform with global reach. Using hurricane name mentions as a proxy for awareness, we find that the exogenous temporal dynamics are remarkably similar across storms, but that overall collective attention vari...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	170,457
2409.05070	Lepskii Principle for Distributed Kernel Ridge Regression	Parameter selection without communicating local data is quite challenging in distributed learning, exhibing an inconsistency between theoretical analysis and practical application of it in tackling distributively stored data. Motivated by the recently developed Lepskii principle and non-privacy communication protocol f...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	486,626
2102.12362	Detecting Compliance of Privacy Policies with Data Protection Laws	Privacy Policies are the legal documents that describe the practices that an organization or company has adopted in the handling of the personal data of its users. But as policies are a legal document, they are often written in extensive legal jargon that is difficult to understand. Though work has been done on privacy...	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	221,711
2209.10166	Chaotic Hedging with Iterated Integrals and Neural Networks	In this paper, we extend the Wiener-Ito chaos decomposition to the class of continuous semimartingales that are exponentially integrable, which includes in particular affine and some polynomial diffusion processes. By omitting the orthogonality in the expansion, we are able to show that every $p$-integrable functional ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	318,774
2210.08197	DyFEn: Agent-Based Fee Setting in Payment Channel Networks	In recent years, with the development of easy to use learning environments, implementing and reproducible benchmarking of reinforcement learning algorithms has been largely accelerated by utilizing these frameworks. In this article, we introduce the Dynamic Fee learning Environment (DyFEn), an open-source real-world fi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	324,036
2205.11255	A Template-based Method for Constrained Neural Machine Translation	Machine translation systems are expected to cope with various types of constraints in many practical scenarios. While neural machine translation (NMT) has achieved strong performance in unconstrained cases, it is non-trivial to impose pre-specified constraints into the translation process of NMT models. Although many a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	298,073
2312.04819	Attention-Guided Contrastive Role Representations for Multi-Agent Reinforcement Learning	Real-world multi-agent tasks usually involve dynamic team composition with the emergence of roles, which should also be a key to efficient cooperation in multi-agent reinforcement learning (MARL). Drawing inspiration from the correlation between roles and agent's behavior patterns, we propose a novel framework of A...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	413,841
2310.06585	A Black-Box Physics-Informed Estimator based on Gaussian Process Regression for Robot Inverse Dynamics Identification	Learning the inverse dynamics of robots directly from data, adopting a black-box approach, is interesting for several real-world scenarios where limited knowledge about the system is available. In this paper, we propose a black-box model based on Gaussian Process (GP) Regression for the identification of the inverse dy...	false	false	false	false	true	false	true	true	false	false	true	false	false	false	false	false	false	false	398,640
1112.0054	Improving the User Query for the Boolean Model Using Genetic Algorithms	The Use of genetic algorithms in the Information retrieval (IR) area, especially in optimizing a user query in Arabic data collections is presented in this paper. Very little research has been carried out on Arabic text collections. Boolean model have been used in this research. To optimize the query using GA we used d...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	13,265
2001.03224	Identifying Distinct, Effective Treatments for Acute Hypotension with SODA-RL: Safely Optimized Diverse Accurate Reinforcement Learning	Hypotension in critical care settings is a life-threatening emergency that must be recognized and treated early. While fluid bolus therapy and vasopressors are common treatments, it is often unclear which interventions to give, in what amounts, and for how long. Observational data in the form of electronic health recor...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	159,912
2306.07272	Zero-shot Composed Text-Image Retrieval	In this paper, we consider the problem of composed image retrieval (CIR), it aims to train a model that can fuse multi-modal information, e.g., text and images, to accurately retrieve images that match the query, extending the user's expression ability. We make the following contributions: (i) we initiate a scalable pi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	372,949
2005.13421	Thirty Musts for Meaning Banking	Meaning banking--creating a semantically annotated corpus for the purpose of semantic parsing or generation--is a challenging task. It is quite simple to come up with a complex meaning representation, but it is hard to design a simple meaning representation that captures many nuances of meaning. This paper lists some l...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	179,006
2011.04482	DynaVSR: Dynamic Adaptive Blind Video Super-Resolution	Most conventional supervised super-resolution (SR) algorithms assume that low-resolution (LR) data is obtained by downscaling high-resolution (HR) data with a fixed known kernel, but such an assumption often does not hold in real scenarios. Some recent blind SR algorithms have been proposed to estimate different downsc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	205,603
2311.15685	The Battleship Approach to the Low Resource Entity Matching Problem	Entity matching, a core data integration problem, is the task of deciding whether two data tuples refer to the same real-world entity. Recent advances in deep learning methods, using pre-trained language models, were proposed for resolving entity matching. Although demonstrating unprecedented results, these solutions s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	410,609
1911.09723	Fast Sparse ConvNets	Historically, the pursuit of efficient inference has been one of the driving forces behind research into new deep learning architectures and building blocks. Some recent examples include: the squeeze-and-excitation module, depthwise separable convolutions in Xception, and the inverted bottleneck in MobileNet v2. Notabl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	154,591
2407.11735	ProSub: Probabilistic Open-Set Semi-Supervised Learning with Subspace-Based Out-of-Distribution Detection	In open-set semi-supervised learning (OSSL), we consider unlabeled datasets that may contain unknown classes. Existing OSSL methods often use the softmax confidence for classifying data as in-distribution (ID) or out-of-distribution (OOD). Additionally, many works for OSSL rely on ad-hoc thresholds for ID/OOD classific...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	473,594
2309.04453	WiSARD: A Labeled Visual and Thermal Image Dataset for Wilderness Search and Rescue	Sensor-equipped unoccupied aerial vehicles (UAVs) have the potential to help reduce search times and alleviate safety risks for first responders carrying out Wilderness Search and Rescue (WiSAR) operations, the process of finding and rescuing person(s) lost in wilderness areas. Unfortunately, visual sensors alone do no...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	390,732
2309.09358	An Automatic Tuning MPC with Application to Ecological Cruise Control	Model predictive control (MPC) is a powerful tool for planning and controlling dynamical systems due to its capacity for handling constraints and taking advantage of preview information. Nevertheless, MPC performance is highly dependent on the choice of cost function tuning parameters. In this work, we demonstrate an a...	false	true	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	392,575
2102.05998	A Survey on Synchronous Augmented, Virtual and Mixed Reality Remote Collaboration Systems	Remote collaboration systems have become increasingly important in today's society, especially during times where physical distancing is advised. Industry, research and individuals face the challenging task of collaborating and networking over long distances. While video and teleconferencing are already widespread, col...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	219,606
1811.00498	Multilingual NMT with a language-independent attention bridge	In this paper, we propose a multilingual encoder-decoder architecture capable of obtaining multilingual sentence representations by means of incorporating an intermediate {\em attention bridge} that is shared across all languages. That is, we train the model with language-specific encoders and decoders that are connect...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	112,113
2305.11464	A Real-Time Limit Order Book as a Market Mechanism for Transactive Energy Systems	This paper presents a limit order book (LOB) market mechanism design for transactive energy systems. The proposed design is planned for deployment in New Hampshire and Maine under a US Department of Energy Connected Communities project. The new LOB mechanism is intended to replace or work in conjunction with the conven...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	365,543
1506.01743	Socially Driven News Recommendation	The participatory Web has enabled the ubiquitous and pervasive access of information, accompanied by an increase of speed and reach in information sharing. Data dissemination services such as news aggregators are expected to provide up-to-date, real-time information to the end users. News aggregators are in essence rec...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	43,822
0710.0564	TP Decoding	`Tree pruning' (TP) is an algorithm for probabilistic inference on binary Markov random fields. It has been recently derived by Dror Weitz and used to construct the first fully polynomial approximation scheme for counting independent sets up to the `tree uniqueness threshold.' It can be regarded as a clever method for ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	727
2201.09635	State-Conditioned Adversarial Subgoal Generation	Hierarchical reinforcement learning (HRL) proposes to solve difficult tasks by performing decision-making and control at successively higher levels of temporal abstraction. However, off-policy HRL often suffers from the problem of a non-stationary high-level policy since the low-level policy is constantly changing. In ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	276,735
2410.15642	Resource-Efficient Medical Report Generation using Large Language Models	Medical report generation is the task of automatically writing radiology reports for chest X-ray images. Manually composing these reports is a time-consuming process that is also prone to human errors. Generating medical reports can therefore help reduce the burden on radiologists. In other words, we can promote greate...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	500,653
1606.04155	Rationalizing Neural Predictions	Prediction without justification has limited applicability. As a remedy, we learn to extract pieces of input text as justifications -- rationales -- that are tailored to be short and coherent, yet sufficient for making the same prediction. Our approach combines two modular components, generator and encoder, which are t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	57,196
1801.07395	On the Computation of Optimal Control Problems with Terminal Inequality Constraint via Variation Evolution	Studies regarding the computation of Optimal Control Problems (OCPs) with terminal inequality constraint, under the frame of the Variation Evolving Method (VEM), are carried out. The attributes of equality constraints and inequality constraints in the generalized optimization problem is traversed, and the intrinsic rel...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	88,780
1612.06835	Box constrained $\ell_1$ optimization in random linear systems -- asymptotics	In this paper we consider box constrained adaptations of $\ell_1$ optimization heuristic when applied for solving random linear systems. These are typically employed when on top of being sparse the systems' solutions are also known to be confined in a specific way to an interval on the real axis. Two particular $\ell_1...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	65,867
2411.02045	Conversations with Data: How Data Journalism Affects Online Comments in the New York Times	Users in the data age have access to more data than ever before, but little is known how they interact with it. Using transparency and multimedia, data journalism (DJ) lets users explore and interpret data on their own. This study examines how DJ affects online comments as a case study of user interactions with data. T...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	505,329
2209.06612	Distribution Calibration for Out-of-Domain Detection with Bayesian Approximation	Out-of-Domain (OOD) detection is a key component in a task-oriented dialog system, which aims to identify whether a query falls outside the predefined supported intent set. Previous softmax-based detection algorithms are proved to be overconfident for OOD samples. In this paper, we analyze overconfident OOD comes from ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	317,455
2405.00747	Soft Preference Optimization: Aligning Language Models to Expert Distributions	We propose Soft Preference Optimization (SPO), a method for aligning generative models, such as Large Language Models (LLMs), with human preferences, without the need for a reward model. SPO optimizes model outputs directly over a preference dataset through a natural loss function that integrates preference loss with a...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	451,067
2211.00497	Modelling black-box audio effects with time-varying feature modulation	Deep learning approaches for black-box modelling of audio effects have shown promise, however, the majority of existing work focuses on nonlinear effects with behaviour on relatively short time-scales, such as guitar amplifiers and distortion. While recurrent and convolutional architectures can theoretically be extende...	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	327,891
2004.11726	A Two-Stage Multiple Instance Learning Framework for the Detection of Breast Cancer in Mammograms	Mammograms are commonly employed in the large scale screening of breast cancer which is primarily characterized by the presence of malignant masses. However, automated image-level detection of malignancy is a challenging task given the small size of the mass regions and difficulty in discriminating between malignant, b...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	174,001
2107.11246	Chance Constrained Economic Dispatch Considering the Capability of Network Flexibility Against Renewable Uncertainties	This paper incorporates a continuous-type network flexibility into chance constrained economic dispatch (CCED). In the proposed model, both power generations and line susceptances are continuous variables to minimize the expected generation cost and guarantee a low probability of constraint violation in terms of genera...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	247,541
2501.16138	Quantifying the Self-Interest Level of Markov Social Dilemmas	This paper introduces a novel method for estimating the self-interest level of computationally intractable Markov social dilemmas. We extend the concept of self-interest level from normal-form games to Markov games, providing a quantitative measure of the minimum reward exchange required to incentivize cooperation by a...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	527,831
2310.19263	A Metadata-Driven Approach to Understand Graph Neural Networks	Graph Neural Networks (GNNs) have achieved remarkable success in various applications, but their performance can be sensitive to specific data properties of the graph datasets they operate on. Current literature on understanding the limitations of GNNs has primarily employed a $\textit{model-driven}$ approach that leve...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	403,923
2201.05405	The Implicit Regularization of Momentum Gradient Descent with Early Stopping	The study on the implicit regularization induced by gradient-based optimization is a longstanding pursuit. In the present paper, we characterize the implicit regularization of momentum gradient descent (MGD) with early stopping by comparing with the explicit $\ell_2$-regularization (ridge). In details, we study MGD in ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	275,381
2310.05149	Retrieval-Generation Synergy Augmented Large Language Models	Large language models augmented with task-relevant documents have demonstrated impressive performance on knowledge-intensive tasks. However, regarding how to obtain effective documents, the existing methods are mainly divided into two categories. One is to retrieve from an external knowledge base, and the other is to u...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	398,008
1809.05142	A Deep Learning and Gamification Approach to Energy Conservation at Nanyang Technological University	The implementation of smart building technology in the form of smart infrastructure applications has great potential to improve sustainability and energy efficiency by leveraging humans-in-the-loop strategy. However, human preference in regard to living conditions is usually unknown and heterogeneous in its manifestati...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	107,724
2411.08019	Language Models as Causal Effect Generators	We present a framework for large language model (LLM) based data generation with controllable causal structure. In particular, we define a procedure for turning any language model and any directed acyclic graph (DAG) into a sequence-driven structural causal model (SD-SCM). Broadly speaking, an SD-SCM is a causal model ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	507,750
2502.06788	EVEv2: Improved Baselines for Encoder-Free Vision-Language Models	Existing encoder-free vision-language models (VLMs) are rapidly narrowing the performance gap with their encoder-based counterparts, highlighting the promising potential for unified multimodal systems with structural simplicity and efficient deployment. We systematically clarify the performance gap between VLMs using p...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	532,245
2304.01094	Data-Efficient Policy Selection for Navigation in Partial Maps via Subgoal-Based Abstraction	We present a novel approach for fast and reliable policy selection for navigation in partial maps. Leveraging the recent learning-augmented model-based Learning over Subgoals Planning (LSP) abstraction to plan, our robot reuses data collected during navigation to evaluate how well other alternative policies could have ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	355,933
2105.08721	A LightGBM based Forecasting of Dominant Wave Periods in Oceanic Waters	In this paper, we propose a Light Gradient Boosting (LightGBM) to forecast dominant wave periods in oceanic waters. First, we use the data collected from CDIP buoys and apply various data filtering methods. The data filtering methods allow us to obtain a high-quality dataset for training and validation purposes. We the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	235,851

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