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
1912.11371	Comparison of the P300 detection accuracy related to the BCI speller and image recognition scenarios	There are several protocols in the Electroencephalography (EEG) recording scenarios which produce various types of event-related potentials (ERP). P300 pattern is a well-known ERP which produced by auditory and visual oddball paradigm and BCI speller system. In this study, P300 and non-P300 separability are investigate...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	158,554
0909.2234	Universal and Composite Hypothesis Testing via Mismatched Divergence	For the universal hypothesis testing problem, where the goal is to decide between the known null hypothesis distribution and some other unknown distribution, Hoeffding proposed a universal test in the nineteen sixties. Hoeffding's universal test statistic can be written in terms of Kullback-Leibler (K-L) divergence bet...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	4,476
2311.01933	ForecastPFN: Synthetically-Trained Zero-Shot Forecasting	The vast majority of time-series forecasting approaches require a substantial training dataset. However, many real-life forecasting applications have very little initial observations, sometimes just 40 or fewer. Thus, the applicability of most forecasting methods is restricted in data-sparse commercial applications. Wh...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	405,234
2002.11477	Learning a Directional Soft Lane Affordance Model for Road Scenes Using Self-Supervision	Humans navigate complex environments in an organized yet flexible manner, adapting to the context and implicit social rules. Understanding these naturally learned patterns of behavior is essential for applications such as autonomous vehicles. However, algorithmically defining these implicit rules of human behavior rema...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	165,720
1701.01742	Automated Design of CubeSats and Small Spacecrafts	The miniaturization of electronics, sensors and actuators has enabled the growing use of CubeSats and sub-20 kg spacecraft. Their reduced mass and volume has the potential to translate into significant reductions in required propellant and launch mass for interplanetary missions, earth observation and for astrophysics ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	66,445
1609.06283	Robotic Swarm Control from Spatio-Temporal Specifications	In this paper, we study the problem of controlling a two-dimensional robotic swarm with the purpose of achieving high level and complex spatio-temporal patterns. We use a rich spatio-temporal logic that is capable of describing a wide range of time varying and complex spatial configurations, and develop a method to enc...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	61,265
1902.10365	A Distributionally Robust Optimization Method for Adversarial Multiple Kernel Learning	We propose a novel data-driven method to learn a mixture of multiple kernels with random features that is certifiabaly robust against adverserial inputs. Specifically, we consider a distributionally robust optimization of the kernel-target alignment with respect to the distribution of training samples over a distributi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	122,659
0901.2665	A Density Matrix-based Algorithm for Solving Eigenvalue Problems	A new numerical algorithm for solving the symmetric eigenvalue problem is presented. The technique deviates fundamentally from the traditional Krylov subspace iteration based techniques (Arnoldi and Lanczos algorithms) or other Davidson-Jacobi techniques, and takes its inspiration from the contour integration and densi...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	2,998
2106.05907	DAIR: Disentangled Attention Intrinsic Regularization for Safe and Efficient Bimanual Manipulation	We address the problem of safely solving complex bimanual robot manipulation tasks with sparse rewards. Such challenging tasks can be decomposed into sub-tasks that are accomplishable by different robots concurrently or sequentially for better efficiency. While previous reinforcement learning approaches primarily focus...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	240,275
2311.12289	ATLANTIC: Structure-Aware Retrieval-Augmented Language Model for Interdisciplinary Science	Large language models record impressive performance on many natural language processing tasks. However, their knowledge capacity is limited to the pretraining corpus. Retrieval augmentation offers an effective solution by retrieving context from external knowledge sources to complement the language model. However, exis...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	409,274
2302.08617	Quantum Computing Provides Exponential Regret Improvement in Episodic Reinforcement Learning	In this paper, we investigate the problem of \textit{episodic reinforcement learning} with quantum oracles for state evolution. To this end, we propose an \textit{Upper Confidence Bound} (UCB) based quantum algorithmic framework to facilitate learning of a finite-horizon MDP. Our quantum algorithm achieves an exponenti...	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	346,106
2401.08658	End-To-End Planning of Autonomous Driving in Industry and Academia: 2022-2023	This paper aims to provide a quick review of the methods including the technologies in detail that are currently reported in industry and academia. Specifically, this paper reviews the end-to-end planning, including Tesla FSD V12, Momenta 2023, Horizon Robotics 2023, Motional RoboTaxi 2022, Woven Planet (Toyota): Urban...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	421,976
2205.09296	Opinion Manipulation on Farsi Twitter	For Iranians and the Iranian diaspora, the Farsi Twittersphere provides an important alternative to state media and an outlet for political discourse. But this understudied online space has become an opinion manipulation battleground, with diverse actors using inauthentic accounts to advance their goals and shape onlin...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	297,214
1110.2906	Multiple dynamical time-scales in networks with hierarchically nested modular organization	Many natural and engineered complex networks have intricate mesoscopic organization, e.g., the clustering of the constituent nodes into several communities or modules. Often, such modularity is manifested at several different hierarchical levels, where the clusters defined at one level appear as elementary entities at ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	12,636
2410.19940	Cobblestone: Iterative Automation for Formal Verification	Formal verification using proof assistants, such as Coq, is an effective way of improving software quality, but it is expensive. Writing proofs manually requires both significant effort and expertise. Recent research has used machine learning to automatically synthesize proofs, reducing verification effort, but these t...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	502,578
2305.10114	Automatic Hyperparameter Tuning in Sparse Matrix Factorization	We study the problem of hyperparameter tuning in sparse matrix factorization under Bayesian framework. In the prior work, an analytical solution of sparse matrix factorization with Laplace prior was obtained by variational Bayes method under several approximations. Based on this solution, we propose a novel numerical m...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	364,913
2105.06977	Do Context-Aware Translation Models Pay the Right Attention?	Context-aware machine translation models are designed to leverage contextual information, but often fail to do so. As a result, they inaccurately disambiguate pronouns and polysemous words that require context for resolution. In this paper, we ask several questions: What contexts do human translators use to resolve amb...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	235,281
2111.06593	Using Deep Learning Sequence Models to Identify SARS-CoV-2 Divergence	SARS-CoV-2 is an upper respiratory system RNA virus that has caused over 3 million deaths and infecting over 150 million worldwide as of May 2021. With thousands of strains sequenced to date, SARS-CoV-2 mutations pose significant challenges to scientists on keeping pace with vaccine development and public health measur...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	266,118
1911.07323	Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks	Graph convolutional networks (GCNs) have recently received wide attentions, due to their successful applications in different graph tasks and different domains. Training GCNs for a large graph, however, is still a challenge. Original full-batch GCN training requires calculating the representation of all the nodes in th...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	153,807
2204.12022	Estimating the Resize Parameter in End-to-end Learned Image Compression	We describe a search-free resizing framework that can further improve the rate-distortion tradeoff of recent learned image compression models. Our approach is simple: compose a pair of differentiable downsampling/upsampling layers that sandwich a neural compression model. To determine resize factors for different input...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	293,339
2311.00260	Incentivized Collaboration in Active Learning	In collaborative active learning, where multiple agents try to learn labels from a common hypothesis, we introduce an innovative framework for incentivized collaboration. Here, rational agents aim to obtain labels for their data sets while keeping label complexity at a minimum. We focus on designing (strict) individual...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	404,567
2101.11217	Automated Crop Field Surveillance using Computer Vision	Artificial Intelligence is everywhere today. But unfortunately, Agriculture has not been able to get that much attention from Artificial Intelligence (AI). A lack of automation persists in the agriculture industry. For over many years, farmers and crop field owners have been facing a problem of trespassing of wild anim...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	217,199
2405.12247	Focus on Low-Resolution Information: Multi-Granular Information-Lossless Model for Low-Resolution Human Pose Estimation	In real-world applications of human pose estimation, low-resolution input images are frequently encountered when the performance of the image acquisition equipment is limited or the shooting distance is too far. However, existing state-of-the-art models for human pose estimation perform poorly on low-resolution images....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	455,457
2405.07369	Incorporating Anatomical Awareness for Enhanced Generalizability and Progression Prediction in Deep Learning-Based Radiographic Sacroiliitis Detection	Purpose: To examine whether incorporating anatomical awareness into a deep learning model can improve generalizability and enable prediction of disease progression. Methods: This retrospective multicenter study included conventional pelvic radiographs of 4 different patient cohorts focusing on axial spondyloarthritis...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	453,685
2110.14578	Spatio-Temporal Federated Learning for Massive Wireless Edge Networks	This paper presents a novel approach to conduct highly efficient federated learning (FL) over a massive wireless edge network, where an edge server and numerous mobile devices (clients) jointly learn a global model without transporting the huge amount of data collected by the mobile devices to the edge server. The prop...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	263,575
2410.20639	A Comparative Study of Multiple Deep Learning Algorithms for Efficient Localization of Bone Joints in the Upper Limbs of Human Body	This paper addresses the medical imaging problem of joint detection in the upper limbs, viz. elbow, shoulder, wrist and finger joints. Localization of joints from X-Ray and Computerized Tomography (CT) scans is an essential step for the assessment of various bone-related medical conditions like Osteoarthritis, Rheumato...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	502,895
2102.06525	Leveraging Reinforcement Learning for evaluating Robustness of KNN Search Algorithms	The problem of finding K-nearest neighbors in the given dataset for a given query point has been worked upon since several years. In very high dimensional spaces the K-nearest neighbor search (KNNS) suffers in terms of complexity in computation of high dimensional distances. With the issue of curse of dimensionality, i...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	219,778
2111.11348	Paris-CARLA-3D: A Real and Synthetic Outdoor Point Cloud Dataset for Challenging Tasks in 3D Mapping	Paris-CARLA-3D is a dataset of several dense colored point clouds of outdoor environments built by a mobile LiDAR and camera system. The data are composed of two sets with synthetic data from the open source CARLA simulator (700 million points) and real data acquired in the city of Paris (60 million points), hence the ...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	267,637
1910.09441	DeepMNavigate: Deep Reinforced Multi-Robot Navigation Unifying Local & Global Collision Avoidance	We present a novel algorithm (DeepMNavigate) for global multi-agent navigation in dense scenarios using deep reinforcement learning (DRL). Our approach uses local and global information for each robot from motion information maps. We use a three-layer CNN that takes these maps as input to generate a suitable action to ...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	true	false	false	false	150,193
2210.14893	Superstabilizing Control of Discrete-Time ARX Models under Error in Variables	This paper applies a polynomial optimization based framework towards the superstabilizing control of an Autoregressive with Exogenous Input (ARX) model given noisy data observations. The recorded input and output values are corrupted with L-infinity bounded noise where the bounds are known. This is an instance of Error...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	326,722
2304.01205	When Evolutionary Computation Meets Privacy	Recently, evolutionary computation (EC) has been promoted by machine learning, distributed computing, and big data technologies, resulting in new research directions of EC like distributed EC and surrogate-assisted EC. These advances have significantly improved the performance and the application scope of EC, but also ...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	true	false	false	355,973
2309.11086	From Unstable Contacts to Stable Control: A Deep Learning Paradigm for HD-sEMG in Neurorobotics	In the past decade, there has been significant advancement in designing wearable neural interfaces for controlling neurorobotic systems, particularly bionic limbs. These interfaces function by decoding signals captured non-invasively from the skin's surface. Portable high-density surface electromyography (HD-sEMG) modu...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	393,273
2306.06823	Weakly supervised information extraction from inscrutable handwritten document images	State-of-the-art information extraction methods are limited by OCR errors. They work well for printed text in form-like documents, but unstructured, handwritten documents still remain a challenge. Adapting existing models to domain-specific training data is quite expensive, because of two factors, 1) limited availabili...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	372,767
2302.10150	Information Retrieval in long documents: Word clustering approach for improving Semantics	In this paper, we propose an alternative to deep neural networks for semantic information retrieval for the case of long documents. This new approach exploiting clustering techniques to take into account the meaning of words in Information Retrieval systems targeting long as well as short documents. This approach uses ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	346,689
2001.08981	Variants of Partial Update Augmented CLMS Algorithm and Their Performance Analysis	Naturally complex-valued information or those presented in complex domain are effectively processed by an augmented complex least-mean-square (ACLMS) algorithm. In some applications, the ACLMS algorithm may be too computationally- and memory-intensive to implement. In this paper, a new algorithm, termed partial-update ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	161,446
2310.06404	Hexa: Self-Improving for Knowledge-Grounded Dialogue System	A common practice in knowledge-grounded dialogue generation is to explicitly utilize intermediate steps (e.g., web-search, memory retrieval) with modular approaches. However, data for such steps are often inaccessible compared to those of dialogue responses as they are unobservable in an ordinary dialogue. To fill in t...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	398,565
1912.05743	Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning	Saliency maps are frequently used to support explanations of the behavior of deep reinforcement learning (RL) agents. However, a review of how saliency maps are used in practice indicates that the derived explanations are often unfalsifiable and can be highly subjective. We introduce an empirical approach grounded in c...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	157,182
2212.09034	Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs	Graph neural networks (GNNs), as the de-facto model class for representation learning on graphs, are built upon the multi-layer perceptrons (MLP) architecture with additional message passing layers to allow features to flow across nodes. While conventional wisdom commonly attributes the success of GNNs to their advance...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	336,972
1609.03912	Information Theoretic Structure Learning with Confidence	Information theoretic measures (e.g. the Kullback Liebler divergence and Shannon mutual information) have been used for exploring possibly nonlinear multivariate dependencies in high dimension. If these dependencies are assumed to follow a Markov factor graph model, this exploration process is called structure discover...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	60,941
1812.03565	The Gap Between Model-Based and Model-Free Methods on the Linear Quadratic Regulator: An Asymptotic Viewpoint	The effectiveness of model-based versus model-free methods is a long-standing question in reinforcement learning (RL). Motivated by recent empirical success of RL on continuous control tasks, we study the sample complexity of popular model-based and model-free algorithms on the Linear Quadratic Regulator (LQR). We show...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	116,048
1509.01770	Theoretical and Experimental Analyses of Tensor-Based Regression and Classification	We theoretically and experimentally investigate tensor-based regression and classification. Our focus is regularization with various tensor norms, including the overlapped trace norm, the latent trace norm, and the scaled latent trace norm. We first give dual optimization methods using the alternating direction method ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	46,652
2310.08085	Low-Resource Clickbait Spoiling for Indonesian via Question Answering	Clickbait spoiling aims to generate a short text to satisfy the curiosity induced by a clickbait post. As it is a newly introduced task, the dataset is only available in English so far. Our contributions include the construction of manually labeled clickbait spoiling corpus in Indonesian and an evaluation on using cros...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	399,256
2403.09039	Detecting Anomalies in Dynamic Graphs via Memory enhanced Normality	Anomaly detection in dynamic graphs presents a significant challenge due to the temporal evolution of graph structures and attributes. The conventional approaches that tackle this problem typically employ an unsupervised learning framework, capturing normality patterns with exclusive normal data during training and ide...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	437,599
1709.06653	Unique Information via Dependency Constraints	The partial information decomposition (PID) is perhaps the leading proposal for resolving information shared between a set of sources and a target into redundant, synergistic, and unique constituents. Unfortunately, the PID framework has been hindered by a lack of a generally agreed-upon, multivariate method of quantif...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	81,141
2212.10762	AgAsk: An Agent to Help Answer Farmer's Questions From Scientific Documents	Decisions in agriculture are increasingly data-driven; however, valuable agricultural knowledge is often locked away in free-text reports, manuals and journal articles. Specialised search systems are needed that can mine agricultural information to provide relevant answers to users' questions. This paper presents AgAsk...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	337,593
2012.09390	Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection	Recent works within machine learning have been tackling inputs of ever-increasing size, with cybersecurity presenting sequence classification problems of particularly extreme lengths. In the case of Windows executable malware detection, inputs may exceed $100$ MB, which corresponds to a time series with $T=100,000,000$...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	212,056
1910.13427	Distribution Density, Tails, and Outliers in Machine Learning: Metrics and Applications	We develop techniques to quantify the degree to which a given (training or testing) example is an outlier in the underlying distribution. We evaluate five methods to score examples in a dataset by how well-represented the examples are, for different plausible definitions of "well-represented", and apply these to four c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	151,389
2208.12834	Improving the Efficiency of Gradient Descent Algorithms Applied to Optimization Problems with Dynamical Constraints	We introduce two block coordinate descent algorithms for solving optimization problems with ordinary differential equations (ODEs) as dynamical constraints. The algorithms do not need to implement direct or adjoint sensitivity analysis methods to evaluate loss function gradients. They results from reformulation of the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	314,867
2006.01966	The Typology of Polysemy: A Multilingual Distributional Framework	Lexical semantic typology has identified important cross-linguistic generalizations about the variation and commonalities in polysemy patterns---how languages package up meanings into words. Recent computational research has enabled investigation of lexical semantics at a much larger scale, but little work has explored...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	179,913
2210.11660	Learning Action Duration and Synergy in Task Planning for Human-Robot Collaboration	A good estimation of the actions' cost is key in task planning for human-robot collaboration. The duration of an action depends on agents' capabilities and the correlation between actions performed simultaneously by the human and the robot. This paper proposes an approach to learning actions' costs and coupling between...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	325,397
2403.14510	Universal Differential Equations as a Common Modeling Language for Neuroscience	The unprecedented availability of large-scale datasets in neuroscience has spurred the exploration of artificial deep neural networks (DNNs) both as empirical tools and as models of natural neural systems. Their appeal lies in their ability to approximate arbitrary functions directly from observations, circumventing th...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	440,110
1904.05724	Improving SIEM for Critical SCADA Water Infrastructures Using Machine Learning	Network Control Systems (NAC) have been used in many industrial processes. They aim to reduce the human factor burden and efficiently handle the complex process and communication of those systems. Supervisory control and data acquisition (SCADA) systems are used in industrial, infrastructure and facility processes (e.g...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	127,390
1409.8518	ProbFuse: A Probabilistic Approach to Data Fusion	Data fusion is the combination of the results of independent searches on a document collection into one single output result set. It has been shown in the past that this can greatly improve retrieval effectiveness over that of the individual results. This paper presents probFuse, a probabilistic approach to data fusi...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	36,417
2008.09394	A Variational Approach to Unsupervised Sentiment Analysis	In this paper, we propose a variational approach to unsupervised sentiment analysis. Instead of using ground truth provided by domain experts, we use target-opinion word pairs as a supervision signal. For example, in a document snippet "the room is big," (room, big) is a target-opinion word pair. These word pairs can b...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	192,702
1105.1247	Machine-Part cell formation through visual decipherable clustering of Self Organizing Map	Machine-part cell formation is used in cellular manufacturing in order to process a large variety, quality, lower work in process levels, reducing manufacturing lead-time and customer response time while retaining flexibility for new products. This paper presents a new and novel approach for obtaining machine cells and...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	10,270
1304.2344	Induction and Uncertainty Management Techniques Applied to Veterinary Medical Diagnosis	This paper discusses a project undertaken between the Departments of Computing Science, Statistics, and the College of Veterinary Medicine to design a medical diagnostic system. On-line medical data has been collected in the hospital database system for several years. A number of induction methods are being used to ext...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	23,652
1501.00311	QANUS: An Open-source Question-Answering Platform	In this paper, we motivate the need for a publicly available, generic software framework for question-answering (QA) systems. We present an open-source QA framework QANUS which researchers can leverage on to build new QA systems easily and rapidly. The framework implements much of the code that will otherwise have been...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	38,977
2311.14533	Introducing 3DCNN ResNets for ASD full-body kinematic assessment: a comparison with hand-crafted features	Autism Spectrum Disorder (ASD) is characterized by challenges in social communication and restricted patterns, with motor abnormalities gaining traction for early detection. However, kinematic analysis in ASD is limited, often lacking robust validation and relying on hand-crafted features for single tasks, leading to i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	410,142
2402.01104	Simulation Framework for Vehicle and Electric Scooter Interaction	The number of shared micro-mobility services such as electric scooters (e-scooters) has an increasing trend due to the advantages of high efficiency and low cost in short-range travel in urban areas. However, due to the unique characteristics of moving behavior, it is commonly seen that e-scooters may share the road wi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	425,859
2305.19292	Revisiting Random Forests in a Comparative Evaluation of Graph Convolutional Neural Network Variants for Traffic Prediction	Traffic prediction is a spatiotemporal predictive task that plays an essential role in intelligent transportation systems. Today, graph convolutional neural networks (GCNNs) have become the prevailing models in the traffic prediction literature since they excel at extracting spatial correlations. In this work, we class...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	369,462
2207.05377	On the Generalization for Transfer Learning: An Information-Theoretic Analysis	Transfer learning, or domain adaptation, is concerned with machine learning problems in which training and testing data come from possibly different probability distributions. In this work, we give an information-theoretic analysis of the generalization error and excess risk of transfer learning algorithms. Our results...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	307,522
1401.6634	Hermitian Self-Dual Cyclic Codes of Length $p^a$ over $GR(p^2,s)$	In this paper, we study cyclic codes over the Galois ring ${\rm GR}({p^2},s)$. The main result is the characterization and enumeration of Hermitian self-dual cyclic codes of length $p^a$ over ${\rm GR}({p^2},s)$. Combining with some known results and the standard Discrete Fourier Transform decomposition, we arrive at t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	30,384
1806.04185	A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literature	We present a corpus of 5,000 richly annotated abstracts of medical articles describing clinical randomized controlled trials. Annotations include demarcations of text spans that describe the Patient population enrolled, the Interventions studied and to what they were Compared, and the Outcomes measured (the `PICO' elem...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	100,166
2111.02824	A unified concurrent-composition method to state/event inference and concealment in discrete-event systems	Discrete-event systems usually consist of discrete states and transitions between them caused by spontaneous occurrences of labelled (aka partially-observed) events. Due to the partially-observed feature, fundamental properties therein could be classified into two categories: state/event-inference-based properties (e.g...	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	264,982
1805.11875	Energy-Efficient Caching for Scalable Videos in Heterogeneous Networks	By suppressing repeated content deliveries, wireless caching has the potential to substantially improve the energy efficiency (EE) of the fifth generation (5G) communication networks. In this paper, we propose two novel energy-efficient caching schemes in heterogeneous networks, namely, scalable video coding (SVC)-base...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	99,039
2007.05811	Efficient List Decoding of Convolutional Polar Codes	An efficient implementation of min-sum SC/list decoding of convolutional polar codes is proposed. The complexity of the proposed implementation of SC decoding is more than two times smaller than the straightforward implementation. Moreover, the proposed list decoding algorithm does not require to copy any LLRs during d...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	186,793
1804.01296	Gaussian Process Uncertainty in Age Estimation as a Measure of Brain Abnormality	Multivariate regression models for age estimation are a powerful tool for assessing abnormal brain morphology associated to neuropathology. Age prediction models are built on cohorts of healthy subjects and are built to reflect normal aging patterns. The application of these multivariate models to diseased subjects usu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	94,203
2409.11579	HEARTS: A Holistic Framework for Explainable, Sustainable and Robust Text Stereotype Detection	Stereotypes are generalised assumptions about societal groups, and even state-of-the-art LLMs using in-context learning struggle to identify them accurately. Due to the subjective nature of stereotypes, where what constitutes a stereotype can vary widely depending on cultural, social, and individual perspectives, robus...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	489,218
2309.15881	Enhancing Cross-Category Learning in Recommendation Systems with Multi-Layer Embedding Training	Modern DNN-based recommendation systems rely on training-derived embeddings of sparse features. Input sparsity makes obtaining high-quality embeddings for rarely-occurring categories harder as their representations are updated infrequently. We demonstrate a training-time technique to produce superior embeddings via eff...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	395,151
2110.02095	Exploring the Limits of Large Scale Pre-training	Recent developments in large-scale machine learning suggest that by scaling up data, model size and training time properly, one might observe that improvements in pre-training would transfer favorably to most downstream tasks. In this work, we systematically study this phenomena and establish that, as we increase the u...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	259,004
2009.05478	Projected Robust PCA with Application to Smooth Image Recovery	Most high-dimensional matrix recovery problems are studied under the assumption that the target matrix has certain intrinsic structures. For image data related matrix recovery problems, approximate low-rankness and smoothness are the two most commonly imposed structures. For approximately low-rank matrix recovery, the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	195,333
2410.07196	EEGUnity: Open-Source Tool in Facilitating Unified EEG Datasets Towards Large-Scale EEG Model	The increasing number of dispersed EEG dataset publications and the advancement of large-scale Electroencephalogram (EEG) models have increased the demand for practical tools to manage diverse EEG datasets. However, the inherent complexity of EEG data, characterized by variability in content data, metadata, and data fo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	496,533
2311.08007	Clearer Frames, Anytime: Resolving Velocity Ambiguity in Video Frame Interpolation	Existing video frame interpolation (VFI) methods blindly predict where each object is at a specific timestep t ("time indexing"), which struggles to predict precise object movements. Given two images of a baseball, there are infinitely many possible trajectories: accelerating or decelerating, straight or curved. This o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	407,558
1711.10921	Local Jet Pattern: A Robust Descriptor for Texture Classification	Methods based on local image features have recently shown promise for texture classification tasks, especially in the presence of large intra-class variation due to illumination, scale, and viewpoint changes. Inspired by the theories of image structure analysis, this paper presents a simple, efficient, yet robust descr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	85,694
2408.00297	EmoTalk3D: High-Fidelity Free-View Synthesis of Emotional 3D Talking Head	We present a novel approach for synthesizing 3D talking heads with controllable emotion, featuring enhanced lip synchronization and rendering quality. Despite significant progress in the field, prior methods still suffer from multi-view consistency and a lack of emotional expressiveness. To address these issues, we col...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	477,781
2311.00993	Scalable Probabilistic Forecasting in Retail with Gradient Boosted Trees: A Practitioner's Approach	The recent M5 competition has advanced the state-of-the-art in retail forecasting. However, we notice important differences between the competition challenge and the challenges we face in a large e-commerce company. The datasets in our scenario are larger (hundreds of thousands of time series), and e-commerce can affor...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	404,862
1809.01859	Deep Learning-Based Decoding for Constrained Sequence Codes	Constrained sequence codes have been widely used in modern communication and data storage systems. Sequences encoded with constrained sequence codes satisfy constraints imposed by the physical channel, hence enabling efficient and reliable transmission of coded symbols. Traditional encoding and decoding of constrained ...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	106,911
2401.12800	Deep Learning in Physical Layer: Review on Data Driven End-to-End Communication Systems and their Enabling Semantic Applications	Deep learning (DL) has revolutionized wireless communication systems by introducing datadriven end-to-end (E2E) learning, where the physical layer (PHY) is transformed into DL architectures to achieve peak optimization. Leveraging DL for E2E optimization in PHY significantly enhances its adaptability and performance in...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	423,500
2205.05202	Deep Learning-based Channel Estimation for Wideband Hybrid MmWave Massive MIMO	Hybrid analog-digital (HAD) architecture is widely adopted in practical millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems to reduce hardware cost and energy consumption. However, channel estimation in the context of HAD is challenging due to only limited radio frequency (RF) chains at trans...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	295,868
2310.00372	Deep Active Learning with Noisy Oracle in Object Detection	Obtaining annotations for complex computer vision tasks such as object detection is an expensive and time-intense endeavor involving a large number of human workers or expert opinions. Reducing the amount of annotations required while maintaining algorithm performance is, therefore, desirable for machine learning pract...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	395,952
1510.05436	Color graph based wavelet transform with perceptual information	In this paper, we propose a numerical strategy to define a multiscale analysis for color and multicomponent images based on the representation of data on a graph. Our approach consists in computing the graph of an image using the psychovisual information and analysing it by using the spectral graph wavelet transform. W...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	48,022
1810.08691	Audio-Based Activities of Daily Living (ADL) Recognition with Large-Scale Acoustic Embeddings from Online Videos	Over the years, activity sensing and recognition has been shown to play a key enabling role in a wide range of applications, from sustainability and human-computer interaction to health care. While many recognition tasks have traditionally employed inertial sensors, acoustic-based methods offer the benefit of capturing...	true	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	110,884
0812.4642	Error-Trellis State Complexity of LDPC Convolutional Codes Based on Circulant Matrices	Let H(D) be the parity-check matrix of an LDPC convolutional code corresponding to the parity-check matrix H of a QC code obtained using the method of Tanner et al. We see that the entries in H(D) are all monomials and several rows (columns) have monomial factors. Let us cyclically shift the rows of H. Then the parity-...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	2,853
2412.19455	NijiGAN: Transform What You See into Anime with Contrastive Semi-Supervised Learning and Neural Ordinary Differential Equations	Generative AI has transformed the animation industry. Several models have been developed for image-to-image translation, particularly focusing on converting real-world images into anime through unpaired translation. Scenimefy, a notable approach utilizing contrastive learning, achieves high fidelity anime scene transla...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	520,848
2107.05344	Post Triangular Rewiring Method for Shorter RRT Robot Path Planning	This paper proposed the 'Post Triangular Rewiring' method that minimizes the sacrifice of planning time and overcomes the limit of Optimality of sampling-based algorithm such as Rapidly-exploring Random Tree (RRT) algorithm. The proposed 'Post Triangular Rewiring' method creates a closer to the optimal path than RRT al...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	245,749
2502.00563	Complex Wavelet Mutual Information Loss: A Multi-Scale Loss Function for Semantic Segmentation	Recent advancements in deep neural networks have significantly enhanced the performance of semantic segmentation. However, class imbalance and instance imbalance remain persistent challenges, where smaller instances and thin boundaries are often overshadowed by larger structures. To address the multiscale nature of seg...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	529,438
1605.08415	Structure-based control of complex networks with nonlinear dynamics	What can we learn about controlling a system solely from its underlying network structure? Here we adapt a recently developed framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based f...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	56,435
2212.09280	Superimposed Channel Estimation in OTFS Modulation Using Compressive Sensing	Orthogonal time frequency space (OTFS) technique is a two-dimensional modulation method that multiplexes information symbols in the delay-Doppler (DD) domain. OTFS combats high Doppler shift existing in high speed wireless communication. However, conventional channel estimation in OTFS suffers from high pilot overhead ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	337,060
2112.00592	BeamSync: Over-The-Air Carrier Synchronization in Distributed RadioWeaves	In a distributed multi-antenna system, multiple geographically separated transmit nodes communicate simultaneously to a receive node. Synchronization of these nodes is essential to achieve a good performance at the receiver. RadioWeaves is a new paradigm of cell-free massive MIMO array deployment using distributed mult...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	269,189
2309.12351	Establishing trust in automated reasoning	Since its beginnings in the 1940s, automated reasoning by computers has become a tool of ever growing importance in scientific research. So far, the rules underlying automated reasoning have mainly been formulated by humans, in the form of program source code. Rules derived from large amounts of data, via machine learn...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	393,769
2011.09980	Geography-Aware Self-Supervised Learning	Contrastive learning methods have significantly narrowed the gap between supervised and unsupervised learning on computer vision tasks. In this paper, we explore their application to geo-located datasets, e.g. remote sensing, where unlabeled data is often abundant but labeled data is scarce. We first show that due to t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	207,382
2409.06163	MCDGLN: Masked Connection-based Dynamic Graph Learning Network for Autism Spectrum Disorder	Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by complex physiological processes. Previous research has predominantly focused on static cerebral interactions, often neglecting the brain's dynamic nature and the challenges posed by network noise. To address these gaps, we introduce the Ma...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	487,019
2004.11896	The number of almost perfect nonlinear functions grows exponentially	Almost perfect nonlinear (APN) functions play an important role in the design of block ciphers as they offer the strongest resistance against differential cryptanalysis. Despite more than 25 years of research, only a limited number of APN functions are known. In this paper, we show that a recent construction by Taniguc...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	174,060
1805.07412	Wasserstein Measure Coresets	The proliferation of large data sets and Bayesian inference techniques motivates demand for better data sparsification. Coresets provide a principled way of summarizing a large dataset via a smaller one that is guaranteed to match the performance of the full data set on specific problems. Classical coresets, however, n...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	97,807
2305.15215	Shadow Cones: A Generalized Framework for Partial Order Embeddings	Hyperbolic space has proven to be well-suited for capturing hierarchical relations in data, such as trees and directed acyclic graphs. Prior work introduced the concept of entailment cones, which uses partial orders defined by nested cones in the Poincar\'e ball to model hierarchies. Here, we introduce the ``shadow con...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	367,507
2306.09519	Relation-Aware Network with Attention-Based Loss for Few-Shot Knowledge Graph Completion	Few-shot knowledge graph completion (FKGC) task aims to predict unseen facts of a relation with few-shot reference entity pairs. Current approaches randomly select one negative sample for each reference entity pair to minimize a margin-based ranking loss, which easily leads to a zero-loss problem if the negative sample...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	373,857
2309.01961	NICE: CVPR 2023 Challenge on Zero-shot Image Captioning	In this report, we introduce NICE (New frontiers for zero-shot Image Captioning Evaluation) project and share the results and outcomes of 2023 challenge. This project is designed to challenge the computer vision community to develop robust image captioning models that advance the state-of-the-art both in terms of accur...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	389,871
2207.03965	Power Response and Modelling Aspects of Power Electronic Loads in Case of Voltage Drops	In this paper, the power response of power electronic loads in case of voltage drops are measured and their dynamics are analysed. Based on this, dynamic simulation models are derived which can be used for voltage stability investigations. For this, four loads with different power factor techniques are considered. In a...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	307,034
0906.1339	Error Exponents for Broadcast Channels with Degraded Message Sets	We consider a broadcast channel with a degraded message set, in which a single transmitter sends a common message to two receivers and a private message to one of the receivers only. The main goal of this work is to find new lower bounds to the error exponents of the strong user, the one that should decode both message...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	3,841
1704.00148	Co-location Epidemic Tracking on London Public Transports Using Low Power Mobile Magnetometer	The public transports provide an ideal means to enable contagious diseases transmission. This paper introduces a novel idea to detect co-location of people in such environment using just the ubiquitous geomagnetic field sensor on the smart phone. Essentially, given that all passengers must share the same journey betwee...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	71,035

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