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
2010.04196	A Fully Tensorized Recurrent Neural Network	Recurrent neural networks (RNNs) are powerful tools for sequential modeling, but typically require significant overparameterization and regularization to achieve optimal performance. This leads to difficulties in the deployment of large RNNs in resource-limited settings, while also introducing complications in hyperpar...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	199,643
2003.06156	Gimme Signals: Discriminative signal encoding for multimodal activity recognition	We present a simple, yet effective and flexible method for action recognition supporting multiple sensor modalities. Multivariate signal sequences are encoded in an image and are then classified using a recently proposed EfficientNet CNN architecture. Our focus was to find an approach that generalizes well across diffe...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	168,045
1605.04812	Off-policy evaluation for slate recommendation	This paper studies the evaluation of policies that recommend an ordered set of items (e.g., a ranking) based on some context---a common scenario in web search, ads, and recommendation. We build on techniques from combinatorial bandits to introduce a new practical estimator that uses logged data to estimate a policy's p...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	55,921
2212.00552	An Effective Deployment of Contrastive Learning in Multi-label Text Classification	The effectiveness of contrastive learning technology in natural language processing tasks is yet to be explored and analyzed. How to construct positive and negative samples correctly and reasonably is the core challenge of contrastive learning. It is even harder to discover contrastive objects in multi-label text class...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	334,098
1805.08380	Optimal transport natural gradient for statistical manifolds with continuous sample space	We study the Wasserstein natural gradient in parametric statistical models with continuous sample spaces. Our approach is to pull back the $L^2$-Wasserstein metric tensor in the probability density space to a parameter space, equipping the latter with a positive definite metric tensor, under which it becomes a Riemanni...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	98,121
2405.00666	RGB$\leftrightarrow$X: Image decomposition and synthesis using material- and lighting-aware diffusion models	The three areas of realistic forward rendering, per-pixel inverse rendering, and generative image synthesis may seem like separate and unrelated sub-fields of graphics and vision. However, recent work has demonstrated improved estimation of per-pixel intrinsic channels (albedo, roughness, metallicity) based on a diffus...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	451,010
2307.16121	Uncertainty-Encoded Multi-Modal Fusion for Robust Object Detection in Autonomous Driving	Multi-modal fusion has shown initial promising results for object detection of autonomous driving perception. However, many existing fusion schemes do not consider the quality of each fusion input and may suffer from adverse conditions on one or more sensors. While predictive uncertainty has been applied to characteriz...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	382,482
2004.06076	Adversarial Augmentation Policy Search for Domain and Cross-Lingual Generalization in Reading Comprehension	Reading comprehension models often overfit to nuances of training datasets and fail at adversarial evaluation. Training with adversarially augmented dataset improves robustness against those adversarial attacks but hurts generalization of the models. In this work, we present several effective adversaries and automated ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	172,410
2002.08254	Weakly Supervised Semantic Segmentation of Satellite Images for Land Cover Mapping -- Challenges and Opportunities	Fully automatic large-scale land cover mapping belongs to the core challenges addressed by the remote sensing community. Usually, the basis of this task is formed by (supervised) machine learning models. However, in spite of recent growth in the availability of satellite observations, accurate training data remains com...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	164,697
2006.05582	Contrastive Multi-View Representation Learning on Graphs	We introduce a self-supervised approach for learning node and graph level representations by contrasting structural views of graphs. We show that unlike visual representation learning, increasing the number of views to more than two or contrasting multi-scale encodings do not improve performance, and the best performan...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,118
2008.01438	Controlling Information Capacity of Binary Neural Network	Despite the growing popularity of deep learning technologies, high memory requirements and power consumption are essentially limiting their application in mobile and IoT areas. While binary convolutional networks can alleviate these problems, the limited bitwidth of weights is often leading to significant degradation o...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	190,315
1906.10015	A Review on Neural Network Models of Schizophrenia and Autism Spectrum Disorder	This survey presents the most relevant neural network models of autism spectrum disorder and schizophrenia, from the first connectionist models to recent deep network architectures. We analyzed and compared the most representative symptoms with its neural model counterpart, detailing the alteration introduced in the ne...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	136,332
2010.08600	Robot Navigation in Constrained Pedestrian Environments using Reinforcement Learning	Navigating fluently around pedestrians is a necessary capability for mobile robots deployed in human environments, such as buildings and homes. While research on social navigation has focused mainly on the scalability with the number of pedestrians in open spaces, typical indoor environments present the additional chal...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	201,226
2311.02801	On the Intersection of Self-Correction and Trust in Language Models	Large Language Models (LLMs) have demonstrated remarkable capabilities in performing complex cognitive tasks. However, their complexity and lack of transparency have raised several trustworthiness concerns, including the propagation of misinformation and toxicity. Recent research has explored the self-correction capabi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	405,588
2502.07282	Leader-follower formation enabled by pressure sensing in free-swimming undulatory robotic fish	Fish use their lateral lines to sense flows and pressure gradients, enabling them to detect nearby objects and organisms. Towards replicating this capability, we demonstrated successful leader-follower formation swimming using flow pressure sensing in our undulatory robotic fish ($\mu$Bot/MUBot). The follower $\mu$Bot ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	532,524
2201.01933	Mission Design of DESTINY+: Toward Active Asteroid (3200) Phaethon and Multiple Small Bodies	DESTINY+ is an upcoming JAXA Epsilon medium-class mission to fly by the Geminids meteor shower parent body (3200) Phaethon. It will be the world's first spacecraft to escape from a near-geostationary transfer orbit into deep space using a low-thrust propulsion system. In doing so, DESTINY+ will demonstrate a number of ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	274,400
2404.10211	Anomaly Correction of Business Processes Using Transformer Autoencoder	Event log records all events that occur during the execution of business processes, so detecting and correcting anomalies in event log can provide reliable guarantee for subsequent process analysis. The previous works mainly include next event prediction based methods and autoencoder-based methods. These methods cannot...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	446,998
2204.12263	Science Checker: Extractive-Boolean Question Answering For Scientific Fact Checking	With the explosive growth of scientific publications, making the synthesis of scientific knowledge and fact checking becomes an increasingly complex task. In this paper, we propose a multi-task approach for verifying the scientific questions based on a joint reasoning from facts and evidence in research articles. We pr...	false	false	false	false	true	true	true	false	true	false	false	false	false	false	false	false	false	false	293,421
2210.06171	Learning to Optimize Quasi-Newton Methods	Fast gradient-based optimization algorithms have become increasingly essential for the computationally efficient training of machine learning models. One technique is to multiply the gradient by a preconditioner matrix to produce a step, but it is unclear what the best preconditioner matrix is. This paper introduces a ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	323,164
2405.18731	VBIM-Net: Variational Born Iterative Network for Inverse Scattering Problems	Recently, studies have shown the potential of integrating field-type iterative methods with deep learning (DL) techniques in solving inverse scattering problems (ISPs). In this article, we propose a novel Variational Born Iterative Network, namely, VBIM-Net, to solve the full-wave ISPs with significantly improved struc...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	458,562
2302.10886	Some Fundamental Aspects about Lipschitz Continuity of Neural Networks	Lipschitz continuity is a crucial functional property of any predictive model, that naturally governs its robustness, generalisation, as well as adversarial vulnerability. Contrary to other works that focus on obtaining tighter bounds and developing different practical strategies to enforce certain Lipschitz properties...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	346,992
1805.04579	Using Statistical and Semantic Models for Multi-Document Summarization	We report a series of experiments with different semantic models on top of various statistical models for extractive text summarization. Though statistical models may better capture word co-occurrences and distribution around the text, they fail to detect the context and the sense of sentences /words as a whole. Semant...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	97,261
2309.10095	A Semi-Supervised Approach for Power System Event Identification	Event identification is increasingly recognized as crucial for enhancing the reliability, security, and stability of the electric power system. With the growing deployment of Phasor Measurement Units (PMUs) and advancements in data science, there are promising opportunities to explore data-driven event identification v...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	392,858
2204.12070	Symlink: A New Dataset for Scientific Symbol-Description Linking	Mathematical symbols and descriptions appear in various forms across document section boundaries without explicit markup. In this paper, we present a new large-scale dataset that emphasizes extracting symbols and descriptions in scientific documents. Symlink annotates scientific papers of 5 different domains (i.e., com...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	293,360
2211.05612	Power Grid Congestion Management via Topology Optimization with AlphaZero	The energy sector is facing rapid changes in the transition towards clean renewable sources. However, the growing share of volatile, fluctuating renewable generation such as wind or solar energy has already led to an increase in power grid congestion and network security concerns. Grid operators mitigate these by modif...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	329,621
2010.04124	Extending the Hint Factory for the assistance dilemma: A novel, data-driven HelpNeed Predictor for proactive problem-solving help	Determining when and whether to provide personalized support is a well-known challenge called the assistance dilemma. A core problem in solving the assistance dilemma is the need to discover when students are unproductive so that the tutor can intervene. Such a task is particularly challenging for open-ended domains, e...	true	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	199,629
2011.14610	Output Feedback Consensus for Networked Heterogeneous Nonlinear Negative-Imaginary Systems with Free Body Motion	This paper provides a protocol to address the robust output feedback consensus problem for networked heterogeneous nonlinear negative-imaginary (NI) systems with free body dynamics. We extend the definition of nonlinear NI systems to allow for systems with free body motion. A new stability result is developed for the i...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	208,833
1907.13079	Deformable Filter Convolution for Point Cloud Reasoning	Point clouds are the native output of many real-world 3D sensors. To borrow the success of 2D convolutional network architectures, a majority of popular 3D perception models voxelize the points, which can result in a loss of local geometric details that cannot be recovered. In this paper, we propose a novel learnable c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	140,292
2404.10392	Generating 6-D Trajectories for Omnidirectional Multirotor Aerial Vehicles in Cluttered Environments	As fully-actuated systems, omnidirectional multirotor aerial vehicles (OMAVs) have more flexible maneuverability and advantages in aggressive flight in cluttered environments than traditional underactuated MAVs. %Due to the high dimensionality of configuration space, making the designed trajectory generation algorithm ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	447,082
2304.05832	Few Shot Semantic Segmentation: a review of methodologies, benchmarks, and open challenges	Semantic segmentation, vital for applications ranging from autonomous driving to robotics, faces significant challenges in domains where collecting large annotated datasets is difficult or prohibitively expensive. In such contexts, such as medicine and agriculture, the scarcity of training images hampers progress. In...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	357,758
1303.2257	A stochastic gradient approach on compressive sensing signal reconstruction based on adaptive filtering framework	Based on the methodological similarity between sparse signal reconstruction and system identification, a new approach for sparse signal reconstruction in compressive sensing (CS) is proposed in this paper. This approach employs a stochastic gradient-based adaptive filtering framework, which is commonly used in system i...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	22,810
2206.15101	The maximum capability of a topological feature in link prediction	Networks offer a powerful approach to modeling complex systems by representing the underlying set of pairwise interactions. Link prediction is the task that predicts links of a network that are not directly visible, with profound applications in biological, social, and other complex systems. Despite intensive utilizati...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	305,486
2410.21113	Zero-Shot Action Recognition in Surveillance Videos	The growing demand for surveillance in public spaces presents significant challenges due to the shortage of human resources. Current AI-based video surveillance systems heavily rely on core computer vision models that require extensive finetuning, which is particularly difficult in surveillance settings due to limited ...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	503,093
1905.12568	Predicting Sparse Clients' Actions with CPOPT-Net in the Banking Environment	The digital revolution of the banking system with evolving European regulations have pushed the major banking actors to innovate by a newly use of their clients' digital information. Given highly sparse client activities, we propose CPOPT-Net, an algorithm that combines the CP canonical tensor decomposition, a multidim...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	132,801
2305.15673	BookGPT: A General Framework for Book Recommendation Empowered by Large Language Model	With the continuous development and change exhibited by large language model (LLM) technology, represented by generative pretrained transformers (GPTs), many classic scenarios in various fields have re-emerged with new opportunities. This paper takes ChatGPT as the modeling object, incorporates LLM technology into the ...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	367,715
2306.01391	Chemical Property-Guided Neural Networks for Naphtha Composition Prediction	The naphtha cracking process heavily relies on the composition of naphtha, which is a complex blend of different hydrocarbons. Predicting the naphtha composition accurately is crucial for efficiently controlling the cracking process and achieving maximum performance. Traditional methods, such as gas chromatography and ...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	370,435
2303.09523	Fast 3D Volumetric Image Reconstruction from 2D MRI Slices by Parallel Processing	Magnetic Resonance Imaging (MRI) is a technology for non-invasive imaging of anatomical features in detail. It can help in functional analysis of organs of a specimen but it is very costly. In this work, methods for (i) virtual three-dimensional (3D) reconstruction from a single sequence of two-dimensional (2D) slices ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	352,079
2006.07648	Structure learning for CTBN's via penalized maximum likelihood methods	The continuous-time Bayesian networks (CTBNs) represent a class of stochastic processes, which can be used to model complex phenomena, for instance, they can describe interactions occurring in living processes, in social science models or in medicine. The literature on this topic is usually focused on the case when the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,889
1801.04297	Optimizing Floating Locations in Hard Disk Drive by Solving Max-min Optimization	Floating operation is very critical in power management in hard disk drive (HDD), during which no control command is applied to the read/write head but a fixed current to counteract actuator flex bias. External disturbance induced drift of head may result in interference of head and bump on the disk during drifting, le...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	88,247
2304.04211	AGAD: Adversarial Generative Anomaly Detection	Anomaly detection suffered from the lack of anomalies due to the diversity of abnormalities and the difficulties of obtaining large-scale anomaly data. Semi-supervised anomaly detection methods are often used to solely leverage normal data to detect abnormalities that deviated from the learnt normality distributions. M...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	357,132
2303.16859	Group polarization, influence, and domination in online interaction networks: A case study of the 2022 Brazilian elections	In this work, we investigate the evolution of polarization, influence, and domination in online interaction networks. Twitter data collected before and during the 2022 Brazilian elections is used as a case study. From a theoretical perspective, we develop a methodology called d-modularity that allows discovering the co...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	355,012
1704.08824	Generalized Spatial Modulation Aided MmWave MIMO with Sub-Connected Hybrid Precoding Scheme	Due to the high cost and low energy efficiency of the dedicated radio frequency (RF) chains, the number of RF chains in a millimeter wave (mmWave) multiple-input multiple-output (MIMO) system is usually limited from a practical point of view. In this case, the maximum number of independent data streams is also restrict...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	72,580
2208.08836	A Multi-modal Registration and Visualization Software Tool for Artworks using CraquelureNet	For art investigations of paintings, multiple imaging technologies, such as visual light photography, infrared reflectography, ultraviolet fluorescence photography, and x-radiography are often used. For a pixel-wise comparison, the multi-modal images have to be registered. We present a registration and visualization so...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	313,496
1809.08993	Improved Semantic Stixels via Multimodal Sensor Fusion	This paper presents a compact and accurate representation of 3D scenes that are observed by a LiDAR sensor and a monocular camera. The proposed method is based on the well-established Stixel model originally developed for stereo vision applications. We extend this Stixel concept to incorporate data from multiple sensor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	108,630
2410.17863	CASCRNet: An Atrous Spatial Pyramid Pooling and Shared Channel Residual based Network for Capsule Endoscopy	This manuscript summarizes work on the Capsule Vision Challenge 2024 by MISAHUB. To address the multi-class disease classification task, which is challenging due to the complexity and imbalance in the Capsule Vision challenge dataset, this paper proposes CASCRNet (Capsule endoscopy-Aspp-SCR-Network), a parameter-effici...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	501,645
2309.05785	Use of a low-cost forward-looking sonar for collision avoidance in small AUVs, analysis and experimental results	In this paper, we seek to evaluate the effectiveness of a novel forward-looking sonar system with a limited number of beams for collision avoidance for small autonomous underwater vehicles (AUVs). We present a collision avoidance strategy specifically designed for a novel forward-looking sonar system based on posterior...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	391,185
2106.05642	U2++: Unified Two-pass Bidirectional End-to-end Model for Speech Recognition	The unified streaming and non-streaming two-pass (U2) end-to-end model for speech recognition has shown great performance in terms of streaming capability, accuracy, real-time factor (RTF), and latency. In this paper, we present U2++, an enhanced version of U2 to further improve the accuracy. The core idea of U2++ is t...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	240,174
2203.05759	Federated Remote Physiological Measurement with Imperfect Data	The growing need for technology that supports remote healthcare is being acutely highlighted by an aging population and the COVID-19 pandemic. In health-related machine learning applications the ability to learn predictive models without data leaving a private device is attractive, especially when these data might cont...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	284,902
2502.06501	Learning Clustering-based Prototypes for Compositional Zero-shot Learning	Learning primitive (i.e., attribute and object) concepts from seen compositions is the primary challenge of Compositional Zero-Shot Learning (CZSL). Existing CZSL solutions typically rely on oversimplified data assumptions, e.g., modeling each primitive with a single centroid primitive representation, ignoring the natu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	532,107
1910.11090	Emotion Generation and Recognition: A StarGAN Approach	The main idea of this ISO is to use StarGAN (A type of GAN model) to perform training and testing on an emotion dataset resulting in a emotion recognition which can be generated by the valence arousal score of the 7 basic expressions. We have created an entirely new dataset consisting of 4K videos. This dataset consist...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	150,674
1506.06988	From Entropy to Information: Biased Typewriters and the Origin of Life	The origin of life can be understood mathematically to be the origin of information that can replicate. The likelihood that entropy spontaneously becomes information can be calculated from first principles, and depends exponentially on the amount of information that is necessary for replication. We do not know what the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	44,470
1301.2287	Hypothesis Management in Situation-Specific Network Construction	This paper considers the problem of knowledge-based model construction in the presence of uncertainty about the association of domain entities to random variables. Multi-entity Bayesian networks (MEBNs) are defined as a representation for knowledge in domains characterized by uncertainty in the number of relevant entit...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	20,962
2305.05768	DifFIQA: Face Image Quality Assessment Using Denoising Diffusion Probabilistic Models	Modern face recognition (FR) models excel in constrained scenarios, but often suffer from decreased performance when deployed in unconstrained (real-world) environments due to uncertainties surrounding the quality of the captured facial data. Face image quality assessment (FIQA) techniques aim to mitigate these perform...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	363,270
1805.06270	Real-time Robot-assisted Ergonomics	This paper describes a novel approach in human robot interaction driven by ergonomics. With a clear focus on optimising ergonomics, the approach proposed here continuously observes a human user's posture and by invoking appropriate cooperative robot movements, the user's posture is, whenever required, brought back to a...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	97,572
1510.06541	Multi-antenna Wireless Powered Communication with Co-channel Energy and Information Transfer	This letter studies a multi-antenna wireless powered communication (WPC) system with co-channel energy and information transfer, where a wireless device (WD), powered up by wireless energy transfer (WET) from an energy transmitter (ET), communicates to an information receiver (IR) over the same frequency band. We maxim...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	48,122
2012.03201	A Two-Systems Perspective for Computational Thinking	Computational Thinking (CT) has emerged as one of the vital thinking skills in recent times, especially for Science, Technology, Engineering and Management (STEM) graduates. Educators are in search of underlying cognitive models against which CT can be analyzed and evaluated. This paper suggests adopting Kahneman's two...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	210,030
2104.11833	Selecting a number of voters for a voting ensemble	For a voting ensemble that selects an odd-sized subset of the ensemble classifiers at random for each example, applies them to the example, and returns the majority vote, we show that any number of voters may minimize the error rate over an out-of-sample distribution. The optimal number of voters depends on the out-of-...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	232,029
2105.08053	Algorithm-Agnostic Explainability for Unsupervised Clustering	Supervised machine learning explainability has developed rapidly in recent years. However, clustering explainability has lagged behind. Here, we demonstrate the first adaptation of model-agnostic explainability methods to explain unsupervised clustering. We present two novel "algorithm-agnostic" explainability methods ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	235,640
1807.05691	Teaching machines to understand data science code by semantic enrichment of dataflow graphs	Your computer is continuously executing programs, but does it really understand them? Not in any meaningful sense. That burden falls upon human knowledge workers, who are increasingly asked to write and understand code. They deserve to have intelligent tools that reveal the connections between code and its subject matt...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	102,976
2006.05573	Global Data Science Project for COVID-19	This paper aims at providing the summary of the Global Data Science Project (GDSC) for COVID-19. as on May 31 2020. COVID-19 has largely impacted on our societies through both direct and indirect effects transmitted by the policy measures to counter the spread of viruses. We quantitatively analysed the multifaceted imp...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,114
0801.4746	Concerning Olga, the Beautiful Little Street Dancer (Adjectives as Higher-Order Polymorphic Functions)	In this paper we suggest a typed compositional seman-tics for nominal compounds of the form [Adj Noun] that models adjectives as higher-order polymorphic functions, and where types are assumed to represent concepts in an ontology that reflects our commonsense view of the world and the way we talk about it in or-dinary ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	1,233
2006.09987	Multilevel Image Thresholding Using a Fully Informed Cuckoo Search Algorithm	Though effective in the segmentation, conventional multilevel thresholding methods are computationally expensive as exhaustive search are used for optimal thresholds to optimize the objective functions. To overcome this problem, population-based metaheuristic algorithms are widely used to improve the searching capacity...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	182,727
1401.0943	LB2CO: A Semantic Ontology Framework for B2C eCommerce Transaction on the Internet	Business ontology can enhance the successful development of complex enterprise system; this is being achieved through knowledge sharing and the ease of communication between every entity in the domain. Through human semantic interaction with the web resources, machines to interpret the data published in a machine inter...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	29,609
1911.07643	Influence-aware Memory Architectures for Deep Reinforcement Learning	Due to its perceptual limitations, an agent may have too little information about the state of the environment to act optimally. In such cases, it is important to keep track of the observation history to uncover hidden state. Recent deep reinforcement learning methods use recurrent neural networks (RNN) to memorize pas...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	153,919
2111.10365	Joint Delay and Phase Precoding Under True-Time Delay Constraints for THz Massive MIMO	A new approach is presented to the problem of compensating the beam squint effect arising in wideband terahertz (THz) hybrid massive multiple-input multiple-output (MIMO) systems, based on the joint optimization of the phase shifter (PS) and true-time delay (TTD) values under per-TTD device time delay constraints. Unli...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	267,297
2502.09268	GEVRM: Goal-Expressive Video Generation Model For Robust Visual Manipulation	With the rapid development of embodied artificial intelligence, significant progress has been made in vision-language-action (VLA) models for general robot decision-making. However, the majority of existing VLAs fail to account for the inevitable external perturbations encountered during deployment. These perturbations...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	533,383
2302.01090	Goniometers are a Powerful Acoustic Feature for Music Information Retrieval Tasks	Goniometers, also known as Phase Scopes or Vector Scopes, are audio metering tools that help music producers and mixing engineers monitor spatial aspects of a music mix, such as the stereo panorama, the width of single sources, the amount and diffuseness of reverberation as well as phase cancellations that may occur on...	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	343,477
1604.01166	An Efficient Algorithm for Mining Frequent Sequence with Constraint Programming	The main advantage of Constraint Programming (CP) approaches for sequential pattern mining (SPM) is their modularity, which includes the ability to add new constraints (regular expressions, length restrictions, etc). The current best CP approach for SPM uses a global constraint (module) that computes the projected data...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	54,155
2007.14535	Dreaming: Model-based Reinforcement Learning by Latent Imagination without Reconstruction	In the present paper, we propose a decoder-free extension of Dreamer, a leading model-based reinforcement learning (MBRL) method from pixels. Dreamer is a sample- and cost-efficient solution to robot learning, as it is used to train latent state-space models based on a variational autoencoder and to conduct policy opti...	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	189,427
2103.16874	VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalization	The task of image-based virtual try-on aims to transfer a target clothing item onto the corresponding region of a person, which is commonly tackled by fitting the item to the desired body part and fusing the warped item with the person. While an increasing number of studies have been conducted, the resolution of synthe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	227,733
2210.10849	Black Box Model Explanations and the Human Interpretability Expectations -- An Analysis in the Context of Homicide Prediction	Strategies based on Explainable Artificial Intelligence (XAI) have promoted better human interpretability of the results of black box models. This opens up the possibility of questioning whether explanations created by XAI methods meet human expectations. The XAI methods being currently used (Ciu, Dalex, Eli5, Lofo, Sh...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	325,081
2207.11414	Modeling and Analysis of a Coupled SIS Bi-Virus Model	The paper deals with the setting where two viruses (say virus 1 and virus 2) coexist in a population, and they are not necessarily mutually exclusive, in the sense that infection due to one virus does not preclude the possibility of simultaneous infection due to the other. We develop a coupled bi-virus susceptible-infe...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	309,624
2410.13894	Deep Learning Based XIoT Malware Analysis: A Comprehensive Survey, Taxonomy, and Research Challenges	The Internet of Things (IoT) is one of the fastest-growing computing industries. By the end of 2027, more than 29 billion devices are expected to be connected. These smart devices can communicate with each other with and without human intervention. This rapid growth has led to the emergence of new types of malware. How...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	499,761
2406.14563	Model Merging and Safety Alignment: One Bad Model Spoils the Bunch	Merging Large Language Models (LLMs) is a cost-effective technique for combining multiple expert LLMs into a single versatile model, retaining the expertise of the original ones. However, current approaches often overlook the importance of safety alignment during merging, leading to highly misaligned models. This work ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	466,374
2111.00314	ECG synthesis with Neural ODE and GAN models	Continuous medical time series data such as ECG is one of the most complex time series due to its dynamic and high dimensional characteristics. In addition, due to its sensitive nature, privacy concerns and legal restrictions, it is often even complex to use actual data for different medical research. As a result, gene...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	264,178
2211.08370	Methodological proposal to identify the nationality of Twitter users through Random-Forests	We disclose a methodology to determine the participants in discussions and their contributions in social networks with a local relationship (e.g., nationality), providing certain levels of trust and efficiency in the process. The dynamic is a challenge that has demanded studies and some approximations to recent solutio...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	330,585
1303.7043	Inductive Hashing on Manifolds	Learning based hashing methods have attracted considerable attention due to their ability to greatly increase the scale at which existing algorithms may operate. Most of these methods are designed to generate binary codes that preserve the Euclidean distance in the original space. Manifold learning techniques, in contr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	23,314
2311.09243	Evaluating the Efficacy of Interactive Language Therapy Based on LLM for High-Functioning Autistic Adolescent Psychological Counseling	This study investigates the efficacy of Large Language Models (LLMs) in interactive language therapy for high-functioning autistic adolescents. With the rapid advancement of artificial intelligence, particularly in natural language processing, LLMs present a novel opportunity to augment traditional psychological counse...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	408,060
2108.09588	Decomposition Multi-Objective Evolutionary Optimization: From State-of-the-Art to Future Opportunities	Decomposition has been the mainstream approach in the classic mathematical programming for multi-objective optimization and multi-criterion decision-making. However, it was not properly studied in the context of evolutionary multi-objective optimization until the development of multi-objective evolutionary algorithm ba...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	251,647
1906.00421	Air Learning: A Deep Reinforcement Learning Gym for Autonomous Aerial Robot Visual Navigation	We introduce Air Learning, an open-source simulator, and a gym environment for deep reinforcement learning research on resource-constrained aerial robots. Equipped with domain randomization, Air Learning exposes a UAV agent to a diverse set of challenging scenarios. We seed the toolset with point-to-point obstacle avoi...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	133,388
2303.00530	An Ultra-Wideband Microstrip MIMO Antenna with EBG Loading for WLAN and Sub-6G Applications	This manuscript presents an ultra-wideband Microstrip multiple-input-multiple-output (MIMO) antenna covering the 2.4GHz to 6.5 GHz wireless local networks (WLAN) and Sub-6G bands. The applied MIMO antenna is composed of two symmetrical microstrip antenna elements. Each microstrip is designed based on the stepped impeda...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	348,631
2306.07372	Composing Efficient, Robust Tests for Policy Selection	Modern reinforcement learning systems produce many high-quality policies throughout the learning process. However, to choose which policy to actually deploy in the real world, they must be tested under an intractable number of environmental conditions. We introduce RPOSST, an algorithm to select a small set of test cas...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	372,988
2405.15143	Intelligent Go-Explore: Standing on the Shoulders of Giant Foundation Models	Go-Explore is a powerful family of algorithms designed to solve hard-exploration problems built on the principle of archiving discovered states, and iteratively returning to and exploring from the most promising states. This approach has led to superhuman performance across a wide variety of challenging problems includ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	456,767
1812.02310	A case study : Influence of Dimension Reduction on regression trees-based Algorithms -Predicting Aeronautics Loads of a Derivative Aircraft	In aircraft industry, market needs evolve quickly in a high competitiveness context. This requires adapting a given aircraft model in minimum time considering for example an increase of range or the number of passengers (cf A330 NEO family). The computation of loads and stress to resize the airframe is on the critical ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	115,727
1903.01977	Crowdsourced Behavior-Driven Development: Implementing Microservices through Microtasks	Key to the effectiveness of crowdsourcing approaches for software engineering is workflow design, describing how complex work is organized into small, relatively independent microtasks. In this paper, we introduce a Behavior-Driven Development (BDD) workflow for accomplishing programming work through self-contained mic...	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	123,389
1910.06462	Active versus Passive Coherent Equalization of Passive Linear Quantum Systems	The paper considers the problem of equalization of passive linear quantum systems. While our previous work was concerned with the analysis and synthesis of passive equalizers, in this paper we analyze coherent quantum equalizers whose annihilation (respectively, creation) operator dynamics in the Heisenberg picture are...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	149,341
2311.10883	Labeling Indoor Scenes with Fusion of Out-of-the-Box Perception Models	The image annotation stage is a critical and often the most time-consuming part required for training and evaluating object detection and semantic segmentation models. Deployment of the existing models in novel environments often requires detecting novel semantic classes not present in the training data. Furthermore, i...	false	false	false	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	408,702
2407.00315	Learning Unsupervised Gaze Representation via Eye Mask Driven Information Bottleneck	Appearance-based supervised methods with full-face image input have made tremendous advances in recent gaze estimation tasks. However, intensive human annotation requirement inhibits current methods from achieving industrial level accuracy and robustness. Although current unsupervised pre-training frameworks have achie...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	468,807
2209.11282	Automated detection of Alzheimer disease using MRI images and deep neural networks- A review	Early detection of Alzheimer disease is crucial for deploying interventions and slowing the disease progression. A lot of machine learning and deep learning algorithms have been explored in the past decade with the aim of building an automated detection for Alzheimer. Advancements in data augmentation techniques and ad...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	319,134
2112.00425	How to use Persistent Memory in your Database	Persistent or Non Volatile Memory (PMEM or NVM) has recently become commercially available under several configurations with different purposes and goals. Despite the attention to the topic, we are not aware of a comprehensive empirical analysis of existing relational database engines under different PMEM configuration...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	269,134
2412.14854	Surrogate-assisted multi-objective design of complex multibody systems	The optimization of large-scale multibody systems is a numerically challenging task, in particular when considering multiple conflicting criteria at the same time. In this situation, we need to approximate the Pareto set of optimal compromises, which is significantly more expensive than finding a single optimum in sing...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	518,882
1706.08260	Deep Semantics-Aware Photo Adjustment	Automatic photo adjustment is to mimic the photo retouching style of professional photographers and automatically adjust photos to the learned style. There have been many attempts to model the tone and the color adjustment globally with low-level color statistics. Also, spatially varying photo adjustment methods have b...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	75,970
2402.00835	ALISON: Fast and Effective Stylometric Authorship Obfuscation	Authorship Attribution (AA) and Authorship Obfuscation (AO) are two competing tasks of increasing importance in privacy research. Modern AA leverages an author's consistent writing style to match a text to its author using an AA classifier. AO is the corresponding adversarial task, aiming to modify a text in such a way...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	425,741
2211.04550	OutlierDetection.jl: A modular outlier detection ecosystem for the Julia programming language	OutlierDetection.jl is an open-source ecosystem for outlier detection in Julia. It provides a range of high-performance outlier detection algorithms implemented directly in Julia. In contrast to previous packages, our ecosystem enables the development highly-scalable outlier detection algorithms using a high-level prog...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	329,277
2110.06537	Well-classified Examples are Underestimated in Classification with Deep Neural Networks	The conventional wisdom behind learning deep classification models is to focus on bad-classified examples and ignore well-classified examples that are far from the decision boundary. For instance, when training with cross-entropy loss, examples with higher likelihoods (i.e., well-classified examples) contribute smaller...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	260,659
2304.00138	Robust Tracking Control for Nonlinear Systems: Performance optimization via extremum seeking	This paper presents a controller design and optimization framework for nonlinear dynamic systems to track a given reference signal in the presence of disturbances when the task is repeated over a finite-time interval. This novel framework mainly consists of two steps. The first step is to design a robust linear quadrat...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	355,568
2406.00689	Hybrid Beamforming Design for Integrated Sensing and Communication Exploiting Prior Information	In this paper, we investigate the hybrid beamforming design for a multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system, where a multi-antenna base station (BS) with hybrid analog-digital transmit antenna arrays sends dual-functional signals to communicate with a multi-antenna user an...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	459,982
2104.03502	Emotion Recognition from Speech Using Wav2vec 2.0 Embeddings	Emotion recognition datasets are relatively small, making the use of the more sophisticated deep learning approaches challenging. In this work, we propose a transfer learning method for speech emotion recognition where features extracted from pre-trained wav2vec 2.0 models are modeled using simple neural networks. We p...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	229,084
2012.13599	Early Indicators of Scientific Impact: Predicting Citations with Altmetrics	Identifying important scholarly literature at an early stage is vital to the academic research community and other stakeholders such as technology companies and government bodies. Due to the sheer amount of research published and the growth of ever-changing interdisciplinary areas, researchers need an efficient way to ...	false	false	false	true	false	false	true	false	false	false	false	false	false	true	false	false	false	true	213,265
2407.00905	Learning Robust 3D Representation from CLIP via Dual Denoising	In this paper, we explore a critical yet under-investigated issue: how to learn robust and well-generalized 3D representation from pre-trained vision language models such as CLIP. Previous works have demonstrated that cross-modal distillation can provide rich and useful knowledge for 3D data. However, like most deep le...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	469,050

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