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
2312.08538	Contractive error feedback for gradient compression	On-device memory concerns in distributed deep learning have become severe due to (i) the growth of model size in multi-GPU training, and (ii) the wide adoption of deep neural networks for federated learning on IoT devices which have limited storage. In such settings, communication efficient optimization methods are att...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	415,335
1909.06480	An Alert-Generation Framework for Improving Resiliency in Human-Supervised, Multi-Agent Teams	Human-supervision in multi-agent teams is a critical requirement to ensure that the decision-maker's risk preferences are utilized to assign tasks to robots. In stressful complex missions that pose risk to human health and life, such as humanitarian-assistance and disaster-relief missions, human mistakes or delays in t...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	true	false	false	false	145,384
2412.05214	AI's assigned gender affects human-AI cooperation	Cooperation between humans and machines is increasingly vital as artificial intelligence (AI) becomes more integrated into daily life. Research indicates that people are often less willing to cooperate with AI agents than with humans, more readily exploiting AI for personal gain. While prior studies have shown that giv...	true	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	true	514,738
2411.16832	Edit Away and My Face Will not Stay: Personal Biometric Defense against Malicious Generative Editing	Recent advancements in diffusion models have made generative image editing more accessible, enabling creative edits but raising ethical concerns, particularly regarding malicious edits to human portraits that threaten privacy and identity security. Existing protection methods primarily rely on adversarial perturbations...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	511,213
2312.00250	Advancements and Trends in Ultra-High-Resolution Image Processing: An Overview	Currently, to further improve visual enjoyment, Ultra-High-Definition (UHD) images are catching wide attention. Here, UHD images are usually referred to as having a resolution greater than or equal to $3840 \times 2160$. However, since the imaging equipment is subject to environmental noise or equipment jitter, UHD ima...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	411,973
2305.09257	A new node-shift encoding representation for the travelling salesman problem	This paper presents a new genetic algorithm encoding representation to solve the travelling salesman problem. To assess the performance of the proposed chromosome structure, we compare it with state-of-the-art encoding representations. For that purpose, we use 14 benchmarks of different sizes taken from TSPLIB. Finally...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	364,577
2101.01897	Performance Analysis and Optimization of Bidirectional Overlay Cognitive Radio Networks with Hybrid-SWIPT	This paper considers a cooperative cognitive radio network with two primary users (PUs) and two secondary users (SUs) that enables two-way communications of primary and secondary systems in conjunction with non-linear energy harvesting based simultaneous wireless information and power transfer (SWIPT). With the conside...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	214,480
2407.02516	EditFollower: Tunable Car Following Models for Customizable Adaptive Cruise Control Systems	In the realm of driving technologies, fully autonomous vehicles have not been widely adopted yet, making advanced driver assistance systems (ADAS) crucial for enhancing driving experiences. Adaptive Cruise Control (ACC) emerges as a pivotal component of ADAS. However, current ACC systems often employ fixed settings, fa...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	469,773
2310.02207	Language Models Represent Space and Time	The capabilities of large language models (LLMs) have sparked debate over whether such systems just learn an enormous collection of superficial statistics or a set of more coherent and grounded representations that reflect the real world. We find evidence for the latter by analyzing the learned representations of three...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	396,743
2301.10803	Evaluating Probabilistic Classifiers: The Triptych	Probability forecasts for binary outcomes, often referred to as probabilistic classifiers or confidence scores, are ubiquitous in science and society, and methods for evaluating and comparing them are in great demand. We propose and study a triptych of diagnostic graphics that focus on distinct and complementary aspect...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	341,910
1204.0156	Ranking Tweets Considering Trust and Relevance	The increasing popularity of Twitter and other microblogs makes improved trustworthiness and relevance assessment of microblogs evermore important. We propose a method of ranking of tweets considering trustworthiness and content based popularity. The analysis of trustworthiness and popularity exploits the implicit rela...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	15,213
2003.13197	Cross-Domain Document Object Detection: Benchmark Suite and Method	Decomposing images of document pages into high-level semantic regions (e.g., figures, tables, paragraphs), document object detection (DOD) is fundamental for downstream tasks like intelligent document editing and understanding. DOD remains a challenging problem as document objects vary significantly in layout, size, as...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	170,134
1506.00231	Channel Equalization and Beamforming for Quaternion-Valued Wireless Communication Systems	Quaternion-valued wireless communication systems have been studied in the past. Although progress has been made in this promising area, a crucial missing link is lack of effective and efficient quaternion-valued signal processing algorithms for channel equalization and beamforming. With most recent developments in quat...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	43,638
1905.10777	Cross-Resolution Face Recognition via Prior-Aided Face Hallucination and Residual Knowledge Distillation	Recent deep learning based face recognition methods have achieved great performance, but it still remains challenging to recognize very low-resolution query face like 28x28 pixels when CCTV camera is far from the captured subject. Such face with very low-resolution is totally out of detail information of the face ident...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	132,192
2104.05367	Visiting the Invisible: Layer-by-Layer Completed Scene Decomposition	Existing scene understanding systems mainly focus on recognizing the visible parts of a scene, ignoring the intact appearance of physical objects in the real-world. Concurrently, image completion has aimed to create plausible appearance for the invisible regions, but requires a manual mask as input. In this work, we pr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	229,701
2007.06507	Industry Adoption Scenarios for Authoritative Data Stores using the ISDA Common Domain Model	In this paper we explore opportunities for the post-trade industry to standardize and simplify in order to significantly increase efficiency and reduce costs. We start by summarizing relevant industry problems (inconsistent processes, inconsistent data and duplicated data) and then present the corresponding potential i...	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	false	187,031
2406.06105	The Evolution of Applications, Hardware Design, and Channel Modeling for Terahertz (THz) Band Communications and Sensing: Ready for 6G?	For decades, the terahertz (THz) frequency band had been primarily explored in the context of radar, imaging, and spectroscopy, where multi-gigahertz (GHz) and even THz-wide channels and the properties of terahertz photons offered attractive target accuracy, resolution, and classification capabilities. Meanwhile, the e...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	462,441
2411.11222	The Sound of Water: Inferring Physical Properties from Pouring Liquids	We study the connection between audio-visual observations and the underlying physics of a mundane yet intriguing everyday activity: pouring liquids. Given only the sound of liquid pouring into a container, our objective is to automatically infer physical properties such as the liquid level, the shape and size of the co...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	508,965
2303.18132	A Desynchronization-Based Countermeasure Against Side-Channel Analysis of Neural Networks	Model extraction attacks have been widely applied, which can normally be used to recover confidential parameters of neural networks for multiple layers. Recently, side-channel analysis of neural networks allows parameter extraction even for networks with several multiple deep layers with high effectiveness. It is there...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	355,474
2104.04546	One-class Autoencoder Approach for Optimal Electrode Set-up Identification in Wearable EEG Event Monitoring	A limiting factor towards the wide routine use of wearables devices for continuous healthcare monitoring is their cumbersome and obtrusive nature. This is particularly true for electroencephalography (EEG) recordings, which require the placement of multiple electrodes in contact with the scalp. In this work, we propose...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	229,417
1412.6170	Manycore processing of repeated k-NN queries over massive moving objects observations	The ability to timely process significant amounts of continuously updated spatial data is mandatory for an increasing number of applications. In this paper we focus on a specific data-intensive problem concerning the repeated processing of huge amounts of k nearest neighbours (k-NN) queries over massive sets of moving ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	38,599
2303.03922	Structure Pretraining and Prompt Tuning for Knowledge Graph Transfer	Knowledge graphs (KG) are essential background knowledge providers in many tasks. When designing models for KG-related tasks, one of the key tasks is to devise the Knowledge Representation and Fusion (KRF) module that learns the representation of elements from KGs and fuses them with task representations. While due to ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	349,894
1802.04416	Neural Tensor Factorization	Neural collaborative filtering (NCF) and recurrent recommender systems (RRN) have been successful in modeling user-item relational data. However, they are also limited in their assumption of static or sequential modeling of relational data as they do not account for evolving users' preference over time as well as chang...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	90,214
2205.07739	The Role of Pseudo-labels in Self-training Linear Classifiers on High-dimensional Gaussian Mixture Data	Self-training (ST) is a simple yet effective semi-supervised learning method. However, why and how ST improves generalization performance by using potentially erroneous pseudo-labels is still not well understood. To deepen the understanding of ST, we derive and analyze a sharp characterization of the behavior of iterat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	296,695
2305.11482	Enhancing Personalized Dialogue Generation with Contrastive Latent Variables: Combining Sparse and Dense Persona	The personalized dialogue explores the consistent relationship between dialogue generation and personality. Existing personalized dialogue agents model persona profiles from three resources: sparse or dense persona descriptions and dialogue histories. However, sparse structured persona attributes are explicit but uninf...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	365,556
2404.06737	Disguised Copyright Infringement of Latent Diffusion Models	Copyright infringement may occur when a generative model produces samples substantially similar to some copyrighted data that it had access to during the training phase. The notion of access usually refers to including copyrighted samples directly in the training dataset, which one may inspect to identify an infringeme...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	445,581
2003.10834	Palm-GAN: Generating Realistic Palmprint Images Using Total-Variation Regularized GAN	Generating realistic palmprint (more generally biometric) images has always been an interesting and, at the same time, challenging problem. Classical statistical models fail to generate realistic-looking palmprint images, as they are not powerful enough to capture the complicated texture representation of palmprint ima...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	169,449
1704.06178	Exploring epoch-dependent stochastic residual networks	The recently proposed stochastic residual networks selectively activate or bypass the layers during training, based on independent stochastic choices, each of which following a probability distribution that is fixed in advance. In this paper we present a first exploration on the use of an epoch-dependent distribution, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	72,131
1803.01090	On Modular Training of Neural Acoustics-to-Word Model for LVCSR	End-to-end (E2E) automatic speech recognition (ASR) systems directly map acoustics to words using a unified model. Previous works mostly focus on E2E training a single model which integrates acoustic and language model into a whole. Although E2E training benefits from sequence modeling and simplified decoding pipelines...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	91,810
2406.16062	Towards Biologically Plausible Computing: A Comprehensive Comparison	Backpropagation is a cornerstone algorithm in training neural networks for supervised learning, which uses a gradient descent method to update network weights by minimizing the discrepancy between actual and desired outputs. Despite its pivotal role in propelling deep learning advancements, the biological plausibility ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	466,981
2312.02372	On the Trade-Off between Stability and Representational Capacity in Graph Neural Networks	Analyzing the stability of graph neural networks (GNNs) under topological perturbations is key to understanding their transferability and the role of each architecture component. However, stability has been investigated only for particular architectures, questioning whether it holds for a broader spectrum of GNNs or on...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	412,839
2210.05185	Meta-Learning with Self-Improving Momentum Target	The idea of using a separately trained target model (or teacher) to improve the performance of the student model has been increasingly popular in various machine learning domains, and meta-learning is no exception; a recent discovery shows that utilizing task-wise target models can significantly boost the generalizatio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	322,742
2301.01673	Text sampling strategies for predicting missing bibliographic links	The paper proposes various strategies for sampling text data when performing automatic sentence classification for the purpose of detecting missing bibliographic links. We construct samples based on sentences as semantic units of the text and add their immediate context which consists of several neighboring sentences. ...	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	false	339,292
2204.06265	Optimal Intermittent Particle Filter	The problem of the optimal allocation (in the expected mean square error sense) of a measurement budget for particle filtering is addressed. We propose three different optimal intermittent filters, whose optimality criteria depend on the information available at the time of decision making. For the first, the stochasti...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	291,288
1802.07226	Implicit Argument Prediction with Event Knowledge	Implicit arguments are not syntactically connected to their predicates, and are therefore hard to extract. Previous work has used models with large numbers of features, evaluated on very small datasets. We propose to train models for implicit argument prediction on a simple cloze task, for which data can be generated a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	90,853
cs/0701118	Optimal Order of Decoding for Max-Min Fairness in $K$-User Memoryless Interference Channels	A $K$-user memoryless interference channel is considered where each receiver sequentially decodes the data of a subset of transmitters before it decodes the data of the designated transmitter. Therefore, the data rate of each transmitter depends on (i) the subset of receivers which decode the data of that transmitter, ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	540,076
2101.04001	Automatic Polyp Segmentation using Fully Convolutional Neural Network	Colorectal cancer is one of fatal cancer worldwide. Colonoscopy is the standard treatment for examination, localization, and removal of colorectal polyps. However, it has been shown that the miss-rate of colorectal polyps during colonoscopy is between 6 to 27%. The use of an automated, accurate, and real-time polyp seg...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	215,045
2502.10693	Extremely Large Full Duplex MIMO for Simultaneous Downlink Communications and Monostatic Sensing at Sub-THz Frequencies	The in-band Full Duplex (FD) technology is lately gaining attention as an enabler for the emerging paradigm of Integrated Sensing and Communications (ISAC), which envisions seamless integration of sensing mechanisms for unconnected entities into next generation wireless networks. In this paper, we present an FD Multipl...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	534,002
2306.00917	Vocabulary-free Image Classification	Recent advances in large vision-language models have revolutionized the image classification paradigm. Despite showing impressive zero-shot capabilities, a pre-defined set of categories, a.k.a. the vocabulary, is assumed at test time for composing the textual prompts. However, such assumption can be impractical when th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	370,208
2006.05698	Rendering Natural Camera Bokeh Effect with Deep Learning	Bokeh is an important artistic effect used to highlight the main object of interest on the photo by blurring all out-of-focus areas. While DSLR and system camera lenses can render this effect naturally, mobile cameras are unable to produce shallow depth-of-field photos due to a very small aperture diameter of their opt...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	181,172
1308.4904	Proceedings Third International Workshop on Hybrid Autonomous Systems	The interest on autonomous systems is increasing both in industry and academia. Such systems must operate with limited human intervention in a changing environment and must be able to compensate for significant system failures without external intervention. The most appropriate models of autonomous systems can be found...	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	26,576
1810.02118	Infill Criterion for Multimodal Model-Based Optimisation	Physical systems are modelled and investigated within simulation software in an increasing range of applications. In reality an investigation of the system is often performed by empirical test scenarios which are related to typical situations. Our aim is to derive a method which generates diverse test scenarios each re...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	109,537
1605.05395	Learning Deep Representations of Fine-grained Visual Descriptions	State-of-the-art methods for zero-shot visual recognition formulate learning as a joint embedding problem of images and side information. In these formulations the current best complement to visual features are attributes: manually encoded vectors describing shared characteristics among categories. Despite good perform...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	55,998
2411.15149	The Fundamental Rights Impact Assessment (FRIA) in the AI Act: Roots, legal obligations and key elements for a model template	What is the context which gave rise to the obligation to carry out a Fundamental Rights Impact Assessment (FRIA) in the AI Act? How has assessment of the impact on fundamental rights been framed by the EU legislator in the AI Act? What methodological criteria should be followed in developing the FRIA? These are the thr...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	510,462
2302.02946	Development of an Immersive Virtual Colonoscopy Viewer for Colon Growths Diagnosis	Desktop-based virtual colonoscopy has been proven to be an asset in the identification of colon anomalies. The process is accurate, although time-consuming. The use of immersive interfaces for virtual colonoscopy is incipient and not yet understood. In this work, we present a new design exploring elements of the VR par...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	344,165
0909.2376	Performing Hybrid Recommendation in Intermodal Transportation-the FTMarket System's Recommendation Module	Diverse recommendation techniques have been already proposed and encapsulated into several e-business applications, aiming to perform a more accurate evaluation of the existing information and accordingly augment the assistance provided to the users involved. This paper reports on the development and integration of a r...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	4,486
2303.05391	Disambiguation of Company names via Deep Recurrent Networks	Name Entity Disambiguation is the Natural Language Processing task of identifying textual records corresponding to the same Named Entity, i.e. real-world entities represented as a list of attributes (names, places, organisations, etc.). In this work, we face the task of disambiguating companies on the basis of their wr...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	true	false	350,448
2406.01870	Understanding Stochastic Natural Gradient Variational Inference	Stochastic natural gradient variational inference (NGVI) is a popular posterior inference method with applications in various probabilistic models. Despite its wide usage, little is known about the non-asymptotic convergence rate in the \emph{stochastic} setting. We aim to lessen this gap and provide a better understan...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	460,498
1104.3250	Adding noise to the input of a model trained with a regularized objective	Regularization is a well studied problem in the context of neural networks. It is usually used to improve the generalization performance when the number of input samples is relatively small or heavily contaminated with noise. The regularization of a parametric model can be achieved in different manners some of which ar...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	10,019
2201.07612	ReGNL: Rapid Prediction of GDP during Disruptive Events using Nightlights	Policy makers often make decisions based on parameters such as GDP, unemployment rate, industrial output, etc. The primary methods to obtain or even estimate such information are resource intensive and time consuming. In order to make timely and well-informed decisions, it is imperative to be able to come up with proxi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	276,080
2108.00065	Model Preserving Compression for Neural Networks	After training complex deep learning models, a common task is to compress the model to reduce compute and storage demands. When compressing, it is desirable to preserve the original model's per-example decisions (e.g., to go beyond top-1 accuracy or preserve robustness), maintain the network's structure, automatically ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	248,585
2106.15374	Polynomial-Time Algorithms for Structurally Observable Graphs by Controlling Minimal Vertices	The aim of this paper is to characterize an important class of marked digraphs, called structurally observable graphs (SOGs), and to solve two minimum realization problems. To begin with, by exploring structural observability of large-scale Boolean networks (LSBNs), an underlying type of SOGs is provided based on a rec...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	243,747
2202.12407	Gaussian Belief Trees for Chance Constrained Asymptotically Optimal Motion Planning	In this paper, we address the problem of sampling-based motion planning under motion and measurement uncertainty with probabilistic guarantees. We generalize traditional sampling-based tree-based motion planning algorithms for deterministic systems and propose belief-$\mathcal{A}$, a framework that extends any kinodyna...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	282,224
1802.01448	Hardening Deep Neural Networks via Adversarial Model Cascades	Deep neural networks (DNNs) are vulnerable to malicious inputs crafted by an adversary to produce erroneous outputs. Works on securing neural networks against adversarial examples achieve high empirical robustness on simple datasets such as MNIST. However, these techniques are inadequate when empirically tested on comp...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	89,606
1108.3153	Differential games of partial information forward-backward doubly stochastic differential equations and applications	This paper is concerned with a new type of differential game problems of forwardbackward stochastic systems. There are three distinguishing features: Firstly, our game systems are forward-backward doubly stochastic differential equations, which is a class of more general game systems than other forward-backward stochas...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	11,675
2112.14297	A Framework for the Joint Optimization of Assignment and Pricing in Mobility-on-Demand Systems with Shared Rides	Mobility-on-Demand (MoD) systems have become a fixture in urban transportation networks, with the rapid growth of ride-hailing services such as Uber and Lyft. Ride-hailing is typically complemented with ridepooling options, which can reduce the negative externalities associated with ride-hailing services and increase t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	273,482
2306.02707	Orca: Progressive Learning from Complex Explanation Traces of GPT-4	Recent research has focused on enhancing the capability of smaller models through imitation learning, drawing on the outputs generated by large foundation models (LFMs). A number of issues impact the quality of these models, ranging from limited imitation signals from shallow LFM outputs; small scale homogeneous traini...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	371,021
2103.11630	Efficient Processing of k-regret Minimization Queries with Theoretical Guarantees	Assisting end users to identify desired results from a large dataset is an important problem for multi-criteria decision making. To address this problem, top-k and skyline queries have been widely adopted, but they both have inherent drawbacks, i.e., the user either has to provide a specific utility function or faces m...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	225,880
2005.05516	Framing Effects on Strategic Information Design under Receiver Distrust and Unknown State	Strategic information design is a framework where a sender designs information strategically to steer its receiver's decision towards a desired choice. Traditionally, such frameworks have always assumed that the sender and the receiver comprehends the state of the choice environment, and that the receiver always trusts...	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	true	176,752
2006.02399	ExKMC: Expanding Explainable $k$-Means Clustering	Despite the popularity of explainable AI, there is limited work on effective methods for unsupervised learning. We study algorithms for $k$-means clustering, focusing on a trade-off between explainability and accuracy. Following prior work, we use a small decision tree to partition a dataset into $k$ clusters. This ena...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	180,029
2205.12096	A generalised, multi-phase-field theory for dissolution-driven stress corrosion cracking and hydrogen embrittlement	We present a phase field-based electro-chemo-mechanical formulation for modelling mechanics-enhanced corrosion and hydrogen-assisted cracking in elastic-plastic solids. A multi-phase-field approach is used to present, for the first time, a general framework for stress corrosion cracking, incorporating both anodic disso...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	298,402
2208.05914	3, 2, 1, Drones Go! A Testbed to Take off UAV Swarm Intelligence for Distributed Sensing	This paper introduces a testbed to study distributed sensing problems of Unmanned Aerial Vehicles (UAVs) exhibiting swarm intelligence. Several Smart City applications, such as transport and disaster response, require efficient collection of sensor data by a swarm of intelligent and cooperative UAVs. This often proves ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	312,544
1803.08999	LayoutNet: Reconstructing the 3D Room Layout from a Single RGB Image	We propose an algorithm to predict room layout from a single image that generalizes across panoramas and perspective images, cuboid layouts and more general layouts (e.g. L-shape room). Our method operates directly on the panoramic image, rather than decomposing into perspective images as do recent works. Our network a...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	93,391
2502.12303	From Gaming to Research: GTA V for Synthetic Data Generation for Robotics and Navigations	In computer vision, the development of robust algorithms capable of generalizing effectively in real-world scenarios more and more often requires large-scale datasets collected under diverse environmental conditions. However, acquiring such datasets is time-consuming, costly, and sometimes unfeasible. To address these ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	534,793
1802.04172	Coded Distributed Computing with Node Cooperation Substantially Increases Speedup Factors	This work explores a distributed computing setting where $K$ nodes are assigned fractions (subtasks) of a computational task in order to perform the computation in parallel. In this setting, a well-known main bottleneck has been the inter-node communication cost required to parallelize the task, because unlike the comp...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	90,159
1604.03212	Recommendations for web service composition by mining usage logs	Web service composition has been one of the most researched topics of the past decade. Novel methods of web service composition are being proposed in the literature include Semantics-based composition, WSDLbased composition. Although these methods provide promising results for composition, search and discovery of web s...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	54,457
2208.00885	Many-to-One Knowledge Distillation of Real-Time Epileptic Seizure Detection for Low-Power Wearable Internet of Things Systems	Integrating low-power wearable Internet of Things (IoT) systems into routine health monitoring is an ongoing challenge. Recent advances in the computation capabilities of wearables make it possible to target complex scenarios by exploiting multiple biosignals and using high-performance algorithms, such as Deep Neural N...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	311,009
2306.01881	Hardware-in-the-Loop and Road Testing of RLVW and GLOSA Connected Vehicle Applications	This paper presents an evaluation of two different Vehicle to Infrastructure (V2I) applications, namely Red Light Violation Warning (RLVW) and Green Light Optimized Speed Advisory (GLOSA). The evaluation method is to first develop and use Hardware-in-the-Loop (HIL) simulator testing, followed by extension of the HIL te...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	370,652
1904.08109	Contextual Aware Joint Probability Model Towards Question Answering System	In this paper, we address the question answering challenge with the SQuAD 2.0 dataset. We design a model architecture which leverages BERT's capability of context-aware word embeddings and BiDAF's context interactive exploration mechanism. By integrating these two state-of-the-art architectures, our system tries to ext...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	127,976
2005.01349	A Directed Spanning Tree Adaptive Control Framework for Time-Varying Formations	In this paper, the time-varying formation and time-varying formation tracking problems are solved for linear multi-agent systems over digraphs without the knowledge of the eigenvalues of the Laplacian matrix associated to the digraph. The solution to these problems relies on a framework that generalizes the directed sp...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	175,556
1803.07739	Assessing Shape Bias Property of Convolutional Neural Networks	It is known that humans display "shape bias" when classifying new items, i.e., they prefer to categorize objects based on their shape rather than color. Convolutional Neural Networks (CNNs) are also designed to take into account the spatial structure of image data. In fact, experiments on image datasets, consisting of ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	93,120
2012.00357	Efficient Data Structures for Model-free Data-Driven Computational Mechanics	The data-driven computing paradigm initially introduced by Kirchdoerfer and Ortiz (2016) enables finite element computations in solid mechanics to be performed directly from material data sets, without an explicit material model. From a computational effort point of view, the most challenging task is the projection of ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	209,112
2208.09577	Real-time Short Video Recommendation on Mobile Devices	Short video applications have attracted billions of users in recent years, fulfilling their various needs with diverse content. Users usually watch short videos on many topics on mobile devices in a short period of time, and give explicit or implicit feedback very quickly to the short videos they watch. The recommender...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	313,743
2207.10282	An Evolutionary Game based Secure Clustering Protocol with Fuzzy Trust Evaluation and Outlier Detection for Wireless Sensor Networks	Trustworthy and reliable data delivery is a challenging task in Wireless Sensor Networks (WSNs) due to unique characteristics and constraints. To acquire secured data delivery and address the conflict between security and energy, in this paper we present an evolutionary game based secure clustering protocol with fuzzy ...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	true	309,199
2010.00463	A Finite Memory Interacting P\'{o}lya Contagion Network and its Approximating Dynamical Systems	We introduce a new model for contagion spread using a network of interacting finite memory two-color P\'{o}lya urns, which we refer to as the finite memory interacting P\'{o}lya contagion network. The urns interact in the sense that the probability of drawing a red ball (which represents an infection state) for a given...	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	198,296
2106.02862	Antenna Array Diagnosis for Millimeter-Wave MIMO Systems	The densely packed antennas of millimeter-Wave (mmWave) MIMO systems are often blocked by the rain, snow, dust and even by fingers, which will change the channel's characteristics and degrades the system's performance. In order to solve this problem, we propose a cross-entropy inspired antenna array diagnosis detection...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	239,066
2008.11185	Bias-Awareness for Zero-Shot Learning the Seen and Unseen	Generalized zero-shot learning recognizes inputs from both seen and unseen classes. Yet, existing methods tend to be biased towards the classes seen during training. In this paper, we strive to mitigate this bias. We propose a bias-aware learner to map inputs to a semantic embedding space for generalized zero-shot lear...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	193,198
2409.03282	Interpretable mixture of experts for time series prediction under recurrent and non-recurrent conditions	Non-recurrent conditions caused by incidents are different from recurrent conditions that follow periodic patterns. Existing traffic speed prediction studies are incident-agnostic and use one single model to learn all possible patterns from these drastically diverse conditions. This study proposes a novel Mixture of Ex...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	485,998
1410.4017	Online Tracking of Skin Colour Regions Against a Complex Background	Online tracking of human activity against a complex background is a challenging task for many applications. In this paper, we have developed a robust technique for localizing skin colour regions from unconstrained image frames. A simple and fast segmentation algorithm is used to train a multiplayer perceptron (MLP) for...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	36,764
2101.11870	Strategic Argumentation Dialogues for Persuasion: Framework and Experiments Based on Modelling the Beliefs and Concerns of the Persuadee	Persuasion is an important and yet complex aspect of human intelligence. When undertaken through dialogue, the deployment of good arguments, and therefore counterarguments, clearly has a significant effect on the ability to be successful in persuasion. Two key dimensions for determining whether an argument is good in a...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	217,412
2006.10641	Shannon meets Myerson: Information Extraction from a Strategic Sender	We study a setting where a receiver must design a questionnaire to recover a sequence of symbols known to strategic sender, whose utility may not be incentive compatible. We allow the receiver the possibility of selecting the alternatives presented in the questionnaire, and thereby linking decisions across the componen...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	true	182,957
2311.12562	Multi-Resolution Planar Region Extraction for Uneven Terrains	This paper studies the problem of extracting planar regions in uneven terrains from unordered point cloud measurements. Such a problem is critical in various robotic applications such as robotic perceptive locomotion. While existing approaches have shown promising results in effectively extracting planar regions from t...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	409,379
2211.03345	Over-the-Air Integrated Sensing, Communication, and Computation in IoT Networks	To facilitate the development of Internet of Things (IoT) services, tremendous IoT devices are deployed in the wireless network to collect and pass data to the server for further processing. Aiming at improving the data sensing and delivering efficiency, the integrated sensing and communication (ISAC) technique has bee...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	328,905
1810.03594	Proximal Online Gradient is Optimum for Dynamic Regret	In online learning, the dynamic regret metric chooses the reference (optimal) solution that may change over time, while the typical (static) regret metric assumes the reference solution to be constant over the whole time horizon. The dynamic regret metric is particularly interesting for applications such as online reco...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	109,844
2410.20981	EEG-Driven 3D Object Reconstruction with Style Consistency and Diffusion Prior	Electroencephalography (EEG)-based visual perception reconstruction has become an important area of research. Neuroscientific studies indicate that humans can decode imagined 3D objects by perceiving or imagining various visual information, such as color, shape, and rotation. Existing EEG-based visual decoding methods ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	503,040
2303.09503	The Intel Neuromorphic DNS Challenge	A critical enabler for progress in neuromorphic computing research is the ability to transparently evaluate different neuromorphic solutions on important tasks and to compare them to state-of-the-art conventional solutions. The Intel Neuromorphic Deep Noise Suppression Challenge (Intel N-DNS Challenge), inspired by the...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	352,072
1804.11297	Sampling strategies in Siamese Networks for unsupervised speech representation learning	Recent studies have investigated siamese network architectures for learning invariant speech representations using same-different side information at the word level. Here we investigate systematically an often ignored component of siamese networks: the sampling procedure (how pairs of same vs. different tokens are sele...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	96,342
2104.06806	Continual learning in cross-modal retrieval	Multimodal representations and continual learning are two areas closely related to human intelligence. The former considers the learning of shared representation spaces where information from different modalities can be compared and integrated (we focus on cross-modal retrieval between language and visual representatio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	230,205
2401.08139	Transferring Core Knowledge via Learngenes	The pre-training paradigm fine-tunes the models trained on large-scale datasets to downstream tasks with enhanced performance. It transfers all knowledge to downstream tasks without discriminating which part is necessary or unnecessary, which may lead to negative transfer. In comparison, knowledge transfer in nature is...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	421,780
2402.19414	Higher-Order Networks Representation and Learning: A Survey	Network data has become widespread, larger, and more complex over the years. Traditional network data is dyadic, capturing the relations among pairs of entities. With the need to model interactions among more than two entities, significant research has focused on higher-order networks and ways to represent, analyze, an...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	433,792
1901.07509	Single-Server Multi-Message Individually-Private Information Retrieval with Side Information	We consider a multi-user variant of the private information retrieval problem described as follows. Suppose there are $D$ users, each of which wants to privately retrieve a distinct message from a server with the help of a trusted agent. We assume that the agent has a random subset of $M$ messages that is not known to ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	119,229
2203.00918	Smart Tracking Tray System for A Smart and Sustainable Wet Lab Community	The laboratories and research institutes are the major places for cutting-edge scientific exploration. Hundreds of millions of research papers were formed from front-line labs. Behind this glorious achievement were unsustainable facts. More and more human investment is required in innovative experimental design and ana...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	283,181
2104.04989	NorDial: A Preliminary Corpus of Written Norwegian Dialect Use	Norway has a large amount of dialectal variation, as well as a general tolerance to its use in the public sphere. There are, however, few available resources to study this variation and its change over time and in more informal areas, \eg on social media. In this paper, we propose a first step to creating a corpus of d...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	229,561
2312.06378	Density-based isogeometric topology optimization of shell structures	Shell structures with a high stiffness-to-weight ratio are desirable in various engineering applications. In such scenarios, topology optimization serves as a popular and effective tool for shell structures design. Among the topology optimization methods, solid isotropic material with penalization method(SIMP) is often...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	414,496
1704.00421	Review on Requirements Modeling and Analysis for Self-Adaptive Systems: A Ten-Year Perspective	Context: Over the last decade, software researchers and engineers have developed a vast body of methodologies and technologies in requirements engineering for self-adaptive systems. Although existing studies have explored various aspects of this field, no systematic study has been performed on summarizing modeling meth...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	71,082
1803.00179	Matching Natural Language Sentences with Hierarchical Sentence Factorization	Semantic matching of natural language sentences or identifying the relationship between two sentences is a core research problem underlying many natural language tasks. Depending on whether training data is available, prior research has proposed both unsupervised distance-based schemes and supervised deep learning sche...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	91,612
2203.11368	Audio visual character profiles for detecting background characters in entertainment media	An essential goal of computational media intelligence is to support understanding how media stories -- be it news, commercial or entertainment media -- represent and reflect society and these portrayals are perceived. People are a central element of media stories. This paper focuses on understanding the representation ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	286,881
2408.06716	Towards Cross-Domain Single Blood Cell Image Classification via Large-Scale LoRA-based Segment Anything Model	Accurate classification of blood cells plays a vital role in hematological analysis as it aids physicians in diagnosing various medical conditions. In this study, we present a novel approach for classifying blood cell images known as BC-SAM. BC-SAM leverages the large-scale foundation model of Segment Anything Model (S...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	480,313
2303.05360	Proceedings 11th International Workshop on Theorem Proving Components for Educational Software	The ThEdu series pursues the smooth transition from an intuitive way of doing mathematics at secondary school to a more formal approach to the subject in STEM education, while favouring software support for this transition by exploiting the power of theorem-proving technologies. What follows is a brief description of h...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	true	350,435
2403.15268	Awakening Augmented Generation: Learning to Awaken Internal Knowledge of Large Language Models for Question Answering	Retrieval-Augmented-Generation and Generation-Augmented-Generation have been proposed to enhance the knowledge required for question answering with Large Language Models (LLMs) by leveraging richer context. However, the former relies on external resources, and both require incorporating explicit documents into the cont...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	440,475

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