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
2006.15646	Expressive Power of Invariant and Equivariant Graph Neural Networks	Various classes of Graph Neural Networks (GNN) have been proposed and shown to be successful in a wide range of applications with graph structured data. In this paper, we propose a theoretical framework able to compare the expressive power of these GNN architectures. The current universality theorems only apply to intr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	184,576
2310.10665	Privacy Preservation in Artificial Intelligence and Extended Reality (AI-XR) Metaverses: A Survey	The metaverse is a nascent concept that envisions a virtual universe, a collaborative space where individuals can interact, create, and participate in a wide range of activities. Privacy in the metaverse is a critical concern as the concept evolves and immersive virtual experiences become more prevalent. The metaverse ...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	400,335
1811.04713	Gauges, Loops, and Polynomials for Partition Functions of Graphical Models	Graphical models represent multivariate and generally not normalized probability distributions. Computing the normalization factor, called the partition function, is the main inference challenge relevant to multiple statistical and optimization applications. The problem is of an exponential complexity with respect to t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	113,155
1504.05308	Automatic Face Recognition from Video	The objective of this work is to automatically recognize faces from video sequences in a realistic, unconstrained setup in which illumination conditions are extreme and greatly changing, viewpoint and user motion pattern have a wide variability, and video input is of low quality. At the centre of focus are face appeara...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	42,252
2303.10974	Translate your gibberish: black-box adversarial attack on machine translation systems	Neural networks are deployed widely in natural language processing tasks on the industrial scale, and perhaps the most often they are used as compounds of automatic machine translation systems. In this work, we present a simple approach to fool state-of-the-art machine translation tools in the task of translation from ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	352,657
2104.01864	FedPandemic: A Cross-Device Federated Learning Approach Towards Elementary Prognosis of Diseases During a Pandemic	The amount of data, manpower and capital required to understand, evaluate and agree on a group of symptoms for the elementary prognosis of pandemic diseases is enormous. In this paper, we present FedPandemic, a novel noise implementation algorithm integrated with cross-device Federated learning for Elementary symptom p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	228,507
2406.00431	SpaFL: Communication-Efficient Federated Learning with Sparse Models and Low computational Overhead	The large communication and computation overhead of federated learning (FL) is one of the main challenges facing its practical deployment over resource-constrained clients and systems. In this work, SpaFL: a communication-efficient FL framework is proposed to optimize sparse model structures with low computational over...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	459,850
2210.10664	Deep Multi-Representation Model for Click-Through Rate Prediction	Click-Through Rate prediction (CTR) is a crucial task in recommender systems, and it gained considerable attention in the past few years. The primary purpose of recent research emphasizes obtaining meaningful and powerful representations through mining low and high feature interactions using various components such as ...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	325,016
cmp-lg/9409012	Towards an Automatic Dictation System for Translators: the TransTalk Project	Professional translators often dictate their translations orally and have them typed afterwards. The TransTalk project aims at automating the second part of this process. Its originality as a dictation system lies in the fact that both the acoustic signal produced by the translator and the source text under translation...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,182
2312.17601	The Tyranny of Possibilities in the Design of Task-Oriented LLM Systems: A Scoping Survey	This scoping survey focuses on our current understanding of the design space for task-oriented LLM systems and elaborates on definitions and relationships among the available design parameters. The paper begins by defining a minimal task-oriented LLM system and exploring the design space of such systems through a thoug...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	418,804
1902.01790	Mobile Information Retrieval	Mobile Information Retrieval (Mobile IR) is a relatively recent branch of Information Retrieval (IR) that is concerned with enabling users to carry out, using a mobile device, all the classical IR operations that they were used to carry out on a desktop. This includes finding content available on local repositories or ...	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	120,733
2412.13081	Prompt Augmentation for Self-supervised Text-guided Image Manipulation	Text-guided image editing finds applications in various creative and practical fields. While recent studies in image generation have advanced the field, they often struggle with the dual challenges of coherent image transformation and context preservation. In response, our work introduces prompt augmentation, a method ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	518,153
2310.00158	Feedback-guided Data Synthesis for Imbalanced Classification	Current status quo in machine learning is to use static datasets of real images for training, which often come from long-tailed distributions. With the recent advances in generative models, researchers have started augmenting these static datasets with synthetic data, reporting moderate performance improvements on clas...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	395,846
2306.11556	NeRF synthesis with shading guidance	The emerging Neural Radiance Field (NeRF) shows great potential in representing 3D scenes, which can render photo-realistic images from novel view with only sparse views given. However, utilizing NeRF to reconstruct real-world scenes requires images from different viewpoints, which limits its practical application. Thi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	374,640
2405.03701	QxEAI: Quantum-like evolutionary algorithm for automated probabilistic forecasting	Forecasting, to estimate future events, is crucial for business and decision-making. This paper proposes QxEAI, a methodology that produces a probabilistic forecast that utilizes a quantum-like evolutionary algorithm based on training a quantum-like logic decision tree and a classical value tree on a small number of re...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	452,283
2406.18536	Reliable Interval Prediction of Minimum Operating Voltage Based on On-chip Monitors via Conformalized Quantile Regression	Predicting the minimum operating voltage ($V_{min}$) of chips is one of the important techniques for improving the manufacturing testing flow, as well as ensuring the long-term reliability and safety of in-field systems. Current $V_{min}$ prediction methods often provide only point estimates, necessitating additional t...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	true	468,045
1907.08051	Self-supervised Training of Proposal-based Segmentation via Background Prediction	While supervised object detection methods achieve impressive accuracy, they generalize poorly to images whose appearance significantly differs from the data they have been trained on. To address this in scenarios where annotating data is prohibitively expensive, we introduce a self-supervised approach to object detecti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	139,019
1606.01341	Neural Architectures for Fine-grained Entity Type Classification	In this work, we investigate several neural network architectures for fine-grained entity type classification. Particularly, we consider extensions to a recently proposed attentive neural architecture and make three key contributions. Previous work on attentive neural architectures do not consider hand-crafted features...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	56,794
2309.07749	OmnimatteRF: Robust Omnimatte with 3D Background Modeling	Video matting has broad applications, from adding interesting effects to casually captured movies to assisting video production professionals. Matting with associated effects such as shadows and reflections has also attracted increasing research activity, and methods like Omnimatte have been proposed to separate dynami...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	391,895
2001.07926	Optimized Generic Feature Learning for Few-shot Classification across Domains	To learn models or features that generalize across tasks and domains is one of the grand goals of machine learning. In this paper, we propose to use cross-domain, cross-task data as validation objective for hyper-parameter optimization (HPO) to improve on this goal. Given a rich enough search space, optimization of hyp...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	161,162
2004.00831	Improving 3D Object Detection through Progressive Population Based Augmentation	Data augmentation has been widely adopted for object detection in 3D point clouds. However, all previous related efforts have focused on manually designing specific data augmentation methods for individual architectures. In this work, we present the first attempt to automate the design of data augmentation policies for...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	170,753
2012.15637	Exploiting Transitivity for Top-k Selection with Score-Based Dueling Bandits	We consider the problem of top-k subset selection in Dueling Bandit problems with score information. Real-world pairwise ranking problems often exhibit a high degree of transitivity and prior work has suggested sampling methods that exploit such transitivity through the use of parametric preference models like the Brad...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	213,852
1806.05713	SIMD Vectorization for the Lennard-Jones Potential with AVX2 and AVX-512 instructions	This work describes the SIMD vectorization of the force calculation of the Lennard-Jones potential with Intel AVX2 and AVX-512 instruction sets. Since the force-calculation kernel of the molecular dynamics method involves indirect access to memory, the data layout is one of the most important factors in vectorization. ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	100,536
2002.11089	Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement	Multi-task reinforcement learning (RL) aims to simultaneously learn policies for solving many tasks. Several prior works have found that relabeling past experience with different reward functions can improve sample efficiency. Relabeling methods typically ask: if, in hindsight, we assume that our experience was optimal...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	165,606
2304.09376	Physical Knowledge Enhanced Deep Neural Network for Sea Surface Temperature Prediction	Traditionally, numerical models have been deployed in oceanography studies to simulate ocean dynamics by representing physical equations. However, many factors pertaining to ocean dynamics seem to be ill-defined. We argue that transferring physical knowledge from observed data could further improve the accuracy of nume...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	359,032
2406.16968	Multimodal Physiological Signals Representation Learning via Multiscale Contrasting for Depression Recognition	Depression recognition based on physiological signals such as functional near-infrared spectroscopy (fNIRS) and electroencephalogram (EEG) has made considerable progress. However, most existing studies ignore the complementarity and semantic consistency of multimodal physiological signals under the same stimulation tas...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	467,370
1910.02043	Fair-by-design explainable models for prediction of recidivism	Recidivism prediction provides decision makers with an assessment of the likelihood that a criminal defendant will reoffend that can be used in pre-trial decision-making. It can also be used for prediction of locations where crimes most occur, profiles that are more likely to commit violent crimes. While such instrumen...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	148,113
2304.02012	EGC: Image Generation and Classification via a Diffusion Energy-Based Model	Learning image classification and image generation using the same set of network parameters is a challenging problem. Recent advanced approaches perform well in one task often exhibit poor performance in the other. This work introduces an energy-based classifier and generator, namely EGC, which can achieve superior per...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	356,292
2211.14931	UAV-Assisted Space-Air-Ground Integrated Networks: A Technical Review of Recent Learning Algorithms	Recent technological advancements in space, air, and ground components have made possible a new network paradigm called space-air-ground integrated network (SAGIN). Unmanned aerial vehicles (UAVs) play a key role in SAGINs. However, due to UAVs' high dynamics and complexity, real-world deployment of a SAGIN becomes a s...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	true	333,050
2401.06161	Trustworthy human-centric based Automated Decision-Making Systems	Automated Decision-Making Systems (ADS) have become pervasive across various fields, activities, and occupations, to enhance performance. However, this widespread adoption introduces potential risks, including the misuse of ADS. Such misuse may manifest when ADS is employed in situations where it is unnecessary or when...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	421,046
2105.07876	The challenges and realities of retailing in a COVID-19 world: Identifying trending and Vital During Crisis keywords during Covid-19 using Machine Learning (Austria as a case study)	From global pandemics to geopolitical turmoil, leaders in logistics, product allocation, procurement and operations are facing increasing difficulty with safeguarding their organizations against supply chain vulnerabilities. It is recommended to opt for forecasting against trending based benchmark because auditing a fu...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	235,582
2406.13870	Splatter a Video: Video Gaussian Representation for Versatile Processing	Video representation is a long-standing problem that is crucial for various down-stream tasks, such as tracking,depth prediction,segmentation,view synthesis,and editing. However, current methods either struggle to model complex motions due to the absence of 3D structure or rely on implicit 3D representations that are i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	466,033
2212.00802	An Introduction to Kernel and Operator Learning Methods for Homogenization by Self-consistent Clustering Analysis	Recent advances in operator learning theory have improved our knowledge about learning maps between infinite dimensional spaces. However, for large-scale engineering problems such as concurrent multiscale simulation for mechanical properties, the training cost for the current operator learning methods is very high. The...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	334,203
2412.20662	Enhancing Table Recognition with Vision LLMs: A Benchmark and Neighbor-Guided Toolchain Reasoner	Pre-trained foundation models have recently significantly progressed in structured table understanding and reasoning. However, despite advancements in areas such as table semantic understanding and table question answering, recognizing the structure and content of unstructured tables using Vision Large Language Models ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	521,305
2406.17282	SetBERT: Enhancing Retrieval Performance for Boolean Logic and Set Operation Queries	We introduce SetBERT, a fine-tuned BERT-based model designed to enhance query embeddings for set operations and Boolean logic queries, such as Intersection (AND), Difference (NOT), and Union (OR). SetBERT significantly improves retrieval performance for logic-structured queries, an area where both traditional and neura...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	467,503
2110.08418	Nuances in Margin Conditions Determine Gains in Active Learning	We consider nonparametric classification with smooth regression functions, where it is well known that notions of margin in $E[Y\|X]$ determine fast or slow rates in both active and passive learning. Here we elucidate a striking distinction between the two settings. Namely, we show that some seemingly benign nuances in ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	261,386
2502.07971	ReTreever: Tree-based Coarse-to-Fine Representations for Retrieval	Document retrieval is a core component of question-answering systems, as it enables conditioning answer generation on new and large-scale corpora. While effective, the standard practice of encoding documents into high-dimensional embeddings for similarity search entails large memory and compute footprints, and also mak...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	532,839
2410.10833	Online Client Scheduling and Resource Allocation for Efficient Federated Edge Learning	Federated learning (FL) enables edge devices to collaboratively train a machine learning model without sharing their raw data. Due to its privacy-protecting benefits, FL has been deployed in many real-world applications. However, deploying FL over mobile edge networks with constrained resources such as power, bandwidth...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	498,259
1703.08362	A new class of three-weight linear codes from weakly regular plateaued functions	Linear codes with few weights have many applications in secret sharing schemes, authentication codes, communication and strongly regular graphs. In this paper, we consider linear codes with three weights in arbitrary characteristic. To do this, we generalize the recent contribution of Mesnager given in [Cryptography an...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	70,568
2411.18440	Learning the Evolution of Physical Structure of Galaxies via Diffusion Models	In astrophysics, understanding the evolution of galaxies in primarily through imaging data is fundamental to comprehending the formation of the Universe. This paper introduces a novel approach to conditioning Denoising Diffusion Probabilistic Models (DDPM) on redshifts for generating galaxy images. We explore whether t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	511,868
2204.00806	HLDC: Hindi Legal Documents Corpus	Many populous countries including India are burdened with a considerable backlog of legal cases. Development of automated systems that could process legal documents and augment legal practitioners can mitigate this. However, there is a dearth of high-quality corpora that is needed to develop such data-driven systems. T...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	289,394
1307.5697	Dimension Reduction via Colour Refinement	Colour refinement is a basic algorithmic routine for graph isomorphism testing, appearing as a subroutine in almost all practical isomorphism solvers. It partitions the vertices of a graph into "colour classes" in such a way that all vertices in the same colour class have the same number of neighbours in every colour c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	25,971
1503.02313	Achieving Secrecy Capacity of the Gaussian Wiretap Channel with Polar Lattices	In this work, an explicit wiretap coding scheme based on polar lattices is proposed to achieve the secrecy capacity of the additive white Gaussian noise (AWGN) wiretap channel. Firstly, polar lattices are used to construct secrecy-good lattices for the mod-$\Lambda_s$ Gaussian wiretap channel. Then we propose an explic...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	40,921
1707.05909	Recovering Latent Signals from a Mixture of Measurements using a Gaussian Process Prior	In sensing applications, sensors cannot always measure the latent quantity of interest at the required resolution, sometimes they can only acquire a blurred version of it due the sensor's transfer function. To recover latent signals when only noisy mixed measurements of the signal are available, we propose the Gaussian...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	77,312
1402.3392	Interleaved entropy coders	The ANS family of arithmetic coders developed by Jarek Duda has the unique property that encoder and decoder are completely symmetric in the sense that a decoder reading bits will be in the exact same state that the encoder was in when writing those bits---all "buffering" of information is explicitly part of the coder ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	30,871
2305.02499	AutoML-GPT: Automatic Machine Learning with GPT	AI tasks encompass a wide range of domains and fields. While numerous AI models have been designed for specific tasks and applications, they often require considerable human efforts in finding the right model architecture, optimization algorithm, and hyperparameters. Recent advances in large language models (LLMs) like...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	362,059
2109.02693	Improving Transferability of Domain Adaptation Networks Through Domain Alignment Layers	Deep learning (DL) has been the primary approach used in various computer vision tasks due to its relevant results achieved on many tasks. However, on real-world scenarios with partially or no labeled data, DL methods are also prone to the well-known domain shift problem. Multi-source unsupervised domain adaptation (MS...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	253,818
2303.01640	Hierarchical Graph Neural Networks for Particle Track Reconstruction	We introduce a novel variant of GNN for particle tracking called Hierarchical Graph Neural Network (HGNN). The architecture creates a set of higher-level representations which correspond to tracks and assigns spacepoints to these tracks, allowing disconnected spacepoints to be assigned to the same track, as well as mul...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	349,045
2403.07924	AI and Identity	AI-empowered technologies' impact on the world is undeniable, reshaping industries, revolutionizing how humans interact with technology, transforming educational paradigms, and redefining social codes. However, this rapid growth is accompanied by two notable challenges: a lack of diversity within the AI field and a wid...	true	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	437,096
2412.03766	End to End Collaborative Synthetic Data Generation	The success of AI is based on the availability of data to train models. While in some cases a single data custodian may have sufficient data to enable AI, often multiple custodians need to collaborate to reach a cumulative size required for meaningful AI research. The latter is, for example, often the case for rare dis...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	514,093
2007.13503	Receptive-Field Regularized CNNs for Music Classification and Tagging	Convolutional Neural Networks (CNNs) have been successfully used in various Music Information Retrieval (MIR) tasks, both as end-to-end models and as feature extractors for more complex systems. However, the MIR field is still dominated by the classical VGG-based CNN architecture variants, often in combination with mor...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	189,151
1807.00571	The Interplay between Lexical Resources and Natural Language Processing	Incorporating linguistic, world and common sense knowledge into AI/NLP systems is currently an important research area, with several open problems and challenges. At the same time, processing and storing this knowledge in lexical resources is not a straightforward task. This tutorial proposes to address these complemen...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	101,871
2407.19077	Flexible graph convolutional network for 3D human pose estimation	Although graph convolutional networks exhibit promising performance in 3D human pose estimation, their reliance on one-hop neighbors limits their ability to capture high-order dependencies among body joints, crucial for mitigating uncertainty arising from occlusion or depth ambiguity. To tackle this limitation, we intr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	476,632
1311.2526	User recommendation in reciprocal and bipartite social networks -- a case study of online dating	Many social networks in our daily life are bipartite networks built on reciprocity. How can we recommend users/friends to a user, so that the user is interested in and attractive to recommended users? In this research, we propose a new collaborative filtering model to improve user recommendations in reciprocal and bipa...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	28,326
2501.02342	Optimizing Small Language Models for In-Vehicle Function-Calling	We propose a holistic approach for deploying Small Language Models (SLMs) as function-calling agents within vehicles as edge devices, offering a more flexible and robust alternative to traditional rule-based systems. By leveraging SLMs, we simplify vehicle control mechanisms and enhance the user experience. Given the i...	true	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	522,442
2310.19558	Privacy-preserving Federated Primal-dual Learning for Non-convex and Non-smooth Problems with Model Sparsification	Federated learning (FL) has been recognized as a rapidly growing research area, where the model is trained over massively distributed clients under the orchestration of a parameter server (PS) without sharing clients' data. This paper delves into a class of federated problems characterized by non-convex and non-smooth ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	404,034
2407.02474	Free Energy in a Circumplex Model of Emotion	Previous active inference accounts of emotion translate fluctuations in free energy to a sense of emotion, mainly focusing on valence. However, in affective science, emotions are often represented as multi-dimensional. In this paper, we propose to adopt a Circumplex Model of emotion by mapping emotions into a two-dimen...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	469,746
2209.05550	Mathematical Framework for Online Social Media Auditing	Social media platforms (SMPs) leverage algorithmic filtering (AF) as a means of selecting the content that constitutes a user's feed with the aim of maximizing their rewards. Selectively choosing the contents to be shown on the user's feed may yield a certain extent of influence, either minor or major, on the user's de...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	317,121
2006.01687	SeqXFilter: A Memory-efficient Denoising Filter for Dynamic Vision Sensors	Neuromorphic event-based dynamic vision sensors (DVS) have much faster sampling rates and a higher dynamic range than frame-based imaging sensors. However, they are sensitive to background activity (BA) events that are unwanted. There are some filters for tackling this problem based on spatio-temporal correlation. Howe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	179,843
2303.11390	Dual-Weight Particle Filter for Radar-Based Dynamic Bayesian Grid Maps	Through constant improvements in recent years radar sensors have become a viable alternative to lidar as the main distancing sensor of an autonomous vehicle. Although robust and with the possibility to directly measure the radial velocity, it brings it's own set of challenges, for which existing algorithms need to be a...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	352,828
0910.4901	Distortion Exponent in MIMO Channels with Feedback	The transmission of a Gaussian source over a block-fading multiple antenna channel in the presence of a feedback link is considered. The feedback link is assumed to be an error and delay free link of capacity 1 bit per channel use. Under the short-term power constraint, the optimal exponential behavior of the end-to-en...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	4,800
2502.10801	FaceSwapGuard: Safeguarding Facial Privacy from DeepFake Threats through Identity Obfuscation	DeepFakes pose a significant threat to our society. One representative DeepFake application is face-swapping, which replaces the identity in a facial image with that of a victim. Although existing methods partially mitigate these risks by degrading the quality of swapped images, they often fail to disrupt the identity ...	false	false	false	false	true	false	false	false	false	false	false	true	true	false	false	false	false	false	534,050
2207.11490	Towards Smart Fake News Detection Through Explainable AI	People now see social media sites as their sole source of information due to their popularity. The Majority of people get their news through social media. At the same time, fake news has grown exponentially on social media platforms in recent years. Several artificial intelligence-based solutions for detecting fake new...	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	false	309,660
1610.02454	Learning What and Where to Draw	Generative Adversarial Networks (GANs) have recently demonstrated the capability to synthesize compelling real-world images, such as room interiors, album covers, manga, faces, birds, and flowers. While existing models can synthesize images based on global constraints such as a class label or caption, they do not provi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	62,098
2303.10728	Training Deep Boltzmann Networks with Sparse Ising Machines	The slowing down of Moore's law has driven the development of unconventional computing paradigms, such as specialized Ising machines tailored to solve combinatorial optimization problems. In this paper, we show a new application domain for probabilistic bit (p-bit) based Ising machines by training deep generative AI mo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	true	352,561
1506.00179	A Deterministic Analysis of Decimation for Sigma-Delta Quantization of Bandlimited Functions	We study Sigma-Delta ($\Sigma\Delta$) quantization of oversampled bandlimited functions. We prove that digitally integrating blocks of bits and then down-sampling, a process known as decimation, can efficiently encode the associated $\Sigma\Delta$ bit-stream. It allows a large reduction in the bit-rate while still perm...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	43,630
2012.11774	Differentially Private Synthetic Medical Data Generation using Convolutional GANs	Deep learning models have demonstrated superior performance in several application problems, such as image classification and speech processing. However, creating a deep learning model using health record data requires addressing certain privacy challenges that bring unique concerns to researchers working in this domai...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	212,722
1903.01777	A New Approach to Adaptive Data Analysis and Learning via Maximal Leakage	There is an increasing concern that most current published research findings are false. The main cause seems to lie in the fundamental disconnection between theory and practice in data analysis. While the former typically relies on statistical independence, the latter is an inherently adaptive process: new hypotheses a...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	123,339
1704.00993	A New Transmitted Reference Pulse Cluster Based Ultra-Wideband Transmitter Design	An energy efficient ultra-wideband (UWB) transmitter based on the novel transmitted reference pulse cluster (TRPC) modulation scheme is presented. The TRPC-UWB transmitter integrates, namely, wideband active baluns, wideband I-Q modulator based up-conversion mixer, and differential to single-ended converter. The integr...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	71,175
2403.15189	Forecasting the load of Parcel Pickup Points using a Markov Jump Process	The growth of e-commerce has resulted in a surge in parcel deliveries, increasing transportation costs and pollution issues. Alternatives to home delivery have emerged, such as the delivery to so-called parcel pick-up points (PUPs), which eliminates delivery failure due to customers not being at home. Nevertheless, par...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	440,438
2205.10861	Contrastive Learning of Coarse-Grained Force Fields	Coarse-grained models have proven helpful for simulating complex systems over long timescales to provide molecular insights into various processes. Methodologies for systematic parameterization of the underlying energy function, or force field that describes the interactions among different components of the system are...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	297,904
2110.01485	JuriBERT: A Masked-Language Model Adaptation for French Legal Text	Language models have proven to be very useful when adapted to specific domains. Nonetheless, little research has been done on the adaptation of domain-specific BERT models in the French language. In this paper, we focus on creating a language model adapted to French legal text with the goal of helping law professionals...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	258,789
2010.01477	Generalized Two-Dimensional Quaternion Principal Component Analysis with Weighting for Color Image Recognition	One of the most powerful methods of color image recognition is the two-dimensional principle component analysis (2DQPCA) approach, which is based on quaternion representation and preserves color information very well. However, the current versions of 2DQPCA are still not feasible to extract different geometric properti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	198,667
1902.01342	Self-Tuning Spectral Clustering for Adaptive Tracking Areas Design in 5G Ultra-Dense Networks	In this paper, we address the issue of automatic tracking areas (TAs) planning in fifth generation (5G) ultra-dense networks (UDNs). By invoking handover (HO) attempts and measurement reports (MRs) statistics of a 4G live network, we first introduce a new kernel function mapping HO attempts, MRs and inter-site distance...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	120,629
2410.02156	The why, what, and how of AI-based coding in scientific research	Computer programming (coding) is indispensable for researchers across disciplines, yet it remains challenging to learn and time-consuming to carry out. Generative AI, particularly large language models (LLMs), has the potential to transform coding into intuitive conversations, but best practices and effective workflows...	false	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	true	494,138
2303.15187	Avatarm: an Avatar With Manipulation Capabilities for the Physical Metaverse	Metaverse is an immersive shared space that remote users can access through virtual and augmented reality interfaces, enabling their avatars to interact with each other and the surrounding. Although digital objects can be manipulated, physical objects cannot be touched, grasped, or moved within the metaverse due to the...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	354,396
2201.06978	ASOCEM: Automatic Segmentation Of Contaminations in cryo-EM	Particle picking is currently a critical step in the cryo-electron microscopy single particle reconstruction pipeline. Contaminations in the acquired micrographs severely degrade the performance of particle pickers, resulting is many ``non-particles'' in the collected stack of particles. In this paper, we present ASOCE...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	275,896
2501.00142	Minimalist Vision with Freeform Pixels	A minimalist vision system uses the smallest number of pixels needed to solve a vision task. While traditional cameras use a large grid of square pixels, a minimalist camera uses freeform pixels that can take on arbitrary shapes to increase their information content. We show that the hardware of a minimalist camera can...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	521,550
1608.05374	DNN-based Speech Synthesis for Indian Languages from ASCII text	Text-to-Speech synthesis in Indian languages has a seen lot of progress over the decade partly due to the annual Blizzard challenges. These systems assume the text to be written in Devanagari or Dravidian scripts which are nearly phonemic orthography scripts. However, the most common form of computer interaction among ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	59,967
2405.03352	Salient Object Detection From Arbitrary Modalities	Toward desirable saliency prediction, the types and numbers of inputs for a salient object detection (SOD) algorithm may dynamically change in many real-life applications. However, existing SOD algorithms are mainly designed or trained for one particular type of inputs, failing to be generalized to other types of input...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	452,152
1511.07218	Convex Optimization Based State Estimation against Sparse Integrity Attacks	We consider the problem of robust estimation in the presence of integrity attacks. There are m sensors monitoring the state and p of them are under attack. The malicious measurements collected by the compromised sensors can be manipulated arbitrarily by the attacker. The classical estimators such as the least squares e...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	49,396
2012.02099	Performance Indicators Contributing To Success At The Group And Play-Off Stages Of The 2019 Rugby World Cup	Performance indicators that contributed to success at the group stage and play-off stages of the 2019 Rugby World Cup were analysed using publicly available data obtained from the official tournament website using both a non-parametric statistical technique, Wilcoxon's signed rank test, and a decision rules technique f...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	209,645
2211.16756	Split-PU: Hardness-aware Training Strategy for Positive-Unlabeled Learning	Positive-Unlabeled (PU) learning aims to learn a model with rare positive samples and abundant unlabeled samples. Compared with classical binary classification, the task of PU learning is much more challenging due to the existence of many incompletely-annotated data instances. Since only part of the most confident posi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	333,738
1411.3550	Investigating Rumor Propagation with TwitterTrails	Social media have become part of modern news reporting, used by journalists to spread information and find sources, or as a news source by individuals. The quest for prominence and recognition on social media sites like Twitter can sometimes eclipse accuracy and lead to the spread of false information. As a way to stud...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	37,510
1904.03259	Is 'Unsupervised Learning' a Misconceived Term?	Is all of machine learning supervised to some degree? The field of machine learning has traditionally been categorized pedagogically into $supervised~vs~unsupervised~learning$; where supervised learning has typically referred to learning from labeled data, while unsupervised learning has typically referred to learning ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	126,649
2402.09240	Switch EMA: A Free Lunch for Better Flatness and Sharpness	Exponential Moving Average (EMA) is a widely used weight averaging (WA) regularization to learn flat optima for better generalizations without extra cost in deep neural network (DNN) optimization. Despite achieving better flatness, existing WA methods might fall into worse final performances or require extra test-time ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	429,429
2205.15695	On Preemption and Learning in Stochastic Scheduling	We study single-machine scheduling of jobs, each belonging to a job type that determines its duration distribution. We start by analyzing the scenario where the type characteristics are known and then move to two learning scenarios where the types are unknown: non-preemptive problems, where each started job must be com...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	299,832
1206.5259	A Tractable Approach to Finding Closest Truncated-commute-time Neighbors in Large Graphs	Recently there has been much interest in graph-based learning, with applications in collaborative filtering for recommender networks, link prediction for social networks and fraud detection. These networks can consist of millions of entities, and so it is very important to develop highly efficient techniques. We are es...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	16,797
cs/0407029	Static versus Dynamic Arbitrage Bounds on Multivariate Option Prices	We compare static arbitrage price bounds on basket calls, i.e. bounds that only involve buy-and-hold trading strategies, with the price range obtained within a multi-variate generalization of the Black-Scholes model. While there is no gap between these two sets of prices in the univariate case, we observe here that con...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	538,267
1806.03378	Cultural Investment and Urban Socio-Economic Development: A Geo-Social Network Approach	Being able to assess the impact of government-led investment onto socio-economic indicators in cities has long been an important target of urban planning. However, due to the lack of large-scale data with a fine spatio-temporal resolution, there have been limitations in terms of how planners can track the impact and me...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	99,981
2310.10659	Exploiting Machine Unlearning for Backdoor Attacks in Deep Learning System	In recent years, the security issues of artificial intelligence have become increasingly prominent due to the rapid development of deep learning research and applications. Backdoor attack is an attack targeting the vulnerability of deep learning models, where hidden backdoors are activated by triggers embedded by the a...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	400,331
2410.03981	A Survey on LLM-based Code Generation for Low-Resource and Domain-Specific Programming Languages	Large Language Models (LLMs) have shown impressive capabilities in code generation for popular programming languages. However, their performance on Low-Resource Programming Languages (LRPLs) and Domain-Specific Languages (DSLs) remains a significant challenge, affecting millions of developers-3.5 million users in Rust ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	495,074
2303.04614	Densely Connected $G$-invariant Deep Neural Networks with Signed Permutation Representations	We introduce and investigate, for finite groups $G$, $G$-invariant deep neural network ($G$-DNN) architectures with ReLU activation that are densely connected-- i.e., include all possible skip connections. In contrast to other $G$-invariant architectures in the literature, the preactivations of the$G$-DNNs presented he...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	350,156
1801.04929	Generalizing, Decoding, and Optimizing Support Vector Machine Classification	The classification of complex data usually requires the composition of processing steps. Here, a major challenge is the selection of optimal algorithms for preprocessing and classification (including parameterizations). Nowadays, parts of the optimization process are automized but expert knowledge and manual work are s...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	88,363
2110.10018	Dynamic pricing and assortment under a contextual MNL demand	We consider dynamic multi-product pricing and assortment problems under an unknown demand over T periods, where in each period, the seller decides on the price for each product or the assortment of products to offer to a customer who chooses according to an unknown Multinomial Logit Model (MNL). Such problems arise in ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	262,008
1704.01250	Relative Learning from Web Images for Content-adaptive Enhancement	Personalized and content-adaptive image enhancement can find many applications in the age of social media and mobile computing. This paper presents a relative-learning-based approach, which, unlike previous methods, does not require matching original and enhanced images for training. This allows the use of massive onli...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	71,223
1812.06397	Connecting Spectral Clustering to Maximum Margins and Level Sets	We study the connections between spectral clustering and the problems of maximum margin clustering, and estimation of the components of level sets of a density function. Specifically, we obtain bounds on the eigenvectors of graph Laplacian matrices in terms of the between cluster separation, and within cluster connecti...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	116,606
2412.01410	CellSeg1: Robust Cell Segmentation with One Training Image	Recent trends in cell segmentation have shifted towards universal models to handle diverse cell morphologies and imaging modalities. However, for continuously emerging cell types and imaging techniques, these models still require hundreds or thousands of annotated cells for fine-tuning. We introduce CellSeg1, a practic...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	513,103
2408.10672	Neural Exploratory Landscape Analysis	Recent research in Meta-Black-Box Optimization (MetaBBO) have shown that meta-trained neural networks can effectively guide the design of black-box optimizers, significantly reducing the need for expert tuning and delivering robust performance across complex problem distributions. Despite their success, a paradox remai...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	481,972
2202.05714	Modeling Reservoir Release Using Pseudo-Prospective Learning and Physical Simulations to Predict Water Temperature	This paper proposes a new data-driven method for predicting water temperature in stream networks with reservoirs. The water flows released from reservoirs greatly affect the water temperature of downstream river segments. However, the information of released water flow is often not available for many reservoirs, which ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	279,961

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.