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
2201.10787	Variational Model Inversion Attacks	Given the ubiquity of deep neural networks, it is important that these models do not reveal information about sensitive data that they have been trained on. In model inversion attacks, a malicious user attempts to recover the private dataset used to train a supervised neural network. A successful model inversion attack...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	277,104
1908.09070	Optimizing Inter-Datacenter Tail Flow Completion Times using Best Worst-case Routing	Flow routing over inter-datacenter networks is a well-known problem where the network assigns a path to a newly arriving flow potentially according to the network conditions and the properties of the new flow. An essential system-wide performance metric for a routing algorithm is the flow completion times, which affect...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	142,742
2405.00717	Exploring News Summarization and Enrichment in a Highly Resource-Scarce Indian Language: A Case Study of Mizo	Obtaining sufficient information in one's mother tongue is crucial for satisfying the information needs of the users. While high-resource languages have abundant online resources, the situation is less than ideal for very low-resource languages. Moreover, the insufficient reporting of vital national and international e...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	451,045
2410.16143	An Explainable Contrastive-based Dilated Convolutional Network with Transformer for Pediatric Pneumonia Detection	Pediatric pneumonia remains a significant global threat, posing a larger mortality risk than any other communicable disease. According to UNICEF, it is a leading cause of mortality in children under five and requires prompt diagnosis. Early diagnosis using chest radiographs is the prevalent standard, but limitations in...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	500,893
2205.15436	Uncertainty Quantification for Fairness in Two-Stage Recommender Systems	Many large-scale recommender systems consist of two stages. The first stage efficiently screens the complete pool of items for a small subset of promising candidates, from which the second-stage model curates the final recommendations. In this paper, we investigate how to ensure group fairness to the items in this two-...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	299,720
2304.12306	Segment Anything in Medical Images	Medical image segmentation is a critical component in clinical practice, facilitating accurate diagnosis, treatment planning, and disease monitoring. However, existing methods, often tailored to specific modalities or disease types, lack generalizability across the diverse spectrum of medical image segmentation tasks. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	360,165
1404.2116	Rational Counterfactuals	This paper introduces the concept of rational countefactuals which is an idea of identifying a counterfactual from the factual (whether perceived or real) that maximizes the attainment of the desired consequent. In counterfactual thinking if we have a factual statement like: Saddam Hussein invaded Kuwait and consequent...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	32,181
2410.04193	Parametric Taylor series based latent dynamics identification neural networks	Numerical solving parameterised partial differential equations (P-PDEs) is highly practical yet computationally expensive, driving the development of reduced-order models (ROMs). Recently, methods that combine latent space identification techniques with deep learning algorithms (e.g., autoencoders) have shown great pot...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	495,165
1704.02809	R-Clustering for Egocentric Video Segmentation	In this paper, we present a new method for egocentric video temporal segmentation based on integrating a statistical mean change detector and agglomerative clustering(AC) within an energy-minimization framework. Given the tendency of most AC methods to oversegment video sequences when clustering their frames, we combin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	71,517
2006.10216	Generating Fundus Fluorescence Angiography Images from Structure Fundus Images Using Generative Adversarial Networks	Fluorescein angiography can provide a map of retinal vascular structure and function, which is commonly used in ophthalmology diagnosis, however, this imaging modality may pose risks of harm to the patients. To help physicians reduce the potential risks of diagnosis, an image translation method is adopted. In this work...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	182,803
1909.13485	The Book of Why: Review	This is a review of "The Book of Why", by Judea Pearl.	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	147,441
1812.07965	Deep learning with asymmetric connections and Hebbian updates	We show that deep networks can be trained using Hebbian updates yielding similar performance to ordinary back-propagation on challenging image datasets. To overcome the unrealistic symmetry in connections between layers, implicit in back-propagation, the feedback weights are separate from the feedforward weights. The f...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	116,912
1811.01183	Unsupervised Identification of Study Descriptors in Toxicology Research: An Experimental Study	Identifying and extracting data elements such as study descriptors in publication full texts is a critical yet manual and labor-intensive step required in a number of tasks. In this paper we address the question of identifying data elements in an unsupervised manner. Specifically, provided a set of criteria describing ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	112,297
2403.19907	Beyond the Known: Novel Class Discovery for Open-world Graph Learning	Node classification on graphs is of great importance in many applications. Due to the limited labeling capability and evolution in real-world open scenarios, novel classes can emerge on unlabeled testing nodes. However, little attention has been paid to novel class discovery on graphs. Discovering novel classes is chal...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	442,531
2012.03257	CoEdge: Cooperative DNN Inference with Adaptive Workload Partitioning over Heterogeneous Edge Devices	Recent advances in artificial intelligence have driven increasing intelligent applications at the network edge, such as smart home, smart factory, and smart city. To deploy computationally intensive Deep Neural Networks (DNNs) on resource-constrained edge devices, traditional approaches have relied on either offloading...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	210,051
1404.1292	Review of Face Detection Systems Based Artificial Neural Networks Algorithms	Face detection is one of the most relevant applications of image processing and biometric systems. Artificial neural networks (ANN) have been used in the field of image processing and pattern recognition. There is lack of literature surveys which give overview about the studies and researches related to the using of AN...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	32,095
2209.14067	Efficient block contrastive learning via parameter-free meta-node approximation	Contrastive learning has recently achieved remarkable success in many domains including graphs. However contrastive loss, especially for graphs, requires a large number of negative samples which is unscalable and computationally prohibitive with a quadratic time complexity. Sub-sampling is not optimal and incorrect neg...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	320,127
1903.01672	Causal Discovery from Heterogeneous/Nonstationary Data with Independent Changes	It is commonplace to encounter heterogeneous or nonstationary data, of which the underlying generating process changes across domains or over time. Such a distribution shift feature presents both challenges and opportunities for causal discovery. In this paper, we develop a framework for causal discovery from such data...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	123,313
1203.5443	Transfer Learning, Soft Distance-Based Bias, and the Hierarchical BOA	An automated technique has recently been proposed to transfer learning in the hierarchical Bayesian optimization algorithm (hBOA) based on distance-based statistics. The technique enables practitioners to improve hBOA efficiency by collecting statistics from probabilistic models obtained in previous hBOA runs and using...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	15,109
2411.13223	Existential Conversations with Large Language Models: Content, Community, and Culture	Contemporary conversational AI systems based on large language models (LLMs) can engage users on a wide variety of topics, including philosophy, spirituality, and religion. Suitably prompted, LLMs can be coaxed into discussing such existentially significant matters as their own putative consciousness and the role of ar...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	509,721
2209.07838	Notch Fracture predictions using the Phase Field method for Ti-6Al-4V produced by Selective Laser Melting after different post-processing conditions	Ti-6Al-4V is a titanium alloy with excellent properties for lightweight applications and its production through Additive Manufacturing processes is attractive for different industrial sectors. In this work, the influence of mechanical properties on the notch fracture resistance of Ti-6Al-4V produced by Selective Laser ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	317,912
2012.13668	Deep Learning Framework Applied for Predicting Anomaly of Respiratory Sounds	This paper proposes a robust deep learning framework used for classifying anomaly of respiratory cycles. Initially, our framework starts with front-end feature extraction step. This step aims to transform the respiratory input sound into a two-dimensional spectrogram where both spectral and temporal features are well p...	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	213,291
2409.11917	LLMs in Education: Novel Perspectives, Challenges, and Opportunities	The role of large language models (LLMs) in education is an increasing area of interest today, considering the new opportunities they offer for teaching, learning, and assessment. This cutting-edge tutorial provides an overview of the educational applications of NLP and the impact that the recent advances in LLMs have ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	489,363
2210.01210	A Reproducible and Realistic Evaluation of Partial Domain Adaptation Methods	Unsupervised Domain Adaptation (UDA) aims at classifying unlabeled target images leveraging source labeled ones. In this work, we consider the Partial Domain Adaptation (PDA) variant, where we have extra source classes not present in the target domain. Most successful algorithms use model selection strategies that rely...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	321,163
2310.01747	5G Network Slicing: Analysis of Multiple Machine Learning Classifiers	The division of one physical 5G communications infrastructure into several virtual network slices with distinct characteristics such as bandwidth, latency, reliability, security, and service quality is known as 5G network slicing. Each slice is a separate logical network that meets the requirements of specific services...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	396,553
2308.08968	On the Performance of Multidimensional Constellation Shaping for Linear and Nonlinear Optical Fiber Channel	Multidimensional constellation shaping of up to 32 dimensions with different spectral efficiencies are compared through AWGN and fiber-optic simulations. The results show that no constellation is universal and the balance of required and effective SNRs should be jointly considered for the specific optical transmission ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	386,103
2411.10524	Robust Communication Design in RIS-Assisted THz Channels	Terahertz (THz) communication offers the necessary bandwidth to meet the high data rate demands of next-generation wireless systems. However, it faces significant challenges, including severe path loss, dynamic blockages, and beam misalignment, which jeopardize communication reliability. Given that many 6G use cases re...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	508,680
1608.08412	A note on how the problem of Partion of Integers show in Caching	In this article, we show how the finding the number of partitions of same size of a positive integer show up in caching networks. We present a stochastic model for caching where user requests (represented with positive integers) are a random process with uniform distribution and the sum of user requests plays an import...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	60,353
1109.5114	Improvements on "Fast space-variant elliptical filtering using box splines"	It is well-known that box filters can be efficiently computed using pre-integrations and local finite-differences [Crow1984,Heckbert1986,Viola2001]. By generalizing this idea and by combining it with a non-standard variant of the Central Limit Theorem, a constant-time or O(1) algorithm was proposed in [Chaudhury2010] t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	12,291
2502.06773	On the Emergence of Thinking in LLMs I: Searching for the Right Intuition	Recent AI advancements, such as OpenAI's new models, are transforming LLMs into LRMs (Large Reasoning Models) that perform reasoning during inference, taking extra time and compute for higher-quality outputs. We aim to uncover the algorithmic framework for training LRMs. Methods like self-consistency, PRM, and AlphaZer...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	532,233
2405.04966	Communication-Efficient Collaborative Perception via Information Filling with Codebook	Collaborative perception empowers each agent to improve its perceptual ability through the exchange of perceptual messages with other agents. It inherently results in a fundamental trade-off between perception ability and communication cost. To address this bottleneck issue, our core idea is to optimize the collaborati...	false	false	false	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	452,746
2412.02610	AI-Driven Resource Allocation Framework for Microservices in Hybrid Cloud Platforms	The increasing demand for scalable, efficient resource management in hybrid cloud environments has led to the exploration of AI-driven approaches for dynamic resource allocation. This paper presents an AI-driven framework for resource allocation among microservices in hybrid cloud platforms. The framework employs reinf...	false	true	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	true	513,602
2401.04636	On the Target Detection Performance of a Molecular Communication Network with Multiple Mobile Nanomachines	A network of nanomachines (NMs) can be used to build a target detection system for a variety of promising applications. They have the potential to detect toxic chemicals, infectious bacteria, and biomarkers of dangerous diseases such as cancer within the human body. Many diseases and health disorders can be detected ea...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	420,491
1709.08127	Robust Facial Landmark Detection under Significant Head Poses and Occlusion	There have been tremendous improvements for facial landmark detection on general "in-the-wild" images. However, it is still challenging to detect the facial landmarks on images with severe occlusion and images with large head poses (e.g. profile face). In fact, the existing algorithms usually can only handle one of the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	81,410
2409.16197	Second Order Bounds for Contextual Bandits with Function Approximation	Many works have developed no-regret algorithms for contextual bandits with function approximation, where the mean reward function over context-action pairs belongs to a function class. Although there are many approaches to this problem, one that has gained in importance is the use of algorithms based on the optimism pr...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	491,241
1703.01405	Convex recovery of continuous domain piecewise constant images from non-uniform Fourier samples	We consider the recovery of a continuous domain piecewise constant image from its non-uniform Fourier samples using a convex matrix completion algorithm. We assume the discontinuities/edges of the image are localized to the zero levelset of a bandlimited function. This assumption induces linear dependencies between the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	69,358
2407.07094	AnyTaskTune: Advanced Domain-Specific Solutions through Task-Fine-Tuning	The pervasive deployment of Large Language Models-LLMs in various sectors often neglects the nuanced requirements of individuals and small organizations, who benefit more from models precisely tailored to their specific business contexts rather than those with broadly superior general capabilities. This work introduces...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	471,649
cmp-lg/9406036	Text Analysis Tools in Spoken Language Processing	This submission contains the postscript of the final version of the slides used in our ACL-94 tutorial.	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,115
1705.07226	RankPL: A Qualitative Probabilistic Programming Language	In this paper we introduce RankPL, a modeling language that can be thought of as a qualitative variant of a probabilistic programming language with a semantics based on Spohn's ranking theory. Broadly speaking, RankPL can be used to represent and reason about processes that exhibit uncertainty expressible by distinguis...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	73,784
2203.09313	EVA2.0: Investigating Open-Domain Chinese Dialogue Systems with Large-Scale Pre-Training	Large-scale pre-training has shown remarkable performance in building open-domain dialogue systems. However, previous works mainly focus on showing and evaluating the conversational performance of the released dialogue model, ignoring the discussion of some key factors towards a powerful human-like chatbot, especially ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	286,114
2206.00820	NIPQ: Noise proxy-based Integrated Pseudo-Quantization	Straight-through estimator (STE), which enables the gradient flow over the non-differentiable function via approximation, has been favored in studies related to quantization-aware training (QAT). However, STE incurs unstable convergence during QAT, resulting in notable quality degradation in low precision. Recently, ps...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	300,266
1905.10979	Scalable K-Medoids via True Error Bound and Familywise Bandits	K-Medoids(KM) is a standard clustering method, used extensively on semi-metric data.Error analyses of KM have traditionally used an in-sample notion of error,which can be far from the true error and suffer from generalization gap. We formalize the true K-Medoid error based on the underlying data distribution.We decompo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	132,286
2201.02740	Best of Both Worlds: A Hybrid Approach for Multi-Hop Explanation with Declarative Facts	Language-enabled AI systems can answer complex, multi-hop questions to high accuracy, but supporting answers with evidence is a more challenging task which is important for the transparency and trustworthiness to users. Prior work in this area typically makes a trade-off between efficiency and accuracy; state-of-the-ar...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	274,634
2404.08372	Opinion dynamics on signed graphs and graphons: Beyond the piece-wise constant case (Extended version)	In this paper we make use of graphon theory to study opinion dynamics on large undirected networks. The opinion dynamics models that we take into consideration allow for negative interactions between the individuals, i.e. competing entities whose opinions can grow apart. We consider both the repelling model and the opp...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	446,217
2412.00980	Incentivizing Truthful Collaboration in Heterogeneous Federated Learning	It is well-known that Federated Learning (FL) is vulnerable to manipulated updates from clients. In this work we study the impact of data heterogeneity on clients' incentives to manipulate their updates. We formulate a game in which clients may upscale their gradient updates in order to ``steer'' the server model to th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	512,893
1711.06420	Look, Imagine and Match: Improving Textual-Visual Cross-Modal Retrieval with Generative Models	Textual-visual cross-modal retrieval has been a hot research topic in both computer vision and natural language processing communities. Learning appropriate representations for multi-modal data is crucial for the cross-modal retrieval performance. Unlike existing image-text retrieval approaches that embed image-text pa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	84,763
1309.6390	Contextually learnt detection of unusual motion-based behaviour in crowded public spaces	In this paper we are interested in analyzing behaviour in crowded public places at the level of holistic motion. Our aim is to learn, without user input, strong scene priors or labelled data, the scope of "normal behaviour" for a particular scene and thus alert to novelty in unseen footage. The first contribution is a ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	27,242
2312.12183	Poincar\'e Differential Privacy for Hierarchy-Aware Graph Embedding	Hierarchy is an important and commonly observed topological property in real-world graphs that indicate the relationships between supervisors and subordinates or the organizational behavior of human groups. As hierarchy is introduced as a new inductive bias into the Graph Neural Networks (GNNs) in various tasks, it imp...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	416,869
1912.07225	Graph-based Neural Sentence Ordering	Sentence ordering is to restore the original paragraph from a set of sentences. It involves capturing global dependencies among sentences regardless of their input order. In this paper, we propose a novel and flexible graph-based neural sentence ordering model, which adopts graph recurrent network \cite{Zhang:acl18} to...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	157,552
1808.08601	CGIntrinsics: Better Intrinsic Image Decomposition through Physically-Based Rendering	Intrinsic image decomposition is a challenging, long-standing computer vision problem for which ground truth data is very difficult to acquire. We explore the use of synthetic data for training CNN-based intrinsic image decomposition models, then applying these learned models to real-world images. To that end, we prese...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	105,987
1006.2718	From RESTful Services to RDF: Connecting the Web and the Semantic Web	RESTful services on the Web expose information through retrievable resource representations that represent self-describing descriptions of resources, and through the way how these resources are interlinked through the hyperlinks that can be found in those representations. This basic design of RESTful services means tha...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	6,780
1209.4922	Monitoring Control Updating Period In Fast Gradient Based NMPC	In this paper, a method is proposed for on-line monitoring of the control updating period in fast-gradient-based Model Predictive Control (MPC) schemes. Such schemes are currently under intense investigation as a way to accommodate for real-time requirements when dealing with systems showing fast dynamics. The method n...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	18,684
1701.00294	The Geodesic Distance between $\mathcal{G}_I^0$ Models and its Application to Region Discrimination	The $\mathcal{G}_I^0$ distribution is able to characterize different regions in monopolarized SAR imagery. It is indexed by three parameters: the number of looks (which can be estimated in the whole image), a scale parameter and a texture parameter. This paper presents a new proposal for feature extraction and region d...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	66,254
2010.08146	Online Decision Trees with Fairness	While artificial intelligence (AI)-based decision-making systems are increasingly popular, significant concerns on the potential discrimination during the AI decision-making process have been observed. For example, the distribution of predictions is usually biased and dependents on the sensitive attributes (e.g., gende...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	201,074
2403.00835	CLLMs: Consistency Large Language Models	Parallel decoding methods such as Jacobi decoding show promise for more efficient LLM inference as it breaks the sequential nature of the LLM decoding process and transforms it into parallelizable computation. However, in practice, it achieves little speedup compared to traditional autoregressive (AR) decoding, primari...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	434,144
2008.13294	Identifying Flux Rope Signatures Using a Deep Neural Network	Among the current challenges in Space Weather, one of the main ones is to forecast the internal magnetic configuration within Interplanetary Coronal Mass Ejections (ICMEs). Currently, a monotonic and coherent magnetic configuration observed is associated with the result of a spacecraft crossing a large flux rope with h...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	193,812
1901.11369	Cross-modality (CT-MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasets	Lack of large expert annotated MR datasets makes training deep learning models difficult. Therefore, a cross-modality (MR-CT) deep learning segmentation approach that augments training data using pseudo MR images produced by transforming expert-segmented CT images was developed. Eighty-One T2-weighted MRI scans from 28...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	120,231
2201.12436	Any-Play: An Intrinsic Augmentation for Zero-Shot Coordination	Cooperative artificial intelligence with human or superhuman proficiency in collaborative tasks stands at the frontier of machine learning research. Prior work has tended to evaluate cooperative AI performance under the restrictive paradigms of self-play (teams composed of agents trained together) and cross-play (teams...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	277,644
2107.14093	A Decision Model for Decentralized Autonomous Organization Platform Selection: Three Industry Case Studies	Decentralized autonomous organizations as a new form of online governance arecollections of smart contracts deployed on a blockchain platform that intercede groupsof people. A growing number of Decentralized Autonomous Organization Platforms,such as Aragon and Colony, have been introduced in the market to facilitate th...	false	false	false	false	true	false	false	false	false	false	false	false	true	true	false	false	false	true	248,374
2302.02356	An adaptive large neighborhood search heuristic for the multi-port continuous berth allocation problem	In this paper, we study a problem that integrates the vessel scheduling problem with the berth allocation into a collaborative problem denoted as the multi-port continuous berth allocation problem (MCBAP). This problem optimizes the berth allocation of a set of ships simultaneously in multiple ports while also consider...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	343,973
0904.3469	Toggling operators in computability logic	Computability logic (CL) (see http://www.cis.upenn.edu/~giorgi/cl.html ) is a research program for redeveloping logic as a formal theory of computability, as opposed to the formal theory of truth which it has more traditionally been. Formulas in CL stand for interactive computational problems, seen as games between a m...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	3,578
2003.10760	Surface Damage Detection Scheme using Convolutional Neural Network and Artificial Neural Network	Surface damage on concrete is important as the damage can affect the structural integrity of the structure. This paper proposes a two-step surface damage detection scheme using Convolutional Neural Network (CNN) and Artificial Neural Network (ANN). The CNN classifies given input images into two categories: positive and...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	169,427
2310.11584	BasahaCorpus: An Expanded Linguistic Resource for Readability Assessment in Central Philippine Languages	Current research on automatic readability assessment (ARA) has focused on improving the performance of models in high-resource languages such as English. In this work, we introduce and release BasahaCorpus as part of an initiative aimed at expanding available corpora and baseline models for readability assessment in lo...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	400,689
2112.08466	ErAConD : Error Annotated Conversational Dialog Dataset for Grammatical Error Correction	Currently available grammatical error correction (GEC) datasets are compiled using well-formed written text, limiting the applicability of these datasets to other domains such as informal writing and dialog. In this paper, we present a novel parallel GEC dataset drawn from open-domain chatbot conversations; this datase...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	271,804
2103.03330	Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture	Graph Convolutional Networks (GCNs) are increasingly adopted in large-scale graph-based recommender systems. Training GCN requires the minibatch generator traversing graphs and sampling the sparsely located neighboring nodes to obtain their features. Since real-world graphs often exceed the capacity of GPU memory, curr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	223,236
2108.12266	MRI-compatible electromagnetic servomotors for image-guided robotic procedures	Combining the unmatched soft-tissue imaging capabilities of magnetic resonance imaging (MRI) with high precision robotics has the potential to improve the accuracy, precision, and safety of a wide range of image-guided medical procedures. However, the goal of highly functional MRI-compatible robotic systems has not yet...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	252,449
2105.11510	Grasp Planning for Flexible Production with Small Lot Sizes based on CAD models using GPIS and Bayesian Optimization	Grasp planning for multi-fingered hands is still a challenging task due to the high nonlinear quality metrics, the high dimensionality of hand posture configuration, and complex object shapes. Analytical-based grasp planning algorithms formulate the grasping problem as a constraint optimization problem using advanced c...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	236,716
2209.01948	A smooth basis for atomistic machine learning	Machine learning frameworks based on correlations of interatomic positions begin with a discretized description of the density of other atoms in the neighbourhood of each atom in the system. Symmetry considerations support the use of spherical harmonics to expand the angular dependence of this density, but there is as ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	316,058
1809.01318	Reconstruction and Registration of Large-Scale Medical Scene Using Point Clouds Data from Different Modalities	Sensing the medical scenario can ensure the safety during the surgical operations. So, in this regard, a monitor platform which can obtain the accurate location information of the surgery room is desperately needed. Compared to 2D camera image, 3D data contains more information of distance and direction. Therefore, 3D ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	106,774
2205.00671	Jack and Masters of all Trades: One-Pass Learning Sets of Model Sets From Large Pre-Trained Models	For deep learning, size is power. Massive neural nets trained on broad data for a spectrum of tasks are at the forefront of artificial intelligence. These large pre-trained models or Jacks of All Trades (JATs), when fine-tuned for downstream tasks, are gaining importance in driving deep learning advancements. However, ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	294,340
2105.03822	RBNN: Memory-Efficient Reconfigurable Deep Binary Neural Network with IP Protection for Internet of Things	Though deep neural network models exhibit outstanding performance for various applications, their large model size and extensive floating-point operations render deployment on mobile computing platforms a major challenge, and, in particular, on Internet of Things devices. One appealing solution is model quantization th...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	234,279
2107.05775	Fast and Explicit Neural View Synthesis	We study the problem of novel view synthesis from sparse source observations of a scene comprised of 3D objects. We propose a simple yet effective approach that is neither continuous nor implicit, challenging recent trends on view synthesis. Our approach explicitly encodes observations into a volumetric representation ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	245,878
2012.05391	Feasibility Assessment of a Cost-Effective Two-Wheel Kian-I Mobile Robot for Autonomous Navigation	A two-wheeled mobile robot, namely Kian-I, is designed and prototyped in this research. The Kian-I is comparable with Khepera-IV in terms of dimensional specifications, mounted sensors, and performance capabilities and can be used for educational purposes and cost-effective experimental tests. A motion control architec...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	210,760
1910.08643	Intracranial Hemorrhage Segmentation Using Deep Convolutional Model	Traumatic brain injuries could cause intracranial hemorrhage (ICH). ICH could lead to disability or death if it is not accurately diagnosed and treated in a time-sensitive procedure. The current clinical protocol to diagnose ICH is examining Computerized Tomography (CT) scans by radiologists to detect ICH and localize ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	149,922
1904.07026	Spatially Coupled LDPC Codes with Non-uniform Coupling for Improved Decoding Speed	We consider spatially coupled low-density parity-check codes with finite smoothing parameters. A finite smoothing parameter is important for designing practical codes that are decoded using low-complexity windowed decoders. By optimizing the amount of coupling between spatial positions, we show that we can construct co...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	127,693
2404.17759	Modular, Resilient, and Scalable System Design Approaches -- Lessons learned in the years after DARPA Subterranean Challenge	Field robotics applications, such as search and rescue, involve robots operating in large, unknown areas. These environments present unique challenges that compound the difficulties faced by a robot operator. The use of multi-robot teams, assisted by carefully designed autonomy, help reduce operator workload and allow ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	449,982
1202.5470	Convergence analysis of the FOCUSS algorithm	FOCal Underdetermined System Solver (FOCUSS) is a powerful tool for sparse representation and underdetermined inverse problems, which is extremely easy to implement. In this paper, we give a comprehensive convergence analysis on the FOCUSS algorithm towards establishing a systematic convergence theory by providing thre...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	14,556
1806.02180	Addressing Two Problems in Deep Knowledge Tracing via Prediction-Consistent Regularization	Knowledge tracing is one of the key research areas for empowering personalized education. It is a task to model students' mastery level of a knowledge component (KC) based on their historical learning trajectories. In recent years, a recurrent neural network model called deep knowledge tracing (DKT) has been proposed t...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	99,720
2409.17830	Unsupervised Learning Based Multi-Scale Exposure Fusion	Unsupervised learning based multi-scale exposure fusion (ULMEF) is efficient for fusing differently exposed low dynamic range (LDR) images into a higher quality LDR image for a high dynamic range (HDR) scene. Unlike supervised learning, loss functions play a crucial role in the ULMEF. In this paper, novel loss function...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	491,994
1507.08452	Unsupervised Sentence Simplification Using Deep Semantics	We present a novel approach to sentence simplification which departs from previous work in two main ways. First, it requires neither hand written rules nor a training corpus of aligned standard and simplified sentences. Second, sentence splitting operates on deep semantic structure. We show (i) that the unsupervised fr...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	45,572
2201.02783	A Fair and Efficient Hybrid Federated Learning Framework based on XGBoost for Distributed Power Prediction	In a modern power system, real-time data on power generation/consumption and its relevant features are stored in various distributed parties, including household meters, transformer stations and external organizations. To fully exploit the underlying patterns of these distributed data for accurate power prediction, fed...	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	274,651
1110.0028	Solving Factored MDPs with Hybrid State and Action Variables	Efficient representations and solutions for large decision problems with continuous and discrete variables are among the most important challenges faced by the designers of automated decision support systems. In this paper, we describe a novel hybrid factored Markov decision process (MDP) model that allows for a compac...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	12,431
2107.04702	Um Metodo para Busca Automatica de Redes Neurais Artificiais	This paper describes a method that automatically searches Artificial Neural Networks using Cellular Genetic Algorithms. The main difference of this method for a common genetic algorithm is the use of a cellular automaton capable of providing the location for individuals, reducing the possibility of local minima in sear...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	245,538
1903.07881	Stabilizability preserving quotients of non-linear systems	In this paper quotients of control systems which are generalizations of system reductions are used to study the stabilizability property of non-linear systems. Given a control system and its quotient we study under what conditions stabilizability of the quotient is sufficient to guarantee stabilizability of the origina...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	124,728
1302.2056	Complexity distribution of agent policies	We analyse the complexity of environments according to the policies that need to be used to achieve high performance. The performance results for a population of policies leads to a distribution that is examined in terms of policy complexity and analysed through several diagrams and indicators. The notion of environmen...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	21,911
2304.13134	LAST: Scalable Lattice-Based Speech Modelling in JAX	We introduce LAST, a LAttice-based Speech Transducer library in JAX. With an emphasis on flexibility, ease-of-use, and scalability, LAST implements differentiable weighted finite state automaton (WFSA) algorithms needed for training \& inference that scale to a large WFSA such as a recognition lattice over the entire u...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	360,465
1904.04399	Sketchforme: Composing Sketched Scenes from Text Descriptions for Interactive Applications	Sketching and natural languages are effective communication media for interactive applications. We introduce Sketchforme, the first neural-network-based system that can generate sketches based on text descriptions specified by users. Sketchforme is capable of gaining high-level and low-level understanding of multi-obje...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	127,023
1906.03323	Empirical Likelihood for Contextual Bandits	We propose an estimator and confidence interval for computing the value of a policy from off-policy data in the contextual bandit setting. To this end we apply empirical likelihood techniques to formulate our estimator and confidence interval as simple convex optimization problems. Using the lower bound of our confiden...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	134,337
2406.08695	Global AI Governance in Healthcare: A Cross-Jurisdictional Regulatory Analysis	Artificial Intelligence (AI) is being adopted across the world and promises a new revolution in healthcare. While AI-enabled medical devices in North America dominate 42.3% of the global market, the use of AI-enabled medical devices in other countries is still a story waiting to be unfolded. We aim to delve deeper into...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	463,585
2304.13736	Automated Whole Slide Imaging for Label-Free Histology using Photon Absorption Remote Sensing Microscopy	The field of histology relies heavily on antiquated tissue processing and staining techniques that limit the efficiency of pathologic diagnoses of cancer and other diseases. Current staining and advanced labeling methods are often destructive and mutually incompatible, requiring new tissue sections for each stain. This...	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	360,691
1502.00395	Threshold Functions in Random s-Intersection Graphs	Random $s$-intersection graphs have recently received considerable attention in a wide range of application areas. In such a graph, each vertex is equipped with a set of items in some random manner, and any two vertices establish an undirected edge in between if and only if they have at least $s$ common items. In parti...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	39,820
2410.09836	Learning Pattern-Specific Experts for Time Series Forecasting Under Patch-level Distribution Shift	Time series forecasting, which aims to predict future values based on historical data, has garnered significant attention due to its broad range of applications. However, real-world time series often exhibit complex non-uniform distribution with varying patterns across segments, such as season, operating condition, or ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	497,790
1904.12987	Optical Transient Object Classification in Wide Field Small Aperture Telescopes with Neural Networks	Wide field small aperture telescopes are working horses for fast sky surveying. Transient discovery is one of their main tasks. Classification of candidate transient images between real sources and artifacts with high accuracy is an important step for transient discovery. In this paper, we propose two transient classif...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	129,263
cs/0405043	Prediction with Expert Advice by Following the Perturbed Leader for General Weights	When applying aggregating strategies to Prediction with Expert Advice, the learning rate must be adaptively tuned. The natural choice of sqrt(complexity/current loss) renders the analysis of Weighted Majority derivatives quite complicated. In particular, for arbitrary weights there have been no results proven so far. T...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	538,196
2405.19355	Enhancing Trust and Security in the Vehicular Metaverse: A Reputation-Based Mechanism for Participants with Moral Hazard	In this paper, we tackle the issue of moral hazard within the realm of the vehicular Metaverse. A pivotal facilitator of the vehicular Metaverse is the effective orchestration of its market elements, primarily comprised of sensing internet of things (SIoT) devices. These SIoT devices play a critical role by furnishing ...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	458,867
1712.10042	Discriminative and Geometry Aware Unsupervised Domain Adaptation	Domain adaptation (DA) aims to generalize a learning model across training and testing data despite the mismatch of their data distributions. In light of a theoretical estimation of upper error bound, we argue in this paper that an effective DA method should 1) search a shared feature subspace where source and target d...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	87,436
2003.08298	Axiom Pinpointing	Axiom pinpointing refers to the task of finding the specific axioms in an ontology which are responsible for a consequence to follow. This task has been studied, under different names, in many research areas, leading to a reformulation and reinvention of techniques. In this work, we present a general overview to axiom ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	168,689
1211.4122	Cost-sensitive C4.5 with post-pruning and competition	Decision tree is an effective classification approach in data mining and machine learning. In applications, test costs and misclassification costs should be considered while inducing decision trees. Recently, some cost-sensitive learning algorithms based on ID3 such as CS-ID3, IDX, \lambda-ID3 have been proposed to dea...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	19,777
2409.19951	Law of the Weakest Link: Cross Capabilities of Large Language Models	The development and evaluation of Large Language Models (LLMs) have largely focused on individual capabilities. However, this overlooks the intersection of multiple abilities across different types of expertise that are often required for real-world tasks, which we term cross capabilities. To systematically explore thi...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	492,928
1911.05978	HUSE: Hierarchical Universal Semantic Embeddings	There is a recent surge of interest in cross-modal representation learning corresponding to images and text. The main challenge lies in mapping images and text to a shared latent space where the embeddings corresponding to a similar semantic concept lie closer to each other than the embeddings corresponding to differen...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	153,428

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