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
2311.06210	Optimal Cooperative Multiplayer Learning Bandits with Noisy Rewards and No Communication	We consider a cooperative multiplayer bandit learning problem where the players are only allowed to agree on a strategy beforehand, but cannot communicate during the learning process. In this problem, each player simultaneously selects an action. Based on the actions selected by all players, the team of players receive...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	406,845
2110.04523	An Empirical Study on Compressed Decentralized Stochastic Gradient Algorithms with Overparameterized Models	This paper considers decentralized optimization with application to machine learning on graphs. The growing size of neural network (NN) models has motivated prior works on decentralized stochastic gradient algorithms to incorporate communication compression. On the other hand, recent works have demonstrated the favorab...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	259,931
2305.08660	Towards Automated COVID-19 Presence and Severity Classification	COVID-19 presence classification and severity prediction via (3D) thorax computed tomography scans have become important tasks in recent times. Especially for capacity planning of intensive care units, predicting the future severity of a COVID-19 patient is crucial. The presented approach follows state-of-theart techni...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	364,359
2412.01837	Enabling Explainable Recommendation in E-commerce with LLM-powered Product Knowledge Graph	How to leverage large language model's superior capability in e-commerce recommendation has been a hot topic. In this paper, we propose LLM-PKG, an efficient approach that distills the knowledge of LLMs into product knowledge graph (PKG) and then applies PKG to provide explainable recommendations. Specifically, we firs...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	513,287
2210.15623	Neural Networks with Quantization Constraints	Enabling low precision implementations of deep learning models, without considerable performance degradation, is necessary in resource and latency constrained settings. Moreover, exploiting the differences in sensitivity to quantization across layers can allow mixed precision implementations to achieve a considerably b...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	327,025
1405.5937	Polynomial trajectory algorithm for a biped robot	Building trajectories for biped robot walking is a complex task considering all degrees of freedom (DOFs) commonly bound within the mechanical structure. A typical problem for such robots is the instability produced by violent transitions between walking phases in particular when a swinging leg impacts the surface. Alt...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	33,320
1912.05357	Feeding the zombies: Synthesizing brain volumes using a 3D progressive growing GAN	Deep learning requires large datasets for training (convolutional) networks with millions of parameters. In neuroimaging, there are few open datasets with more than 100 subjects, which makes it difficult to, for example, train a classifier to discriminate controls from diseased persons. Generative adversarial networks ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	157,087
2101.04017	A Commonsense Reasoning Framework for Explanatory Emotion Attribution, Generation and Re-classification	We present DEGARI (Dynamic Emotion Generator And ReclassIfier), an explainable system for emotion attribution and recommendation. This system relies on a recently introduced commonsense reasoning framework, the TCL logic, which is based on a human-like procedure for the automatic generation of novel concepts in a Descr...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	215,048
2309.15848	SHACIRA: Scalable HAsh-grid Compression for Implicit Neural Representations	Implicit Neural Representations (INR) or neural fields have emerged as a popular framework to encode multimedia signals such as images and radiance fields while retaining high-quality. Recently, learnable feature grids proposed by Instant-NGP have allowed significant speed-up in the training as well as the sampling of ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	395,141
2210.10420	Modeling the impact of external influence on green behaviour spreading in multilayer financial networks	Growing awareness of the impact of business activity on the environment increases the pressure on governing bodies to address this issue. One possibility is to encourage or force the market into green behaviours. However, it is often hard to predict how different actions affect the market. Thus, to help with that, in t...	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	324,912
1102.1536	Evolutionary multiobjective optimization of the multi-location transshipment problem	We consider a multi-location inventory system where inventory choices at each location are centrally coordinated. Lateral transshipments are allowed as recourse actions within the same echelon in the inventory system to reduce costs and improve service level. However, this transshipment process usually causes undesirab...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	9,078
2012.12551	C-RAN Zero-Forcing with Imperfect CSI: Analysis and Precode\&Quantize Feedback	Downlink joint transmission by a cluster of remote radio heads (RRHs) is an essential technique for enhancing throughput in future cellular networks. This method requires global channel state information (CSI) at the processing unit that designs the joint precoder. To this end, a large amount of CSI must be shared betw...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	212,977
2212.12442	Alignment Entropy Regularization	Existing training criteria in automatic speech recognition(ASR) permit the model to freely explore more than one time alignments between the feature and label sequences. In this paper, we use entropy to measure a model's uncertainty, i.e. how it chooses to distribute the probability mass over the set of allowed alignme...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	338,041
1601.02789	Comparison and Adaptation of Automatic Evaluation Metrics for Quality Assessment of Re-Speaking	Re-speaking is a mechanism for obtaining high quality subtitles for use in live broadcast and other public events. Because it relies on humans performing the actual re-speaking, the task of estimating the quality of the results is non-trivial. Most organisations rely on humans to perform the actual quality assessment, ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	50,861
2208.11546	Unsupervised Structure-Consistent Image-to-Image Translation	The Swapping Autoencoder achieved state-of-the-art performance in deep image manipulation and image-to-image translation. We improve this work by introducing a simple yet effective auxiliary module based on gradient reversal layers. The auxiliary module's loss forces the generator to learn to reconstruct an image with ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	314,470
2102.06361	SCOUT: Socially-COnsistent and UndersTandable Graph Attention Network for Trajectory Prediction of Vehicles and VRUs	Autonomous vehicles navigate in dynamically changing environments under a wide variety of conditions, being continuously influenced by surrounding objects. Modelling interactions among agents is essential for accurately forecasting other agents' behaviour and achieving safe and comfortable motion planning. In this work...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	219,724
2005.03186	An Optimal Control Theory for the Traveling Salesman Problem and Its Variants	We show that the traveling salesman problem (TSP) and its many variants may be modeled as functional optimization problems over a graph. In this formulation, all vertices and arcs of the graph are functionals; i.e., a mapping from a space of measurable functions to the field of real numbers. Many variants of the TSP, s...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	true	176,076
2111.14168	Mapping Industry 4.0 Technologies: From Cyber-Physical Systems to Artificial Intelligence	The fourth industrial revolution is rapidly changing the manufacturing landscape. Due to the growing research and fast evolution in this field, no clear definitions of these concepts yet exist. This work provides a clear description of technological trends and gaps. We introduce a novel method to create a map of Indust...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	268,512
2009.02476	Using Machine Teaching to Investigate Human Assumptions when Teaching Reinforcement Learners	Successful teaching requires an assumption of how the learner learns - how the learner uses experiences from the world to update their internal states. We investigate what expectations people have about a learner when they teach them in an online manner using rewards and punishment. We focus on a common reinforcement l...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	194,555
2210.07689	Computational Design of Active Kinesthetic Garments	Garments with the ability to provide kinesthetic force-feedback on-demand can augment human capabilities in a non-obtrusive way, enabling numerous applications in VR haptics, motion assistance, and robotic control. However, designing such garments is a complex, and often manual task, particularly when the goal is to re...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	323,825
1302.6801	A Probabilistic Model of Action for Least-Commitment Planning with Information Gather	AI planning algorithms have addressed the problem of generating sequences of operators that achieve some input goal, usually assuming that the planning agent has perfect control over and information about the world. Relaxing these assumptions requires an extension to the action representation that allows reasoning both...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	22,431
2212.07967	Distributed-Training-and-Execution Multi-Agent Reinforcement Learning for Power Control in HetNet	In heterogeneous networks (HetNets), the overlap of small cells and the macro cell causes severe cross-tier interference. Although there exist some approaches to address this problem, they usually require global channel state information, which is hard to obtain in practice, and get the sub-optimal power allocation pol...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	true	false	false	false	336,585
2205.10259	Random Coordinate Descent for Resource Allocation in Open Multi-Agent Systems	We propose a method for analyzing the distributed random coordinate descent algorithm for solving separable resource allocation problems in the context of an open multiagent system, where agents can be replaced during the process. In particular, we characterize the evolution of the distance to the minimizer in expectat...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	297,632
2208.00690	Generative Bias for Robust Visual Question Answering	The task of Visual Question Answering (VQA) is known to be plagued by the issue of VQA models exploiting biases within the dataset to make its final prediction. Various previous ensemble based debiasing methods have been proposed where an additional model is purposefully trained to be biased in order to train a robust ...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	310,931
2406.17341	Generative Modelling of Structurally Constrained Graphs	Graph diffusion models have emerged as state-of-the-art techniques in graph generation; yet, integrating domain knowledge into these models remains challenging. Domain knowledge is particularly important in real-world scenarios, where invalid generated graphs hinder deployment in practical applications. Unconstrained a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	467,535
2107.03591	Relation-Based Associative Joint Location for Human Pose Estimation in Videos	Video-based human pose estimation (VHPE) is a vital yet challenging task. While deep learning methods have made significant progress for the VHPE, most approaches to this task implicitly model the long-range interaction between joints by enlarging the receptive field of the convolution. Unlike prior methods, we design ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	245,198
2404.06483	RhythmMamba: Fast Remote Physiological Measurement with Arbitrary Length Videos	Remote photoplethysmography (rPPG) is a non-contact method for detecting physiological signals from facial videos, holding great potential in various applications such as healthcare, affective computing, and anti-spoofing. Existing deep learning methods struggle to address two core issues of rPPG simultaneously: extrac...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	445,485
2308.13545	Feature Extraction Using Deep Generative Models for Bangla Text Classification on a New Comprehensive Dataset	The selection of features for text classification is a fundamental task in text mining and information retrieval. Despite being the sixth most widely spoken language in the world, Bangla has received little attention due to the scarcity of text datasets. In this research, we collected, annotated, and prepared a compreh...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	387,960
1501.05606	A rapid algorithm to calculate joint probability matrices for joint entropies of arbitrary order	There is no closed form analytical equation or quick method to calculate probabilities based only on the entropy of a signal or process. Except in the cases where there are constraints on the state probabilities, one must typically derive the underlying probabilities through search algorithms. These become more computa...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,499
2403.06832	Noise-powered Multi-modal Knowledge Graph Representation Framework	The rise of Multi-modal Pre-training highlights the necessity for a unified Multi-Modal Knowledge Graph (MMKG) representation learning framework. Such a framework is essential for embedding structured knowledge into multi-modal Large Language Models effectively, alleviating issues like knowledge misconceptions and mult...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	436,624
2002.05967	Integrating Discrete and Neural Features via Mixed-feature Trans-dimensional Random Field Language Models	There has been a long recognition that discrete features (n-gram features) and neural network based features have complementary strengths for language models (LMs). Improved performance can be obtained by model interpolation, which is, however, a suboptimal two-step integration of discrete and neural features. The tran...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	164,053
2204.08836	System Analysis for Responsible Design of Modern AI/ML Systems	The irresponsible use of ML algorithms in practical settings has received a lot of deserved attention in the recent years. We posit that the traditional system analysis perspective is needed when designing and implementing ML algorithms and systems. Such perspective can provide a formal way for evaluating and enabling ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	292,231
2404.07514	Generalization Gap in Data Augmentation: Insights from Illumination	In the field of computer vision, data augmentation is widely used to enrich the feature complexity of training datasets with deep learning techniques. However, regarding the generalization capabilities of models, the difference in artificial features generated by data augmentation and natural visual features has not be...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	445,864
2202.13710	Best of Many Worlds Guarantees for Online Learning with Knapsacks	We study online learning problems in which a decision maker wants to maximize their expected reward without violating a finite set of $m$ resource constraints. By casting the learning process over a suitably defined space of strategy mixtures, we recover strong duality on a Lagrangian relaxation of the underlying optim...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	282,725
1601.06009	Compressed sensing with corrupted observations	We proposed a weighted l1 minimization to recover a sparse signal vector and the corrupted noise vector from a linear measurement when the sensing matrix A is an m by n row i.i.d subgaussian matrix. We obtain both uniform and nonuniform recovery guarantees when the corrupted observations occupy a constant fraction of t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	51,195
1611.06972	Measuring Sample Quality with Diffusions	Stein's method for measuring convergence to a continuous target distribution relies on an operator characterizing the target and Stein factor bounds on the solutions of an associated differential equation. While such operators and bounds are readily available for a diversity of univariate targets, few multivariate targ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	64,288
1004.2131	A New Full-diversity Criterion and Low-complexity STBCs with Partial Interference Cancellation Decoding	Recently, Guo and Xia gave sufficient conditions for an STBC to achieve full diversity when a PIC (Partial Interference Cancellation) or a PIC-SIC (PIC with Successive Interference Cancellation) decoder is used at the receiver. In this paper, we give alternative conditions for an STBC to achieve full diversity with PIC...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	6,154
2308.15164	ABS-SGD: A Delayed Synchronous Stochastic Gradient Descent Algorithm with Adaptive Batch Size for Heterogeneous GPU Clusters	As the size of models and datasets grows, it has become increasingly common to train models in parallel. However, existing distributed stochastic gradient descent (SGD) algorithms suffer from insufficient utilization of computational resources and poor convergence in heterogeneous clusters. In this paper, we propose a ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	388,590
2001.03856	Fine-grained Image-to-Image Transformation towards Visual Recognition	Existing image-to-image transformation approaches primarily focus on synthesizing visually pleasing data. Generating images with correct identity labels is challenging yet much less explored. It is even more challenging to deal with image transformation tasks with large deformation in poses, viewpoints, or scales while...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	160,081
1912.07725	Robust Adaptive Least Squares Polynomial Chaos Expansions in High-Frequency Applications	We present an algorithm for computing sparse, least squares-based polynomial chaos expansions, incorporating both adaptive polynomial bases and sequential experimental designs. The algorithm is employed to approximate stochastic high-frequency electromagnetic models in a black-box way, in particular, given only a datas...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	157,661
2109.04298	Quantum Machine Learning for Finance	Quantum computers are expected to surpass the computational capabilities of classical computers during this decade, and achieve disruptive impact on numerous industry sectors, particularly finance. In fact, finance is estimated to be the first industry sector to benefit from Quantum Computing not only in the medium and...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	254,346
2305.12906	Latent Magic: An Investigation into Adversarial Examples Crafted in the Semantic Latent Space	Adversarial attacks against Deep Neural Networks(DNN) have been a crutial topic ever since \cite{goodfellow} purposed the vulnerability of DNNs. However, most prior works craft adversarial examples in the pixel space, following the $l_p$ norm constraint. In this paper, we give intuitional explain about why crafting adv...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	366,245
2112.05485	Visual Transformers with Primal Object Queries for Multi-Label Image Classification	Multi-label image classification is about predicting a set of class labels that can be considered as orderless sequential data. Transformers process the sequential data as a whole, therefore they are inherently good at set prediction. The first vision-based transformer model, which was proposed for the object detection...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	270,856
1708.05144	Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation	In this work, we propose to apply trust region optimization to deep reinforcement learning using a recently proposed Kronecker-factored approximation to the curvature. We extend the framework of natural policy gradient and propose to optimize both the actor and the critic using Kronecker-factored approximate curvature ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	79,083
2412.13577	Bridge then Begin Anew: Generating Target-relevant Intermediate Model for Source-free Visual Emotion Adaptation	Visual emotion recognition (VER), which aims at understanding humans' emotional reactions toward different visual stimuli, has attracted increasing attention. Given the subjective and ambiguous characteristics of emotion, annotating a reliable large-scale dataset is hard. For reducing reliance on data labeling, domain ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	518,349
1510.03492	Interference Suppression in Multiuser Systems Based on Bidirectional Algorithms	This paper presents adaptive bidirectional minimum mean-square error parameter estimation algorithms for fast-fading channels. The time correlation between successive channel gains is exploited to improve the estimation and tracking capabilities of adaptive algorithms and provide robustness against time-varying channel...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	47,837
2211.09207	A Graph-Based Context-Aware Model to Understand Online Conversations	Online forums that allow for participatory engagement between users have been transformative for the public discussion of many important issues. However, such conversations can sometimes escalate into full-blown exchanges of hate and misinformation. Existing approaches in natural language processing (NLP), such as deep...	false	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	330,904
2106.00797	QLSD: Quantised Langevin stochastic dynamics for Bayesian federated learning	The objective of Federated Learning (FL) is to perform statistical inference for data which are decentralised and stored locally on networked clients. FL raises many constraints which include privacy and data ownership, communication overhead, statistical heterogeneity, and partial client participation. In this paper, ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	238,260
2003.13332	Stochastic Proximal Gradient Algorithm with Minibatches. Application to Large Scale Learning Models	Stochastic optimization lies at the core of most statistical learning models. The recent great development of stochastic algorithmic tools focused significantly onto proximal gradient iterations, in order to find an efficient approach for nonsmooth (composite) population risk functions. The complexity of finding optima...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	170,182
2001.10280	Reservoir computing model of two-dimensional turbulent convection	Reservoir computing is applied to model the large-scale evolution and the resulting low-order turbulence statistics of a two-dimensional turbulent Rayleigh-B\'{e}nard convection flow at a Rayleigh number ${\rm Ra}=10^7$ and a Prandtl number ${\rm Pr}=7$ in an extended domain with an aspect ratio of 6. Our data-driven a...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	161,779
2302.12803	PiPar: Pipeline Parallelism for Collaborative Machine Learning	Collaborative machine learning (CML) techniques, such as federated learning, have been proposed to train deep learning models across multiple mobile devices and a server. CML techniques are privacy-preserving as a local model that is trained on each device instead of the raw data from the device is shared with the serv...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	347,697
2106.14338	Regret Analysis in Deterministic Reinforcement Learning	We consider Markov Decision Processes (MDPs) with deterministic transitions and study the problem of regret minimization, which is central to the analysis and design of optimal learning algorithms. We present logarithmic problem-specific regret lower bounds that explicitly depend on the system parameter (in contrast to...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	243,373
2302.05631	A Survey on Spectral Graph Neural Networks	Graph neural networks (GNNs) have attracted considerable attention from the research community. It is well established that GNNs are usually roughly divided into spatial and spectral methods. Despite that spectral GNNs play an important role in both graph signal processing and graph representation learning, existing st...	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	false	false	345,114
2310.14579	FedSplitX: Federated Split Learning for Computationally-Constrained Heterogeneous Clients	Foundation models (FMs) have demonstrated remarkable performance in machine learning but demand extensive training data and computational resources. Federated learning (FL) addresses the challenges posed by FMs, especially related to data privacy and computational burdens. However, FL on FMs faces challenges in situati...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	401,927
2402.09739	QuRating: Selecting High-Quality Data for Training Language Models	Selecting high-quality pre-training data is important for creating capable language models, but existing methods rely on simple heuristics. We introduce QuRating, a method for selecting pre-training data that can capture human intuitions about data quality. In this paper, we investigate four qualities - writing style, ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	429,660
2307.02796	VerifAI: Verified Generative AI	Generative AI has made significant strides, yet concerns about the accuracy and reliability of its outputs continue to grow. Such inaccuracies can have serious consequences such as inaccurate decision-making, the spread of false information, privacy violations, legal liabilities, and more. Although efforts to address t...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	377,816
2203.02295	Evaluating Local Model-Agnostic Explanations of Learning to Rank Models with Decision Paths	Local explanations of learning-to-rank (LTR) models are thought to extract the most important features that contribute to the ranking predicted by the LTR model for a single data point. Evaluating the accuracy of such explanations is challenging since the ground truth feature importance scores are not available for mos...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	283,707
1711.10144	The game theoretic p-Laplacian and semi-supervised learning with few labels	We study the game theoretic p-Laplacian for semi-supervised learning on graphs, and show that it is well-posed in the limit of finite labeled data and infinite unlabeled data. In particular, we show that the continuum limit of graph-based semi-supervised learning with the game theoretic p-Laplacian is a weighted versio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	85,530
2202.08153	IoT Smart Plant Monitoring, Watering and Security System	Interest in home gardening has burgeoned since governments around the world-imposed lockdowns to suppress the spread of COVID-19. Nowadays, most families start to do gardening during this lockdown season because they can grow vegetables and fruits or any other plants that they want in their day-to-day life. So, they ca...	false	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	280,783
2312.10588	Post-Training Quantization for Re-parameterization via Coarse & Fine Weight Splitting	Although neural networks have made remarkable advancements in various applications, they require substantial computational and memory resources. Network quantization is a powerful technique to compress neural networks, allowing for more efficient and scalable AI deployments. Recently, Re-parameterization has emerged as...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	416,235
2402.13700	On the Conflict of Robustness and Learning in Collaborative Machine Learning	Collaborative Machine Learning (CML) allows participants to jointly train a machine learning model while keeping their training data private. In many scenarios where CML is seen as the solution to privacy issues, such as health-related applications, safety is also a primary concern. To ensure that CML processes produce...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	431,374
1308.2451	What can Social Media teach us about protests? Analyzing the Chilean 2011-12 Student Movement's Network evolution through Twitter data	Using social media data -specially twitter -of the Chilean 2011-12 student movement, we study their social network evolution over time to analyze how leaders and participants self-organize and spread information. Based on a few key events of the student movement's timeline, we visualize the student network trajectory a...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	26,385
2411.07126	Edify Image: High-Quality Image Generation with Pixel Space Laplacian Diffusion Models	We introduce Edify Image, a family of diffusion models capable of generating photorealistic image content with pixel-perfect accuracy. Edify Image utilizes cascaded pixel-space diffusion models trained using a novel Laplacian diffusion process, in which image signals at different frequency bands are attenuated at varyi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	507,403
2302.04868	MEGANE: Morphable Eyeglass and Avatar Network	Eyeglasses play an important role in the perception of identity. Authentic virtual representations of faces can benefit greatly from their inclusion. However, modeling the geometric and appearance interactions of glasses and the face of virtual representations of humans is challenging. Glasses and faces affect each oth...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	344,855
2106.01045	Cascade versus Direct Speech Translation: Do the Differences Still Make a Difference?	Five years after the first published proofs of concept, direct approaches to speech translation (ST) are now competing with traditional cascade solutions. In light of this steady progress, can we claim that the performance gap between the two is closed? Starting from this question, we present a systematic comparison be...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	238,360
2107.08337	Exploring the Potential of Lexical Paraphrases for Mitigating Noise-Induced Comprehension Errors	Listening in noisy environments can be difficult even for individuals with a normal hearing thresholds. The speech signal can be masked by noise, which may lead to word misperceptions on the side of the listener, and overall difficulty to understand the message. To mitigate hearing difficulties on listeners, a co-opera...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	246,693
2106.09069	Automatic Construction of Evaluation Suites for Natural Language Generation Datasets	Machine learning approaches applied to NLP are often evaluated by summarizing their performance in a single number, for example accuracy. Since most test sets are constructed as an i.i.d. sample from the overall data, this approach overly simplifies the complexity of language and encourages overfitting to the head of t...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	241,531
2309.03843	Gradient-Based Feature Learning under Structured Data	Recent works have demonstrated that the sample complexity of gradient-based learning of single index models, i.e. functions that depend on a 1-dimensional projection of the input data, is governed by their information exponent. However, these results are only concerned with isotropic data, while in practice the input o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	390,530
2009.02188	Phenotypical Ontology Driven Framework for Multi-Task Learning	Despite the large number of patients in Electronic Health Records (EHRs), the subset of usable data for modeling outcomes of specific phenotypes are often imbalanced and of modest size. This can be attributed to the uneven coverage of medical concepts in EHRs. In this paper, we propose OMTL, an Ontology-driven Multi-Ta...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	194,488
2305.02668	LatentAugment: Dynamically Optimized Latent Probabilities of Data Augmentation	Although data augmentation is a powerful technique for improving the performance of image classification tasks, it is difficult to identify the best augmentation policy. The optimal augmentation policy, which is the latent variable, cannot be directly observed. To address this problem, this study proposes $\textit{Late...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	362,130
2401.08236	Interpreting Node Embedding Distances Through $n$-order Proximity Neighbourhoods	In the field of node representation learning the task of interpreting latent dimensions has become a prominent, well-studied research topic. The contribution of this work focuses on appraising the interpretability of another rarely-exploited feature of node embeddings increasingly utilised in recommendation and consump...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	421,818
2012.12465	Future-Guided Incremental Transformer for Simultaneous Translation	Simultaneous translation (ST) starts translations synchronously while reading source sentences, and is used in many online scenarios. The previous wait-k policy is concise and achieved good results in ST. However, wait-k policy faces two weaknesses: low training speed caused by the recalculation of hidden states and la...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	212,943
2402.16116	On Performance of RIS-Aided Fluid Antenna Systems	This letter studies the performance of reconfigurable intelligent surface (RIS)-aided communications for a fluid antenna system (FAS) enabled receiver. Specifically, a fixed singleantenna base station (BS) transmits information through a RIS to a mobile user (MU) which is equipped with a planar fluid antenna in the abs...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	432,430
1603.04614	Scalable Image Retrieval by Sparse Product Quantization	Fast Approximate Nearest Neighbor (ANN) search technique for high-dimensional feature indexing and retrieval is the crux of large-scale image retrieval. A recent promising technique is Product Quantization, which attempts to index high-dimensional image features by decomposing the feature space into a Cartesian product...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	53,268
2205.05320	Arbitrary Shape Text Detection via Boundary Transformer	In arbitrary shape text detection, locating accurate text boundaries is challenging and non-trivial. Existing methods often suffer from indirect text boundary modeling or complex post-processing. In this paper, we systematically present a unified coarse-to-fine framework via boundary learning for arbitrary shape text d...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	295,900
2103.07783	Multi-Object Tracking using Poisson Multi-Bernoulli Mixture Filtering for Autonomous Vehicles	The ability of an autonomous vehicle to perform 3D tracking is essential for safe planing and navigation in cluttered environments. The main challenges for multi-object tracking (MOT) in autonomous driving applications reside in the inherent uncertainties regarding the number of objects, when and where the objects may ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	224,695
2403.09100	Virtual birefringence imaging and histological staining of amyloid deposits in label-free tissue using autofluorescence microscopy and deep learning	Systemic amyloidosis is a group of diseases characterized by the deposition of misfolded proteins in various organs and tissues, leading to progressive organ dysfunction and failure. Congo red stain is the gold standard chemical stain for the visualization of amyloid deposits in tissue sections, as it forms complexes w...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	437,629
2203.03702	On a Continuous-Time Version of Willems' Lemma	In this paper, a method to represent every input-output trajectory of a continuous-time linear system in terms of previously collected data is presented. This corresponds to a continuous-time version of the well-known Willems' lemma. The result is obtained by sampling the continuous signals at regular intervals, and co...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	284,186
2208.11508	PSSAT: A Perturbed Semantic Structure Awareness Transferring Method for Perturbation-Robust Slot Filling	Most existing slot filling models tend to memorize inherent patterns of entities and corresponding contexts from training data. However, these models can lead to system failure or undesirable outputs when being exposed to spoken language perturbation or variation in practice. We propose a perturbed semantic structure a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	314,451
2301.07507	Graphix-T5: Mixing Pre-Trained Transformers with Graph-Aware Layers for Text-to-SQL Parsing	The task of text-to-SQL parsing, which aims at converting natural language questions into executable SQL queries, has garnered increasing attention in recent years, as it can assist end users in efficiently extracting vital information from databases without the need for technical background. One of the major challenge...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	340,941
2411.02464	You are out of context!	This research proposes a novel drift detection methodology for machine learning (ML) models based on the concept of ''deformation'' in the vector space representation of data. Recognizing that new data can act as forces stretching, compressing, or twisting the geometric relationships learned by a model, we explore vari...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	505,518
2405.07550	Wild Berry image dataset collected in Finnish forests and peatlands using drones	Berry picking has long-standing traditions in Finland, yet it is challenging and can potentially be dangerous. The integration of drones equipped with advanced imaging techniques represents a transformative leap forward, optimising harvests and promising sustainable practices. We propose WildBe, the first image dataset...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	453,761
2404.03278	Evaluating Document Simplification: On the Importance of Separately Assessing Simplicity and Meaning Preservation	Text simplification intends to make a text easier to read while preserving its core meaning. Intuitively and as shown in previous works, these two dimensions (simplification and meaning preservation) are often-times inversely correlated. An overly conservative text will fail to simplify sufficiently, whereas extreme si...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	444,191
2203.07772	Fast Autofocusing using Tiny Transformer Networks for Digital Holographic Microscopy	The numerical wavefront backpropagation principle of digital holography confers unique extended focus capabilities, without mechanical displacements along z-axis. However, the determination of the correct focusing distance is a non-trivial and time consuming issue. A deep learning (DL) solution is proposed to cast the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	285,555
1910.03678	Unfolding the Structure of a Document using Deep Learning	Understanding and extracting of information from large documents, such as business opportunities, academic articles, medical documents and technical reports, poses challenges not present in short documents. Such large documents may be multi-themed, complex, noisy and cover diverse topics. We describe a framework that c...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	148,554
2212.12620	Mantis: Enabling Energy-Efficient Autonomous Mobile Agents with Spiking Neural Networks	Autonomous mobile agents such as unmanned aerial vehicles (UAVs) and mobile robots have shown huge potential for improving human productivity. These mobile agents require low power/energy consumption to have a long lifespan since they are usually powered by batteries. These agents also need to adapt to changing/dynamic...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	true	false	false	338,076
2012.12788	Short-term Operational Planning Problem of the Multiple-Energy Carrier Hybrid AC/DC Microgrids	In this paper, the short-term operation problem for a multiple energy carrier hybrid AC/DC microgrid is discussed. The hybrid microgrid consists of AC and DC parts, which are connected by means of inverters as well as natural gas network. The microgrid includes photovoltaic (PV) unit, wind turbine (WT), battery storage...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	213,030
2104.14135	Action Unit Memory Network for Weakly Supervised Temporal Action Localization	Weakly supervised temporal action localization aims to detect and localize actions in untrimmed videos with only video-level labels during training. However, without frame-level annotations, it is challenging to achieve localization completeness and relieve background interference. In this paper, we present an Action U...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	232,732
1909.02119	Inductive-bias-driven Reinforcement Learning For Efficient Schedules in Heterogeneous Clusters	The problem of scheduling of workloads onto heterogeneous processors (e.g., CPUs, GPUs, FPGAs) is of fundamental importance in modern data centers. Current system schedulers rely on application/system-specific heuristics that have to be built on a case-by-case basis. Recent work has demonstrated ML techniques for autom...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	144,097
1108.4096	A Deterministic Equivalent for the Analysis of Non-Gaussian Correlated MIMO Multiple Access Channels	Large dimensional random matrix theory (RMT) has provided an efficient analytical tool to understand multiple-input multiple-output (MIMO) channels and to aid the design of MIMO wireless communication systems. However, previous studies based on large dimensional RMT rely on the assumption that the transmit correlation ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	11,745
2403.09490	Hyper-CL: Conditioning Sentence Representations with Hypernetworks	While the introduction of contrastive learning frameworks in sentence representation learning has significantly contributed to advancements in the field, it still remains unclear whether state-of-the-art sentence embeddings can capture the fine-grained semantics of sentences, particularly when conditioned on specific p...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	437,785
2103.15619	SetVAE: Learning Hierarchical Composition for Generative Modeling of Set-Structured Data	Generative modeling of set-structured data, such as point clouds, requires reasoning over local and global structures at various scales. However, adopting multi-scale frameworks for ordinary sequential data to a set-structured data is nontrivial as it should be invariant to the permutation of its elements. In this pape...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	227,286
2204.00339	Self-triggered MPC robust to bounded packet loss via a min-max approach: extended version	Networked Control Systems typically come with a limited communication bandwidth and thus require special care when designing the underlying control and triggering law. A method that allows to consider hard constraints on the communication traffic as well as on states and inputs is self-triggered model predictive contro...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	289,226
2411.03532	A Behavior Architecture for Fast Humanoid Robot Door Traversals	Towards the role of humanoid robots as squad mates in urban operations and other domains, we identified doors as a major area lacking capability development. In this paper, we focus on the ability of humanoid robots to navigate and deal with doors. Human-sized doors are ubiquitous in many environment domains and the hu...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	505,934
1403.3758	Big Data Analytics - Retour vers le Futur 3; De Statisticien \`a Data Scientist	The rapid evolution of information systems managing more and more voluminous data has caused profound paradigm shifts in the job of statistician, becoming successively data miner, bioinformatician and now data scientist. Without the sake of completeness and after having illustrated these successive mutations, this arti...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	31,598
2502.06486	Biomechanical Reconstruction with Confidence Intervals from Multiview Markerless Motion Capture	Advances in multiview markerless motion capture (MMMC) promise high-quality movement analysis for clinical practice and research. While prior validation studies show MMMC performs well on average, they do not provide what is needed in clinical practice or for large-scale utilization of MMMC -- confidence intervals over...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	532,101
2204.00348	WavFT: Acoustic model finetuning with labelled and unlabelled data	Unsupervised and self-supervised learning methods have leveraged unlabelled data to improve the pretrained models. However, these methods need significantly large amount of unlabelled data and the computational cost of training models with such large amount of data can be prohibitively high. We address this issue by us...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	289,227
2408.15819	Automated Mixture Analysis via Structural Evaluation	The determination of chemical mixture components is vital to a multitude of scientific fields. Oftentimes spectroscopic methods are employed to decipher the composition of these mixtures. However, the sheer density of spectral features present in spectroscopic databases can make unambiguous assignment to individual spe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	484,090
1812.00887	Incorporating Deep Features in the Analysis of Tissue Microarray Images	Tissue microarray (TMA) images have been used increasingly often in cancer studies and the validation of biomarkers. TACOMA---a cutting-edge automatic scoring algorithm for TMA images---is comparable to pathologists in terms of accuracy and repeatability. Here we consider how this algorithm may be further improved. Ins...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	115,374
2402.12272	Analysis of Persian News Agencies on Instagram, A Words Co-occurrence Graph-based Approach	The rise of the Internet and the exponential increase in data have made manual data summarization and analysis a challenging task. Instagram social network is a prominent social network widely utilized in Iran for information sharing and communication across various age groups. The inherent structure of Instagram, char...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	430,783

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