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
2202.09710	A Barrier Certificate-based Simplex Architecture for Systems with Approximate and Hybrid Dynamics	We present Barrier-based Simplex (Bb-Simplex), a new, provably correct design for runtime assurance of continuous dynamical systems. Bb-Simplex is centered around the Simplex control architecture, which consists of a high-performance advanced controller that is not guaranteed to maintain safety of the plant, a verified...	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	281,288
2006.04471	A Comparison of Self-Play Algorithms Under a Generalized Framework	Throughout scientific history, overarching theoretical frameworks have allowed researchers to grow beyond personal intuitions and culturally biased theories. They allow to verify and replicate existing findings, and to link is connected results. The notion of self-play, albeit often cited in multiagent Reinforcement Le...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	180,702
1606.09376	The Design of Arbitrage-Free Data Pricing Schemes	Motivated by a growing market that involves buying and selling data over the web, we study pricing schemes that assign value to queries issued over a database. Previous work studied pricing mechanisms that compute the price of a query by extending a data seller's explicit prices on certain queries, or investigated the ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	57,987
1805.07777	DLBI: Deep learning guided Bayesian inference for structure reconstruction of super-resolution fluorescence microscopy	Super-resolution fluorescence microscopy, with a resolution beyond the diffraction limit of light, has become an indispensable tool to directly visualize biological structures in living cells at a nanometer-scale resolution. Despite advances in high-density super-resolution fluorescent techniques, existing methods stil...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	97,932
1306.3882	Chaining Test Cases for Reactive System Testing (extended version)	Testing of synchronous reactive systems is challenging because long input sequences are often needed to drive them into a state at which a desired feature can be tested. This is particularly problematic in on-target testing, where a system is tested in its real-life application environment and the time required for res...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	25,259
2412.09831	Ensemble Classification-Based Spectrum Sensing Using Support Vector Machine for CRN	As the demand for internet of things (IoT) and device-to-device (D2D) applications in next generation communication systems increases, we are confronted with a challenge of spectrum scarcity. One promising solution to this problem is cognitive radio network (CRN), where the key element is the spectrum - a valuable and ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	516,663
1211.5414	Analysis of a randomized approximation scheme for matrix multiplication	This note gives a simple analysis of a randomized approximation scheme for matrix multiplication proposed by Sarlos (2006) based on a random rotation followed by uniform column sampling. The result follows from a matrix version of Bernstein's inequality and a tail inequality for quadratic forms in subgaussian random ve...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	19,887
2202.02371	Boundary-aware Information Maximization for Self-supervised Medical Image Segmentation	Unsupervised pre-training has been proven as an effective approach to boost various downstream tasks given limited labeled data. Among various methods, contrastive learning learns a discriminative representation by constructing positive and negative pairs. However, it is not trivial to build reasonable pairs for a segm...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	278,775
2009.02732	Convergence Analysis of the Hessian Estimation Evolution Strategy	The class of algorithms called Hessian Estimation Evolution Strategies (HE-ESs) update the covariance matrix of their sampling distribution by directly estimating the curvature of the objective function. The approach is practically efficient, as attested by respectable performance on the BBOB testbed, even on rather ir...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	194,644
1911.12239	Leveraging Self-supervised Denoising for Image Segmentation	Deep learning (DL) has arguably emerged as the method of choice for the detection and segmentation of biological structures in microscopy images. However, DL typically needs copious amounts of annotated training data that is for biomedical projects typically not available and excessively expensive to generate. Addition...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	155,343
2410.20754	Likelihood approximations via Gaussian approximate inference	Non-Gaussian likelihoods are essential for modelling complex real-world observations but pose significant computational challenges in learning and inference. Even with Gaussian priors, non-Gaussian likelihoods often lead to analytically intractable posteriors, necessitating approximation methods. To this end, we propos...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	502,948
2305.04553	Larger Offspring Populations Help the $(1 + (\lambda, \lambda))$ Genetic Algorithm to Overcome the Noise	Evolutionary algorithms are known to be robust to noise in the evaluation of the fitness. In particular, larger offspring population sizes often lead to strong robustness. We analyze to what extent the $(1+(\lambda,\lambda))$ genetic algorithm is robust to noise. This algorithm also works with larger offspring populati...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	362,815
2402.05596	Improved upper bounds for wide-sense frameproof codes	Frameproof codes have been extensively studied for many years due to their application in copyright protection and their connection to extremal set theory. In this paper, we investigate upper bounds on the cardinality of wide-sense $t$-frameproof codes. For $t=2$, we apply results from Sperner theory to give a better u...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	427,924
2408.11490	DocTabQA: Answering Questions from Long Documents Using Tables	We study a new problem setting of question answering (QA), referred to as DocTabQA. Within this setting, given a long document, the goal is to respond to questions by organizing the answers into structured tables derived directly from the document's content. Unlike traditional QA approaches which predominantly rely on ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	482,316
1611.08069	3D Fully Convolutional Network for Vehicle Detection in Point Cloud	2D fully convolutional network has been recently successfully applied to object detection from images. In this paper, we extend the fully convolutional network based detection techniques to 3D and apply it to point cloud data. The proposed approach is verified on the task of vehicle detection from lidar point cloud for...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	64,442
1909.03482	New Graph-based Features For Shape Recognition	Shape recognition is the main challenging problem in computer vision. Different approaches and tools are used to solve this problem. Most existing approaches to object recognition are based on pixels. Pixel-based methods are dependent on the geometry and nature of the pixels, so the destruction of pixels reduces their ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	144,499
2412.09346	Quantitative Evaluation of Motif Sets in Time Series	Time Series Motif Discovery (TSMD), which aims at finding recurring patterns in time series, is an important task in numerous application domains, and many methods for this task exist. These methods are usually evaluated qualitatively. A few metrics for quantitative evaluation, where discovered motifs are compared to s...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	516,448
2307.01217	FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy	Recently, personalized federated learning (pFL) has attracted increasing attention in privacy protection, collaborative learning, and tackling statistical heterogeneity among clients, e.g., hospitals, mobile smartphones, etc. Most existing pFL methods focus on exploiting the global information and personalized informat...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	377,282
2406.17126	MM-SpuBench: Towards Better Understanding of Spurious Biases in Multimodal LLMs	Spurious bias, a tendency to use spurious correlations between non-essential input attributes and target variables for predictions, has revealed a severe robustness pitfall in deep learning models trained on single modality data. Multimodal Large Language Models (MLLMs), which integrate both vision and language models,...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	467,431
1911.04123	Leveraging Dependency Forest for Neural Medical Relation Extraction	Medical relation extraction discovers relations between entity mentions in text, such as research articles. For this task, dependency syntax has been recognized as a crucial source of features. Yet in the medical domain, 1-best parse trees suffer from relatively low accuracies, diminishing their usefulness. We investig...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	152,898
1905.11527	Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies	State-of-the-art efficient model-based Reinforcement Learning (RL) algorithms typically act by iteratively solving empirical models, i.e., by performing \emph{full-planning} on Markov Decision Processes (MDPs) built by the gathered experience. In this paper, we focus on model-based RL in the finite-state finite-horizon...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	132,446
2412.02129	GSOT3D: Towards Generic 3D Single Object Tracking in the Wild	In this paper, we present a novel benchmark, GSOT3D, that aims at facilitating development of generic 3D single object tracking (SOT) in the wild. Specifically, GSOT3D offers 620 sequences with 123K frames, and covers a wide selection of 54 object categories. Each sequence is offered with multiple modalities, including...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	513,395
1904.01178	Person Identification with Visual Summary for a Safe Access to a Smart Home	SafeAccess is an integrated system designed to provide easier and safer access to a smart home for people with or without disabilities. The system is designed to enhance safety and promote the independence of people with disability (i.e., visually impaired). The key functionality of the system includes the detection an...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	126,075
1906.04659	Stable Rank Normalization for Improved Generalization in Neural Networks and GANs	Exciting new work on the generalization bounds for neural networks (NN) given by Neyshabur et al. , Bartlett et al. closely depend on two parameter-depenedent quantities: the Lipschitz constant upper-bound and the stable rank (a softer version of the rank operator). This leads to an interesting question of whether cont...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	134,789
2304.01436	Learning Personalized High Quality Volumetric Head Avatars from Monocular RGB Videos	We propose a method to learn a high-quality implicit 3D head avatar from a monocular RGB video captured in the wild. The learnt avatar is driven by a parametric face model to achieve user-controlled facial expressions and head poses. Our hybrid pipeline combines the geometry prior and dynamic tracking of a 3DMM with a ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	356,072
2307.00852	VOLTA: Improving Generative Diversity by Variational Mutual Information Maximizing Autoencoder	The natural language generation domain has witnessed great success thanks to Transformer models. Although they have achieved state-of-the-art generative quality, they often neglect generative diversity. Prior attempts to tackle this issue suffer from either low model capacity or over-complicated architectures. Some rec...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	377,150
2311.01559	The effect of disruptive events on spatial and social interactions: An assessment of structural changes in pre-and post-COVID-19 pandemic networks	Disruptive events significantly alter spatial and social interactions among people and places. To examine the structural changes in spatial and social interaction networks in pre- and post-periods of the COVID-19 pandemic, we employ the Louvain method to algorithmically detect regions (communities) within the county-to...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	405,086
1109.2993	A Delay-Constrained General Achievable Rate and Certain Capacity Results for UWB Relay Channel	In this paper, we derive UWB version of (i) general best achievable rate for the relay channel with decode-andforward strategy and (ii) max-flow min-cut upper bound, such that the UWB relay channel can be studied considering the obtained lower and upper bounds. Then, we show that by appropriately choosing the noise cor...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	12,155
2203.13387	CrossFormer: Cross Spatio-Temporal Transformer for 3D Human Pose Estimation	3D human pose estimation can be handled by encoding the geometric dependencies between the body parts and enforcing the kinematic constraints. Recently, Transformer has been adopted to encode the long-range dependencies between the joints in the spatial and temporal domains. While they had shown excellence in long-rang...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	287,604
2211.05697	Bayesian hierarchical modelling for battery lifetime early prediction	Accurate prediction of battery health is essential for real-world system management and lab-based experiment design. However, building a life-prediction model from different cycling conditions is still a challenge. Large lifetime variability results from both cycling conditions and initial manufacturing variability, an...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	329,649
2003.07848	Learning to Structure an Image with Few Colors	Color and structure are the two pillars that construct an image. Usually, the structure is well expressed through a rich spectrum of colors, allowing objects in an image to be recognized by neural networks. However, under extreme limitations of color space, the structure tends to vanish, and thus a neural network might...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	168,560
2110.15814	A GIS Data Realistic Road Generation Approach for Traffic Simulation	Road networks exist in the form of polylines with attributes within the GIS databases. Such a representation renders the geographic data impracticable for 3D road traffic simulation. In this work, we propose a method to transform raw GIS data into a realistic, operational model for real-time road traffic simulation. Fo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	264,016
1408.4908	Theoretical Foundations of Equitability and the Maximal Information Coefficient	The maximal information coefficient (MIC) is a tool for finding the strongest pairwise relationships in a data set with many variables (Reshef et al., 2011). MIC is useful because it gives similar scores to equally noisy relationships of different types. This property, called {\em equitability}, is important for analyz...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	35,500
2411.07161	RoundTable: Investigating Group Decision-Making Mechanism in Multi-Agent Collaboration	This study investigates the efficacy of Multi-Agent Systems in eliciting cross-agent communication and enhancing collective intelligence through group decision-making in a decentralized setting. Unlike centralized mechanisms, where a fixed hierarchy governs social choice, decentralized group decision-making allows agen...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	507,418
2203.00641	Multi-Task Multi-Scale Learning For Outcome Prediction in 3D PET Images	Background and Objectives: Predicting patient response to treatment and survival in oncology is a prominent way towards precision medicine. To that end, radiomics was proposed as a field of study where images are used instead of invasive methods. The first step in radiomic analysis is the segmentation of the lesion. Ho...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	283,073
2208.13389	Several classes of Galois self-orthogonal MDS codes and related applications	Let $q=p^h$ be a prime power and $e$ be an integer with $0\leq e\leq h-1$. $e$-Galois self-orthogonal codes are generalizations of Euclidean self-orthogonal codes ($e=0$) and Hermitian self-orthogonal codes ($e=\frac{h}{2}$ and $h$ is even). In this paper, we propose two general methods to construct $e$-Galois self-ort...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	315,044
2405.18692	Movable Antenna Empowered Downlink NOMA Systems: Power Allocation and Antenna Position Optimization	This paper investigates a novel communication paradigm employing movable antennas (MAs) within a multiple-input single-output (MISO) non-orthogonal multiple access (NOMA) downlink framework, where users are equipped with MAs. Initially, leveraging the far-field response, we delineate the channel characteristics concern...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	458,538
2106.12413	Transformer Meets Convolution: A Bilateral Awareness Network for Semantic Segmentation of Very Fine Resolution Urban Scene Images	Semantic segmentation from very fine resolution (VFR) urban scene images plays a significant role in several application scenarios including autonomous driving, land cover classification, and urban planning, etc. However, the tremendous details contained in the VFR image, especially the considerable variations in scale...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	242,720
1911.08160	Deep interval prediction model with gradient descend optimization method for short-term wind power prediction	The application of wind power interval prediction for power systems attempts to give more comprehensive support to dispatchers and operators of the grid. Lower upper bound estimation (LUBE) method is widely applied in interval prediction. However, the existing LUBE approaches are trained by meta-heuristic optimization,...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	154,115
1610.09516	Finding Street Gang Members on Twitter	Most street gang members use Twitter to intimidate others, to present outrageous images and statements to the world, and to share recent illegal activities. Their tweets may thus be useful to law enforcement agencies to discover clues about recent crimes or to anticipate ones that may occur. Finding these posts, howeve...	false	false	false	true	false	true	false	false	true	false	false	false	false	true	false	false	false	false	63,073
2402.03510	Autopilot System for Depth and Pitch Control in Underwater Vehicles: Navigating Near-Surface Waves and Disturbances	This paper introduces a framework for depth and pitch control of underwater vehicles in near-surface wave conditions. By effectively managing tail, sail plane angles and hover tank operations utilizing a Linear Quadratic Regulator controller and L1 Adaptive Autopilot augmentation, the system ensures balanced control in...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	427,047
1107.2693	A Fuzzy View on k-Means Based Signal Quantization with Application in Iris Segmentation	This paper shows that the k-means quantization of a signal can be interpreted both as a crisp indicator function and as a fuzzy membership assignment describing fuzzy clusters and fuzzy boundaries. Combined crisp and fuzzy indicator functions are defined here as natural generalizations of the ordinary crisp and fuzzy i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	11,282
2002.01337	Cooperative Learning via Federated Distillation over Fading Channels	Cooperative training methods for distributed machine learning are typically based on the exchange of local gradients or local model parameters. The latter approach is known as Federated Learning (FL). An alternative solution with reduced communication overhead, referred to as Federated Distillation (FD), was recently p...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	162,632
2005.11347	SentPWNet: A Unified Sentence Pair Weighting Network for Task-specific Sentence Embedding	Pair-based metric learning has been widely adopted to learn sentence embedding in many NLP tasks such as semantic text similarity due to its efficiency in computation. Most existing works employed a sequence encoder model and utilized limited sentence pairs with a pair-based loss to learn discriminating sentence repres...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	178,445
2102.06700	On the Paradox of Certified Training	Certified defenses based on convex relaxations are an established technique for training provably robust models. The key component is the choice of relaxation, varying from simple intervals to tight polyhedra. Counterintuitively, loose interval-based training often leads to higher certified robustness than what can be ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	219,842
2109.02153	Spatial Domain Feature Extraction Methods for Unconstrained Handwritten Malayalam Character Recognition	Handwritten character recognition is an active research challenge,especially for Indian scripts. This paper deals with handwritten Malayalam, with a complete set of basic characters, vowel and consonant signs and compound characters that may be present in the script. Spatial domain features suitable for recognition are...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	253,651
1302.0689	Multi-scale Visual Attention & Saliency Modelling with Decision Theory	Bottom-up saliency, an early human visual processing, behaves like binary classification of interest and null hypothesis. Its discriminant power, mutual information of image features and class distribution, is closely related to saliency value by the well-known centre-surround theory. As classification accuracy very mu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	21,747
2501.01644	Multimodal Contrastive Representation Learning in Augmented Biomedical Knowledge Graphs	Biomedical Knowledge Graphs (BKGs) integrate diverse datasets to elucidate complex relationships within the biomedical field. Effective link prediction on these graphs can uncover valuable connections, such as potential novel drug-disease relations. We introduce a novel multimodal approach that unifies embeddings from ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	522,150
1904.11128	CBHE: Corner-based Building Height Estimation for Complex Street Scene Images	Building height estimation is important in many applications such as 3D city reconstruction, urban planning, and navigation. Recently, a new building height estimation method using street scene images and 2D maps was proposed. This method is more scalable than traditional methods that use high-resolution optical data, ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	128,789
2404.12104	Ethical-Lens: Curbing Malicious Usages of Open-Source Text-to-Image Models	The burgeoning landscape of text-to-image models, exemplified by innovations such as Midjourney and DALLE 3, has revolutionized content creation across diverse sectors. However, these advancements bring forth critical ethical concerns, particularly with the misuse of open-source models to generate content that violates...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	447,740
1711.08330	Adaptive Cardinality Estimation	In this paper we address cardinality estimation problem which is an important subproblem in query optimization. Query optimization is a part of every relational DBMS responsible for finding the best way of the execution for the given query. These ways are called plans. The execution time of different plans may differ b...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	85,184
2305.16296	A Guide Through the Zoo of Biased SGD	Stochastic Gradient Descent (SGD) is arguably the most important single algorithm in modern machine learning. Although SGD with unbiased gradient estimators has been studied extensively over at least half a century, SGD variants relying on biased estimators are rare. Nevertheless, there has been an increased interest i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	368,000
2311.06631	A 3D Conditional Diffusion Model for Image Quality Transfer -- An Application to Low-Field MRI	Low-field (LF) MRI scanners (<1T) are still prevalent in settings with limited resources or unreliable power supply. However, they often yield images with lower spatial resolution and contrast than high-field (HF) scanners. This quality disparity can result in inaccurate clinician interpretations. Image Quality Transfe...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	407,011
2209.15418	Equitable Marketplace Mechanism Design	We consider a trading marketplace that is populated by traders with diverse trading strategies and objectives. The marketplace allows the suppliers to list their goods and facilitates matching between buyers and sellers. In return, such a marketplace typically charges fees for facilitating trade. The goal of this work ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	true	320,602
1305.0015	Inferring ground truth from multi-annotator ordinal data: a probabilistic approach	A popular approach for large scale data annotation tasks is crowdsourcing, wherein each data point is labeled by multiple noisy annotators. We consider the problem of inferring ground truth from noisy ordinal labels obtained from multiple annotators of varying and unknown expertise levels. Annotation models for ordinal...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	24,318
2011.10904	Evolving Search Space for Neural Architecture Search	The automation of neural architecture design has been a coveted alternative to human experts. Recent works have small search space, which is easier to optimize but has a limited upper bound of the optimal solution. Extra human design is needed for those methods to propose a more suitable space with respect to the speci...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	207,663
2101.02824	Neighbor2Neighbor: Self-Supervised Denoising from Single Noisy Images	In the last few years, image denoising has benefited a lot from the fast development of neural networks. However, the requirement of large amounts of noisy-clean image pairs for supervision limits the wide use of these models. Although there have been a few attempts in training an image denoising model with only single...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	214,740
1910.12527	RPM-Oriented Query Rewriting Framework for E-commerce Keyword-Based Sponsored Search	Sponsored search optimizes revenue and relevance, which is estimated by Revenue Per Mille (RPM). Existing sponsored search models are all based on traditional statistical models, which have poor RPM performance when queries follow a heavy-tailed distribution. Here, we propose an RPM-oriented Query Rewriting Framework (...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	151,117
2010.03561	Ensembling geophysical models with Bayesian Neural Networks	Ensembles of geophysical models improve projection accuracy and express uncertainties. We develop a novel data-driven ensembling strategy for combining geophysical models using Bayesian Neural Networks, which infers spatiotemporally varying model weights and bias while accounting for heteroscedastic uncertainties in th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	199,439
2310.08581	Universal Visual Decomposer: Long-Horizon Manipulation Made Easy	Real-world robotic tasks stretch over extended horizons and encompass multiple stages. Learning long-horizon manipulation tasks, however, is a long-standing challenge, and demands decomposing the overarching task into several manageable subtasks to facilitate policy learning and generalization to unseen tasks. Prior ta...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	399,444
2402.10689	Cultural Commonsense Knowledge for Intercultural Dialogues	Despite recent progress, large language models (LLMs) still face the challenge of appropriately reacting to the intricacies of social and cultural conventions. This paper presents MANGO, a methodology for distilling high-accuracy, high-recall assertions of cultural knowledge. We judiciously and iteratively prompt LLMs ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	430,071
2108.12976	Approximating Pandora's Box with Correlations	We revisit the classic Pandora's Box (PB) problem under correlated distributions on the box values. Recent work of arXiv:1911.01632 obtained constant approximate algorithms for a restricted class of policies for the problem that visit boxes in a fixed order. In this work, we study the complexity of approximating the op...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	252,669
2405.17103	Empowering Character-level Text Infilling by Eliminating Sub-Tokens	In infilling tasks, sub-tokens, representing instances where a complete token is segmented into two parts, often emerge at the boundaries of prefixes, middles, and suffixes. Traditional methods focused on training models at the token level, leading to sub-optimal performance in character-level infilling tasks during th...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	457,767
1811.06692	Subtask Gated Networks for Non-Intrusive Load Monitoring	Non-intrusive load monitoring (NILM), also known as energy disaggregation, is a blind source separation problem where a household's aggregate electricity consumption is broken down into electricity usages of individual appliances. In this way, the cost and trouble of installing many measurement devices over numerous ho...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	113,585
2006.06377	STL-SGD: Speeding Up Local SGD with Stagewise Communication Period	Distributed parallel stochastic gradient descent algorithms are workhorses for large scale machine learning tasks. Among them, local stochastic gradient descent (Local SGD) has attracted significant attention due to its low communication complexity. Previous studies prove that the communication complexity of Local SGD ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	181,410
2410.20233	Characterization of $n$-Dimensional Toric and Burst-Error-Correcting Quantum Codes from Lattice Codes	Quantum error correction is essential for the development of any scalable quantum computer. In this work we introduce a generalization of a quantum interleaving method for combating clusters of errors in toric quantum error-correcting codes. We present new $n$-dimensional toric quantum codes, where $n\geq 5$, which are...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	502,713
2107.13602	Domain-matched Pre-training Tasks for Dense Retrieval	Pre-training on larger datasets with ever increasing model size is now a proven recipe for increased performance across almost all NLP tasks. A notable exception is information retrieval, where additional pre-training has so far failed to produce convincing results. We show that, with the right pre-training setup, this...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	248,240
2209.05556	Fragile object transportation by a multi-robot system in an unknown environment using a semi-decentralized control approach	In this paper, we introduce a semi-decentralized control technique for a swarm of robots transporting a fragile object to a destination in an uncertain occluded environment.The proposed approach has been split into two parts. The initial part (Phase 1) includes a centralized control strategy for creating a specific for...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	317,123
2411.12006	A Robust Solver for Phasor-Domain Short-Circuit Analysis with Inverter-Based Resources	The integration of Inverter-Based Resource (IBR) model into phasor-domain short circuit (SC) solvers challenges their numerical stability. To address the challenge, this paper proposes a solver that improves numerical stability by employing the Newton-Raphson iterative method. The solver can integrate the latest implem...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	509,258
2312.11779	Tokenization Matters: Navigating Data-Scarce Tokenization for Gender Inclusive Language Technologies	Gender-inclusive NLP research has documented the harmful limitations of gender binary-centric large language models (LLM), such as the inability to correctly use gender-diverse English neopronouns (e.g., xe, zir, fae). While data scarcity is a known culprit, the precise mechanisms through which scarcity affects this be...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	416,708
2407.01613	Self-adaptive weights based on balanced residual decay rate for physics-informed neural networks and deep operator networks	Physics-informed deep learning has emerged as a promising alternative for solving partial differential equations. However, for complex problems, training these networks can still be challenging, often resulting in unsatisfactory accuracy and efficiency. In this work, we demonstrate that the failure of plain physics-inf...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	469,385
2210.16662	Global Optimization of Energy Efficiency in IRS-Aided Communication Systems via Robust IRS-Element Activation	In this paper, we study an intelligent reflecting surface (IRS) assisted communication system with single-antenna transmitter and receiver, under imperfect channel state information (CSI). More specifically, we deal with the robust selection of binary (on/off) states of the IRS elements in order to maximize the worst-c...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	327,414
2201.13224	Evaluating a Methodology for Increasing AI Transparency: A Case Study	In reaction to growing concerns about the potential harms of artificial intelligence (AI), societies have begun to demand more transparency about how AI models and systems are created and used. To address these concerns, several efforts have proposed documentation templates containing questions to be answered by model ...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	277,916
1811.09054	Enhanced Expressive Power and Fast Training of Neural Networks by Random Projections	Random projections are able to perform dimension reduction efficiently for datasets with nonlinear low-dimensional structures. One well-known example is that random matrices embed sparse vectors into a low-dimensional subspace nearly isometrically, known as the restricted isometric property in compressed sensing. In th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	114,183
2410.15987	Analyzing Closed-loop Training Techniques for Realistic Traffic Agent Models in Autonomous Highway Driving Simulations	Simulation plays a crucial role in the rapid development and safe deployment of autonomous vehicles. Realistic traffic agent models are indispensable for bridging the gap between simulation and the real world. Many existing approaches for imitating human behavior are based on learning from demonstration. However, these...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	true	false	false	false	500,828
2201.03556	Reproducing BowNet: Learning Representations by Predicting Bags of Visual Words	This work aims to reproduce results from the CVPR 2020 paper by Gidaris et al. Self-supervised learning (SSL) is used to learn feature representations of an image using an unlabeled dataset. This work proposes to use bag-of-words (BoW) deep feature descriptors as a self-supervised learning target to learn robust, deep ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	274,882
2011.12850	Relation3DMOT: Exploiting Deep Affinity for 3D Multi-Object Tracking from View Aggregation	Autonomous systems need to localize and track surrounding objects in 3D space for safe motion planning. As a result, 3D multi-object tracking (MOT) plays a vital role in autonomous navigation. Most MOT methods use a tracking-by-detection pipeline, which includes object detection and data association processing. However...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	208,293
2003.00355	Survival Cluster Analysis	Conventional survival analysis approaches estimate risk scores or individualized time-to-event distributions conditioned on covariates. In practice, there is often great population-level phenotypic heterogeneity, resulting from (unknown) subpopulations with diverse risk profiles or survival distributions. As a result, ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	166,268
2004.07411	Leaderless Consensus of a Hierarchical Cyber-Physical System	This paper models a class of hierarchical cyber-physical systems and studies its associated consensus problem. The model has a pyramid structure, which reflects many realistic natural or human systems. By analyzing the spectrum of the coupling matrix, it is shown that all nodes in the physical layer can reach a consens...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	172,775
1808.01688	Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models	The prediction accuracy has been the long-lasting and sole standard for comparing the performance of different image classification models, including the ImageNet competition. However, recent studies have highlighted the lack of robustness in well-trained deep neural networks to adversarial examples. Visually impercept...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	104,627
1912.06282	Joint AGC and Receiver Design for Large-Scale MU-MIMO Systems with Coarsely Quantized Signals and C-RANs	In this work, we propose the joint optimization of the automatic gain control (AGC), which works in the remote radio heads (RHHs), and a low-resolution aware (LRA) linear receive filter based on the minimum mean square error (MMSE), which works on the baseband unit (BBU) pool, for large-scale multi-user multiple-input ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	157,310
2410.11385	Do LLMs Have the Generalization Ability in Conducting Causal Inference?	In causal inference, generalization capability refers to the ability to conduct causal inference methods on new data to estimate the causal-effect between unknown phenomenon, which is crucial for expanding the boundaries of knowledge. Studies have evaluated the causal inference capabilities of Large Language Models (LL...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	498,535
2306.09385	Employing Multimodal Machine Learning for Stress Detection	In the current age, human lifestyle has become more knowledge oriented leading to generation of sedentary employment. This has given rise to a number of health and mental disorders. Mental wellness is one of the most neglected but crucial aspects of today's world. Mental health issues can, both directly and indirectly,...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	373,814
cs/0506062	A CDMA multiuser detection algorithm based on survey propagation	A computationally tractable CDMA multiuser detection algorithm is developed based on survey propagation.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	538,785
2308.08210	Neural Spherical Harmonics for structurally coherent continuous representation of diffusion MRI signal	We present a novel way to model diffusion magnetic resonance imaging (dMRI) datasets, that benefits from the structural coherence of the human brain while only using data from a single subject. Current methods model the dMRI signal in individual voxels, disregarding the intervoxel coherence that is present. We use a ne...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	385,815
2102.03176	Feature Representation in Deep Metric Embeddings	In deep metric learning (DML), high-level input data are represented in a lower-level representation (embedding) space, such that samples from the same class are mapped close together, while samples from disparate classes are mapped further apart. In this lower-level representation, only a single inference sample from ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	218,653
2303.09988	Star-Net: Improving Single Image Desnowing Model With More Efficient Connection and Diverse Feature Interaction	Compared to other severe weather image restoration tasks, single image desnowing is a more challenging task. This is mainly due to the diversity and irregularity of snow shape, which makes it extremely difficult to restore images in snowy scenes. Moreover, snow particles also have a veiling effect similar to haze or mi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	352,265
2007.04933	A Reference Software Architecture for Social Robots	Social Robotics poses tough challenges to software designers who are required to take care of difficult architectural drivers like acceptability, trust of robots as well as to guarantee that robots establish a personalised interaction with their users. Moreover, in this context recurrent software design issues such as ...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	186,516
1806.02405	Polar Code Moderate Deviation: Recovering the Scaling Exponent	In 2008 Arikan proposed polar coding [arXiv:0807.3917] which we summarize as follows: (a) From the root channel $W$ synthesize recursively a series of channels $W_N^{(1)},\dotsc,W_N^{(N)}$. (b) Select sophisticatedly a subset $A$ of synthetic channels. (c) Transmit information using synthetic channels indexed by $A$ an...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	99,772
2102.01405	Child-Computer Interaction with Mobile Devices: Recent Works, New Dataset, and Age Detection	This article provides an overview of recent research in Child-Computer Interaction with mobile devices and describe our framework ChildCI intended for: i) overcoming the lack of large-scale publicly available databases in the area, ii) generating a better understanding of the cognitive and neuromotor development of chi...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	218,102
2011.11139	MAC for Machine Type Communications in Industrial IoT -- Part II: Scheduling and Numerical Results	In the second part of this paper, we develop a centralized packet transmission scheduling scheme to pair with the protocol designed in Part I and complete our medium access control (MAC) design for machine-type communications in the industrial internet of things. For the networking scenario, fine-grained scheduling tha...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	207,733
2308.09359	Training-Free Energy Beamforming Assisted by Wireless Sensing	This paper studies the transmit energy beamforming in a multi-antenna wireless power transfer (WPT) system, in which an access point (AP) equipped with a uniform linear array (ULA) sends radio signals to wirelessly charge multiple single-antenna energy receivers (ERs). Different from conventional energy beamforming des...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	386,259
2409.04945	Fast Deep Predictive Coding Networks for Videos Feature Extraction without Labels	Brain-inspired deep predictive coding networks (DPCNs) effectively model and capture video features through a bi-directional information flow, even without labels. They are based on an overcomplete description of video scenes, and one of the bottlenecks has been the lack of effective sparsification techniques to find d...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	486,571
2205.10089	Kernel Normalized Convolutional Networks	Existing convolutional neural network architectures frequently rely upon batch normalization (BatchNorm) to effectively train the model. BatchNorm, however, performs poorly with small batch sizes, and is inapplicable to differential privacy. To address these limitations, we propose the kernel normalization (KernelNorm)...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	297,555
2412.03837	Movie Gen: SWOT Analysis of Meta's Generative AI Foundation Model for Transforming Media Generation, Advertising, and Entertainment Industries	Generative AI is reshaping the media landscape, enabling unprecedented capabilities in video creation, personalization, and scalability. This paper presents a comprehensive SWOT analysis of Metas Movie Gen, a cutting-edge generative AI foundation model designed to produce 1080p HD videos with synchronized audio from si...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	514,126
2104.02652	Malignancy Prediction and Lesion Identification from Clinical Dermatological Images	We consider machine-learning-based malignancy prediction and lesion identification from clinical dermatological images, which can be indistinctly acquired via smartphone or dermoscopy capture. Additionally, we do not assume that images contain single lesions, thus the framework supports both focal or wide-field images....	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	228,803
1701.01547	Stochastic Optimal Control for Modeling Reaching Movements in the Presence of Obstacles: Theory and Simulation	In many human-in-the-loop robotic applications such as robot-assisted surgery and remote teleoperation, predicting the intended motion of the human operator may be useful for successful implementation of shared control, guidance virtual fixtures, and predictive control. Developing computational models of human movement...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	66,421
2002.01523	A Deep Conditioning Treatment of Neural Networks	We study the role of depth in training randomly initialized overparameterized neural networks. We give a general result showing that depth improves trainability of neural networks by improving the conditioning of certain kernel matrices of the input data. This result holds for arbitrary non-linear activation functions ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	162,666
1906.00671	Unsupervised Neural Generative Semantic Hashing	Fast similarity search is a key component in large-scale information retrieval, where semantic hashing has become a popular strategy for representing documents as binary hash codes. Recent advances in this area have been obtained through neural network based models: generative models trained by learning to reconstruct ...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	133,479
2405.20773	Visual-RolePlay: Universal Jailbreak Attack on MultiModal Large Language Models via Role-playing Image Character	With the advent and widespread deployment of Multimodal Large Language Models (MLLMs), ensuring their safety has become increasingly critical. To achieve this objective, it requires us to proactively discover the vulnerability of MLLMs by exploring the attack methods. Thus, structure-based jailbreak attacks, where harm...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	459,513

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