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
1603.00275	Gland Segmentation in Colon Histology Images: The GlaS Challenge Contest	Colorectal adenocarcinoma originating in intestinal glandular structures is the most common form of colon cancer. In clinical practice, the morphology of intestinal glands, including architectural appearance and glandular formation, is used by pathologists to inform prognosis and plan the treatment of individual patien...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	52,761
2411.00842	Video prediction using score-based conditional density estimation	Temporal prediction is inherently uncertain, but representing the ambiguity in natural image sequences is a challenging high-dimensional probabilistic inference problem. For natural scenes, the curse of dimensionality renders explicit density estimation statistically and computationally intractable. Here, we describe a...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	504,781
2208.08856	Study of General Robust Subband Adaptive Filtering	In this paper, we propose a general robust subband adaptive filtering (GR-SAF) scheme against impulsive noise by minimizing the mean square deviation under the random-walk model with individual weight uncertainty. Specifically, by choosing different scaling factors such as from the M-estimate and maximum correntropy ro...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	313,504
2207.09918	Large Scale Radio Frequency Signal Classification	Existing datasets used to train deep learning models for narrowband radio frequency (RF) signal classification lack enough diversity in signal types and channel impairments to sufficiently assess model performance in the real world. We introduce the Sig53 dataset consisting of 5 million synthetically-generated samples ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	309,071
2412.13507	Novel AI Camera Camouflage: Face Cloaking Without Full Disguise	This study demonstrates a novel approach to facial camouflage that combines targeted cosmetic perturbations and alpha transparency layer manipulation to evade modern facial recognition systems. Unlike previous methods -- such as CV dazzle, adversarial patches, and theatrical disguises -- this work achieves effective ob...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	518,316
2309.13466	Rethinking Social Robot Navigation: Leveraging the Best of Two Worlds	Empowering robots to navigate in a socially compliant manner is essential for the acceptance of robots moving in human-inhabited environments. Previously, roboticists have developed geometric navigation systems with decades of empirical validation to achieve safety and efficiency. However, the many complex factors of s...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	394,219
1803.07192	Diagnostic Classification Of Lung Nodules Using 3D Neural Networks	Lung cancer is the leading cause of cancer-related death worldwide. Early diagnosis of pulmonary nodules in Computed Tomography (CT) chest scans provides an opportunity for designing effective treatment and making financial and care plans. In this paper, we consider the problem of diagnostic classification between beni...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	92,982
2008.04221	Deep learning for photoacoustic imaging: a survey	Machine learning has been developed dramatically and witnessed a lot of applications in various fields over the past few years. This boom originated in 2009, when a new model emerged, that is, the deep artificial neural network, which began to surpass other established mature models on some important benchmarks. Later,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	191,173
2111.13309	Data Augmented 3D Semantic Scene Completion with 2D Segmentation Priors	Semantic scene completion (SSC) is a challenging Computer Vision task with many practical applications, from robotics to assistive computing. Its goal is to infer the 3D geometry in a field of view of a scene and the semantic labels of voxels, including occluded regions. In this work, we present SPAwN, a novel lightwei...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	268,257
2004.03867	S2A: Wasserstein GAN with Spatio-Spectral Laplacian Attention for Multi-Spectral Band Synthesis	Intersection of adversarial learning and satellite image processing is an emerging field in remote sensing. In this study, we intend to address synthesis of high resolution multi-spectral satellite imagery using adversarial learning. Guided by the discovery of attention mechanism, we regulate the process of band synthe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	171,713
2407.09159	Weakly-supervised Autism Severity Assessment in Long Videos	Autism Spectrum Disorder (ASD) is a diverse collection of neurobiological conditions marked by challenges in social communication and reciprocal interactions, as well as repetitive and stereotypical behaviors. Atypical behavior patterns in a long, untrimmed video can serve as biomarkers for children with ASD. In this p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	472,474
2404.06728	A Data Efficient Framework for Learning Local Heuristics	With the advent of machine learning, there have been several recent attempts to learn effective and generalizable heuristics. Local Heuristic A* (LoHA*) is one recent method that instead of learning the entire heuristic estimate, learns a "local" residual heuristic that estimates the cost to escape a region (Veerapanen...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	445,575
1806.00188	Near-Optimal Budgeted Data Exchange for Distributed Loop Closure Detection	Inter-robot loop closure detection is a core problem in collaborative SLAM (CSLAM). Establishing inter-robot loop closures is a resource-demanding process, during which robots must consume a substantial amount of mission-critical resources (e.g., battery and bandwidth) to exchange sensory data. However, even with the m...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	99,260
1703.01506	Accelerating Permutation Testing in Voxel-wise Analysis through Subspace Tracking: A new plugin for SnPM	Permutation testing is a non-parametric method for obtaining the max null distribution used to compute corrected $p$-values that provide strong control of false positives. In neuroimaging, however, the computational burden of running such an algorithm can be significant. We find that by viewing the permutation testing ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	69,379
1804.09000	Style Transfer Through Back-Translation	Style transfer is the task of rephrasing the text to contain specific stylistic properties without changing the intent or affect within the context. This paper introduces a new method for automatic style transfer. We first learn a latent representation of the input sentence which is grounded in a language translation m...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	95,885
2407.12616	Missing Modality Prediction for Unpaired Multimodal Learning via Joint Embedding of Unimodal Models	Multimodal learning typically relies on the assumption that all modalities are fully available during both the training and inference phases. However, in real-world scenarios, consistently acquiring complete multimodal data presents significant challenges due to various factors. This often leads to the issue of missing...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	474,003
2111.03788	d3rlpy: An Offline Deep Reinforcement Learning Library	In this paper, we introduce d3rlpy, an open-sourced offline deep reinforcement learning (RL) library for Python. d3rlpy supports a set of offline deep RL algorithms as well as off-policy online algorithms via a fully documented plug-and-play API. To address a reproducibility issue, we conduct a large-scale benchmark wi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	265,273
2111.07552	Dynamic Placement of Rapidly Deployable Mobile Sensor Robots Using Machine Learning and Expected Value of Information	Although the Industrial Internet of Things has increased the number of sensors permanently installed in industrial plants, there will be gaps in coverage due to broken sensors or sparse density in very large plants, such as in the petrochemical industry. Modern emergency response operations are beginning to use Small U...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	266,413
1607.06235	Haze Visibility Enhancement: A Survey and Quantitative Benchmarking	This paper provides a comprehensive survey of methods dealing with visibility enhancement of images taken in hazy or foggy scenes. The survey begins with discussing the optical models of atmospheric scattering media and image formation. This is followed by a survey of existing methods, which are grouped to multiple ima...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	58,864
2311.05599	SynH2R: Synthesizing Hand-Object Motions for Learning Human-to-Robot Handovers	Vision-based human-to-robot handover is an important and challenging task in human-robot interaction. Recent work has attempted to train robot policies by interacting with dynamic virtual humans in simulated environments, where the policies can later be transferred to the real world. However, a major bottleneck is the ...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	406,634
2104.08510	Exploring Deep Learning for Joint Audio-Visual Lip Biometrics	Audio-visual (AV) lip biometrics is a promising authentication technique that leverages the benefits of both the audio and visual modalities in speech communication. Previous works have demonstrated the usefulness of AV lip biometrics. However, the lack of a sizeable AV database hinders the exploration of deep-learning...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	230,829
2411.02139	Theoretical characterisation of the Gauss-Newton conditioning in Neural Networks	The Gauss-Newton (GN) matrix plays an important role in machine learning, most evident in its use as a preconditioning matrix for a wide family of popular adaptive methods to speed up optimization. Besides, it can also provide key insights into the optimization landscape of neural networks. In the context of deep neura...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	505,373
2007.02246	Blind Inverse Gamma Correction with Maximized Differential Entropy	Unwanted nonlinear gamma distortion frequently occurs in a great diversity of images during the procedures of image acquisition, processing, and/or display. And the gamma distortion often varies with capture setup change and luminance variation. Blind inverse gamma correction, which automatically determines a proper re...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	185,683
2309.10305	Baichuan 2: Open Large-scale Language Models	Large language models (LLMs) have demonstrated remarkable performance on a variety of natural language tasks based on just a few examples of natural language instructions, reducing the need for extensive feature engineering. However, most powerful LLMs are closed-source or limited in their capability for languages othe...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	392,954
2105.07019	Chord Recognition- Music and Audio Information Retrieval	Music Information Retrieval (MIR) is a collaborative scientific study that help to build innovative information research themes, novel frameworks, and developing connected delivery mechanisms in addition to making the world's massive collection of music open for everyone. Modern rock music proved to be difficult to est...	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	235,290
2412.10089	Guidance Not Obstruction: A Conjugate Consistent Enhanced Strategy for Domain Generalization	Domain generalization addresses domain shift in real-world applications. Most approaches adopt a domain angle, seeking invariant representation across domains by aligning their marginal distributions, irrespective of individual classes, naturally leading to insufficient exploration of discriminative information. Switch...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	516,778
1904.08039	A Multi-Task Learning Framework for Overcoming the Catastrophic Forgetting in Automatic Speech Recognition	Recently, data-driven based Automatic Speech Recognition (ASR) systems have achieved state-of-the-art results. And transfer learning is often used when those existing systems are adapted to the target domain, e.g., fine-tuning, retraining. However, in the processes, the system parameters may well deviate too much from ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	127,951
1705.07576	Global Guarantees for Enforcing Deep Generative Priors by Empirical Risk	We examine the theoretical properties of enforcing priors provided by generative deep neural networks via empirical risk minimization. In particular we consider two models, one in which the task is to invert a generative neural network given access to its last layer and another in which the task is to invert a generati...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	73,865
2007.00550	Kalman Filter Meets Subjective Logic: A Self-Assessing Kalman Filter Using Subjective Logic	Self-assessment is a key to safety and robustness in automated driving. In order to design safer and more robust automated driving functions, the goal is to self-assess the performance of each module in a whole automated driving system. One crucial component in automated driving systems is the tracking of surrounding o...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	185,149
2006.03706	Learning from Non-Random Data in Hilbert Spaces: An Optimal Recovery Perspective	The notion of generalization in classical Statistical Learning is often attached to the postulate that data points are independent and identically distributed (IID) random variables. While relevant in many applications, this postulate may not hold in general, encouraging the development of learning frameworks that are ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	180,405
2311.15912	LIFT OFF: LoRaWAN Installation and Fiducial Tracking Operations for the Flightline of the Future	Real-time situational awareness for the location of assets is critical to ensure missions are completed efficiently and requirements are satisfied. In many commercial settings, the application of global positioning system (GPS) sensors is appropriate to achieve timely knowledge of the position of people and equipment. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	410,679
2404.03417	NMF-Based Analysis of Mobile Eye-Tracking Data	The depiction of scanpaths from mobile eye-tracking recordings by thumbnails from the stimulus allows the application of visual computing to detect areas of interest in an unsupervised way. We suggest using nonnegative matrix factorization (NMF) to identify such areas in stimuli. For a user-defined integer k, NMF produ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	444,248
2012.00481	Consistent Representation Learning for High Dimensional Data Analysis	High dimensional data analysis for exploration and discovery includes three fundamental tasks: dimensionality reduction, clustering, and visualization. When the three associated tasks are done separately, as is often the case thus far, inconsistencies can occur among the tasks in terms of data geometry and others. This...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	209,153
2209.04869	Systems with both constant and time-varying delays: a switched systems approach and application to observer-controller co-design	In this paper, we study the application of switched systems stability criteria to derive delay-dependent conditions for systems affected by both a constant and a time-varying delay. The main novelty of our approach lies on the use of path-complete Lyapunov techniques along with the proposition of a new modified functio...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	316,910
2312.13141	Augment on Manifold: Mixup Regularization with UMAP	Data augmentation techniques play an important role in enhancing the performance of deep learning models. Despite their proven benefits in computer vision tasks, their application in the other domains remains limited. This paper proposes a Mixup regularization scheme, referred to as UMAP Mixup, designed for ``on-manifo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	417,221
cmp-lg/9806008	Unlimited Vocabulary Grapheme to Phoneme Conversion for Korean TTS	This paper describes a grapheme-to-phoneme conversion method using phoneme connectivity and CCV conversion rules. The method consists of mainly four modules including morpheme normalization, phrase-break detection, morpheme to phoneme conversion and phoneme connectivity check. The morpheme normalization is to replace...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,882
2010.07524	Unsupervised Video Anomaly Detection via Normalizing Flows with Implicit Latent Features	In contemporary society, surveillance anomaly detection, i.e., spotting anomalous events such as crimes or accidents in surveillance videos, is a critical task. As anomalies occur rarely, most training data consists of unlabeled videos without anomalous events, which makes the task challenging. Most existing methods us...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	200,852
2312.05270	Image and AIS Data Fusion Technique for Maritime Computer Vision Applications	Deep learning object detection methods, like YOLOv5, are effective in identifying maritime vessels but often lack detailed information important for practical applications. In this paper, we addressed this problem by developing a technique that fuses Automatic Identification System (AIS) data with vessels detected in i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	414,010
2411.18700	On the Effectiveness of Incremental Training of Large Language Models	Training large language models is a computationally intensive process that often requires substantial resources to achieve state-of-the-art results. Incremental layer-wise training has been proposed as a potential strategy to optimize the training process by progressively introducing layers, with the expectation that t...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	511,973
1806.02003	Deep Algorithms: designs for networks	A new design methodology for neural networks that is guided by traditional algorithm design is presented. To prove our point, we present two heuristics and demonstrate an algorithmic technique for incorporating additional weights in their signal-flow graphs. We show that with training the performance of these networks ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	99,684
2312.04049	An Actuator with Magnetic Restoration, Part II: Drive Circuit and Control Loops	In part II, an op-amp-based drive is proposed and designed. Subsequently, a very accurate model for the drive circuit and the current loop is developed as a simulation platform, while its simplified version is derived, tailored for efficient design purposes. Through a comprehensive evaluation, the accuracy and efficacy...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	413,526
1612.05665	PAM: Parallel Augmented Maps	Ordered (key-value) maps are an important and widely-used data type for large-scale data processing frameworks. Beyond simple search, insertion and deletion, more advanced operations such as range extraction, filtering, and bulk updates form a critical part of these frameworks. We describe an interface for ordered ma...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	65,709
1403.7074	Analyzing Network Reliability Using Structural Motifs	This paper uses the reliability polynomial, introduced by Moore and Shannon in 1956, to analyze the effect of network structure on diffusive dynamics such as the spread of infectious disease. We exhibit a representation for the reliability polynomial in terms of what we call {\em structural motifs} that is well suited ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	31,868
2203.09885	Formally Modeling Autonomous Vehicles in LNT for Simulation and Testing	We present two behavioral models of an autonomous vehicle and its interaction with the environment. Both models use the formal modeling language LNT provided by the CADP toolbox. This paper discusses the modeling choices and the challenges of our autonomous vehicle models, and also illustrates how formal validation too...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	286,323
2305.09407	A Novel Strategy for Improving Robustness in Computer Vision Manufacturing Defect Detection	Visual quality inspection in high performance manufacturing can benefit from automation, due to cost savings and improved rigor. Deep learning techniques are the current state of the art for generic computer vision tasks like classification and object detection. Manufacturing data can pose a challenge for deep learning...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	364,626
2210.11539	ConfMix: Unsupervised Domain Adaptation for Object Detection via Confidence-based Mixing	Unsupervised Domain Adaptation (UDA) for object detection aims to adapt a model trained on a source domain to detect instances from a new target domain for which annotations are not available. Different from traditional approaches, we propose ConfMix, the first method that introduces a sample mixing strategy based on r...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	325,350
2308.12013	Quantum-Noise-Driven Generative Diffusion Models	Generative models realized with machine learning techniques are powerful tools to infer complex and unknown data distributions from a finite number of training samples in order to produce new synthetic data. Diffusion models are an emerging framework that have recently overcome the performance of the generative adversa...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	387,376
2207.02059	Transformer based Models for Unsupervised Anomaly Segmentation in Brain MR Images	The quality of patient care associated with diagnostic radiology is proportionate to a physician workload. Segmentation is a fundamental limiting precursor to both diagnostic and therapeutic procedures. Advances in machine learning (ML) aim to increase diagnostic efficiency by replacing a single application with genera...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	306,385
2104.12676	Solving a class of non-convex min-max games using adaptive momentum methods	Adaptive momentum methods have recently attracted a lot of attention for training of deep neural networks. They use an exponential moving average of past gradients of the objective function to update both search directions and learning rates. However, these methods are not suited for solving min-max optimization proble...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	232,289
2305.07894	Voxel-wise classification for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural networks	Additive Manufacturing (AM) has emerged as a manufacturing process that allows the direct production of samples from digital models. To ensure that quality standards are met in all manufactured samples of a batch, X-ray computed tomography (X-CT) is often used combined with automated anomaly detection. For the latter, ...	false	true	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	364,076
2411.05418	Development of Underactuated Geometric Compliant (UGC) Module with Variable Radial for Robotic Applications	This paper introduces a novel underactuated geometric compliant (UGC) robot and investigates the behaviors of underactuated compliant modules with variable radial stiffness, aiming to enhance the versatility and functionality of UGC robots. We initiate the study by designing and fabricating various compliant semi-rigid...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	506,658
2309.11305	Create and Find Flatness: Building Flat Training Spaces in Advance for Continual Learning	Catastrophic forgetting remains a critical challenge in the field of continual learning, where neural networks struggle to retain prior knowledge while assimilating new information. Most existing studies emphasize mitigating this issue only when encountering new tasks, overlooking the significance of the pre-task phase...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	393,355
2312.14227	ElasticTrainer: Speeding Up On-Device Training with Runtime Elastic Tensor Selection	On-device training is essential for neural networks (NNs) to continuously adapt to new online data, but can be time-consuming due to the device's limited computing power. To speed up on-device training, existing schemes select trainable NN portion offline or conduct unrecoverable selection at runtime, but the evolution...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	417,553
2501.08271	Comparative Analysis of Efficient Adapter-Based Fine-Tuning of State-of-the-Art Transformer Models	In this work, we investigate the efficacy of various adapter architectures on supervised binary classification tasks from the SuperGLUE benchmark as well as a supervised multi-class news category classification task from Kaggle. Specifically, we compare classification performance and time complexity of three transforme...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	524,695
1811.06031	A Hierarchical Multi-task Approach for Learning Embeddings from Semantic Tasks	Much effort has been devoted to evaluate whether multi-task learning can be leveraged to learn rich representations that can be used in various Natural Language Processing (NLP) down-stream applications. However, there is still a lack of understanding of the settings in which multi-task learning has a significant effec...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	113,430
2311.17514	Reinforcement Replaces Supervision: Query focused Summarization using Deep Reinforcement Learning	Query-focused Summarization (QfS) deals with systems that generate summaries from document(s) based on a query. Motivated by the insight that Reinforcement Learning (RL) provides a generalization to Supervised Learning (SL) for Natural Language Generation, and thereby performs better (empirically) than SL, we use an RL...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	411,327
2403.04106	Understanding Biology in the Age of Artificial Intelligence	Modern life sciences research is increasingly relying on artificial intelligence approaches to model biological systems, primarily centered around the use of machine learning (ML) models. Although ML is undeniably useful for identifying patterns in large, complex data sets, its widespread application in biological scie...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	435,453
1805.01358	SIPs: Succinct Interest Points from Unsupervised Inlierness Probability Learning	A wide range of computer vision algorithms rely on identifying sparse interest points in images and establishing correspondences between them. However, only a subset of the initially identified interest points results in true correspondences (inliers). In this paper, we seek a detector that finds the minimum number of ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	96,640
2207.02637	On the Complexity of Rational Verification	Rational verification refers to the problem of checking which temporal logic properties hold of a concurrent multiagent system, under the assumption that agents in the system choose strategies that form a game-theoretic equilibrium. Rational verification can be understood as a counterpart to model checking for multiage...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	true	306,577
2404.17498	Learning text-to-video retrieval from image captioning	We describe a protocol to study text-to-video retrieval training with unlabeled videos, where we assume (i) no access to labels for any videos, i.e., no access to the set of ground-truth captions, but (ii) access to labeled images in the form of text. Using image expert models is a realistic scenario given that annotat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	449,878
2405.01228	RaffeSDG: Random Frequency Filtering enabled Single-source Domain Generalization for Medical Image Segmentation	Deep learning models often encounter challenges in making accurate inferences when there are domain shifts between the source and target data. This issue is particularly pronounced in clinical settings due to the scarcity of annotated data resulting from the professional and private nature of medical data. Despite the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	451,279
2308.13579	A Comparative Study on Routing Selection Algorithms for Dynamic Planning of EONs over C+L Bands	The performance of three routing selection algorithms is compared in terms of bandwidth blocking probability, quality of transmission, and run time in EONs over the C+L band. The min-max frequency algorithm shows the best performance on all metrics.	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	387,981
2208.11015	META-CODE: Community Detection via Exploratory Learning in Topologically Unknown Networks	The discovery of community structures in social networks has gained considerable attention as a fundamental problem for various network analysis tasks. However, due to privacy concerns or access restrictions, the network structure is often unknown, thereby rendering established community detection approaches ineffectiv...	false	false	false	true	true	true	true	false	false	false	false	false	false	false	false	true	false	false	314,283
2306.04217	Effective Neural Topic Modeling with Embedding Clustering Regularization	Topic models have been prevalent for decades with various applications. However, existing topic models commonly suffer from the notorious topic collapsing: discovered topics semantically collapse towards each other, leading to highly repetitive topics, insufficient topic discovery, and damaged model interpretability. I...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	371,652
2308.13246	Model-free Reinforcement Learning with Stochastic Reward Stabilization for Recommender Systems	Model-free RL-based recommender systems have recently received increasing research attention due to their capability to handle partial feedback and long-term rewards. However, most existing research has ignored a critical feature in recommender systems: one user's feedback on the same item at different times is random....	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	387,842
2107.10690	A Tethered Quadrotor UAV$-$Buoy System for Marine Locomotion	Unmanned aerial vehicles (UAVs) are finding their way into offshore applications. In this work, we postulate an original system that entails a marine locomotive quadrotor UAV that manipulates the velocity of a floating buoy by means of a cable. By leveraging the advantages of UAVs relative to high speed, maneuverabilit...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	247,371
2311.02564	Relation Extraction Model Based on Semantic Enhancement Mechanism	Relational extraction is one of the basic tasks related to information extraction in the field of natural language processing, and is an important link and core task in the fields of information extraction, natural language understanding, and information retrieval. None of the existing relation extraction methods can e...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	405,493
2407.20668	Mimicking the Mavens: Agent-based Opinion Synthesis and Emotion Prediction for Social Media Influencers	Predicting influencers' views and public sentiment on social media is crucial for anticipating societal trends and guiding strategic responses. This study introduces a novel computational framework to predict opinion leaders' perspectives and the emotive reactions of the populace, addressing the inherent challenges pos...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	477,243
1505.02890	Sparse 3D convolutional neural networks	We have implemented a convolutional neural network designed for processing sparse three-dimensional input data. The world we live in is three dimensional so there are a large number of potential applications including 3D object recognition and analysis of space-time objects. In the quest for efficiency, we experiment w...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	43,012
2207.08803	Adversarial Pixel Restoration as a Pretext Task for Transferable Perturbations	Transferable adversarial attacks optimize adversaries from a pretrained surrogate model and known label space to fool the unknown black-box models. Therefore, these attacks are restricted by the availability of an effective surrogate model. In this work, we relax this assumption and propose Adversarial Pixel Restoratio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	308,690
2407.07787	Continuous Control with Coarse-to-fine Reinforcement Learning	Despite recent advances in improving the sample-efficiency of reinforcement learning (RL) algorithms, designing an RL algorithm that can be practically deployed in real-world environments remains a challenge. In this paper, we present Coarse-to-fine Reinforcement Learning (CRL), a framework that trains RL agents to zoo...	false	false	false	false	true	false	true	true	false	false	true	true	false	false	false	false	false	false	471,901
1108.5096	Minimalist Grammars and Minimalist Categorial Grammars, definitions toward inclusion of generated languages	Stabler proposes an implementation of the Chomskyan Minimalist Program, Chomsky 95 with Minimalist Grammars - MG, Stabler 97. This framework inherits a long linguistic tradition. But the semantic calculus is more easily added if one uses the Curry-Howard isomorphism. Minimalist Categorial Grammars - MCG, based on an ex...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	11,814
1107.2699	Linear Latent Force Models using Gaussian Processes	Purely data driven approaches for machine learning present difficulties when data is scarce relative to the complexity of the model or when the model is forced to extrapolate. On the other hand, purely mechanistic approaches need to identify and specify all the interactions in the problem at hand (which may not be feas...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	11,284
1912.09572	Implementation of encryption on telemedicine	In the era of technology, data security is one of the most important things that both individuals and companies need. Information plays a huge role in our everyday life and keeping it safe should be our number one priority. Nowadays most of the information is transferred via the internet. One of the ways to use it is t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	158,101
2304.07993	In-Context Operator Learning with Data Prompts for Differential Equation Problems	This paper introduces a new neural-network-based approach, namely In-Context Operator Networks (ICON), to simultaneously learn operators from the prompted data and apply it to new questions during the inference stage, without any weight update. Existing methods are limited to using a neural network to approximate a spe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	358,556
2405.12716	Reinforcement Learning Enabled Peer-to-Peer Energy Trading for Dairy Farms	Farm businesses are increasingly adopting renewables to enhance energy efficiency and reduce reliance on fossil fuels and the grid. This shift aims to decrease dairy farms' dependence on traditional electricity grids by enabling the sale of surplus renewable energy in Peer-to-Peer markets. However, the dynamic nature o...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	455,628
1901.07766	Programmable Neural Network Trojan for Pre-Trained Feature Extractor	Neural network (NN) trojaning attack is an emerging and important attack model that can broadly damage the system deployed with NN models. Existing studies have explored the outsourced training attack scenario and transfer learning attack scenario in some small datasets for specific domains, with limited numbers of fix...	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	true	false	false	119,298
2411.11592	Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting	This study presents a framework for predicting unsteady transonic wing pressure distributions, integrating an autoencoder architecture with graph convolutional networks and graph-based temporal layers to model time dependencies. The framework compresses high-dimensional pressure distribution data into a lower-dimension...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	509,110
cs/0604027	Unification of multi-lingual scientific terminological resources using the ISO 16642 standard. The TermSciences initiative	This paper presents the TermSciences portal, which deals with the implementation of a conceptual model that uses the recent ISO 16642 standard (Terminological Markup Framework). This standard turns out to be suitable for concept modeling since it allowed for organizing the original resources by concepts and to associat...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	539,374
2403.07027	FWin transformer for dengue prediction under climate and ocean influence	Dengue fever is one of the most deadly mosquito-born tropical infectious diseases. Detailed long range forecast model is vital in controlling the spread of disease and making mitigation efforts. In this study, we examine methods used to forecast dengue cases for long range predictions. The dataset consists of local cli...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	436,712
1704.05693	Unsupervised Creation of Parameterized Avatars	We study the problem of mapping an input image to a tied pair consisting of a vector of parameters and an image that is created using a graphical engine from the vector of parameters. The mapping's objective is to have the output image as similar as possible to the input image. During training, no supervision is given ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	72,054
2201.12675	Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models	A central tenet of Federated learning (FL), which trains models without centralizing user data, is privacy. However, previous work has shown that the gradient updates used in FL can leak user information. While the most industrial uses of FL are for text applications (e.g. keystroke prediction), nearly all attacks on F...	false	false	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	277,736
2107.00143	One-class Steel Detector Using Patch GAN Discriminator for Visualising Anomalous Feature Map	For steel product manufacturing in indoor factories, steel defect detection is important for quality control. For example, a steel sheet is extremely delicate, and must be accurately inspected. However, to maintain the painted steel parts of the infrastructure around a severe outdoor environment, corrosion detection is...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	244,050
2310.14400	A Pytorch Reproduction of Masked Generative Image Transformer	In this technical report, we present a reproduction of MaskGIT: Masked Generative Image Transformer, using PyTorch. The approach involves leveraging a masked bidirectional transformer architecture, enabling image generation with only few steps (8~16 steps) for 512 x 512 resolution images, i.e., ~64x faster than an auto...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	401,833
2009.08265	Dimension Reduction in Contextual Online Learning via Nonparametric Variable Selection	We consider a contextual online learning (multi-armed bandit) problem with high-dimensional covariate $\mathbf{x}$ and decision $\mathbf{y}$. The reward function to learn, $f(\mathbf{x},\mathbf{y})$, does not have a particular parametric form. The literature has shown that the optimal regret is $\tilde{O}(T^{(d_x+d_y+1...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	196,183
2010.12423	GraphSpeech: Syntax-Aware Graph Attention Network For Neural Speech Synthesis	Attention-based end-to-end text-to-speech synthesis (TTS) is superior to conventional statistical methods in many ways. Transformer-based TTS is one of such successful implementations. While Transformer TTS models the speech frame sequence well with a self-attention mechanism, it does not associate input text with outp...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	202,690
2405.19112	Reconstructing Interpretable Features in Computational Super-Resolution microscopy via Regularized Latent Search	Supervised deep learning approaches can artificially increase the resolution of microscopy images by learning a mapping between two image resolutions or modalities. However, such methods often require a large set of hard-to-get low-res/high-res image pairs and produce synthetic images with a moderate increase in resolu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	458,757
1707.06314	Fast, Simple Calcium Imaging Segmentation with Fully Convolutional Networks	Calcium imaging is a technique for observing neuron activity as a series of images showing indicator fluorescence over time. Manually segmenting neurons is time-consuming, leading to research on automated calcium imaging segmentation (ACIS). We evaluated several deep learning models for ACIS on the Neurofinder competit...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	77,392
2012.15575	A Deep Retinal Image Quality Assessment Network with Salient Structure Priors	Retinal image quality assessment is an essential prerequisite for diagnosis of retinal diseases. Its goal is to identify retinal images in which anatomic structures and lesions attracting ophthalmologists' attention most are exhibited clearly and definitely while reject poor quality fundus images. Motivated by this, we...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	213,840
2207.06899	Factorized and Controllable Neural Re-Rendering of Outdoor Scene for Photo Extrapolation	Expanding an existing tourist photo from a partially captured scene to a full scene is one of the desired experiences for photography applications. Although photo extrapolation has been well studied, it is much more challenging to extrapolate a photo (i.e., selfie) from a narrow field of view to a wider one while maint...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	308,032
2303.01064	Adopting the Multi-answer Questioning Task with an Auxiliary Metric for Extreme Multi-label Text Classification Utilizing the Label Hierarchy	Extreme multi-label text classification utilizes the label hierarchy to partition extreme labels into multiple label groups, turning the task into simple multi-group multi-label classification tasks. Current research encodes labels as a vector with fixed length which needs establish multiple classifiers for different l...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	348,818
1709.03815	OpenNMT: Open-source Toolkit for Neural Machine Translation	We introduce an open-source toolkit for neural machine translation (NMT) to support research into model architectures, feature representations, and source modalities, while maintaining competitive performance, modularity and reasonable training requirements.	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	80,541
2407.16234	A Multi-view Mask Contrastive Learning Graph Convolutional Neural Network for Age Estimation	The age estimation task aims to use facial features to predict the age of people and is widely used in public security, marketing, identification, and other fields. However, the features are mainly concentrated in facial keypoints, and existing CNN and Transformer-based methods have inflexibility and redundancy for mod...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	475,517
2005.07352	Decoding of NB-LDPC codes over Subfields	The non-binary low-density parity-check (NB-LDPC) codes can offer promising performance advantages but suffer from high decoding complexity. To tackle this challenge, in this paper, we consider NB-LDPC codes over finite fields as codes over \textit{subfields} as a means of reducing decoding complexity. In particular, o...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	177,256
1908.10402	A Near-Optimal Change-Detection Based Algorithm for Piecewise-Stationary Combinatorial Semi-Bandits	We investigate the piecewise-stationary combinatorial semi-bandit problem. Compared to the original combinatorial semi-bandit problem, our setting assumes the reward distributions of base arms may change in a piecewise-stationary manner at unknown time steps. We propose an algorithm, \texttt{GLR-CUCB}, which incorporat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	143,105
1603.00110	Robust Multi-body Feature Tracker: A Segmentation-free Approach	Feature tracking is a fundamental problem in computer vision, with applications in many computer vision tasks, such as visual SLAM and action recognition. This paper introduces a novel multi-body feature tracker that exploits a multi-body rigidity assumption to improve tracking robustness under a general perspective ca...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	52,739
1810.10422	Reduced order modeling of subsurface multiphase flow models using deep residual recurrent neural networks	We present a reduced order modeling (ROM) technique for subsurface multi-phase flow problems building on the recently introduced deep residual recurrent neural network (DR-RNN) [1]. DR-RNN is a physics aware recurrent neural network for modeling the evolution of dynamical systems. The DR-RNN architecture is inspired by...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	111,289
1908.04920	Aggregating Votes with Local Differential Privacy: Usefulness, Soundness vs. Indistinguishability	Voting plays a central role in bringing crowd wisdom to collective decision making, meanwhile data privacy has been a common ethical/legal issue in eliciting preferences from individuals. This work studies the problem of aggregating individual's voting data under the local differential privacy setting, where usefulness...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	141,601
2211.11434	Privacy in Practice: Private COVID-19 Detection in X-Ray Images (Extended Version)	Machine learning (ML) can help fight pandemics like COVID-19 by enabling rapid screening of large volumes of images. To perform data analysis while maintaining patient privacy, we create ML models that satisfy Differential Privacy (DP). Previous works exploring private COVID-19 models are in part based on small dataset...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	331,731
2409.11302	Beyond LoRA: Exploring Efficient Fine-Tuning Techniques for Time Series Foundational Models	Time Series Foundation Models (TSFMs) have recently garnered attention for their ability to model complex, large-scale time series data across domains such as retail, finance, and transportation. However, their application to sensitive, domain-specific fields like healthcare remains challenging, primarily due to the di...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	489,099

Subsets and Splits

No community queries yet

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