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
1908.01308	Theme-Aware Aesthetic Distribution Prediction With Full-Resolution Photographs	Aesthetic quality assessment (AQA) is a challenging task due to complex aesthetic factors. Currently, it is common to conduct AQA using deep neural networks that require fixed-size inputs. Existing methods mainly transform images by resizing, cropping, and padding or employ adaptive pooling to alternately capture the a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	140,729
2006.16893	FVV Live: Real-Time, Low-Cost, Free Viewpoint Video	FVV Live is a novel real-time, low-latency, end-to-end free viewpoint system including capture, transmission, synthesis on an edge server and visualization and control on a mobile terminal. The system has been specially designed for low-cost and real-time operation, only using off-the-shelf components.	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	184,939
1410.0113	CONCERT: A Cloud-Based Architecture for Next-generation Cellular Systems	Cellular networks are one of the corner stones of our information-driven society. However, existing cellular systems have been seriously challenged by the explosion of mobile data traffic, the emergence of machine-type communications and the flourish of mobile Internet services. In this article, we propose CONCERT (CON...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	36,437
1911.12990	Semi-Relaxed Quantization with DropBits: Training Low-Bit Neural Networks via Bit-wise Regularization	Network quantization, which aims to reduce the bit-lengths of the network weights and activations, has emerged as one of the key ingredients to reduce the size of neural networks for their deployments to resource-limited devices. In order to overcome the nature of transforming continuous activations and weights to disc...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	155,551
1909.00383	Self-Attention with Structural Position Representations	Although self-attention networks (SANs) have advanced the state-of-the-art on various NLP tasks, one criticism of SANs is their ability of encoding positions of input words (Shaw et al., 2018). In this work, we propose to augment SANs with structural position representations to model the latent structure of the input s...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	143,618
2404.14025	DHRNet: A Dual-Path Hierarchical Relation Network for Multi-Person Pose Estimation	Multi-person pose estimation (MPPE) presents a formidable yet crucial challenge in computer vision. Most existing methods predominantly concentrate on isolated interaction either between instances or joints, which is inadequate for scenarios demanding concurrent localization of both instances and joints. This paper int...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	448,539
1703.09794	Probabilistic Models for Computerized Adaptive Testing	In this paper we follow our previous research in the area of Computerized Adaptive Testing (CAT). We present three different methods for CAT. One of them, the item response theory, is a well established method, while the other two, Bayesian and neural networks, are new in the area of educational testing. In the first p...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	70,803
2306.04746	Using Imperfect Surrogates for Downstream Inference: Design-based Supervised Learning for Social Science Applications of Large Language Models	In computational social science (CSS), researchers analyze documents to explain social and political phenomena. In most scenarios, CSS researchers first obtain labels for documents and then explain labels using interpretable regression analyses in the second step. One increasingly common way to annotate documents cheap...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	371,878
2109.09658	FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging	The recent advancements in artificial intelligence (AI) combined with the extensive amount of data generated by today's clinical systems, has led to the development of imaging AI solutions across the whole value chain of medical imaging, including image reconstruction, medical image segmentation, image-based diagnosis ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	256,350
2211.12638	Projection-free Adaptive Regret with Membership Oracles	In the framework of online convex optimization, most iterative algorithms require the computation of projections onto convex sets, which can be computationally expensive. To tackle this problem HK12 proposed the study of projection-free methods that replace projections with less expensive computations. The most common ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	332,178
2311.07758	Synchrophasor Data Anomaly Detection on Grid Edge by 5G Communication and Adjacent Compute	The fifth-generation mobile communication (5G) technology offers opportunities to enhance the real-time monitoring of grids. The 5G-enabled phasor measurement units (PMUs) feature flexible positioning and cost-effective long-term maintenance without the constraints of fixing wires. This paper is the first to demonstrat...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	407,455
2008.02742	Compositional Networks Enable Systematic Generalization for Grounded Language Understanding	Humans are remarkably flexible when understanding new sentences that include combinations of concepts they have never encountered before. Recent work has shown that while deep networks can mimic some human language abilities when presented with novel sentences, systematic variation uncovers the limitations in the langu...	false	false	false	false	true	false	false	true	true	false	false	false	false	false	false	false	false	false	190,697
1907.02228	RFBTD: RFB Text Detector	Text detection plays a critical role in the whole procedure of textual information extraction and understanding. On a high note, recent years have seen a surge in the high recall text detectors in scene text images, however text boxes for individual words is still a challenging when dense text is present in the scene. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	137,566
0902.4481	Stability of Finite Population ALOHA with Variable Packets	ALOHA is one of the most basic Medium Access Control (MAC) protocols and represents a foundation for other more sophisticated distributed and asynchronous MAC protocols, e.g., CSMA. In this paper, unlike in the traditional work that focused on mean value analysis, we study the distributional properties of packet transm...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	3,234
2404.15192	Measuring Diversity of Game Scenarios	This survey comprehensively reviews the multi-dimensionality of game scenario diversity, spotlighting the innovative use of procedural content generation and other fields as cornerstones for enriching player experiences through diverse game scenarios. By traversing a wide array of disciplines, from affective modeling a...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	448,976
1112.0708	Information-Theoretically Optimal Compressed Sensing via Spatial Coupling and Approximate Message Passing	We study the compressed sensing reconstruction problem for a broad class of random, band-diagonal sensing matrices. This construction is inspired by the idea of spatial coupling in coding theory. As demonstrated heuristically and numerically by Krzakala et al. \cite{KrzakalaEtAl}, message passing algorithms can effecti...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	13,302
2306.16925	MIS-FM: 3D Medical Image Segmentation using Foundation Models Pretrained on a Large-Scale Unannotated Dataset	Pretraining with large-scale 3D volumes has a potential for improving the segmentation performance on a target medical image dataset where the training images and annotations are limited. Due to the high cost of acquiring pixel-level segmentation annotations on the large-scale pretraining dataset, pretraining with unan...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	376,535
2206.12784	Learning to Rearrange with Physics-Inspired Risk Awareness	Real-world applications require a robot operating in the physical world with awareness of potential risks besides accomplishing the task. A large part of risky behaviors arises from interacting with objects in ignorance of affordance. To prevent the agent from making unsafe decisions, we propose to train a robotic agen...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	304,732
2402.12065	WKVQuant: Quantizing Weight and Key/Value Cache for Large Language Models Gains More	Large Language Models (LLMs) face significant deployment challenges due to their substantial memory requirements and the computational demands of auto-regressive text generation process. This paper addresses these challenges by focusing on the quantization of LLMs, a technique that reduces memory consumption by convert...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	430,700
2207.08301	Vision-based Relative Detection and Tracking for Teams of Micro Aerial Vehicles	In this paper, we address the vision-based detection and tracking problems of multiple aerial vehicles using a single camera and Inertial Measurement Unit (IMU) as well as the corresponding perception consensus problem (i.e., uniqueness and identical IDs across all observing agents). We design several vision-based dece...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	308,534
2110.08248	Probabilistic Time Series Forecasts with Autoregressive Transformation Models	Probabilistic forecasting of time series is an important matter in many applications and research fields. In order to draw conclusions from a probabilistic forecast, we must ensure that the model class used to approximate the true forecasting distribution is expressive enough. Yet, characteristics of the model itself, ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	261,312
2208.05280	TSInterpret: A unified framework for time series interpretability	With the increasing application of deep learning algorithms to time series classification, especially in high-stake scenarios, the relevance of interpreting those algorithms becomes key. Although research in time series interpretability has grown, accessibility for practitioners is still an obstacle. Interpretability a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	312,362
2303.06295	Semi-Tensor Product of Hypermatrices with Application to Compound Hypermatrices	The semi-tensor product (STP) of matrices is extended to the STP of hypermatrices. Some basic properties of the STP of matrices are extended to the STP of hypermatrices. The hyperdeterminant of hypersquares is introduced. Some algebraic and geometric structures of matrices are extended to hypermatrices. Then the compou...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	350,779
2101.11191	On Small-World Networks: Survey and Properties Analysis	Complex networks has been a hot topic of research over the past several years over crossing many disciplines, starting from mathematics and computer science and ending by the social and biological sciences. Random graphs were studied to observe the qualitative features they have in common in planetary scale data sets w...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	217,188
2405.10575	Accurate Training Data for Occupancy Map Prediction in Automated Driving Using Evidence Theory	Automated driving fundamentally requires knowledge about the surrounding geometry of the scene. Modern approaches use only captured images to predict occupancy maps that represent the geometry. Training these approaches requires accurate data that may be acquired with the help of LiDAR scanners. We show that the techni...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	454,810
2107.08565	Learning point embedding for 3D data processing	Among 2D convolutional networks on point clouds, point-based approaches consume point clouds of fixed size directly. By analysis of PointNet, a pioneer in introducing deep learning into point sets, we reveal that current point-based methods are essentially spatial relationship processing networks. In this paper, we tak...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	246,763
2403.14974	AVT2-DWF: Improving Deepfake Detection with Audio-Visual Fusion and Dynamic Weighting Strategies	With the continuous improvements of deepfake methods, forgery messages have transitioned from single-modality to multi-modal fusion, posing new challenges for existing forgery detection algorithms. In this paper, we propose AVT2-DWF, the Audio-Visual dual Transformers grounded in Dynamic Weight Fusion, which aims to am...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	440,333
2405.18549	Learning from Uncertain Data: From Possible Worlds to Possible Models	We introduce an efficient method for learning linear models from uncertain data, where uncertainty is represented as a set of possible variations in the data, leading to predictive multiplicity. Our approach leverages abstract interpretation and zonotopes, a type of convex polytope, to compactly represent these dataset...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	true	458,470
2012.09632	From Weakly Supervised Learning to Biquality Learning: an Introduction	The field of Weakly Supervised Learning (WSL) has recently seen a surge of popularity, with numerous papers addressing different types of "supervision deficiencies". In WSL use cases, a variety of situations exists where the collected "information" is imperfect. The paradigm of WSL attempts to list and cover these prob...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	212,127
1703.06988	The Fake News Spreading Plague: Was it Preventable?	In 2010, a paper entitled "From Obscurity to Prominence in Minutes: Political Speech and Real-time search" won the Best Paper Prize of the Web Science 2010 Conference. Among its findings were the discovery and documentation of what was termed a "Twitter-bomb", an organized effort to spread misinformation about the demo...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	70,310
2211.13928	MUSTER: A Multi-scale Transformer-based Decoder for Semantic Segmentation	In recent works on semantic segmentation, there has been a significant focus on designing and integrating transformer-based encoders. However, less attention has been given to transformer-based decoders. We emphasize that the decoder stage is equally vital as the encoder in achieving superior segmentation performance. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	332,653
2203.06574	Worst Case Matters for Few-Shot Recognition	Few-shot recognition learns a recognition model with very few (e.g., 1 or 5) images per category, and current few-shot learning methods focus on improving the average accuracy over many episodes. We argue that in real-world applications we may often only try one episode instead of many, and hence maximizing the worst-c...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	285,158
1807.01996	A Formal Ontology-Based Classification of Lexemes and its Applications	The paper describes the enrichment of OntoSenseNet - a verb-centric lexical resource for Indian Languages. A major contribution of this work is preservation of an authentic Telugu dictionary by developing a computational version of the same. It is important because native speakers can better annotate the sense-types wh...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	102,178
2404.04526	DATENeRF: Depth-Aware Text-based Editing of NeRFs	Recent advancements in diffusion models have shown remarkable proficiency in editing 2D images based on text prompts. However, extending these techniques to edit scenes in Neural Radiance Fields (NeRF) is complex, as editing individual 2D frames can result in inconsistencies across multiple views. Our crucial insight i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	444,683
2210.09558	Bag of Tricks for Developing Diabetic Retinopathy Analysis Framework to Overcome Data Scarcity	Recently, diabetic retinopathy (DR) screening utilizing ultra-wide optical coherence tomography angiography (UW-OCTA) has been used in clinical practices to detect signs of early DR. However, developing a deep learning-based DR analysis system using UW-OCTA images is not trivial due to the difficulty of data collection...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	324,583
1312.2844	mARC: Memory by Association and Reinforcement of Contexts	This paper introduces the memory by Association and Reinforcement of Contexts (mARC). mARC is a novel data modeling technology rooted in the second quantization formulation of quantum mechanics. It is an all-purpose incremental and unsupervised data storage and retrieval system which can be applied to all types of sign...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	28,994
2404.18933	Learning Low-Rank Feature for Thorax Disease Classification	Deep neural networks, including Convolutional Neural Networks (CNNs) and Visual Transformers (ViT), have achieved stunning success in medical image domain. We study thorax disease classification in this paper. Effective extraction of features for the disease areas is crucial for disease classification on radiographic i...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	450,442
2405.20233	Grokfast: Accelerated Grokking by Amplifying Slow Gradients	One puzzling artifact in machine learning dubbed grokking is where delayed generalization is achieved tenfolds of iterations after near perfect overfitting to the training data. Focusing on the long delay itself on behalf of machine learning practitioners, our goal is to accelerate generalization of a model under grokk...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	459,252
1405.4957	Symbol-Based Successive Cancellation List Decoder for Polar Codes	Polar codes is promising because they can provably achieve the channel capacity while having an explicit construction method. Lots of work have been done for the bit-based decoding algorithm for polar codes. In this paper, generalized symbol-based successive cancellation (SC) and SC list decoding algorithms are discuss...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	33,224
1907.01538	Taint analysis of the Bitcoin network	Determining the trust of an individual Bitcoin wallet is a difficult problem. There are no ratings, that offer vendors or exchanges meaningful information about the level of the taint of Bitcoins they are receiving. Lack of such information places exchanges liable in an event when the received Bitcoins are stolen or il...	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	137,357
1811.04201	Adversarially-Trained Normalized Noisy-Feature Auto-Encoder for Text Generation	This article proposes Adversarially-Trained Normalized Noisy-Feature Auto-Encoder (ATNNFAE) for byte-level text generation. An ATNNFAE consists of an auto-encoder where the internal code is normalized on the unit sphere and corrupted by additive noise. Simultaneously, a replica of the decoder (sharing the same paramete...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	113,021
1809.01477	A Supervised Learning Approach For Heading Detection	As the Portable Document Format (PDF) file format increases in popularity, research in analysing its structure for text extraction and analysis is necessary. Detecting headings can be a crucial component of classifying and extracting meaningful data. This research involves training a supervised learning model to detect...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	106,813
2308.12431	Advance Simulation Method for Wheel-Terrain Interactions of Space Rovers: A Case Study on the UAE Rashid Rover	A thorough analysis of wheel-terrain interaction is critical to ensure the safe and efficient operation of space rovers on extraterrestrial surfaces like the Moon or Mars. This paper presents an approach for developing and experimentally validating a virtual wheel-terrain interaction model for the UAE Rashid rover. The...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	387,529
1810.09109	Evolution of holonic control architectures towards Industry 4.0: A short overview	The flexibility claimed by the next generation production systems induces a deep modification of the behavior and the core itself of the control systems. Overconnectivity and data management abilities targeted by Industry 4.0 paradigm enable the emergence of more flexible and reactive control systems, based on the coop...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	110,988
0708.4311	2006: Celebrating 75 years of AI - History and Outlook: the Next 25 Years	When Kurt Goedel layed the foundations of theoretical computer science in 1931, he also introduced essential concepts of the theory of Artificial Intelligence (AI). Although much of subsequent AI research has focused on heuristics, which still play a major role in many practical AI applications, in the new millennium A...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	617
1301.6694	Qualitative Models for Decision Under Uncertainty without the Commensurability Assumption	This paper investigates a purely qualitative version of Savage's theory for decision making under uncertainty. Until now, most representation theorems for preference over acts rely on a numerical representation of utility and uncertainty where utility and uncertainty are commensurate. Disrupting the tradition, we relax...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	21,487
1705.02999	Real-Time User-Guided Image Colorization with Learned Deep Priors	We propose a deep learning approach for user-guided image colorization. The system directly maps a grayscale image, along with sparse, local user "hints" to an output colorization with a Convolutional Neural Network (CNN). Rather than using hand-defined rules, the network propagates user edits by fusing low-level cues ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	73,106
2404.03272	Cryptographic Hardness of Score Estimation	We show that $L^2$-accurate score estimation, in the absence of strong assumptions on the data distribution, is computationally hard even when sample complexity is polynomial in the relevant problem parameters. Our reduction builds on the result of Chen et al. (ICLR 2023), who showed that the problem of generating samp...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	444,185
2409.02530	Understanding eGFR Trajectories and Kidney Function Decline via Large Multimodal Models	The estimated Glomerular Filtration Rate (eGFR) is an essential indicator of kidney function in clinical practice. Although traditional equations and Machine Learning (ML) models using clinical and laboratory data can estimate eGFR, accurately predicting future eGFR levels remains a significant challenge for nephrologi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	485,740
2203.02498	Computational Fluid Dynamics and Machine Learning as tools for Optimization of Micromixers geometry	This work explores a new approach for optimization in the field of microfluidics, using the combination of CFD (Computational Fluid Dynamics), and Machine Learning techniques. The objective of this combination is to enable global optimization with lower computational cost. The initial geometry is inspired in a Y-type m...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	283,766
1908.07362	A Novel method for IDC Prediction in Breast Cancer Histopathology images using Deep Residual Neural Networks	Invasive ductal carcinoma (IDC), which is also sometimes known as the infiltrating ductal carcinoma, is the most regular form of breast cancer. It accounts for about 80% of all breast cancers. According to the American Cancer Society, more than 180,000 women in the United States are diagnosed with invasive breast cance...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	142,266
2106.15561	A Survey on Neural Speech Synthesis	Text to speech (TTS), or speech synthesis, which aims to synthesize intelligible and natural speech given text, is a hot research topic in speech, language, and machine learning communities and has broad applications in the industry. As the development of deep learning and artificial intelligence, neural network-based ...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	243,808
1908.04610	Practical Active Disturbance Rejection Control: Bumpless Transfer, Rate Limitation and Incremental Algorithm	Practical applications of controllers often impose further requirements on the implementation beyond the actual control performance, such as the ability to switch between manual and automatic control or between different control laws or controller parameter settings, known as bumpless transfer. Another common requireme...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	141,527
2401.04570	An Automatic Cascaded Model for Hemorrhagic Stroke Segmentation and Hemorrhagic Volume Estimation	Hemorrhagic Stroke (HS) has a rapid onset and is a serious condition that poses a great health threat. Promptly and accurately delineating the bleeding region and estimating the volume of bleeding in Computer Tomography (CT) images can assist clinicians in treatment planning, leading to improved treatment outcomes for ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	420,472
2406.15163	A Syntax-Injected Approach for Faster and More Accurate Sentiment Analysis	Sentiment Analysis (SA) is a crucial aspect of Natural Language Processing (NLP), addressing subjective assessments in textual content. Syntactic parsing is useful in SA because explicit syntactic information can improve accuracy while providing explainability, but it tends to be a computational bottleneck in practice ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	466,641
2109.06467	Dodging Attack Using Carefully Crafted Natural Makeup	Deep learning face recognition models are used by state-of-the-art surveillance systems to identify individuals passing through public areas (e.g., airports). Previous studies have demonstrated the use of adversarial machine learning (AML) attacks to successfully evade identification by such systems, both in the digita...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	255,160
1012.4889	Tight Bounds for Lp Samplers, Finding Duplicates in Streams, and Related Problems	In this paper, we present near-optimal space bounds for Lp-samplers. Given a stream of updates (additions and subtraction) to the coordinates of an underlying vector x \in R^n, a perfect Lp sampler outputs the i-th coordinate with probability \|x_i\|^p/\|\|x\|\|_p^p. In SODA 2010, Monemizadeh and Woodruff showed polylog spac...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	8,624
2305.14122	Transferring Learning Trajectories of Neural Networks	Training deep neural networks (DNNs) is computationally expensive, which is problematic especially when performing duplicated or similar training runs in model ensemble or fine-tuning pre-trained models, for example. Once we have trained one DNN on some dataset, we have its learning trajectory (i.e., a sequence of inte...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	366,867
2102.03002	Zero Training Overhead Portfolios for Learning to Solve Combinatorial Problems	There has been an increasing interest in harnessing deep learning to tackle combinatorial optimization (CO) problems in recent years. Typical CO deep learning approaches leverage the problem structure in the model architecture. Nevertheless, the model selection is still mainly based on the conventional machine learning...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	218,597
1309.1913	Dynamic Team Theory of Stochastic Differential Decision Systems with Decentralized Noisy Information Structures via Girsanov's Measure Transformation	In this paper, we present two methods which generalize static team theory to dynamic team theory, in the context of continuous-time stochastic nonlinear differential decentralized decision systems, with relaxed strategies, which are measurable to different noisy information structures. For both methods we apply Girsano...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	26,907
2303.16891	Mask-free OVIS: Open-Vocabulary Instance Segmentation without Manual Mask Annotations	Existing instance segmentation models learn task-specific information using manual mask annotations from base (training) categories. These mask annotations require tremendous human effort, limiting the scalability to annotate novel (new) categories. To alleviate this problem, Open-Vocabulary (OV) methods leverage large...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	355,029
1102.1498	On Rate-Splitting by a Secondary Link in Multiple Access Primary Network	An achievable rate region is obtained for a primary multiple access network coexisting with a secondary link of one transmitter and a corresponding receiver. The rate region depicts the sum primary rate versus the secondary rate and is established assuming that the secondary link performs rate-splitting. The achievable...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	9,074
2202.11868	CG-SSD: Corner Guided Single Stage 3D Object Detection from LiDAR Point Cloud	At present, the anchor-based or anchor-free models that use LiDAR point clouds for 3D object detection use the center assigner strategy to infer the 3D bounding boxes. However, in a real world scene, the LiDAR can only acquire a limited object surface point clouds, but the center point of the object does not exist. Obt...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	282,028
2012.04280	Towards Uncovering the Intrinsic Data Structures for Unsupervised Domain Adaptation using Structurally Regularized Deep Clustering	Unsupervised domain adaptation (UDA) is to learn classification models that make predictions for unlabeled data on a target domain, given labeled data on a source domain whose distribution diverges from the target one. Mainstream UDA methods strive to learn domain-aligned features such that classifiers trained on the s...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	210,406
2010.06176	ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding	Neural architecture search (NAS) aims to produce the optimal sparse solution from a high-dimensional space spanned by all candidate connections. Current gradient-based NAS methods commonly ignore the constraint of sparsity in the search phase, but project the optimized solution onto a sparse one by post-processing. As ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	200,390
2105.14762	Emotional Voice Conversion: Theory, Databases and ESD	In this paper, we first provide a review of the state-of-the-art emotional voice conversion research, and the existing emotional speech databases. We then motivate the development of a novel emotional speech database (ESD) that addresses the increasing research need. With this paper, the ESD database is now made availa...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	237,798
2501.13007	PairJudge RM: Perform Best-of-N Sampling with Knockout Tournament	Best-of-N (BoN) sampling, a common strategy for test-time scaling of Large Language Models (LLMs), relies on reward models to select the best candidate solution from multiple generations. However, traditional reward models often assign arbitrary and inconsistent scores, limiting their effectiveness. To address this, we...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	526,521
2303.06819	TranSG: Transformer-Based Skeleton Graph Prototype Contrastive Learning with Structure-Trajectory Prompted Reconstruction for Person Re-Identification	Person re-identification (re-ID) via 3D skeleton data is an emerging topic with prominent advantages. Existing methods usually design skeleton descriptors with raw body joints or perform skeleton sequence representation learning. However, they typically cannot concurrently model different body-component relations, and ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	350,998
2411.12278	Versatile Cataract Fundus Image Restoration Model Utilizing Unpaired Cataract and High-quality Images	Cataract is one of the most common blinding eye diseases and can be treated by surgery. However, because cataract patients may also suffer from other blinding eye diseases, ophthalmologists must diagnose them before surgery. The cloudy lens of cataract patients forms a hazy degeneration in the fundus images, making it ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	509,363
1205.3630	Alignment and integration of complex networks by hypergraph-based spectral clustering	Complex networks possess a rich, multi-scale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction or to go beyond simple pairwise interactions, but currently the...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	16,035
1611.00812	Leveraging tagging and rating for recommendation: RMF meets weighted diffusion on tripartite graphs	Recommender systems (RSs) have been a widely exploited approach to solving the information overload problem. However, the performance is still limited due to the extreme sparsity of the rating data. With the popularity of Web 2.0, the social tagging system provides more external information to improve recommendation ac...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	63,281
1001.1966	A New Method to Extract Dorsal Hand Vein Pattern using Quadratic Inference Function	Among all biometric, dorsal hand vein pattern is attracting the attention of researchers, of late. Extensive research is being carried out on various techniques in the hope of finding an efficient one which can be applied on dorsal hand vein pattern to improve its accuracy and matching time. One of the crucial step in ...	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	5,337
2201.02750	Message Expiration-Based Distributed Multi-Robot Task Management	Distributed task assignment for multiple agents raises fundamental and novel control theory and robotics problems. A new challenge is the development of distributed algorithms that dynamically assign tasks to multiple agents, not relying on prior assignment information. This work presents a distributed method for multi...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	274,637
1407.6423	Performance evaluation of wavelet scattering network in image texture classification in various color spaces	Texture plays an important role in many image analysis applications. In this paper, we give a performance evaluation of color texture classification by performing wavelet scattering network in various color spaces. Experimental results on the KTH_TIPS_COL database show that opponent RGB based wavelet scattering network...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	34,864
1911.04453	Structural Pruning in Deep Neural Networks: A Small-World Approach	Deep Neural Networks (DNNs) are usually over-parameterized, causing excessive memory and interconnection cost on the hardware platform. Existing pruning approaches remove secondary parameters at the end of training to reduce the model size; but without exploiting the intrinsic network property, they still require the f...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	152,996
1712.06961	Unsupervised Word Mapping Using Structural Similarities in Monolingual Embeddings	Most existing methods for automatic bilingual dictionary induction rely on prior alignments between the source and target languages, such as parallel corpora or seed dictionaries. For many language pairs, such supervised alignments are not readily available. We propose an unsupervised approach for learning a bilingual ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	86,967
2104.09301	Vision-Based Guidance for Tracking Dynamic Objects	In this paper, we present a novel vision-based framework for tracking dynamic objects using guidance laws based on a rendezvous cone approach. These guidance laws enable an unmanned aircraft system equipped with a monocular camera to continuously follow a moving object within the sensor's field of view. We identify and...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	231,181
2406.18237	PlaMo: Plan and Move in Rich 3D Physical Environments	Controlling humanoids in complex physically simulated worlds is a long-standing challenge with numerous applications in gaming, simulation, and visual content creation. In our setup, given a rich and complex 3D scene, the user provides a list of instructions composed of target locations and locomotion types. To solve t...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	true	467,929
1501.03214	Quantifying Prosodic Variability in Middle English Alliterative Poetry	Interest in the mathematical structure of poetry dates back to at least the 19th century: after retiring from his mathematics position, J. J. Sylvester wrote a book on prosody called $\textit{The Laws of Verse}$. Today there is interest in the computer analysis of poems, and this paper discusses how a statistical appro...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	39,253
2407.13003	Planning and Perception for Unmanned Aerial Vehicles in Object and Environmental Monitoring	Unmanned Aerial Vehicles (UAVs) equipped with high-resolution sensors enable extensive data collection from previously inaccessible areas at a remarkable spatio-temporal scale, promising to revolutionize fields such as precision agriculture and infrastructure inspection. To fully exploit their potential, developing aut...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	474,193
2402.15662	GiMeFive: Towards Interpretable Facial Emotion Classification	Deep convolutional neural networks have been shown to successfully recognize facial emotions for the past years in the realm of computer vision. However, the existing detection approaches are not always reliable or explainable, we here propose our model GiMeFive with interpretations, i.e., via layer activations and gra...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	432,233
2403.09260	Belief and Persuasion in Scientific Discourse on Social Media: A Study of the COVID-19 Pandemic	Research into COVID-19 has been rapidly evolving since the onset of the pandemic. This occasionally results in contradictory recommendations by credible sources of scientific opinion, public health authorities, and medical professionals. In this study, we examine whether this has resulted in a lack of trust in scientif...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	437,696
2410.14627	CELI: Controller-Embedded Language Model Interactions	We introduce Controller-Embedded Language Model Interactions (CELI), a framework that integrates control logic directly within language model (LM) prompts, facilitating complex, multi-stage task execution. CELI addresses limitations of existing prompt engineering and workflow optimization techniques by embedding contro...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	true	500,111
2106.09000	Deriving Autism Spectrum Disorder Functional Networks from RS-FMRI Data using Group ICA and Dictionary Learning	The objective of this study is to derive functional networks for the autism spectrum disorder (ASD) population using the group ICA and dictionary learning model together and to classify ASD and typically developing (TD) participants using the functional connectivity calculated from the derived functional networks. In o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	241,509
2308.12969	ROAM: Robust and Object-Aware Motion Generation Using Neural Pose Descriptors	Existing automatic approaches for 3D virtual character motion synthesis supporting scene interactions do not generalise well to new objects outside training distributions, even when trained on extensive motion capture datasets with diverse objects and annotated interactions. This paper addresses this limitation and sho...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	387,741
2008.13609	Detecting Generic Music Features with Single Layer Feedforward Network using Unsupervised Hebbian Computation	With the ever-increasing number of digital music and vast music track features through popular online music streaming software and apps, feature recognition using the neural network is being used for experimentation to produce a wide range of results across a variety of experiments recently. Through this work, the auth...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	193,895
2410.14406	On the Benefits of Robot Platooning for Navigating Crowded Environments	This paper studies how groups of robots can effectively navigate through a crowd of agents. It quantifies the performance of platooning and less constrained, greedy strategies, and the extent to which these strategies disrupt the crowd agents. Three scenarios are considered: (i) passive crowds, (ii) counter-flow crowds...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	500,016
2303.17212	SARGAN: Spatial Attention-based Residuals for Facial Expression Manipulation	Encoder-decoder based architecture has been widely used in the generator of generative adversarial networks for facial manipulation. However, we observe that the current architecture fails to recover the input image color, rich facial details such as skin color or texture and introduces artifacts as well. In this paper...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	355,141
1810.02125	A Machine Learning-based Recommendation System for Swaptions Strategies	Derivative traders are usually required to scan through hundreds, even thousands of possible trades on a daily basis. Up to now, not a single solution is available to aid in their job. Hence, this work aims to develop a trading recommendation system, and apply this system to the so-called Mid-Curve Calendar Spread (MCC...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	109,538
2209.12875	Realistic Hair Synthesis with Generative Adversarial Networks	Recent successes in generative modeling have accelerated studies on this subject and attracted the attention of researchers. One of the most important methods used to achieve this success is Generative Adversarial Networks (GANs). It has many application areas such as; virtual reality (VR), augmented reality (AR), supe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	319,692
2311.11234	Enhancing Radiology Diagnosis through Convolutional Neural Networks for Computer Vision in Healthcare	The transformative power of Convolutional Neural Networks (CNNs) in radiology diagnostics is examined in this study, with a focus on interpretability, effectiveness, and ethical issues. With an altered DenseNet architecture, the CNN performs admirably in terms of particularity, sensitivity, as well as accuracy. Its sup...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	408,864
2308.07026	AdvCLIP: Downstream-agnostic Adversarial Examples in Multimodal Contrastive Learning	Multimodal contrastive learning aims to train a general-purpose feature extractor, such as CLIP, on vast amounts of raw, unlabeled paired image-text data. This can greatly benefit various complex downstream tasks, including cross-modal image-text retrieval and image classification. Despite its promising prospect, the s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	385,367
1011.5962	Edge Preserving Image Denoising in Reproducing Kernel Hilbert Spaces	The goal of this paper is the development of a novel approach for the problem of Noise Removal, based on the theory of Reproducing Kernels Hilbert Spaces (RKHS). The problem is cast as an optimization task in a RKHS, by taking advantage of the celebrated semiparametric Representer Theorem. Examples verify that in the p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	8,351
2406.14981	Human-AI collectives produce the most accurate differential diagnoses	Artificial intelligence systems, particularly large language models (LLMs), are increasingly being employed in high-stakes decisions that impact both individuals and society at large, often without adequate safeguards to ensure safety, quality, and equity. Yet LLMs hallucinate, lack common sense, and are biased - short...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	466,568
2201.02821	Classification of Hyperspectral Images by Using Spectral Data and Fully Connected Neural Network	It is observed that high classification performance is achieved for one- and two-dimensional signals by using deep learning methods. In this context, most researchers have tried to classify hyperspectral images by using deep learning methods and classification success over 90% has been achieved for these images. Deep n...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	274,663
2402.05279	Safety Filters for Black-Box Dynamical Systems by Learning Discriminating Hyperplanes	Learning-based approaches are emerging as an effective approach for safety filters for black-box dynamical systems. Existing methods have relied on certificate functions like Control Barrier Functions (CBFs) and Hamilton-Jacobi (HJ) reachability value functions. The primary motivation for our work is the recognition th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	427,797
2202.00095	Deconfounded Representation Similarity for Comparison of Neural Networks	Similarity metrics such as representational similarity analysis (RSA) and centered kernel alignment (CKA) have been used to compare layer-wise representations between neural networks. However, these metrics are confounded by the population structure of data items in the input space, leading to spuriously high similarit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	278,021
2308.12864	Auto-weighted Bayesian Physics-Informed Neural Networks and robust estimations for multitask inverse problems in pore-scale imaging of dissolution	In this article, we present a novel data assimilation strategy in pore-scale imaging and demonstrate that this makes it possible to robustly address reactive inverse problems incorporating Uncertainty Quantification (UQ). Pore-scale modeling of reactive flow offers a valuable opportunity to investigate the evolution of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	true	387,697
2310.17471	Foundation Model Based Native AI Framework in 6G with Cloud-Edge-End Collaboration	Future wireless communication networks are in a position to move beyond data-centric, device-oriented connectivity and offer intelligent, immersive experiences based on task-oriented connections, especially in the context of the thriving development of pre-trained foundation models (PFM) and the evolving vision of 6G n...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	403,149
1910.09347	Approximate Sampling using an Accelerated Metropolis-Hastings based on Bayesian Optimization and Gaussian Processes	Markov Chain Monte Carlo (MCMC) methods have a drawback when working with a target distribution or likelihood function that is computationally expensive to evaluate, specially when working with big data. This paper focuses on Metropolis-Hastings (MH) algorithm for unimodal distributions. Here, an enhanced MH algorithm ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	150,163

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