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
2401.08643	Exploratory Driving Performance and Car-Following Modeling for Autonomous Shuttles Based on Field Data	Autonomous shuttles (AS) operate in several cities and have shown potential to improve the public transport network. However, there is no car following model that is based on field data and allows decision-makers to assess and plan for AS operations. To fill this gap, this study collected field data from AS, analyzed t...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	421,970
2412.03283	Black-Box Forgery Attacks on Semantic Watermarks for Diffusion Models	Integrating watermarking into the generation process of latent diffusion models (LDMs) simplifies detection and attribution of generated content. Semantic watermarks, such as Tree-Rings and Gaussian Shading, represent a novel class of watermarking techniques that are easy to implement and highly robust against various ...	false	false	false	false	true	false	false	false	false	false	false	true	true	false	false	false	false	false	513,899
2112.04828	Avoiding C-hacking when evaluating survival distribution predictions with discrimination measures	In this paper we consider how to evaluate survival distribution predictions with measures of discrimination. This is a non-trivial problem as discrimination measures are the most commonly used in survival analysis and yet there is no clear method to derive a risk prediction from a distribution prediction. We survey met...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	270,657
1203.0714	Towards an intelligence based conceptual framework for e-maintenance	Since the time when concept of e-maintenance was introduced, most of the works insisted on the relevance of the underlying Information and Communication Technologies infrastructure. Through a review of current e-maintenance conceptual approaches and realizations, this paper aims to reconsider the predominance of ICT wi...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	14,712
1802.08659	Skew cyclic codes over F_{p}+uF_{p}+\dots +u^{k-1}F_{p}	In this article, we study the skew cyclic codes over R_{k}=F_{p}+uF_{p}+\dots +u^{k-1}F_{p} of length n. We characterize the skew cyclic codes of length $n$ over R_{k} as free left R_{k}[x;\theta]-submodules of R_{k}[x;\theta]/\langle x^{n}-1\rangle and construct their generators and minimal generating sets. Also, an a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	91,150
2103.02654	A Robust Adversarial Network-Based End-to-End Communications System With Strong Generalization Ability Against Adversarial Attacks	We propose a novel defensive mechanism based on a generative adversarial network (GAN) framework to defend against adversarial attacks in end-to-end communications systems. Specifically, we utilize a generative network to model a powerful adversary and enable the end-to-end communications system to combat the generativ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	223,024
2302.08427	Learning to diagnose cirrhosis from radiological and histological labels with joint self and weakly-supervised pretraining strategies	Identifying cirrhosis is key to correctly assess the health of the liver. However, the gold standard diagnosis of the cirrhosis needs a medical intervention to obtain the histological confirmation, e.g. the METAVIR score, as the radiological presentation can be equivocal. In this work, we propose to leverage transfer l...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	346,047
1412.7961	Reasoning for Improved Sensor Data Interpretation in a Smart Home	In this paper an ontological representation and reasoning paradigm has been proposed for interpretation of time-series signals. The signals come from sensors observing a smart environment. The signal chosen for the annotation process is a set of unintuitive and complex gas sensor data. The ontology of this paradigm is ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	38,870
1209.6308	Scalable Triadic Analysis of Large-Scale Graphs: Multi-Core vs. Multi- Processor vs. Multi-Threaded Shared Memory Architectures	Triadic analysis encompasses a useful set of graph mining methods that are centered on the concept of a triad, which is a subgraph of three nodes. Such methods are often applied in the social sciences as well as many other diverse fields. Triadic methods commonly operate on a triad census that counts the number of tria...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	18,804
2410.01580	Learning-Augmented Robust Algorithmic Recourse	The widespread use of machine learning models in high-stakes domains can have a major negative impact, especially on individuals who receive undesirable outcomes. Algorithmic recourse provides such individuals with suggestions of minimum-cost improvements they can make to achieve a desirable outcome in the future. Howe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	493,834
1811.07491	A Self-Adaptive Network For Multiple Sclerosis Lesion Segmentation From Multi-Contrast MRI With Various Imaging Protocols	Deep neural networks (DNN) have shown promises in the lesion segmentation of multiple sclerosis (MS) from multicontrast MRI including T1, T2, proton density (PD) and FLAIR sequences. However, one challenge in deploying such networks into clinical practice is the variability of imaging protocols, which often differ from...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	113,788
1806.06949	Full deep neural network training on a pruned weight budget	We introduce a DNN training technique that learns only a fraction of the full parameter set without incurring an accuracy penalty. To do this, our algorithm constrains the total number of weights updated during backpropagation to those with the highest total gradients. The remaining weights are not tracked, and their i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	100,798
2006.06733	IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method	We introduce a framework for designing primal methods under the decentralized optimization setting where local functions are smooth and strongly convex. Our approach consists of approximately solving a sequence of sub-problems induced by the accelerated augmented Lagrangian method, thereby providing a systematic way fo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,534
2501.11139	Community Detection for Contextual-LSBM: Theoretical Limitations of Misclassification Rate and Efficient Algorithms	The integration of network information and node attribute information has recently gained significant attention in the community detection literature. In this work, we consider community detection in the Contextual Labeled Stochastic Block Model (CLSBM), where the network follows an LSBM and node attributes follow a Ga...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	525,804
1304.7355	Web graph compression with fast access	In recent years studying the content of the World Wide Web became a very important yet rather difficult task. There is a need for a compression technique that would allow a web graph representation to be put into the memory while maintaining random access time competitive to the time needed to access uncompressed web g...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	true	24,248
2405.14195	Enhanced Object Tracking by Self-Supervised Auxiliary Depth Estimation Learning	RGB-D tracking significantly improves the accuracy of object tracking. However, its dependency on real depth inputs and the complexity involved in multi-modal fusion limit its applicability across various scenarios. The utilization of depth information in RGB-D tracking inspired us to propose a new method, named MDETra...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	456,301
2007.15258	Weakly-Supervised Cell Tracking via Backward-and-Forward Propagation	We propose a weakly-supervised cell tracking method that can train a convolutional neural network (CNN) by using only the annotation of "cell detection" (i.e., the coordinates of cell positions) without association information, in which cell positions can be easily obtained by nuclear staining. First, we train co-detec...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	189,628
2303.15647	Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning	This paper presents a systematic overview of parameter-efficient fine-tuning methods, covering over 50 papers published between early 2019 and mid-2024. These methods aim to address the challenges of fine-tuning large language models by training only a small subset of parameters. We provide a taxonomy that covers a bro...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	354,562
0711.3675	Derivations of Normalized Mutual Information in Binary Classifications	This correspondence studies the basic problem of classifications - how to evaluate different classifiers. Although the conventional performance indexes, such as accuracy, are commonly used in classifier selection or evaluation, information-based criteria, such as mutual information, are becoming popular in feature/mode...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	947
2305.02032	Unsupervised Mutual Transformer Learning for Multi-Gigapixel Whole Slide Image Classification	Classification of gigapixel Whole Slide Images (WSIs) is an important prediction task in the emerging area of computational pathology. There has been a surge of research in deep learning models for WSI classification with clinical applications such as cancer detection or prediction of molecular mutations from WSIs. Mos...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	361,885
2405.18448	Multi-objective Representation for Numbers in Clinical Narratives Using CamemBERT-bio	This research aims to classify numerical values extracted from medical documents across seven distinct physiological categories, employing CamemBERT-bio. Previous studies suggested that transformer-based models might not perform as well as traditional NLP models in such tasks. To enhance CamemBERT-bio's performances, w...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	458,434
1304.3795	An Investigation of Wavelet Packet Transform for Spectrum Estimation	In this article, we investigate the application of wavelet packet transform as a novel spectrum sensing approach. The main attraction for wavelet packets is the tradeoffs they offer in terms of satisfying various performance metrics such as frequency resolution, variance of the estimated power spectral density (PSD) an...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	23,926
2010.03142	Pre-training Multilingual Neural Machine Translation by Leveraging Alignment Information	We investigate the following question for machine translation (MT): can we develop a single universal MT model to serve as the common seed and obtain derivative and improved models on arbitrary language pairs? We propose mRASP, an approach to pre-train a universal multilingual neural machine translation model. Our key ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	199,293
2011.05767	Simulating Autonomous Driving in Massive Mixed Urban Traffic	Autonomous driving in an unregulated urban crowd is an outstanding challenge, especially, in the presence of many aggressive, high-speed traffic participants. This paper presents SUMMIT, a high-fidelity simulator that facilitates the development and testing of crowd-driving algorithms. SUMMIT simulates dense, unregulat...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	206,035
2103.11614	ast2vec: Utilizing Recursive Neural Encodings of Python Programs	Educational datamining involves the application of datamining techniques to student activity. However, in the context of computer programming, many datamining techniques can not be applied because they expect vector-shaped input whereas computer programs have the form of syntax trees. In this paper, we present ast2vec,...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	true	false	false	225,872
2003.02836	Guided Generative Adversarial Neural Network for Representation Learning and High Fidelity Audio Generation using Fewer Labelled Audio Data	Recent improvements in Generative Adversarial Neural Networks (GANs) have shown their ability to generate higher quality samples as well as to learn good representations for transfer learning. Most of the representation learning methods based on GANs learn representations ignoring their post-use scenario, which can lea...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	167,053
2312.15867	Punctuation Matters! Stealthy Backdoor Attack for Language Models	Recent studies have pointed out that natural language processing (NLP) models are vulnerable to backdoor attacks. A backdoored model produces normal outputs on the clean samples while performing improperly on the texts with triggers that the adversary injects. However, previous studies on textual backdoor attack pay li...	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	418,167
2008.03806	Neural Light Transport for Relighting and View Synthesis	The light transport (LT) of a scene describes how it appears under different lighting and viewing directions, and complete knowledge of a scene's LT enables the synthesis of novel views under arbitrary lighting. In this paper, we focus on image-based LT acquisition, primarily for human bodies within a light stage setup...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	191,036
2012.15466	CLEAR: Contrastive Learning for Sentence Representation	Pre-trained language models have proven their unique powers in capturing implicit language features. However, most pre-training approaches focus on the word-level training objective, while sentence-level objectives are rarely studied. In this paper, we propose Contrastive LEArning for sentence Representation (CLEAR), w...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	213,797
2403.16979	An Optimal Solution to Infinite Horizon Nonlinear Control Problems: Part II	This paper considers the infinite horizon optimal control problem for nonlinear systems. Under the condition of nonlinear controllability of the system to any terminal set containing the origin and forward invariance of the terminal set, we establish a regularized solution approach consisting of a ``finite free final t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	441,267
2010.11550	Learning Dual Semantic Relations with Graph Attention for Image-Text Matching	Image-Text Matching is one major task in cross-modal information processing. The main challenge is to learn the unified visual and textual representations. Previous methods that perform well on this task primarily focus on not only the alignment between region features in images and the corresponding words in sentences...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	202,307
1906.05096	eSLAM: An Energy-Efficient Accelerator for Real-Time ORB-SLAM on FPGA Platform	Simultaneous Localization and Mapping (SLAM) is a critical task for autonomous navigation. However, due to the computational complexity of SLAM algorithms, it is very difficult to achieve real-time implementation on low-power platforms.We propose an energy efficient architecture for real-time ORB (Oriented-FAST and Rot...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	134,926
2305.01319	Long-Term Rhythmic Video Soundtracker	We consider the problem of generating musical soundtracks in sync with rhythmic visual cues. Most existing works rely on pre-defined music representations, leading to the incompetence of generative flexibility and complexity. Other methods directly generating video-conditioned waveforms suffer from limited scenarios, s...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	361,640
2402.04519	BioDrone: A Bionic Drone-based Single Object Tracking Benchmark for Robust Vision	Single object tracking (SOT) is a fundamental problem in computer vision, with a wide range of applications, including autonomous driving, augmented reality, and robot navigation. The robustness of SOT faces two main challenges: tiny target and fast motion. These challenges are especially manifested in videos captured ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	427,485
2408.14514	Improving Nonlinear Projection Heads using Pretrained Autoencoder Embeddings	This empirical study aims at improving the effectiveness of the standard 2-layer MLP projection head $g(\cdot)$ featured in the SimCLR framework through the use of pretrained autoencoder embeddings. Given a contrastive learning task with a largely unlabeled image classification dataset, we first train a shallow autoenc...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	483,577
1508.03755	Beat-Event Detection in Action Movie Franchises	While important advances were recently made towards temporally localizing and recognizing specific human actions or activities in videos, efficient detection and classification of long video chunks belonging to semantically defined categories such as "pursuit" or "romance" remains challenging.We introduce a new dataset...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	46,036
2201.08622	Reproducing Personalised Session Search over the AOL Query Log	Despite its troubled past, the AOL Query Log continues to be an important resource to the research community -- particularly for tasks like search personalisation. When using the query log these ranking experiments, little attention is usually paid to the document corpus. Recent work typically uses a corpus containing ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	276,396
1605.06898	Social and Spatial Clustering of People at Humanity's Largest Gathering	Macroscopic behavior of scientific and societal systems results from the aggregation of microscopic behaviors of their constituent elements, but connecting the macroscopic with the microscopic in human behavior has traditionally been difficult. Manifestations of homophily, the notion that individuals tend to interact w...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	56,210
1704.05204	HPSLPred: An Ensemble Multi-label Classifier for Human Protein Subcellular Location Prediction with Imbalanced Source	Predicting the subcellular localization of proteins is an important and challenging problem. Traditional experimental approaches are often expensive and time-consuming. Consequently, a growing number of research efforts employ a series of machine learning approaches to predict the subcellular location of proteins. Ther...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	71,966
2007.14032	Lane-Change Initiation and Planning Approach for Highly Automated Driving on Freeways	Quantifying and encoding occupants' preferences as an objective function for the tactical decision making of autonomous vehicles is a challenging task. This paper presents a low-complexity approach for lane-change initiation and planning to facilitate highly automated driving on freeways. Conditions under which human d...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	189,290
2306.02323	LoRa Backscatter Communications: Temporal, Spectral, and Error Performance Analysis	LoRa backscatter (LB) communication systems can be considered as a potential candidate for ultra low power wide area networks (LPWAN) because of their low cost and low power consumption. In this paper, we comprehensively analyze LB modulation from various aspects, i.e., temporal, spectral, and error performance charact...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	370,855
1406.7438	Does Offline Political Segregation Affect the Filter Bubble? An Empirical Analysis of Information Diversity for Dutch and Turkish Twitter Users	From a liberal perspective, pluralism and viewpoint diversity are seen as a necessary condition for a well-functioning democracy. Recently, there have been claims that viewpoint diversity is diminishing in online social networks, putting users in a "bubble", where they receive political information which they agree wit...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	34,215
2210.14774	Unknown area exploration for robots with energy constraints using a modified Butterfly Optimization Algorithm	Butterfly Optimization Algorithm (BOA) is a recent metaheuristic that has been used in several optimization problems. In this paper, we propose a new version of the algorithm (xBOA) based on the crossover operator and compare its results to the original BOA and 3 other variants recently introduced in the literature. We...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	true	false	false	false	326,680
2310.09166	Developing a Natural Language Understanding Model to Characterize Cable News Bias	Media bias has been extensively studied by both social and computational sciences. However, current work still has a large reliance on human input and subjective assessment to label biases. This is especially true for cable news research. To address these issues, we develop an unsupervised machine learning method to ch...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	399,677
2007.00644	Measuring Robustness to Natural Distribution Shifts in Image Classification	We study how robust current ImageNet models are to distribution shifts arising from natural variations in datasets. Most research on robustness focuses on synthetic image perturbations (noise, simulated weather artifacts, adversarial examples, etc.), which leaves open how robustness on synthetic distribution shift rela...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	185,171
1902.06006	Contextual Word Representations: A Contextual Introduction	This introduction aims to tell the story of how we put words into computers. It is part of the story of the field of natural language processing (NLP), a branch of artificial intelligence. It targets a wide audience with a basic understanding of computer programming, but avoids a detailed mathematical treatment, and it...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	121,657
cs/0607086	Representing Knowledge about Norms	Norms are essential to extend inference: inferences based on norms are far richer than those based on logical implications. In the recent decades, much effort has been devoted to reason on a domain, once its norms are represented. How to extract and express those norms has received far less attention. Extraction is dif...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	539,596
2308.10411	In-Rack Test Tube Pose Estimation Using RGB-D Data	Accurate robotic manipulation of test tubes in biology and medical industries is becoming increasingly important to address workforce shortages and improve worker safety. The detection and localization of test tubes are essential for the robots to successfully manipulate test tubes. In this paper, we present a framewor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	386,715
2408.13648	Explanatory Model Monitoring to Understand the Effects of Feature Shifts on Performance	Monitoring and maintaining machine learning models are among the most critical challenges in translating recent advances in the field into real-world applications. However, current monitoring methods lack the capability of provide actionable insights answering the question of why the performance of a particular model r...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	483,228
2009.03884	Edge Selection in Bilinear Dynamical Networks	We develop some basic principles for the design and robustness analysis of a continuous-time bilinear dynamical network, where an attacker can manipulate the strength of the interconnections/edges between some of the agents/nodes. We formulate the edge protection optimization problem of picking a limited number of atta...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	194,916
2204.10461	WaBERT: A Low-resource End-to-end Model for Spoken Language Understanding and Speech-to-BERT Alignment	Historically lower-level tasks such as automatic speech recognition (ASR) and speaker identification are the main focus in the speech field. Interest has been growing in higher-level spoken language understanding (SLU) tasks recently, like sentiment analysis (SA). However, improving performances on SLU tasks remains a ...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	292,792
2304.06319	Continual Learning of Hand Gestures for Human-Robot Interaction	In this paper, we present an efficient method to incrementally learn to classify static hand gestures. This method allows users to teach a robot to recognize new symbols in an incremental manner. Contrary to other works which use special sensors or external devices such as color or data gloves, our proposed approach ma...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	357,932
2206.07840	Architectural Backdoors in Neural Networks	Machine learning is vulnerable to adversarial manipulation. Previous literature has demonstrated that at the training stage attackers can manipulate data and data sampling procedures to control model behaviour. A common attack goal is to plant backdoors i.e. force the victim model to learn to recognise a trigger known ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	302,906
2312.13503	InfoVisDial: An Informative Visual Dialogue Dataset by Bridging Large Multimodal and Language Models	In this paper, we build a visual dialogue dataset, named InfoVisDial, which provides rich informative answers in each round even with external knowledge related to the visual content. Different from existing datasets where the answer is compact and short, InfoVisDial contains long free-form answers with rich informatio...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	417,330
2405.18804	Tilde: Teleoperation for Dexterous In-Hand Manipulation Learning with a DeltaHand	Dexterous robotic manipulation remains a challenging domain due to its strict demands for precision and robustness on both hardware and software. While dexterous robotic hands have demonstrated remarkable capabilities in complex tasks, efficiently learning adaptive control policies for hands still presents a significan...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	458,606
2207.10553	MABe22: A Multi-Species Multi-Task Benchmark for Learned Representations of Behavior	We introduce MABe22, a large-scale, multi-agent video and trajectory benchmark to assess the quality of learned behavior representations. This dataset is collected from a variety of biology experiments, and includes triplets of interacting mice (4.7 million frames video+pose tracking data, 10 million frames pose only),...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	true	false	false	false	309,301
2011.13246	IFSS-Net: Interactive Few-Shot Siamese Network for Faster Muscle Segmentation and Propagation in Volumetric Ultrasound	We present an accurate, fast and efficient method for segmentation and muscle mask propagation in 3D freehand ultrasound data, towards accurate volume quantification. A deep Siamese 3D Encoder-Decoder network that captures the evolution of the muscle appearance and shape for contiguous slices is deployed. We uses it to...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	208,425
2401.15439	Pre-training and Diagnosing Knowledge Base Completion Models	In this work, we introduce and analyze an approach to knowledge transfer from one collection of facts to another without the need for entity or relation matching. The method works for both canonicalized knowledge bases and uncanonicalized or open knowledge bases, i.e., knowledge bases where more than one copy of a real...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	424,443
1804.09396	Quantitative Susceptibility Map Reconstruction Using Annihilating Filter-based Low-Rank Hankel Matrix Approach	Quantitative susceptibility mapping (QSM) inevitably suffers from streaking artifacts caused by zeros on the conical surface of the dipole kernel in k-space. This work proposes a novel and accurate QSM reconstruction method based on a direct k-space interpolation approach, avoiding problems of over smoothing and streak...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	95,963
1604.03193	Application of the Second-Order Statistics for Estimation of the Pure Spectra of Individual Components from the Visible Hyperspectral Images of Their Mixture	The second-order statistics (SOS) can be applied in estimation of the pure spectra of chemical components from the spectrum of their mixture, when SOS seems to be good at estimation of spectral patterns, but their peak directions are opposite in some cases. In this paper, one method for judgment of the peak direction o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	54,449
2106.06095	Sparse Bayesian Learning via Stepwise Regression	Sparse Bayesian Learning (SBL) is a powerful framework for attaining sparsity in probabilistic models. Herein, we propose a coordinate ascent algorithm for SBL termed Relevance Matching Pursuit (RMP) and show that, as its noise variance parameter goes to zero, RMP exhibits a surprising connection to Stepwise Regression...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	240,354
2404.17044	A new Taxonomy for Automated Driving: Structuring Applications based on their Operational Design Domain, Level of Automation and Automation Readiness	The aim of this paper is to investigate the relationship between operational design domains (ODD), automated driving SAE Levels, and Technology Readiness Level (TRL). The first highly automated vehicles, like robotaxis, are in commercial use, and the first vehicles with highway pilot systems have been delivered to priv...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	449,714
2301.09033	Continuous-Time Ultra-Wideband-Inertial Fusion	We introduce a novel framework of continuous-time ultra-wideband-inertial sensor fusion for online motion estimation. Quaternion-based cubic cumulative B-splines are exploited for parameterizing motion states continuously over time. Systematic derivations of analytic kinematic interpolations and spatial differentiation...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	341,381
1603.06265	Collaborative prediction with expert advice	Many practical learning systems aggregate data across many users, while learning theory traditionally considers a single learner who trusts all of their observations. A case in point is the foundational learning problem of prediction with expert advice. To date, there has been no theoretical study of the general collab...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	53,470
2407.07275	Remastering Divide and Remaster: A Cinematic Audio Source Separation Dataset with Multilingual Support	Cinematic audio source separation (CASS), as a problem of extracting the dialogue, music, and effects stems from their mixture, is a relatively new subtask of audio source separation. To date, only one publicly available dataset exists for CASS, that is, the Divide and Remaster (DnR) dataset, which is currently at vers...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	471,689
1409.0494	Distortion Exponent in MIMO Fading Channels with Time-Varying Source Side Information	Transmission of a Gaussian source over a time-varying multiple-input multiple-output (MIMO) channel is studied under strict delay constraints. Availability of a correlated side information at the receiver is assumed, whose quality, i.e., correlation with the source signal, also varies over time. A block-fading model is...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	35,735
2206.03271	On the Effectiveness of Fine-tuning Versus Meta-reinforcement Learning	Intelligent agents should have the ability to leverage knowledge from previously learned tasks in order to learn new ones quickly and efficiently. Meta-learning approaches have emerged as a popular solution to achieve this. However, meta-reinforcement learning (meta-RL) algorithms have thus far been restricted to simpl...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	301,210
2310.00288	Parallel in-memory wireless computing	Parallel wireless digital communication with ultralow power consumption is critical for emerging edge technologies such as 5G and Internet of Things. However, the physical separation between digital computing units and analogue transmission units in traditional wireless technology leads to high power consumption. Here ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	395,913
2210.07617	Quantifying Quality of Class-Conditional Generative Models in Time-Series Domain	Generative models are designed to address the data scarcity problem. Even with the exploding amount of data, due to computational advancements, some applications (e.g., health care, weather forecast, fault detection) still suffer from data insufficiency, especially in the time-series domain. Thus generative models are ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	323,798
2107.04197	REX: Revisiting Budgeted Training with an Improved Schedule	Deep learning practitioners often operate on a computational and monetary budget. Thus, it is critical to design optimization algorithms that perform well under any budget. The linear learning rate schedule is considered the best budget-aware schedule, as it outperforms most other schedules in the low budget regime. On...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	245,379
2404.14567	WangLab at MEDIQA-M3G 2024: Multimodal Medical Answer Generation using Large Language Models	This paper outlines our submission to the MEDIQA2024 Multilingual and Multimodal Medical Answer Generation (M3G) shared task. We report results for two standalone solutions under the English category of the task, the first involving two consecutive API calls to the Claude 3 Opus API and the second involving training an...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	448,726
2106.13503	Data-based Design of Inferential Sensors for Petrochemical Industry	Inferential (or soft) sensors are used in industry to infer the values of imprecisely and rarely measured (or completely unmeasured) variables from variables measured online (e.g., pressures, temperatures). The main challenge, akin to classical model overfitting, in designing an effective inferential sensor is the sele...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	243,096
1710.09012	An Energy-Efficient Mixed-Signal Neuron for Inherently Error-Resilient Neuromorphic Systems	This work presents the design and analysis of a mixed-signal neuron (MS-N) for convolutional neural networks (CNN) and compares its performance with a digital neuron (Dig-N) in terms of operating frequency, power and noise. The circuit-level implementation of the MS-N in 65 nm CMOS technology exhibits 2-3 orders of mag...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	83,152
1103.3866	Multibeam Satellite Frequency/Time Duality Study and Capacity Optimization	In this paper, we investigate two new candidate transmission schemes, Non-Orthogonal Frequency Reuse (NOFR) and Beam-Hoping (BH). They operate in different domains (frequency and time/space, respectively), and we want to know which domain shows overall best performance. We propose a novel formulation of the Signal-to-I...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	9,684
2410.00728	Simplified priors for Object-Centric Learning	Humans excel at abstracting data and constructing \emph{reusable} concepts, a capability lacking in current continual learning systems. The field of object-centric learning addresses this by developing abstract representations, or slots, from data without human supervision. Different methods have been proposed to tackl...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	493,483
2104.08043	Data Generating Process to Evaluate Causal Discovery Techniques for Time Series Data	Going beyond correlations, the understanding and identification of causal relationships in observational time series, an important subfield of Causal Discovery, poses a major challenge. The lack of access to a well-defined ground truth for real-world data creates the need to rely on synthetic data for the evaluation of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	230,643
2301.10602	DreamWaQ: Learning Robust Quadrupedal Locomotion With Implicit Terrain Imagination via Deep Reinforcement Learning	Quadrupedal robots resemble the physical ability of legged animals to walk through unstructured terrains. However, designing a controller for quadrupedal robots poses a significant challenge due to their functional complexity and requires adaptation to various terrains. Recently, deep reinforcement learning, inspired b...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	341,857
1903.02541	Relational Pooling for Graph Representations	This work generalizes graph neural networks (GNNs) beyond those based on the Weisfeiler-Lehman (WL) algorithm, graph Laplacians, and diffusions. Our approach, denoted Relational Pooling (RP), draws from the theory of finite partial exchangeability to provide a framework with maximal representation power for graphs. RP ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	123,520
2407.19890	Quantum Dynamics of Machine Learning	The quantum dynamic equation (QDE) of machine learning is obtained based on Schr\"odinger equation and potential energy equivalence relationship. Through Wick rotation, the relationship between quantum dynamics and thermodynamics is also established in this paper. This equation reformulates the iterative process of mac...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	476,971
1911.08532	Optimal Robust Learning of Discrete Distributions from Batches	Many applications, including natural language processing, sensor networks, collaborative filtering, and federated learning, call for estimating discrete distributions from data collected in batches, some of which may be untrustworthy, erroneous, faulty, or even adversarial. Previous estimators for this setting ran in...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	154,209
2206.14202	Building Matters: Spatial Variability in Machine Learning Based Thermal Comfort Prediction in Winters	Thermal comfort in indoor environments has an enormous impact on the health, well-being, and performance of occupants. Given the focus on energy efficiency and Internet-of-Things enabled smart buildings, machine learning (ML) is being increasingly used for data-driven thermal comfort (TC) prediction. Generally, ML-base...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	305,210
2405.16662	Conjunctive categorial grammars and Lambek grammars with additives	A new family of categorial grammars is proposed, defined by enriching basic categorial grammars with a conjunction operation. It is proved that the formalism obtained in this way has the same expressive power as conjunctive grammars, that is, context-free grammars enhanced with conjunction. It is also shown that catego...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	457,540
1902.01429	A Spiking Neural Network with Local Learning Rules Derived From Nonnegative Similarity Matching	The design and analysis of spiking neural network algorithms will be accelerated by the advent of new theoretical approaches. In an attempt at such approach, we provide a principled derivation of a spiking algorithm for unsupervised learning, starting from the nonnegative similarity matching cost function. The resultin...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	120,650
2305.05294	Construction of Control Barrier Functions Using Predictions with Finite Horizon	In this paper, we show that under mild controllability assumptions a time-invariant Control Barrier Function (CBF) can be constructed based on predictions with a finite horizon. As a starting point, we require only a known subset of a control-invariant set where the latter set does not need to be explicitly known. We s...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	363,088
1204.5046	Instantaneous Relaying: Optimal Strategies and Interference Neutralization	In a multi-user wireless network equipped with multiple relay nodes, some relays are more intelligent than other relay nodes. The intelligent relays are able to gather channel state information, perform linear processing and forward signals whereas the dumb relays is only able to serve as amplifiers. As the dumb relays...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	15,630
2012.05586	Full Matching on Low Resolution for Disparity Estimation	A Multistage Full Matching disparity estimation scheme (MFM) is proposed in this work. We demonstrate that decouple all similarity scores directly from the low-resolution 4D volume step by step instead of estimating low-resolution 3D cost volume through focusing on optimizing the low-resolution 4D volume iteratively le...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	210,832
1904.07079	The Native AQM for L4S Traffic	This memo focuses solely on the native AQM of Low Latency Low Loss Scalable throughput (L4S) traffic and proposes various improvements to the original step design. One motivation for DCTCP to use simple step marking was that it was possible to deploy it by merely configuring the RED implementations in existing hardware...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	127,702
2206.12923	Video Activity Localisation with Uncertainties in Temporal Boundary	Current methods for video activity localisation over time assume implicitly that activity temporal boundaries labelled for model training are determined and precise. However, in unscripted natural videos, different activities mostly transit smoothly, so that it is intrinsically ambiguous to determine in labelling preci...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	304,779
2407.16095	Robotically adjustable kinematics in a wrist-driven orthosis eases grasping across tasks	Without finger function, people with C5-7 spinal cord injury (SCI) regularly utilize wrist extension to passively close the fingers and thumb together for grasping. Wearable assistive grasping devices often focus on this familiar wrist-driven technique to provide additional support and amplify grasp force. Despite rece...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	475,451
1502.04539	Hybrid Centralized-Distributed Resource Allocation for Device-to-Device Communication Underlaying Cellular Networks	The basic idea of device-to-device (D2D) communication is that pairs of suitably selected wireless devices reuse the cellular spectrum to establish direct communication links, provided that the adverse effects of D2D communication on cellular users is minimized and cellular users are given a higher priority in using li...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	40,279
2402.15134	Deep Coupling Network For Multivariate Time Series Forecasting	Multivariate time series (MTS) forecasting is crucial in many real-world applications. To achieve accurate MTS forecasting, it is essential to simultaneously consider both intra- and inter-series relationships among time series data. However, previous work has typically modeled intra- and inter-series relationships sep...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	432,004
2403.00411	Cross-Lingual Learning vs. Low-Resource Fine-Tuning: A Case Study with Fact-Checking in Turkish	The rapid spread of misinformation through social media platforms has raised concerns regarding its impact on public opinion. While misinformation is prevalent in other languages, the majority of research in this field has concentrated on the English language. Hence, there is a scarcity of datasets for other languages,...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	433,969
2403.00228	DISORF: A Distributed Online 3D Reconstruction Framework for Mobile Robots	We present a framework, DISORF, to enable online 3D reconstruction and visualization of scenes captured by resource-constrained mobile robots and edge devices. To address the limited computing capabilities of edge devices and potentially limited network availability, we design a framework that efficiently distributes c...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	433,902
1904.01400	Vehicle Re-identification in Aerial Imagery: Dataset and Approach	In this work, we construct a large-scale dataset for vehicle re-identification (ReID), which contains 137k images of 13k vehicle instances captured by UAV-mounted cameras. To our knowledge, it is the largest UAV-based vehicle ReID dataset. To increase intra-class variation, each vehicle is captured by at least two UAVs...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	126,134
2401.02265	Breeding protocols are advantageous for finite-length entanglement distillation	Bennett et al. proposed a family of protocols for entanglement distillation, namely, hashing, recurrence and breeding protocols. The last one is inferior to the hashing protocol in the asymptotic regime and has been investigated little. In this paper, we propose a framework of converting a stabilizer quantum error-corr...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	419,654
2412.04577	Data-Driven, Parameterized Reduced-order Models for Predicting Distortion in Metal 3D Printing	In Laser Powder Bed Fusion (LPBF), the applied laser energy produces high thermal gradients that lead to unacceptable final part distortion. Accurate distortion prediction is essential for optimizing the 3D printing process and manufacturing a part that meets geometric accuracy requirements. This study introduces data-...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	514,470
2205.02490	FastRE: Towards Fast Relation Extraction with Convolutional Encoder and Improved Cascade Binary Tagging Framework	Recent work for extracting relations from texts has achieved excellent performance. However, most existing methods pay less attention to the efficiency, making it still challenging to quickly extract relations from massive or streaming text data in realistic scenarios. The main efficiency bottleneck is that these metho...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	294,961
1702.08042	Instant restore after a media failure	Media failures usually leave database systems unavailable for several hours until recovery is complete, especially in applications with large devices and high transaction volume. Previous work introduced a technique called single-pass restore, which increases restore bandwidth and thus substantially decreases time to r...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	68,901
2303.01818	Word-As-Image for Semantic Typography	A word-as-image is a semantic typography technique where a word illustration presents a visualization of the meaning of the word, while also preserving its readability. We present a method to create word-as-image illustrations automatically. This task is highly challenging as it requires semantic understanding of the w...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	349,123
2308.00727	Adaptive Semantic Consistency for Cross-domain Few-shot Classification	Cross-domain few-shot classification (CD-FSC) aims to identify novel target classes with a few samples, assuming that there exists a domain shift between source and target domains. Existing state-of-the-art practices typically pre-train on source domain and then finetune on the few-shot target data to yield task-adapti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	383,034

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