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
1912.04265	In Defense of Uniform Convergence: Generalization via derandomization with an application to interpolating predictors	We propose to study the generalization error of a learned predictor $\hat h$ in terms of that of a surrogate (potentially randomized) predictor that is coupled to $\hat h$ and designed to trade empirical risk for control of generalization error. In the case where $\hat h$ interpolates the data, it is interesting to con...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	156,806
2205.10022	Towards Consistency in Adversarial Classification	In this paper, we study the problem of consistency in the context of adversarial examples. Specifically, we tackle the following question: can surrogate losses still be used as a proxy for minimizing the $0/1$ loss in the presence of an adversary that alters the inputs at test-time? Different from the standard classifi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	297,521
2401.05409	Image-based Data Representations of Time Series: A Comparative Analysis in EEG Artifact Detection	Alternative data representations are powerful tools that augment the performance of downstream models. However, there is an abundance of such representations within the machine learning toolbox, and the field lacks a comparative understanding of the suitability of each representation method. In this paper, we propose...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	420,768
2402.15409	Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps	It is well-known that the statistical performance of Lasso can suffer significantly when the covariates of interest have strong correlations. In particular, the prediction error of Lasso becomes much worse than computationally inefficient alternatives like Best Subset Selection. Due to a large conjectured computational...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	432,129
2405.17880	Diffusion Rejection Sampling	Recent advances in powerful pre-trained diffusion models encourage the development of methods to improve the sampling performance under well-trained diffusion models. This paper introduces Diffusion Rejection Sampling (DiffRS), which uses a rejection sampling scheme that aligns the sampling transition kernels with the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	458,165
2007.12402	Fully Convolutional Networks for Continuous Sign Language Recognition	Continuous sign language recognition (SLR) is a challenging task that requires learning on both spatial and temporal dimensions of signing frame sequences. Most recent work accomplishes this by using CNN and RNN hybrid networks. However, training these networks is generally non-trivial, and most of them fail in learnin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	188,812
1907.01301	An Integrated Image Filter for Enhancing Change Detection Results	Change detection is a fundamental task in computer vision. Despite significant advances have been made, most of the change detection methods fail to work well in challenging scenes due to ubiquitous noise and interferences. Nowadays, post-processing methods (e.g. MRF, and CRF) aiming to enhance the binary change detect...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	137,286
2401.02861	Reversing the Irreversible: A Survey on Inverse Biometrics	With the widespread use of biometric recognition, several issues related to the privacy and security provided by this technology have been recently raised and analysed. As a result, the early common belief among the biometrics community of templates irreversibility has been proven wrong. It is now an accepted fact that...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	419,870
1206.0981	An Informed Model of Personal Information Release in Social Networking Sites	The emergence of online social networks and the growing popularity of digital communication has resulted in an increasingly amount of information about individuals available on the Internet. Social network users are given the freedom to create complex digital identities, and enrich them with truthful or even fake perso...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	16,328
2410.14528	Domain Adaptive Safety Filters via Deep Operator Learning	Learning-based approaches for constructing Control Barrier Functions (CBFs) are increasingly being explored for safety-critical control systems. However, these methods typically require complete retraining when applied to unseen environments, limiting their adaptability. To address this, we propose a self-supervised de...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	500,060
1811.11124	LEASGD: an Efficient and Privacy-Preserving Decentralized Algorithm for Distributed Learning	Distributed learning systems have enabled training large-scale models over large amount of data in significantly shorter time. In this paper, we focus on decentralized distributed deep learning systems and aim to achieve differential privacy with good convergence rate and low communication cost. To achieve this goal, w...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	114,687
2001.00218	Lossless Compression of Deep Neural Networks	Deep neural networks have been successful in many predictive modeling tasks, such as image and language recognition, where large neural networks are often used to obtain good accuracy. Consequently, it is challenging to deploy these networks under limited computational resources, such as in mobile devices. In this work...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	159,162
2308.12199	Towards Real-Time Analysis of Broadcast Badminton Videos	Analysis of player movements is a crucial subset of sports analysis. Existing player movement analysis methods use recorded videos after the match is over. In this work, we propose an end-to-end framework for player movement analysis for badminton matches on live broadcast match videos. We only use the visual inputs fr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	387,451
2309.03211	Improving the State of the Art for Training Human-AI Teams: Technical Report #1 -- Results of Subject-Matter Expert Knowledge Elicitation Survey	A consensus report produced for the Air Force Research Laboratory by the National Academies of Sciences, Engineering, and Mathematics documented a prevalent and increasing desire to support human-Artificial Intelligence (AI) teaming across military service branches. Sonalysts has begun an internal initiative to explore...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	390,305
1708.05978	Stochastic Primal-Dual Proximal ExtraGradient Descent for Compositely Regularized Optimization	We consider a wide range of regularized stochastic minimization problems with two regularization terms, one of which is composed with a linear function. This optimization model abstracts a number of important applications in artificial intelligence and machine learning, such as fused Lasso, fused logistic regression, a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	79,244
1902.03940	A P2P-dominant Distribution System Architecture	Peer-to-peer interactions between small-scale energy resources exploit distribution network infrastructure as an electricity carrier, but remain financially unaccountable to electric power utilities. This status-quo raises multiple challenges. First, peer-to-peer energy trading reduces the portion of electricity suppli...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	121,227
2403.19043	Illicit object detection in X-ray images using Vision Transformers	Illicit object detection is a critical task performed at various high-security locations, including airports, train stations, subways, and ports. The continuous and tedious work of examining thousands of X-ray images per hour can be mentally taxing. Thus, Deep Neural Networks (DNNs) can be used to automate the X-ray im...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	442,176
2205.07774	Gradient-based Counterfactual Explanations using Tractable Probabilistic Models	Counterfactual examples are an appealing class of post-hoc explanations for machine learning models. Given input $x$ of class $y_1$, its counterfactual is a contrastive example $x^\prime$ of another class $y_0$. Current approaches primarily solve this task by a complex optimization: define an objective function based o...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	296,707
1612.03373	A probabilistic graphical model approach in 30 m land cover mapping with multiple data sources	There is a trend to acquire high accuracy land-cover maps using multi-source classification methods, most of which are based on data fusion, especially pixel- or feature-level fusions. A probabilistic graphical model (PGM) approach is proposed in this research for 30 m resolution land-cover mapping with multi-temporal ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	65,375
1105.1733	Linear Hybrid System Falsification With Descent	In this paper, we address the problem of local search for the falsification of hybrid automata with affine dynamics. Namely, if we are given a sequence of locations and a maximum simulation time, we return the trajectory that comes the closest to the unsafe set. In order to solve this problem, we formulate it as a diff...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	10,300
2501.12216	RL-RC-DoT: A Block-level RL agent for Task-Aware Video Compression	Video encoders optimize compression for human perception by minimizing reconstruction error under bit-rate constraints. In many modern applications such as autonomous driving, an overwhelming majority of videos serve as input for AI systems performing tasks like object recognition or segmentation, rather than being wat...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	526,211
2006.00838	Efficient EUD Parsing	We present the system submission from the FASTPARSE team for the EUD Shared Task at IWPT 2020. We engaged with the task by focusing on efficiency. For this we considered training costs and inference efficiency. Our models are a combination of distilled neural dependency parsers and a rule-based system that projects UD ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	179,586
2309.03508	Dynamic Frame Interpolation in Wavelet Domain	Video frame interpolation is an important low-level vision task, which can increase frame rate for more fluent visual experience. Existing methods have achieved great success by employing advanced motion models and synthesis networks. However, the spatial redundancy when synthesizing the target frame has not been fully...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	390,403
2502.12977	Time-series attribution maps with regularized contrastive learning	Gradient-based attribution methods aim to explain decisions of deep learning models but so far lack identifiability guarantees. Here, we propose a method to generate attribution maps with identifiability guarantees by developing a regularized contrastive learning algorithm trained on time-series data plus a new attribu...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	535,142
2011.02544	Social Choice with Changing Preferences: Representation Theorems and Long-Run Policies	We study group decision making with changing preferences as a Markov Decision Process. We are motivated by the increasing prevalence of automated decision-making systems when making choices for groups of people over time. Our main contribution is to show how classic representation theorems from social choice theory can...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	204,950
2402.16994	GEM3D: GEnerative Medial Abstractions for 3D Shape Synthesis	We introduce GEM3D -- a new deep, topology-aware generative model of 3D shapes. The key ingredient of our method is a neural skeleton-based representation encoding information on both shape topology and geometry. Through a denoising diffusion probabilistic model, our method first generates skeleton-based representation...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	true	432,795
2411.16719	Learn2Synth: Learning Optimal Data Synthesis Using Hypergradients	Domain randomization through synthesis is a powerful strategy to train networks that are unbiased with respect to the domain of the input images. Randomization allows networks to see a virtually infinite range of intensities and artifacts during training, thereby minimizing overfitting to appearance and maximizing gene...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	511,133
2309.07103	Comparing Llama-2 and GPT-3 LLMs for HPC kernels generation	We evaluate the use of the open-source Llama-2 model for generating well-known, high-performance computing kernels (e.g., AXPY, GEMV, GEMM) on different parallel programming models and languages (e.g., C++: OpenMP, OpenMP Offload, OpenACC, CUDA, HIP; Fortran: OpenMP, OpenMP Offload, OpenACC; Python: numpy, Numba, pyCUD...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	391,651
2010.06045	Spectral Synthesis for Satellite-to-Satellite Translation	Earth observing satellites carrying multi-spectral sensors are widely used to monitor the physical and biological states of the atmosphere, land, and oceans. These satellites have different vantage points above the earth and different spectral imaging bands resulting in inconsistent imagery from one to another. This pr...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	200,341
1107.3099	Algorithm for Optimal Mode Scheduling in Switched Systems	This paper considers the problem of computing the schedule of modes in a switched dynamical system, that minimizes a cost functional defined on the trajectory of the system's continuous state variable. A recent approach to such optimal control problems consists of algorithms that alternate between computing the optimal...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	11,311
1904.10171	Driving Decision and Control for Autonomous Lane Change based on Deep Reinforcement Learning	We apply Deep Q-network (DQN) with the consideration of safety during the task for deciding whether to conduct the maneuver. Furthermore, we design two similar Deep Q learning frameworks with quadratic approximator for deciding how to select a comfortable gap and just follow the preceding vehicle. Finally, a polynomial...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	128,575
1605.07346	Multi-Level Analysis and Annotation of Arabic Corpora for Text-to-Sign Language MT	In this paper, we present an ongoing effort in lexical semantic analysis and annotation of Modern Standard Arabic (MSA) text, a semi automatic annotation tool concerned with the morphologic, syntactic, and semantic levels of description.	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	56,284
1707.03979	A Brief Study of In-Domain Transfer and Learning from Fewer Samples using A Few Simple Priors	Domain knowledge can often be encoded in the structure of a network, such as convolutional layers for vision, which has been shown to increase generalization and decrease sample complexity, or the number of samples required for successful learning. In this study, we ask whether sample complexity can be reduced for syst...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	76,964
2409.16728	SDCL: Students Discrepancy-Informed Correction Learning for Semi-supervised Medical Image Segmentation	Semi-supervised medical image segmentation (SSMIS) has been demonstrated the potential to mitigate the issue of limited medical labeled data. However, confirmation and cognitive biases may affect the prevalent teacher-student based SSMIS methods due to erroneous pseudo-labels. To tackle this challenge, we improve the m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	491,483
1407.1395	CB-REFIM: A Practical Coordinated Beamforming in Multicell Networks	Performance of multicell systems is inevitably limited by interference and available resources. Although intercell interference can be mitigated by Base Station (BS) Coordination, the demand on inter-BS information exchange and computational complexity grows rapidly with the number of cells, subcarriers, and users. On ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	34,422
2107.07136	Learning Mixed-Integer Linear Programs from Contextual Examples	Mixed-integer linear programs (MILPs) are widely used in artificial intelligence and operations research to model complex decision problems like scheduling and routing. Designing such programs however requires both domain and modelling expertise. In this paper, we study the problem of acquiring MILPs from contextual ex...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	246,328
2105.07426	Curiosity-driven Intuitive Physics Learning	Biological infants are naturally curious and try to comprehend their physical surroundings by interacting, in myriad multisensory ways, with different objects - primarily macroscopic solid objects - around them. Through their various interactions, they build hypotheses and predictions, and eventually learn, infer and u...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	235,430
2106.10591	Low-rank Characteristic Tensor Density Estimation Part II: Compression and Latent Density Estimation	Learning generative probabilistic models is a core problem in machine learning, which presents significant challenges due to the curse of dimensionality. This paper proposes a joint dimensionality reduction and non-parametric density estimation framework, using a novel estimator that can explicitly capture the underlyi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	242,076
2004.04265	Extremist ideology as a complex contagion: the spread of far-right radicalization in the United States between 2005-2017	Increasing levels of far-right extremist violence have generated public concern about the spread of radicalization in the United States. Previous research suggests that radicalized individuals are destabilized by various environmental (or endemic) factors, exposed to extremist ideology, and subsequently reinforced by m...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	171,825
2501.15921	CREATOR Case: PMSM and IM Electric Machine Data for Validation and Benchmarking of Simulation and Modeling Approaches	This paper describes the complete sets of data of two different machines, a PMSM and an IM, that are made available to the public for modeling and simulation validation and benchmarking. For both machines, not only the complete sets of design parameters, i.e., motor geometry, electrical parameters, material properties,...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	527,762
2502.02051	Sound Judgment: Properties of Consequential Sounds Affecting Human-Perception of Robots	Positive human-perception of robots is critical to achieving sustained use of robots in shared environments. One key factor affecting human-perception of robots are their sounds, especially the consequential sounds which robots (as machines) must produce as they operate. This paper explores qualitative responses from 1...	true	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	530,160
2412.02811	Kernel-based Koopman approximants for control: Flexible sampling, error analysis, and stability	Data-driven techniques for analysis, modeling, and control of complex dynamical systems are on the uptake. Koopman theory provides the theoretical foundation for the extremely popular kernel extended dynamic mode decomposition (kEDMD). In this work we propose a novel kEDMD scheme to approximate nonlinear control system...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	513,690
2412.19518	Dust to Tower: Coarse-to-Fine Photo-Realistic Scene Reconstruction from Sparse Uncalibrated Images	Photo-realistic scene reconstruction from sparse-view, uncalibrated images is highly required in practice. Although some successes have been made, existing methods are either Sparse-View but require accurate camera parameters (i.e., intrinsic and extrinsic), or SfM-free but need densely captured images. To combine the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	520,881
2306.00876	Quantifying Deep Learning Model Uncertainty in Conformal Prediction	Precise estimation of predictive uncertainty in deep neural networks is a critical requirement for reliable decision-making in machine learning and statistical modeling, particularly in the context of medical AI. Conformal Prediction (CP) has emerged as a promising framework for representing the model uncertainty by pr...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	370,196
2304.06788	Heterogeneous Oblique Double Random Forest	The decision tree ensembles use a single data feature at each node for splitting the data. However, splitting in this manner may fail to capture the geometric properties of the data. Thus, oblique decision trees generate the oblique hyperplane for splitting the data at each non-leaf node. Oblique decision trees capture...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	358,100
2301.08959	Successive Subspace Learning for Cardiac Disease Classification with Two-phase Deformation Fields from Cine MRI	Cardiac cine magnetic resonance imaging (MRI) has been used to characterize cardiovascular diseases (CVD), often providing a noninvasive phenotyping tool.~While recently flourished deep learning based approaches using cine MRI yield accurate characterization results, the performance is often degraded by small training ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	341,355
2106.07349	Using Integrated Gradients and Constituency Parse Trees to explain Linguistic Acceptability learnt by BERT	Linguistic Acceptability is the task of determining whether a sentence is grammatical or ungrammatical. It has applications in several use cases like Question-Answering, Natural Language Generation, Neural Machine Translation, where grammatical correctness is crucial. In this paper we aim to understand the decision-mak...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	240,888
2109.10665	A Survey on Reinforcement Learning for Recommender Systems	Recommender systems have been widely applied in different real-life scenarios to help us find useful information. In particular, Reinforcement Learning (RL) based recommender systems have become an emerging research topic in recent years, owing to the interactive nature and autonomous learning ability. Empirical result...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	256,703
2205.11126	KRNet: Towards Efficient Knowledge Replay	The knowledge replay technique has been widely used in many tasks such as continual learning and continuous domain adaptation. The key lies in how to effectively encode the knowledge extracted from previous data and replay them during current training procedure. A simple yet effective model to achieve knowledge replay ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	298,011
2111.01674	Minimizing Energy Consumption Leads to the Emergence of Gaits in Legged Robots	Legged locomotion is commonly studied and expressed as a discrete set of gait patterns, like walk, trot, gallop, which are usually treated as given and pre-programmed in legged robots for efficient locomotion at different speeds. However, fixing a set of pre-programmed gaits limits the generality of locomotion. Recent ...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	264,626
1901.06551	Synthesizing facial photometries and corresponding geometries using generative adversarial networks	Artificial data synthesis is currently a well studied topic with useful applications in data science, computer vision, graphics and many other fields. Generating realistic data is especially challenging since human perception is highly sensitive to non realistic appearance. In recent times, new levels of realism have b...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	119,024
2112.07391	TASSY -- A Text Annotation Survey System	We present a free and open-source tool for creating web-based surveys that include text annotation tasks. Existing tools offer either text annotation or survey functionality but not both. Combining the two input types is particularly relevant for investigating a reader's perception of a text which also depends on the r...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	271,466
2311.04879	LongQLoRA: Efficient and Effective Method to Extend Context Length of Large Language Models	We present LongQLoRA, an efficient and effective method to extend context length of large language models with less training resources. LongQLoRA combines the advantages of Position Interpolation, QLoRA and Shift Short Attention of LongLoRA. With a single 32GB V100 GPU, LongQLoRA can extend the context length of LLaMA2...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	406,373
1612.03316	Label Visualization and Exploration in IR	There is a renaissance in visual analytics systems for data analysis and sharing, in particular, in the current wave of big data applications. We introduce RAVE, a prototype that automates the generation of an interface that uses facets and visualization techniques for exploring and analyzing relevance assessments data...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	65,364
2501.17711	STGCN-LSTM for Olympic Medal Prediction: Dynamic Power Modeling and Causal Policy Optimization	This paper proposes a novel hybrid model, STGCN-LSTM, to forecast Olympic medal distributions by integrating the spatio-temporal relationships among countries and the long-term dependencies of national performance. The Spatial-Temporal Graph Convolution Network (STGCN) captures geographic and interactive factors-such a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	528,427
2403.06659	Zero-Shot ECG Classification with Multimodal Learning and Test-time Clinical Knowledge Enhancement	Electrocardiograms (ECGs) are non-invasive diagnostic tools crucial for detecting cardiac arrhythmic diseases in clinical practice. While ECG Self-supervised Learning (eSSL) methods show promise in representation learning from unannotated ECG data, they often overlook the clinical knowledge that can be found in reports...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	436,550
1908.08767	KLDivNet: An unsupervised neural network for multi-modality image registration	Multi-modality image registration is one of the most underlined processes in medical image analysis. Recently, convolutional neural networks (CNNs) have shown significant potential in deformable registration. However, the lack of voxel-wise ground truth challenges the training of CNNs for an accurate registration. In t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	142,645
2110.03504	Mandarin-English Code-switching Speech Recognition with Self-supervised Speech Representation Models	Code-switching (CS) is common in daily conversations where more than one language is used within a sentence. The difficulties of CS speech recognition lie in alternating languages and the lack of transcribed data. Therefore, this paper uses the recently successful self-supervised learning (SSL) methods to leverage many...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	259,525
2108.12575	Goal-driven text descriptions for images	A big part of achieving Artificial General Intelligence(AGI) is to build a machine that can see and listen like humans. Much work has focused on designing models for image classification, video classification, object detection, pose estimation, speech recognition, etc., and has achieved significant progress in recent y...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	252,536
2207.12346	Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification	Model agnostic meta-learning algorithms aim to infer priors from several observed tasks that can then be used to adapt to a new task with few examples. Given the inherent diversity of tasks arising in existing benchmarks, recent methods use separate, learnable structure, such as hierarchies or graphs, for enabling task...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	309,982
2402.08539	Intelligent Diagnosis of Alzheimer's Disease Based on Machine Learning	This study is based on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset and aims to explore early detection and disease progression in Alzheimer's disease (AD). We employ innovative data preprocessing strategies, including the use of the random forest algorithm to fill missing data and the handling of out...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	429,132
cmp-lg/9503019	SATZ - An Adaptive Sentence Segmentation System	This paper provides a detailed description of the sentence segmentation system first introduced in cmp-lg/9411022. It provides results of systematic experiments involving sentence boundary determination, including context size, lexicon size, and single-case texts. Also included are the results of successfully adapting ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,319
0906.0612	Community detection in graphs	The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices of the same cluster and c...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	3,816
1805.10274	UMDSub at SemEval-2018 Task 2: Multilingual Emoji Prediction Multi-channel Convolutional Neural Network on Subword Embedding	This paper describes the UMDSub system that participated in Task 2 of SemEval-2018. We developed a system that predicts an emoji given the raw text in a English tweet. The system is a Multi-channel Convolutional Neural Network based on subword embeddings for the representation of tweets. This model improves on characte...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	98,631
2207.04900	UM4: Unified Multilingual Multiple Teacher-Student Model for Zero-Resource Neural Machine Translation	Most translation tasks among languages belong to the zero-resource translation problem where parallel corpora are unavailable. Multilingual neural machine translation (MNMT) enables one-pass translation using shared semantic space for all languages compared to the two-pass pivot translation but often underperforms the ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	307,357
2411.15585	Boosting Semi-Supervised Scene Text Recognition via Viewing and Summarizing	Existing scene text recognition (STR) methods struggle to recognize challenging texts, especially for artistic and severely distorted characters. The limitation lies in the insufficient exploration of character morphologies, including the monotonousness of widely used synthetic training data and the sensitivity of the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	510,673
2304.10310	LA3: Efficient Label-Aware AutoAugment	Automated augmentation is an emerging and effective technique to search for data augmentation policies to improve generalizability of deep neural network training. Most existing work focuses on constructing a unified policy applicable to all data samples in a given dataset, without considering sample or class variation...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	359,369
2211.02320	Aircraft Ground Taxiing Deduction and Conflict Early Warning Method Based on Control Command Information	Aircraft taxiing conflict is a threat to the safety of airport operations, mainly due to the human error in control command infor-mation. In order to solve the problem, The aircraft taxiing deduction and conflict early warning method based on control order information is proposed. This method does not need additional e...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	328,547
2209.09448	Attributed Network Embedding Model for Exposing COVID-19 Spread Trajectory Archetypes	The spread of COVID-19 revealed that transmission risk patterns are not homogenous across different cities and communities, and various heterogeneous features can influence the spread trajectories. Hence, for predictive pandemic monitoring, it is essential to explore latent heterogeneous features in cities and communit...	false	false	false	true	false	false	true	false	false	false	false	false	false	true	false	false	false	false	318,513
2002.11193	Computing the Relative Value of Spatio-Temporal Data in Wholesale and Retail Data Marketplaces	Spatio-temporal information is used for driving a plethora of intelligent transportation, smart-city, and crowd-sensing applications. Since data is now considered a valuable production factor, data marketplaces have appeared to help individuals and enterprises bring it to market to satisfy the ever-growing demand. In s...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	165,630
2112.03053	Fast 3D registration with accurate optimisation and little learning for Learn2Reg 2021	Current approaches for deformable medical image registration often struggle to fulfill all of the following criteria: versatile applicability, small computation or training times, and the being able to estimate large deformations. Furthermore, end-to-end networks for supervised training of registration often become ove...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	270,072
2211.04591	Learning to Follow Instructions in Text-Based Games	Text-based games present a unique class of sequential decision making problem in which agents interact with a partially observable, simulated environment via actions and observations conveyed through natural language. Such observations typically include instructions that, in a reinforcement learning (RL) setting, can d...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	329,291
2412.03609	Online Physics-Informed Dynamic Mode Decomposition: Theory and Applications	Dynamic Mode Decomposition (DMD) has received increasing research attention due to its capability to analyze and model complex dynamical systems. However, it faces challenges in computational efficiency, noise sensitivity, and difficulty adhering to physical laws, which negatively affect its performance. Addressing the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	514,036
2311.05117	Unsupervised Translation Quality Estimation Exploiting Synthetic Data and Pre-trained Multilingual Encoder	Translation quality estimation (TQE) is the task of predicting translation quality without reference translations. Due to the enormous cost of creating training data for TQE, only a few translation directions can benefit from supervised training. To address this issue, unsupervised TQE methods have been studied. In thi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	406,480
2007.06278	Robotized Ultrasound Imaging of the Peripheral Arteries -- a Phantom Study	The first choice in diagnostic imaging for patients suffering from peripheral arterial disease is 2D ultrasound (US). However, for a proper imaging process, a skilled and experienced sonographer is required. Additionally, it is a highly user-dependent operation. A robotized US system that autonomously scans the periphe...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	186,963
2406.00738	Global Rewards in Restless Multi-Armed Bandits	Restless multi-armed bandits (RMAB) extend multi-armed bandits so pulling an arm impacts future states. Despite the success of RMABs, a key limiting assumption is the separability of rewards into a sum across arms. We address this deficiency by proposing restless-multi-armed bandit with global rewards (RMAB-G), a gener...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	460,002
1909.08525	Measure Contribution of Participants in Federated Learning	Federated Machine Learning (FML) creates an ecosystem for multiple parties to collaborate on building models while protecting data privacy for the participants. A measure of the contribution for each party in FML enables fair credits allocation. In this paper we develop simple but powerful techniques to fairly calculat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	145,995
2203.04199	Trustable Co-label Learning from Multiple Noisy Annotators	Supervised deep learning depends on massive accurately annotated examples, which is usually impractical in many real-world scenarios. A typical alternative is learning from multiple noisy annotators. Numerous earlier works assume that all labels are noisy, while it is usually the case that a few trusted samples with cl...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	284,380
2401.10150	Motion-Zero: Zero-Shot Moving Object Control Framework for Diffusion-Based Video Generation	Recent large-scale pre-trained diffusion models have demonstrated a powerful generative ability to produce high-quality videos from detailed text descriptions. However, exerting control over the motion of objects in videos generated by any video diffusion model is a challenging problem. In this paper, we propose a nove...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	422,504
2410.08182	MRAG-Bench: Vision-Centric Evaluation for Retrieval-Augmented Multimodal Models	Existing multimodal retrieval benchmarks primarily focus on evaluating whether models can retrieve and utilize external textual knowledge for question answering. However, there are scenarios where retrieving visual information is either more beneficial or easier to access than textual data. In this paper, we introduce ...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	496,988
2001.03690	Understanding Graph Isomorphism Network for rs-fMRI Functional Connectivity Analysis	Graph neural networks (GNN) rely on graph operations that include neural network training for various graph related tasks. Recently, several attempts have been made to apply the GNNs to functional magnetic resonance image (fMRI) data. Despite recent progresses, a common limitation is its difficulty to explain the class...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	160,034
2501.07196	Crowdsourced human-based computational approach for tagging peripheral blood smear sample images from Sickle Cell Disease patients using non-expert users	In this paper, we present a human-based computation approach for the analysis of peripheral blood smear (PBS) images images in patients with Sickle Cell Disease (SCD). We used the Mechanical Turk microtask market to crowdsource the labeling of PBS images. We then use the expert-tagged erythrocytesIDB dataset to assess ...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	524,305
2412.10469	Comparative Analysis of Mel-Frequency Cepstral Coefficients and Wavelet Based Audio Signal Processing for Emotion Detection and Mental Health Assessment in Spoken Speech	The intersection of technology and mental health has spurred innovative approaches to assessing emotional well-being, particularly through computational techniques applied to audio data analysis. This study explores the application of Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) models on wavele...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	516,952
2202.01909	Ad-datasets: a meta-collection of data sets for autonomous driving	Autonomous driving is among the largest domains in which deep learning has been fundamental for progress within the last years. The rise of datasets went hand in hand with this development. All the more striking is the fact that researchers do not have a tool available that provides a quick, comprehensive and up-to-dat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	278,634
1909.06873	A Robust Closed-Loop Biped Locomotion Planner Based on Time Varying Model Predictive Control	Developing robust locomotion for humanoid robots is a complex task due to the unstable nature of these robots and also to the unpredictability of the terrain. A robust locomotion planner is one of the fundamental components for generating stable biped locomotion. This paper presents an optimal closed-loop biped locomot...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	145,508
2209.04838	Localization with Single or Antipodal Distance Measurements	Given a polygonal workspace $W$, a depth sensor placed at point $p=(x,y)$ inside $W$ and oriented in direction $\theta$ measures the distance $d=h(x,y,\theta)$ between $p$ and the closest point on the boundary of $W$ along a ray emanating from $p$ in direction $\theta$. We study the following problem: For a polygon $W$...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	316,901
2306.00807	Auto-Spikformer: Spikformer Architecture Search	The integration of self-attention mechanisms into Spiking Neural Networks (SNNs) has garnered considerable interest in the realm of advanced deep learning, primarily due to their biological properties. Recent advancements in SNN architecture, such as Spikformer, have demonstrated promising outcomes by leveraging Spikin...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	370,169
2203.07809	Image Quality Assessment for Magnetic Resonance Imaging	Image quality assessment (IQA) algorithms aim to reproduce the human's perception of the image quality. The growing popularity of image enhancement, generation, and recovery models instigated the development of many methods to assess their performance. However, most IQA solutions are designed to predict image quality i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	285,570
1711.09584	Joint Cuts and Matching of Partitions in One Graph	As two fundamental problems, graph cuts and graph matching have been investigated over decades, resulting in vast literature in these two topics respectively. However the way of jointly applying and solving graph cuts and matching receives few attention. In this paper, we first formalize the problem of simultaneously c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	85,443
2105.03800	Fine-Grained $\epsilon$-Margin Closed-Form Stabilization of Parametric Hawkes Processes	Hawkes Processes have undergone increasing popularity as default tools for modeling self- and mutually exciting interactions of discrete events in continuous-time event streams. A Maximum Likelihood Estimation (MLE) unconstrained optimization procedure over parametrically assumed forms of the triggering kernels of the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	234,267
1612.08506	Generic and lifted probabilistic comparisons -- max replaces minmax	In this paper we introduce a collection of powerful statistical comparison results. We first present the results that we obtained while developing a general comparison concept. After that we introduce a separate lifting procedure that is a comparison concept on its own. We then show how in certain scenarios the lifting...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	66,083
2111.08062	Synthetic Unknown Class Learning for Learning Unknowns	This paper addresses the open set recognition (OSR) problem, where the goal is to correctly classify samples of known classes while detecting unknown samples to reject. In the OSR problem, "unknown" is assumed to have infinite possibilities because we have no knowledge about unknowns until they emerge. Intuitively, the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	266,553
1909.06981	Universal proofs of entropic continuity bounds via majorization flow	We introduce a notion of majorization flow, and demonstrate it to be a powerful tool for deriving simple and universal proofs of continuity bounds for entropic functions relevant in information theory. In particular, for the case of the alpha-R\'enyi entropy, whose connections to thermodynamics are discussed in this ar...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	145,554
2501.17183	LLM Evaluation Based on Aerospace Manufacturing Expertise: Automated Generation and Multi-Model Question Answering	Aerospace manufacturing demands exceptionally high precision in technical parameters. The remarkable performance of Large Language Models (LLMs), such as GPT-4 and QWen, in Natural Language Processing has sparked industry interest in their application to tasks including process design, material selection, and tool info...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	528,245
1909.00799	White-Box Evaluation of Fingerprint Matchers: Robustness to Minutiae Perturbations	Prevailing evaluations of fingerprint recognition systems have been performed as end-to-end black-box tests of fingerprint identification or authentication accuracy. However, performance of the end-to-end system is subject to errors arising in any of its constituent modules, including: fingerprint scanning, preprocessi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	143,723
1811.00728	Improving the Robustness of Speech Translation	Although neural machine translation (NMT) has achieved impressive progress recently, it is usually trained on the clean parallel data set and hence cannot work well when the input sentence is the production of the automatic speech recognition (ASR) system due to the enormous errors in the source. To solve this problem,...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	112,178
0904.0477	Message Passing for Optimization and Control of Power Grid: Model of Distribution System with Redundancy	We use a power grid model with $M$ generators and $N$ consumption units to optimize the grid and its control. Each consumer demand is drawn from a predefined finite-size-support distribution, thus simulating the instantaneous load fluctuations. Each generator has a maximum power capability. A generator is not overloade...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	3,468
2204.00127	Future-Focused Control Barrier Functions for Autonomous Vehicle Control	In this paper, we introduce a class of future-focused control barrier functions (ff-CBF) aimed at improving traditionally myopic CBF based control design and study their efficacy in the context of an unsignaled four-way intersection crossing problem for collections of both communicating and non-communicating autonomous...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	289,142
2103.10159	SPOT: A framework for selection of prototypes using optimal transport	In this work, we develop an optimal transport (OT) based framework to select informative prototypical examples that best represent a given target dataset. Summarizing a given target dataset via representative examples is an important problem in several machine learning applications where human understanding of the lear...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	225,368
2007.14660	Ergodicity of the underdamped mean-field Langevin dynamics	We study the long time behavior of an underdamped mean-field Langevin (MFL) equation, and provide a general convergence as well as an exponential convergence rate result under different conditions. The results on the MFL equation can be applied to study the convergence of the Hamiltonian gradient descent algorithm for ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	189,468

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