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
1912.03036	Improved PAC-Bayesian Bounds for Linear Regression	In this paper, we improve the PAC-Bayesian error bound for linear regression derived in Germain et al. [10]. The improvements are twofold. First, the proposed error bound is tighter, and converges to the generalization loss with a well-chosen temperature parameter. Second, the error bound also holds for training data t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	156,501
2410.22908	Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents	In this paper, we present the Federated Upper Confidence Bound Value Iteration algorithm ($\texttt{Fed-UCBVI}$), a novel extension of the $\texttt{UCBVI}$ algorithm (Azar et al., 2017) tailored for the federated learning framework. We prove that the regret of $\texttt{Fed-UCBVI}$ scales as $\tilde{\mathcal{O}}(\sqrt{H^...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	503,821
1612.09296	Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization	We propose a general theory for studying the \xl{landscape} of nonconvex \xl{optimization} with underlying symmetric structures \tz{for a class of machine learning problems (e.g., low-rank matrix factorization, phase retrieval, and deep linear neural networks)}. In specific, we characterize the locations of stationary ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	66,175
1503.00082	Group Event Detection with a Varying Number of Group Members for Video Surveillance	This paper presents a novel approach for automatic recognition of group activities for video surveillance applications. We propose to use a group representative to handle the recognition with a varying number of group members, and use an Asynchronous Hidden Markov Model (AHMM) to model the relationship between people. ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	40,661
2312.01087	Prompted Zero-Shot Multi-label Classification of Factual Incorrectness in Machine-Generated Summaries	This study addresses the critical issue of factual inaccuracies in machine-generated text summaries, an increasingly prevalent issue in information dissemination. Recognizing the potential of such errors to compromise information reliability, we investigate the nature of factual inconsistencies across machine-summarize...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	412,306
2212.01462	Topic Modeling on Clinical Social Work Notes for Exploring Social Determinants of Health Factors	Most research studying social determinants of health (SDoH) has focused on physician notes or structured elements of the electronic medical record (EMR). We hypothesize that clinical notes from social workers, whose role is to ameliorate social and economic factors, might provide a richer source of data on SDoH. We sou...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	334,441
2106.01870	Maximizing Extractable Value from Automated Market Makers	Automated Market Makers (AMMs) are decentralized applications that allow users to exchange crypto-tokens without the need for a matching exchange order. AMMs are one of the most successful DeFi use cases: indeed, major AMM platforms process a daily volume of transactions worth USD billions. Despite their popularity, AM...	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	true	238,650
2112.01688	Machine Learning Subsystem for Autonomous Collision Avoidance on a small UAS with Embedded GPU	Interest in unmanned aerial system (UAS) powered solutions for 6G communication networks has grown immensely with the widespread availability of machine learning based autonomy modules and embedded graphical processing units (GPUs). While these technologies have revolutionized the possibilities of UAS solutions, design...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	269,573
2411.08699	FedSub: Introducing class-aware Subnetworks Fusion to Enhance Personalized Federated Learning in Ubiquitous Systems	Personalized Federated Learning is essential in AI-driven ubiquitous systems, supporting the distributed development of models able to adapt to diverse and evolving user behaviors while safeguarding privacy. Despite addressing heterogeneous user data distributions in collaborative model training, existing methods often...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	507,981
2302.02005	DeepAstroUDA: Semi-Supervised Universal Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection	Artificial intelligence methods show great promise in increasing the quality and speed of work with large astronomical datasets, but the high complexity of these methods leads to the extraction of dataset-specific, non-robust features. Therefore, such methods do not generalize well across multiple datasets. We present ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	343,813
2212.09314	Bounds on Mixed Codes with Finite Alphabets	Mixed codes, which are error-correcting codes in the Cartesian product of different-sized spaces, model degrading storage systems well. While such codes have previously been studied for their algebraic properties (e.g., existence of perfect codes) or in the case of unbounded alphabet sizes, we focus on the case of fini...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	337,074
2312.16154	Clustered Orienteering Problem with Subgroups	This paper introduces an extension to the Orienteering Problem (OP), called Clustered Orienteering Problem with Subgroups (COPS). In this variant, nodes are arranged into subgroups, and the subgroups are organized into clusters. A reward is associated with each subgroup and is gained only if all of its nodes are visite...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	418,282
1402.6366	LSSVM-ABC Algorithm for Stock Price prediction	In this paper, Artificial Bee Colony (ABC) algorithm which inspired from the behavior of honey bees swarm is presented. ABC is a stochastic population-based evolutionary algorithm for problem solving. ABC algorithm, which is considered one of the most recently swarm intelligent techniques, is proposed to optimize least...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	31,169
1909.02712	Decentralized Stochastic Gradient Tracking for Non-convex Empirical Risk Minimization	This paper studies a decentralized stochastic gradient tracking (DSGT) algorithm for non-convex empirical risk minimization problems over a peer-to-peer network of nodes, which is in sharp contrast to the existing DSGT only for convex problems. To ensure exact convergence and handle the variance among decentralized dat...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	true	false	false	true	144,264
1904.08310	LegenDary 2012 Soccer 2D Simulation Team Description Paper	In LegenDary project, we started a new research based on Agent2D in RoboCup 2D soccer simulation. In this paper, we mainly present the team algorithms and structures which we used to develop our team in separated section. We have focused on passing, dribbling and blocking skills. We improved them and made the team read...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	128,026
2206.13188	Self-supervised Learning in Remote Sensing: A Review	In deep learning research, self-supervised learning (SSL) has received great attention triggering interest within both the computer vision and remote sensing communities. While there has been a big success in computer vision, most of the potential of SSL in the domain of earth observation remains locked. In this paper,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	304,872
1801.01663	Energy Efficiency Analysis of Heterogeneous Cellular Networks With Extra Cell Range Expansion	The split control and user plane is key to the future heterogeneous cellular network (HCN), where the small cells are dedicated for the most data transmission while the macrocells are mainly responsible for the control signaling. Adapting to this technology, we propose a general and tractable framework of extra cell ra...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	87,775
0802.1412	Extreme Learning Machine for land cover classification	This paper explores the potential of extreme learning machine based supervised classification algorithm for land cover classification. In comparison to a backpropagation neural network, which requires setting of several user-defined parameters and may produce local minima, extreme learning machine require setting of on...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	1,275
2202.02389	The impact of feature importance methods on the interpretation of defect classifiers	Classifier specific (CS) and classifier agnostic (CA) feature importance methods are widely used (often interchangeably) by prior studies to derive feature importance ranks from a defect classifier. However, different feature importance methods are likely to compute different feature importance ranks even for the same ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	278,781
2010.01999	A Novel Actor Dual-Critic Model for Remote Sensing Image Captioning	We deal with the problem of generating textual captions from optical remote sensing (RS) images using the notion of deep reinforcement learning. Due to the high inter-class similarity in reference sentences describing remote sensing data, jointly encoding the sentences and images encourages prediction of captions that ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	198,872
1802.07091	An Efficient Semismooth Newton Based Algorithm for Convex Clustering	Clustering may be the most fundamental problem in unsupervised learning which is still active in machine learning research because its importance in many applications. Popular methods like K-means, may suffer from instability as they are prone to get stuck in its local minima. Recently, the sum-of-norms (SON) model (al...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	90,828
1904.11611	Control from Signal Temporal Logic Specifications with Smooth Cumulative Quantitative Semantics	We present a framework to synthesize control policies for nonlinear dynamical systems from complex temporal constraints specified in a rich temporal logic called Signal Temporal Logic (STL). We propose a novel smooth and differentiable STL quantitative semantics called cumulative robustness, and efficiently compute con...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	128,900
2309.14991	Robust Sequential DeepFake Detection	Since photorealistic faces can be readily generated by facial manipulation technologies nowadays, potential malicious abuse of these technologies has drawn great concerns. Numerous deepfake detection methods are thus proposed. However, existing methods only focus on detecting one-step facial manipulation. As the emerge...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	394,810
2111.11439	Image prediction of disease progression by style-based manifold extrapolation	Disease-modifying management aims to prevent deterioration and progression of the disease, not just relieve symptoms. Unfortunately, the development of necessary therapies is often hampered by the failure to recognize the presymptomatic disease and limited understanding of disease development. We present a generic solu...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	267,671
1912.00811	Application of information gap decision theory in practical energy problems: A comprehensive review	The uncertainty quantification and risk modeling are hot topics in the operation and planning of energy systems. The system operators and planners are decision-makers that need to handle the uncertainty of input data of their models. As an example, energy consumption has always been a critical problem for operators sin...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	155,896
2004.10270	Learnings from Technological Interventions in a Low Resource Language: A Case-Study on Gondi	The primary obstacle to developing technologies for low-resource languages is the lack of usable data. In this paper, we report the adoption and deployment of 4 technology-driven methods of data collection for Gondi, a low-resource vulnerable language spoken by around 2.3 million tribal people in south and central Indi...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	173,588
1010.4293	Generalized Erdos Numbers	We propose a simple real-valued generalization of the well known integer-valued Erdos number as a topological, non-metric measure of the `closeness' felt between two nodes in an undirected, weighted graph. These real-valued Erdos numbers are asymmetric and are able to distinguish between network topologies that standar...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	7,968
1907.03063	MRI Super-Resolution with Ensemble Learning and Complementary Priors	Magnetic resonance imaging (MRI) is a widely used medical imaging modality. However, due to the limitations in hardware, scan time, and throughput, it is often clinically challenging to obtain high-quality MR images. The super-resolution approach is potentially promising to improve MR image quality without any hardware...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	137,754
2304.00170	Fixation probability in evolutionary dynamics on switching temporal networks	Population structure has been known to substantially affect evolutionary dynamics. Networks that promote the spreading of fitter mutants are called amplifiers of natural selection, and those that suppress the spreading of fitter mutants are called suppressors. Research in the past two decades has found various families...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	355,578
2405.02984	E-TSL: A Continuous Educational Turkish Sign Language Dataset with Baseline Methods	This study introduces the continuous Educational Turkish Sign Language (E-TSL) dataset, collected from online Turkish language lessons for 5th, 6th, and 8th grades. The dataset comprises 1,410 videos totaling nearly 24 hours and includes performances from 11 signers. Turkish, an agglutinative language, poses unique cha...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	452,006
2112.11209	Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations	Intelligent Tutoring Systems have become critically important in future learning environments. Knowledge Tracing (KT) is a crucial part of that system. It is about inferring the skill mastery of students and predicting their performance to adjust the curriculum accordingly. Deep Learning-based KT models have shown sign...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	272,637
2210.14962	Identifying Diversity, Equity, Inclusion, and Accessibility (DEIA) Indicators for Transportation Systems using Social Media Data: The Case of New York City during Covid-19 Pandemic	The adoption of transportation policies that prioritized highway expansion over public transportation has disproportionately impacted minorities and low-income people by restricting their access to social and economic opportunities and thus resulting in residential segregation. Policymakers, transportation researchers,...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	326,744
2102.08661	A Large-Scale Study of the Twitter Follower Network to Characterize the Spread of Prescription Drug Abuse Tweets	In this article, we perform a large-scale study of the Twitter follower network, involving around 0.42 million users who justify DA, to characterize the spreading of DA tweets across the network. Our observations reveal the existence of a very large giant component involving 99% of these users with dense local connecti...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	220,537
2307.10810	On Combining Expert Demonstrations in Imitation Learning via Optimal Transport	Imitation learning (IL) seeks to teach agents specific tasks through expert demonstrations. One of the key approaches to IL is to define a distance between agent and expert and to find an agent policy that minimizes that distance. Optimal transport methods have been widely used in imitation learning as they provide way...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	380,697
2402.18817	Gradient Alignment for Cross-Domain Face Anti-Spoofing	Recent advancements in domain generalization (DG) for face anti-spoofing (FAS) have garnered considerable attention. Traditional methods have focused on designing learning objectives and additional modules to isolate domain-specific features while retaining domain-invariant characteristics in their representations. How...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	433,573
2408.06336	Moo-ving Beyond Tradition: Revolutionizing Cattle Behavioural Phenotyping with Pose Estimation Techniques	The cattle industry has been a major contributor to the economy of many countries, including the US and Canada. The integration of Artificial Intelligence (AI) has revolutionized this sector, mirroring its transformative impact across all industries by enabling scalable and automated monitoring and intervention practic...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	480,166
1804.00566	The Effectiveness of Classification on Information Retrieval System (Case Study)	Large amount of unstructured designed information is difficult to deal with. Obtaining specific information is a hard mission and takes a lot of time. Information Retrieval System (IR) is a way to solve this kind of problem. IR is a good mechanism but does not give the perfect solution. Other techniques have been added...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	94,069
2012.15183	Temporally-Transferable Perturbations: Efficient, One-Shot Adversarial Attacks for Online Visual Object Trackers	In recent years, the trackers based on Siamese networks have emerged as highly effective and efficient for visual object tracking (VOT). While these methods were shown to be vulnerable to adversarial attacks, as most deep networks for visual recognition tasks, the existing attacks for VOT trackers all require perturbin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	213,717
2408.10292	Leveraging Superfluous Information in Contrastive Representation Learning	Contrastive representation learning, which aims to learnthe shared information between different views of unlabeled data by maximizing the mutual information between them, has shown its powerful competence in self-supervised learning for downstream tasks. However, recent works have demonstrated that more estimated mutu...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	481,805
2105.01305	Large-scale Taxonomy Induction Using Entity and Word Embeddings	Taxonomies are an important ingredient of knowledge organization, and serve as a backbone for more sophisticated knowledge representations in intelligent systems, such as formal ontologies. However, building taxonomies manually is a costly endeavor, and hence, automatic methods for taxonomy induction are a good alterna...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	233,490
1404.5756	A Revised Scheme to Compute Horizontal Covariances in an Oceanographic 3D-VAR Assimilation System	We propose an improvement of an oceanographic three dimensional variational assimilation scheme (3D-VAR), named OceanVar, by introducing a recursive filter (RF) with the third order of accuracy (3rd-RF), instead of a RF with first order of accuracy (1st-RF), to approximate horizontal Gaussian covariances. An advantage ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	32,531
1706.03725	Transferring a Semantic Representation for Person Re-Identification and Search	Learning semantic attributes for person re-identification and description-based person search has gained increasing interest due to attributes' great potential as a pose and view-invariant representation. However, existing attribute-centric approaches have thus far underperformed state-of-the-art conventional approache...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	75,214
2403.07289	Rediscovering BCE Loss for Uniform Classification	This paper introduces the concept of uniform classification, which employs a unified threshold to classify all samples rather than adaptive threshold classifying each individual sample. We also propose the uniform classification accuracy as a metric to measure the model's performance in uniform classification. Furtherm...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	436,817
2202.07894	Knowledge Transfer from Large-scale Pretrained Language Models to End-to-end Speech Recognizers	End-to-end speech recognition is a promising technology for enabling compact automatic speech recognition (ASR) systems since it can unify the acoustic and language model into a single neural network. However, as a drawback, training of end-to-end speech recognizers always requires transcribed utterances. Since end-to-...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	280,697
1609.05396	A Deep Metric for Multimodal Registration	Multimodal registration is a challenging problem in medical imaging due the high variability of tissue appearance under different imaging modalities. The crucial component here is the choice of the right similarity measure. We make a step towards a general learning-based solution that can be adapted to specific situati...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	61,137
1506.05274	Partial Functional Correspondence	In this paper, we propose a method for computing partial functional correspondence between non-rigid shapes. We use perturbation analysis to show how removal of shape parts changes the Laplace-Beltrami eigenfunctions, and exploit it as a prior on the spectral representation of the correspondence. Corresponding parts ar...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	44,284
2210.11946	RT-MOT: Confidence-Aware Real-Time Scheduling Framework for Multi-Object Tracking Tasks	Different from existing MOT (Multi-Object Tracking) techniques that usually aim at improving tracking accuracy and average FPS, real-time systems such as autonomous vehicles necessitate new requirements of MOT under limited computing resources: (R1) guarantee of timely execution and (R2) high tracking accuracy. In this...	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	325,519
1505.03085	Indonesian Social Media Sentiment Analysis With Sarcasm Detection	Sarcasm is considered one of the most difficult problem in sentiment analysis. In our ob-servation on Indonesian social media, for cer-tain topics, people tend to criticize something using sarcasm. Here, we proposed two additional features to detect sarcasm after a common sentiment analysis is conducted. The features a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	43,040
1711.01506	Towards Automatic 3D Shape Instantiation for Deployed Stent Grafts: 2D Multiple-class and Class-imbalance Marker Segmentation with Equally-weighted Focal U-Net	Robot-assisted Fenestrated Endovascular Aortic Repair (FEVAR) is currently navigated by 2D fluoroscopy which is insufficiently informative. Previously, a semi-automatic 3D shape instantiation method was developed to instantiate the 3D shape of a main, deployed, and fenestrated stent graft from a single fluoroscopy proj...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	83,900
2204.09098	PICT@DravidianLangTech-ACL2022: Neural Machine Translation On Dravidian Languages	This paper presents a summary of the findings that we obtained based on the shared task on machine translation of Dravidian languages. We stood first in three of the five sub-tasks which were assigned to us for the main shared task. We carried out neural machine translation for the following five language pairs: Kannad...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	292,315
2412.00999	A Compact Hybrid Battery Thermal Management System for Enhanced Cooling	Hybrid battery thermal management systems (HBTMS) combining active liquid cooling and passive phase change materials (PCM) cooling have shown a potential for the thermal management of lithium-ion batteries. However, the fill volume of coolant and PCM in hybrid cooling systems is limited by the size and weight of the HB...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	512,899
2203.01587	Multi-Tailed Vision Transformer for Efficient Inference	Recently, Vision Transformer (ViT) has achieved promising performance in image recognition and gradually serves as a powerful backbone in various vision tasks. To satisfy the sequential input of Transformer, the tail of ViT first splits each image into a sequence of visual tokens with a fixed length. Then the following...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	283,437
1910.07187	Sub-Channel Allocation for Device-to-Device Underlaying Full-Duplex mmWave Small Cells using Coalition Formation Games	The small cells in millimeter wave (mmWave) have been utilized extensively for the fifth generation (5G) mobile networks. And full-duplex (FD) communications become possible with the development of self-interference (SI) cancellation technology. In this paper, we focus on the optimal allocation of the sub-channels in t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	149,545
2206.03321	Early Abnormal Detection of Sewage Pipe Network: Bagging of Various Abnormal Detection Algorithms	Abnormalities of the sewage pipe network will affect the normal operation of the whole city. Therefore, it is important to detect the abnormalities early. This paper propose an early abnormal-detection method. The abnormalities are detected by using the conventional algorithms, such as isolation forest algorithm, two i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	301,231
2302.04625	Weakly Supervised Human Skin Segmentation using Guidance Attention Mechanisms	Human skin segmentation is a crucial task in computer vision and biometric systems, yet it poses several challenges such as variability in skin color, pose, and illumination. This paper presents a robust data-driven skin segmentation method for a single image that addresses these challenges through the integration of c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	344,767
cs/0508099	Search Process and Probabilistic Bifix Approach	An analytical approach to a search process is a mathematical prerequisite for digital synchronization acquisition analysis and optimization. A search is performed for an arbitrary set of sequences within random but not equiprobable L-ary data. This paper derives in detail an expression for probability distribution func...	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	538,908
2106.05181	Condition Integration Memory Network: An Interpretation of the Meaning of the Neuronal Design	Understanding the basic operational logics of the nervous system is essential to advancing neuroscientific research. However, theoretical efforts to tackle this fundamental problem are lacking, despite the abundant empirical data about the brain that has been collected in the past few decades. To address this shortcomi...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	239,998
2106.01534	Deconfounded Video Moment Retrieval with Causal Intervention	We tackle the task of video moment retrieval (VMR), which aims to localize a specific moment in a video according to a textual query. Existing methods primarily model the matching relationship between query and moment by complex cross-modal interactions. Despite their effectiveness, current models mostly exploit datase...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	238,529
2312.10512	Value of Information and Timing-aware Scheduling for Federated Learning	Data possesses significant value as it fuels advancements in AI. However, protecting the privacy of the data generated by end-user devices has become crucial. Federated Learning (FL) offers a solution by preserving data privacy during training. FL brings the model directly to User Equipments (UEs) for local training by...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	416,198
1104.0654	Block-Sparse Recovery via Convex Optimization	Given a dictionary that consists of multiple blocks and a signal that lives in the range space of only a few blocks, we study the problem of finding a block-sparse representation of the signal, i.e., a representation that uses the minimum number of blocks. Motivated by signal/image processing and computer vision applic...	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	9,865
2004.02001	Graph Sequential Network for Reasoning over Sequences	Recently Graph Neural Network (GNN) has been applied successfully to various NLP tasks that require reasoning, such as multi-hop machine reading comprehension. In this paper, we consider a novel case where reasoning is needed over graphs built from sequences, i.e. graph nodes with sequence data. Existing GNN models ful...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	171,080
2307.14262	Artifact Restoration in Histology Images with Diffusion Probabilistic Models	Histological whole slide images (WSIs) can be usually compromised by artifacts, such as tissue folding and bubbles, which will increase the examination difficulty for both pathologists and Computer-Aided Diagnosis (CAD) systems. Existing approaches to restoring artifact images are confined to Generative Adversarial Net...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	381,861
2108.13461	Time Series Prediction using Deep Learning Methods in Healthcare	Traditional machine learning methods face two main challenges in dealing with healthcare predictive analytics tasks. First, the high-dimensional nature of healthcare data needs labor-intensive and time-consuming processes to select an appropriate set of features for each new task. Second, these methods depend on featur...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	252,806
2301.11763	Gene Teams are on the Field: Evaluation of Variants in Gene-Networks Using High Dimensional Modelling	In medical genetics, each genetic variant is evaluated as an independent entity regarding its clinical importance. However, in most complex diseases, variant combinations in specific gene networks, rather than the presence of a particular single variant, predominates. In the case of complex diseases, disease status can...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	342,266
2212.01470	Prediction of Scene Plausibility	Understanding the 3D world from 2D images involves more than detection and segmentation of the objects within the scene. It also includes the interpretation of the structure and arrangement of the scene elements. Such understanding is often rooted in recognizing the physical world and its limitations, and in prior know...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	334,443
1910.08800	Kernels of Mallows Models under the Hamming Distance for solving the Quadratic Assignment Problem	The Quadratic Assignment Problem (QAP) is a well-known permutation-based combinatorial optimization problem with real applications in industrial and logistics environments. Motivated by the challenge that this NP-hard problem represents, it has captured the attention of the optimization community for decades. As a resu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	149,975
1607.04509	Optimizing Synchronization Stability of the Kuramoto Model in Complex Networks and Power Grids	Maintaining the stability of synchronization state is crucial for the functioning of many natural and artificial systems. In this study, we develop methods to optimize the synchronization stability of the Kuramoto model by minimizing the dominant Lyapunov exponent. With the help of the recently proposed cut-set space a...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	58,625
1304.3448	Strong & Weak Methods: A Logical View of Uncertainty	The last few years has seen a growing debate about techniques for managing uncertainty in AI systems. Unfortunately this debate has been cast as a rivalry between AI methods and classical probability based ones. Three arguments for extending the probability framework of uncertainty are presented, none of which imply a ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	23,887
1901.09296	Variational Smoothing in Recurrent Neural Network Language Models	We present a new theoretical perspective of data noising in recurrent neural network language models (Xie et al., 2017). We show that each variant of data noising is an instance of Bayesian recurrent neural networks with a particular variational distribution (i.e., a mixture of Gaussians whose weights depend on statist...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	119,709
2404.08958	AMU-Tuning: Effective Logit Bias for CLIP-based Few-shot Learning	Recently, pre-trained vision-language models (e.g., CLIP) have shown great potential in few-shot learning and attracted a lot of research interest. Although efforts have been made to improve few-shot ability of CLIP, key factors on the effectiveness of existing methods have not been well studied, limiting further explo...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	446,477
2305.14788	Adapting Language Models to Compress Contexts	Transformer-based language models (LMs) are powerful and widely-applicable tools, but their usefulness is constrained by a finite context window and the expensive computational cost of processing long text documents. We propose to adapt pre-trained LMs into AutoCompressors. These language models are capable of compress...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	367,258
2304.03728	Interpretable Unified Language Checking	Despite recent concerns about undesirable behaviors generated by large language models (LLMs), including non-factual, biased, and hateful language, we find LLMs are inherent multi-task language checkers based on their latent representations of natural and social knowledge. We present an interpretable, unified, language...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	356,922
2112.08132	Improving Self-supervised Learning with Automated Unsupervised Outlier Arbitration	Our work reveals a structured shortcoming of the existing mainstream self-supervised learning methods. Whereas self-supervised learning frameworks usually take the prevailing perfect instance level invariance hypothesis for granted, we carefully investigate the pitfalls behind. Particularly, we argue that the existing ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	271,704
1212.6031	Tangent Bundle Manifold Learning via Grassmann&Stiefel Eigenmaps	One of the ultimate goals of Manifold Learning (ML) is to reconstruct an unknown nonlinear low-dimensional manifold embedded in a high-dimensional observation space by a given set of data points from the manifold. We derive a local lower bound for the maximum reconstruction error in a small neighborhood of an arbitrary...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	20,611
2109.11418	Layered Neural Atlases for Consistent Video Editing	We present a method that decomposes, or "unwraps", an input video into a set of layered 2D atlases, each providing a unified representation of the appearance of an object (or background) over the video. For each pixel in the video, our method estimates its corresponding 2D coordinate in each of the atlases, giving us a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	256,942
2305.12125	A Framework for Provably Stable and Consistent Training of Deep Feedforward Networks	We present a novel algorithm for training deep neural networks in supervised (classification and regression) and unsupervised (reinforcement learning) scenarios. This algorithm combines the standard stochastic gradient descent and the gradient clipping method. The output layer is updated using clipped gradients, the re...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	365,849
2306.08879	Motion Perceiver: Real-Time Occupancy Forecasting for Embedded Systems	This work introduces a novel and adaptable architecture designed for real-time occupancy forecasting that outperforms existing state-of-the-art models on the Waymo Open Motion Dataset in Soft IOU. The proposed model uses recursive latent state estimation with learned transformer-based functions to effectively update an...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	373,583
1604.04842	Subjects and Their Objects: Localizing Interactees for a Person-Centric View of Importance	Understanding images with people often entails understanding their \emph{interactions} with other objects or people. As such, given a novel image, a vision system ought to infer which other objects/people play an important role in a given person's activity. However, existing methods are limited to learning action-speci...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	54,721
2302.00198	A fuzzy adaptive metaheuristic algorithm for identifying sustainable, economical, lightweight, and earthquake-resistant reinforced concrete cantilever retaining walls	In earthquake-prone zones, the seismic performance of reinforced concrete cantilever (RCC) retaining walls is significant. In this study, the seismic performance was investigated using horizontal and vertical pseudo-static coefficients. To tackle RCC weights and forces resulting from these earth pressures, 26 constrain...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	true	343,137
2306.16893	Traceable Group-Wise Self-Optimizing Feature Transformation Learning: A Dual Optimization Perspective	Feature transformation aims to reconstruct an effective representation space by mathematically refining the existing features. It serves as a pivotal approach to combat the curse of dimensionality, enhance model generalization, mitigate data sparsity, and extend the applicability of classical models. Existing research ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	376,520
2209.13917	A simple but strong baseline for online continual learning: Repeated Augmented Rehearsal	Online continual learning (OCL) aims to train neural networks incrementally from a non-stationary data stream with a single pass through data. Rehearsal-based methods attempt to approximate the observed input distributions over time with a small memory and revisit them later to avoid forgetting. Despite its strong empi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	320,076
1701.07266	k*-Nearest Neighbors: From Global to Local	The weighted k-nearest neighbors algorithm is one of the most fundamental non-parametric methods in pattern recognition and machine learning. The question of setting the optimal number of neighbors as well as the optimal weights has received much attention throughout the years, nevertheless this problem seems to have r...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	67,262
2410.00698	Analysis of Cross-Domain Message Passing for OTFS Transmissions	In this paper, we investigate the performance of the cross-domain iterative detection (CDID) framework with orthogonal time frequency space (OTFS) modulation, where two distinct CDID algorithms are presented. The proposed schemes estimate/detect the information symbols iteratively across the frequency domain and the de...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	493,465
1905.12330	Word-order biases in deep-agent emergent communication	Sequence-processing neural networks led to remarkable progress on many NLP tasks. As a consequence, there has been increasing interest in understanding to what extent they process language as humans do. We aim here to uncover which biases such models display with respect to "natural" word-order constraints. We train mo...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	132,736
2410.10365	SpeGCL: Self-supervised Graph Spectrum Contrastive Learning without Positive Samples	Graph Contrastive Learning (GCL) excels at managing noise and fluctuations in input data, making it popular in various fields (e.g., social networks, and knowledge graphs). Our study finds that the difference in high-frequency information between augmented graphs is greater than that in low-frequency information. Howev...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	498,036
2411.18324	RITA: Automatic Framework for Designing of Resilient IoT Applications	Designing resilient Internet of Things (IoT) systems requires i) identification of IoT Critical Objects (ICOs) such as services, devices, and resources, ii) threat analysis, and iii) mitigation strategy selection. However, the traditional process for designing resilient IoT systems is still manual, leading to inefficie...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	511,834
2108.02756	BOSS: Bidirectional One-Shot Synthesis of Adversarial Examples	The design of additive imperceptible perturbations to the inputs of deep classifiers to maximize their misclassification rates is a central focus of adversarial machine learning. An alternative approach is to synthesize adversarial examples from scratch using GAN-like structures, albeit with the use of large amounts of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	249,436
2306.09372	SAFER: Situation Aware Facial Emotion Recognition	In this paper, we present SAFER, a novel system for emotion recognition from facial expressions. It employs state-of-the-art deep learning techniques to extract various features from facial images and incorporates contextual information, such as background and location type, to enhance its performance. The system has b...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	373,803
2011.08982	Patient-Specific Seizure Prediction Using Single Seizure Electroencephalography Recording	Electroencephalogram (EEG) is a prominent way to measure the brain activity for studying epilepsy, thereby helping in predicting seizures. Seizure prediction is an active research area with many deep learning based approaches dominating the recent literature for solving this problem. But these models require a consider...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	207,049
2408.08645	Extracting polygonal footprints in off-nadir images with Segment Anything Model	Building Footprint Extraction (BFE) from off-nadir aerial images often involves roof segmentation and offset prediction to adjust roof boundaries to the building footprint. However, this multi-stage approach typically produces low-quality results, limiting its applicability in real-world data production. To address thi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	481,083
2009.14276	Compact 200 line MATLAB code for inverse design in photonics by topology optimization: tutorial	We provide a compact 200 line MATLAB code demonstrating how topology optimization (TopOpt) as an inverse design tool may be used in photonics, targeting the design of two-dimensional dielectric metalenses and a metallic reflector as examples. The physics model is solved using the finite element method, and the code uti...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	197,981
2008.00994	Cluster-Based Cooperative Digital Over-the-Air Aggregation for Wireless Federated Edge Learning	In this paper, we study a federated learning system at the wireless edge that uses over-the-air computation (AirComp). In such a system, users transmit their messages over a multi-access channel concurrently to achieve fast model aggregation. Recently, an AirComp scheme based on digital modulation has been proposed fea...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	190,175
2404.06647	From Protoscience to Epistemic Monoculture: How Benchmarking Set the Stage for the Deep Learning Revolution	Over the past decade, AI research has focused heavily on building ever-larger deep learning models. This approach has simultaneously unlocked incredible achievements in science and technology, and hindered AI from overcoming long-standing limitations with respect to explainability, ethical harms, and environmental effi...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	445,536
2211.09386	BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object Detection	3D object detection from multiple image views is a fundamental and challenging task for visual scene understanding. Owing to its low cost and high efficiency, multi-view 3D object detection has demonstrated promising application prospects. However, accurately detecting objects through perspective views is extremely dif...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	330,958
2304.04949	Intelligent humanoids in manufacturing to address worker shortage and skill gaps: Case of Tesla Optimus	Technological evolution in the field of robotics is emerging with major breakthroughs in recent years. This was especially fostered by revolutionary new software applications leading to humanoid robots. Humanoids are being envisioned for manufacturing applications to form human-robot teams. But their implication in man...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	357,424
2206.01256	PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images	In this paper, we propose PETRv2, a unified framework for 3D perception from multi-view images. Based on PETR, PETRv2 explores the effectiveness of temporal modeling, which utilizes the temporal information of previous frames to boost 3D object detection. More specifically, we extend the 3D position embedding (3D PE) i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	300,401
2501.14524	Training-Free Style and Content Transfer by Leveraging U-Net Skip Connections in Stable Diffusion 2.*	Despite significant recent advances in image generation with diffusion models, their internal latent representations remain poorly understood. Existing works focus on the bottleneck layer (h-space) of Stable Diffusion's U-Net or leverage the cross-attention, self-attention, or decoding layers. Our model, SkipInject tak...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	527,154
2208.00784	Deep COVID-19 Recognition using Chest X-ray Images: A Comparative Analysis	The novel coronavirus variant, which is also widely known as COVID-19, is currently a common threat to all humans across the world. Effective recognition of COVID-19 using advanced machine learning methods is a timely need. Although many sophisticated approaches have been proposed in the recent past, they still struggl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	310,968
2410.14147	Leveraging Large Language Models for Enhancing Public Transit Services	Public transit systems play a crucial role in providing efficient and sustainable transportation options in urban areas. However, these systems face various challenges in meeting commuters' needs. On the other hand, despite the rapid development of Large Language Models (LLMs) worldwide, their integration into transit ...	false	false	false	true	true	false	true	false	false	false	false	false	false	true	false	false	false	false	499,892
1901.07592	What Can Machine Learning Teach Us about Communications?	Rapid improvements in machine learning over the past decade are beginning to have far-reaching effects. For communications, engineers with limited domain expertise can now use off-the-shelf learning packages to design high-performance systems based on simulations. Prior to the current revolution in machine learning, th...	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	119,244

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