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
2303.14689	Weak Recovery Threshold for the Hypergraph Stochastic Block Model	We study the weak recovery problem on the $r$-uniform hypergraph stochastic block model ($r$-HSBM) with two balanced communities. In HSBM a random graph is constructed by placing hyperedges with higher density if all vertices of a hyperedge share the same binary label, and weak recovery asks to recover a non-trivial fr...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	354,204
2405.12790	A Novel Methodology for Autonomous Planetary Exploration Using Multi-Robot Teams	One of the fundamental limiting factors in planetary exploration is the autonomous capabilities of planetary exploration rovers. This study proposes a novel methodology for trustworthy autonomous multi-robot teams which incorporates data from multiple sources (HiRISE orbiter imaging, probability distribution maps, and ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	455,656
2110.06133	Hotel Preference Rank based on Online Customer Review	Topline hotels are now shifting into the digital way in how they understand their customers to maintain and ensuring satisfaction. Rather than the conventional way which uses written reviews or interviews, the hotel is now heavily investing in Artificial Intelligence particularly Machine Learning solutions. Analysis of...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	260,509
2102.09193	SeaPearl: A Constraint Programming Solver guided by Reinforcement Learning	The design of efficient and generic algorithms for solving combinatorial optimization problems has been an active field of research for many years. Standard exact solving approaches are based on a clever and complete enumeration of the solution set. A critical and non-trivial design choice with such methods is the bran...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	220,694
2407.21734	Human-Machine Co-Adaptation for Robot-Assisted Rehabilitation via Dual-Agent Multiple Model Reinforcement Learning (DAMMRL)	This study introduces a novel approach to robot-assisted ankle rehabilitation by proposing a Dual-Agent Multiple Model Reinforcement Learning (DAMMRL) framework, leveraging multiple model adaptive control (MMAC) and co-adaptive control strategies. In robot-assisted rehabilitation, one of the key challenges is modelling...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	477,651
2203.13309	Weakly-Supervised Online Action Segmentation in Multi-View Instructional Videos	This paper addresses a new problem of weakly-supervised online action segmentation in instructional videos. We present a framework to segment streaming videos online at test time using Dynamic Programming and show its advantages over greedy sliding window approach. We improve our framework by introducing the Online-Off...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	287,581
2011.07697	Ensemble of Models Trained by Key-based Transformed Images for Adversarially Robust Defense Against Black-box Attacks	We propose a voting ensemble of models trained by using block-wise transformed images with secret keys for an adversarially robust defense. Key-based adversarial defenses were demonstrated to outperform state-of-the-art defenses against gradient-based (white-box) attacks. However, the key-based defenses are not effecti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	206,643
0902.4098	Coordination in multiagent systems and Laplacian spectra of digraphs	Constructing and studying distributed control systems requires the analysis of the Laplacian spectra and the forest structure of directed graphs. In this paper, we present some basic results of this analysis partially obtained by the present authors. We also discuss the application of these results to decentralized con...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	3,221
2405.04773	Hypergraph-enhanced Dual Semi-supervised Graph Classification	In this paper, we study semi-supervised graph classification, which aims at accurately predicting the categories of graphs in scenarios with limited labeled graphs and abundant unlabeled graphs. Despite the promising capability of graph neural networks (GNNs), they typically require a large number of costly labeled gra...	false	false	false	true	true	true	true	false	false	false	false	false	false	false	false	false	false	false	452,674
2311.04199	Exploring Recommendation Capabilities of GPT-4V(ision): A Preliminary Case Study	Large Multimodal Models (LMMs) have demonstrated impressive performance across various vision and language tasks, yet their potential applications in recommendation tasks with visual assistance remain unexplored. To bridge this gap, we present a preliminary case study investigating the recommendation capabilities of GP...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	406,134
2306.13686	Broadening the perspective for sustainable AI: Comprehensive sustainability criteria and indicators for AI systems	The increased use of AI systems is associated with multi-faceted societal, environmental, and economic consequences. These include non-transparent decision-making processes, discrimination, increasing inequalities, rising energy consumption and greenhouse gas emissions in AI model development and application, and an in...	true	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	375,363
2210.00102	MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization	Training graph neural networks (GNNs) on large graphs is complex and extremely time consuming. This is attributed to overheads caused by sparse matrix multiplication, which are sidestepped when training multi-layer perceptrons (MLPs) with only node features. MLPs, by ignoring graph context, are simple and faster for gr...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	320,732
1904.01333	Point in, Box out: Beyond Counting Persons in Crowds	Modern crowd counting methods usually employ deep neural networks (DNN) to estimate crowd counts via density regression. Despite their significant improvements, the regression-based methods are incapable of providing the detection of individuals in crowds. The detection-based methods, on the other hand, have not been l...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	126,117
2303.17878	Fused Depthwise Tiling for Memory Optimization in TinyML Deep Neural Network Inference	Memory optimization for deep neural network (DNN) inference gains high relevance with the emergence of TinyML, which refers to the deployment of DNN inference tasks on tiny, low-power microcontrollers. Applications such as audio keyword detection or radar-based gesture recognition are heavily constrained by the limited...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	355,376
2305.14728	SenteCon: Leveraging Lexicons to Learn Human-Interpretable Language Representations	Although deep language representations have become the dominant form of language featurization in recent years, in many settings it is important to understand a model's decision-making process. This necessitates not only an interpretable model but also interpretable features. In particular, language must be featurized ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	367,217
2311.00445	A Systematic Comparison of Syllogistic Reasoning in Humans and Language Models	A central component of rational behavior is logical inference: the process of determining which conclusions follow from a set of premises. Psychologists have documented several ways in which humans' inferences deviate from the rules of logic. Do language models, which are trained on text generated by humans, replicate ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	404,656
0708.1558	Construction of a 3-Dimensional MDS code	In this paper, we describe a procedure for constructing $q$--ary $[N,3,N-2]$--MDS codes, of length $N\leq q+1$ (for $q$ odd) or $N\leq q+2$ (for $q$ even), using a set of non--degenerate Hermitian forms in $PG(2,q^2)$.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	544
2105.14190	RaspberryPI for mosquito neutralization by power laser	In this article for the first time, comprehensive studies of mosquito neutralization using machine vision and a 1 W power laser are considered. Developed laser installation with Raspberry Pi that changing the direction of the laser with a galvanometer. We developed a program for mosquito tracking in real. The possibili...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	237,569
cs/0504066	Comparison of the Bayesian and Randomised Decision Tree Ensembles within an Uncertainty Envelope Technique	Multiple Classifier Systems (MCSs) allow evaluation of the uncertainty of classification outcomes that is of crucial importance for safety critical applications. The uncertainty of classification is determined by a trade-off between the amount of data available for training, the classifier diversity and the required pe...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	538,676
2404.16304	BezierFormer: A Unified Architecture for 2D and 3D Lane Detection	Lane detection has made significant progress in recent years, but there is not a unified architecture for its two sub-tasks: 2D lane detection and 3D lane detection. To fill this gap, we introduce B\'{e}zierFormer, a unified 2D and 3D lane detection architecture based on B\'{e}zier curve lane representation. B\'{e}zier...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	449,433
1407.4694	Distributed Pricing-Based User Association for Downlink Heterogeneous Cellular Networks	This paper considers the optimization of the user and base-station (BS) association in a wireless downlink heterogeneous cellular network under the proportional fairness criterion. We first consider the case where each BS has a single antenna and transmits at fixed power, and propose a distributed price update strategy...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	34,722
1911.00038	Context-Aware Local Differential Privacy	Local differential privacy (LDP) is a strong notion of privacy for individual users that often comes at the expense of a significant drop in utility. The classical definition of LDP assumes that all elements in the data domain are equally sensitive. However, in many applications, some symbols are more sensitive than ot...	false	false	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	true	151,710
2412.08316	Rumor Detection on Social Media with Temporal Propagation Structure Optimization	Traditional methods for detecting rumors on social media primarily focus on analyzing textual content, often struggling to capture the complexity of online interactions. Recent research has shifted towards leveraging graph neural networks to model the hierarchical conversation structure that emerges during rumor propag...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	516,042
2412.06146	Homogeneous Dynamics Space for Heterogeneous Humans	Analyses of human motion kinematics have achieved tremendous advances. However, the production mechanism, known as human dynamics, is still undercovered. In this paper, we aim to push data-driven human dynamics understanding forward. We identify a major obstacle to this as the heterogeneity of existing human motion und...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	515,112
2310.15887	AdaptiX -- A Transitional XR Framework for Development and Evaluation of Shared Control Applications in Assistive Robotics	With the ongoing efforts to empower people with mobility impairments and the increase in technological acceptance by the general public, assistive technologies, such as collaborative robotic arms, are gaining popularity. Yet, their widespread success is limited by usability issues, specifically the disparity between us...	true	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	true	402,487
0802.4112	Hubs in Languages: Scale Free Networks of Synonyms	Natural languages are described in this paper in terms of networks of synonyms: a word is identified with a node, and synonyms are connected by undirected links. Our statistical analysis of the network of synonyms in Polish language showed it is scale-free; similar to what is known for English. The statistical properti...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	1,359
2010.03249	Exploring and Evaluating Attributes, Values, and Structures for Entity Alignment	Entity alignment (EA) aims at building a unified Knowledge Graph (KG) of rich content by linking the equivalent entities from various KGs. GNN-based EA methods present promising performances by modeling the KG structure defined by relation triples. However, attribute triples can also provide crucial alignment signal bu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	199,341
2310.09196	A 4-approximation algorithm for min max correlation clustering	We introduce a lower bounding technique for the min max correlation clustering problem and, based on this technique, a combinatorial 4-approximation algorithm for complete graphs. This improves upon the previous best known approximation guarantees of 5, using a linear program formulation (Kalhan et al., 2019), and 40, ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	399,686
2412.07587	A Hype-Adjusted Probability Measure for NLP Stock Return Forecasting	This article introduces a Hype-Adjusted Probability Measure in the context of a new Natural Language Processing (NLP) approach for stock return and volatility forecasting. A novel sentiment score equation is proposed to represent the impact of intraday news on forecasting next-period stock return and volatility for sel...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	515,724
2404.13879	Explicit Lipschitz Value Estimation Enhances Policy Robustness Against Perturbation	In robotic control tasks, policies trained by reinforcement learning (RL) in simulation often experience a performance drop when deployed on physical hardware, due to modeling error, measurement error, and unpredictable perturbations in the real world. Robust RL methods account for this issue by approximating a worst-c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	448,483
2402.07229	Successive Refinement in Large-Scale Computation: Advancing Model Inference Applications	Modern computationally-intensive applications often operate under time constraints, necessitating acceleration methods and distribution of computational workloads across multiple entities. However, the outcome is either achieved within the desired timeline or not, and in the latter case, valuable resources are wasted. ...	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	428,620
2108.08454	Improving Human Sequential Decision-Making with Reinforcement Learning	Workers spend a significant amount of time learning how to make good decisions. Evaluating the efficacy of a given decision, however, can be complicated -- e.g., decision outcomes are often long-term and relate to the original decision in complex ways. Surprisingly, even though learning good decision-making strategies ...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	251,254
2005.13439	HPC compact quasi-Newton algorithm for interface problems	In this work we present a robust interface coupling algorithm called Compact Interface quasi-Newton (CIQN). It is designed for computationally intensive applications using an MPI multi-code partitioned scheme. The algorithm allows to reuse information from previous time steps, feature that has been previously proposed ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	179,010
2111.06334	Identification of Fine-Grained Location Mentions in Crisis Tweets	Identification of fine-grained location mentions in crisis tweets is central in transforming situational awareness information extracted from social media into actionable information. Most prior works have focused on identifying generic locations, without considering their specific types. To facilitate progress on the ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	266,042
1409.7476	Short-term solar irradiance and irradiation forecasts via different time series techniques: A preliminary study	This communication is devoted to solar irradiance and irradiation short-term forecasts, which are useful for electricity production. Several different time series approaches are employed. Our results and the corresponding numerical simulations show that techniques which do not need a large amount of historical data beh...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	36,329
2407.06099	Physics-Informed Machine Learning Towards A Real-Time Spacecraft Thermal Simulator	Modeling thermal states for complex space missions, such as the surface exploration of airless bodies, requires high computation, whether used in ground-based analysis for spacecraft design or during onboard reasoning for autonomous operations. For example, a finite-element thermal model with hundreds of elements can t...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	471,252
0806.4391	Prediction with Expert Advice in Games with Unbounded One-Step Gains	The games of prediction with expert advice are considered in this paper. We present some modification of Kalai and Vempala algorithm of following the perturbed leader for the case of unrestrictedly large one-step gains. We show that in general case the cumulative gain of any probabilistic prediction algorithm can be mu...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	1,989
1705.08218	XOR-Sampling for Network Design with Correlated Stochastic Events	Many network optimization problems can be formulated as stochastic network design problems in which edges are present or absent stochastically. Furthermore, protective actions can guarantee that edges will remain present. We consider the problem of finding the optimal protection strategy under a budget limit in order t...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	73,979
2305.02819	Algorithmic Computability of the Capacity of Gaussian Channels with Colored Noise	Designing capacity-achieving coding schemes for the band-limited additive colored Gaussian noise (ACGN) channel has been and is still a challenge. In this paper, the capacity of the band-limited ACGN channel is studied from a fundamental algorithmic point of view by addressing the question of whether or not the capacit...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	362,187
1303.5003	Convolutional Codes: Techniques of Construction	In this paper we show how to construct new convolutional codes from old ones by applying the well-known techniques: puncturing, extending, expanding, direct sum, the (u\|u + v) construction and the product code construction. By applying these methods, several new families of convolutional codes can be constructed. As an...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	23,049
1609.08685	Understanding and Exploiting Object Interaction Landscapes	Interactions play a key role in understanding objects and scenes, for both virtual and real world agents. We introduce a new general representation for proximal interactions among physical objects that is agnostic to the type of objects or interaction involved. The representation is based on tracking particles on one o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	61,623
2312.04180	AI and Jobs: Has the Inflection Point Arrived? Evidence from an Online Labor Platform	The emergence of Large Language Models (LLMs) has renewed the debate on the important issue of "technology displacement". While prior research has investigated the effect of information technology in general on human labor from a macro perspective, this paper complements the literature by examining the impact of LLMs o...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	413,584
2308.02396	HOOD: Real-Time Human Presence and Out-of-Distribution Detection Using FMCW Radar	Detecting human presence indoors with millimeter-wave frequency-modulated continuous-wave (FMCW) radar faces challenges from both moving and stationary clutter. This work proposes a robust and real-time capable human presence and out-of-distribution (OOD) detection method using 60 GHz short-range FMCW radar. HOOD solve...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	383,603
1711.06127	SUPRA: Open Source Software Defined Ultrasound Processing for Real-Time Applications	Research in ultrasound imaging is limited in reproducibility by two factors: First, many existing ultrasound pipelines are protected by intellectual property, rendering exchange of code difficult. Second, most pipelines are implemented in special hardware, resulting in limited flexibility of implemented processing step...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	84,715
2402.17780	Constraint Latent Space Matters: An Anti-anomalous Waveform Transformation Solution from Photoplethysmography to Arterial Blood Pressure	Arterial blood pressure (ABP) holds substantial promise for proactive cardiovascular health management. Notwithstanding its potential, the invasive nature of ABP measurements confines their utility primarily to clinical environments, limiting their applicability for continuous monitoring beyond medical facilities. The ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	433,146
2010.09158	Extended Abstract: Motion Planners Learned from Geometric Hallucination	Learning motion planners to move robot from one point to another within an obstacle-occupied space in a collision-free manner requires either an extensive amount of data or high-quality demonstrations. This requirement is caused by the fact that among the variety of maneuvers the robot can perform, it is difficult to f...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	201,427
1910.13294	Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control	Selective rationalization has become a common mechanism to ensure that predictive models reveal how they use any available features. The selection may be soft or hard, and identifies a subset of input features relevant for prediction. The setup can be viewed as a co-operate game between the selector (aka rationale gene...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	151,353
2304.14647	An Adaptive Policy to Employ Sharpness-Aware Minimization	Sharpness-aware minimization (SAM), which searches for flat minima by min-max optimization, has been shown to be useful in improving model generalization. However, since each SAM update requires computing two gradients, its computational cost and training time are both doubled compared to standard empirical risk minimi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	361,050
1611.06322	Spotting Rumors via Novelty Detection	Rumour detection is hard because the most accurate systems operate retrospectively, only recognizing rumours once they have collected repeated signals. By then the rumours might have already spread and caused harm. We introduce a new category of features based on novelty, tailored to detect rumours early on. To compens...	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	false	false	64,165
2309.08551	Augmenting conformers with structured state-space sequence models for online speech recognition	Online speech recognition, where the model only accesses context to the left, is an important and challenging use case for ASR systems. In this work, we investigate augmenting neural encoders for online ASR by incorporating structured state-space sequence models (S4), a family of models that provide a parameter-efficie...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	392,214
2108.02571	Learning Linearized Assignment Flows for Image Labeling	We introduce a novel algorithm for estimating optimal parameters of linearized assignment flows for image labeling. An exact formula is derived for the parameter gradient of any loss function that is constrained by the linear system of ODEs determining the linearized assignment flow. We show how to efficiently evaluate...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	249,375
1909.08267	An NMPC Approach using Convex Inner Approximations for Online Motion Planning with Guaranteed Collision Avoidance	Even though mobile robots have been around for decades, trajectory optimization and continuous time collision avoidance remain subject of active research. Existing methods trade off between path quality, computational complexity, and kinodynamic feasibility. This work approaches the problem using a nonlinear model pred...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	145,940
2102.06626	Do-calculus enables estimation of causal effects in partially observed biomolecular pathways	Estimating causal queries, such as changes in protein abundance in response to a perturbation, is a fundamental task in the analysis of biomolecular pathways. The estimation requires experimental measurements on the pathway components. However, in practice many pathway components are left unobserved (latent) because th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	219,821
1807.03555	An Empirical Approach For Probing the Definiteness of Kernels	Models like support vector machines or Gaussian process regression often require positive semi-definite kernels. These kernels may be based on distance functions. While definiteness is proven for common distances and kernels, a proof for a new kernel may require too much time and effort for users who simply aim at prac...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	102,556
2412.17408	Just What You Desire: Constrained Timeline Summarization with Self-Reflection for Enhanced Relevance	Given news articles about an entity, such as a public figure or organization, timeline summarization (TLS) involves generating a timeline that summarizes the key events about the entity. However, the TLS task is too underspecified, since what is of interest to each reader may vary, and hence there is not a single ideal...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	519,969
1108.4801	Supervised Rank Aggregation for Predicting Influence in Networks	Much work in Social Network Analysis has focused on the identification of the most important actors in a social network. This has resulted in several measures of influence and authority. While most of such sociometrics (e.g., PageRank) are driven by intuitions based on an actors location in a network, asking for the "m...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	true	11,795
2404.10710	Autoregressive Pre-Training on Pixels and Texts	The integration of visual and textual information represents a promising direction in the advancement of language models. In this paper, we explore the dual modality of language--both visual and textual--within an autoregressive framework, pre-trained on both document images and texts. Our method employs a multimodal t...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	447,215
2110.12033	A Simple Baseline for Low-Budget Active Learning	Active learning focuses on choosing a subset of unlabeled data to be labeled. However, most such methods assume that a large subset of the data can be annotated. We are interested in low-budget active learning where only a small subset (e.g., 0.2% of ImageNet) can be annotated. Instead of proposing a new query strategy...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	262,686
2010.06218	Self-Supervised Multi-View Synchronization Learning for 3D Pose Estimation	Current state-of-the-art methods cast monocular 3D human pose estimation as a learning problem by training neural networks on large data sets of images and corresponding skeleton poses. In contrast, we propose an approach that can exploit small annotated data sets by fine-tuning networks pre-trained via self-supervised...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	200,411
2206.07499	Mitigating Intra-Cell Pilot Contamination in Massive MIMO: A Rate Splitting Approach	Massive multiple-input multiple-output (MaMIMO) has become an integral part of the fifth-generation (5G) standard, and is envisioned to be further developed in beyond 5G (B5G) networks. With a massive number of antennas at the base station (BS), MaMIMO is best equipped to cater prominent use cases of B5G networks such ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	302,764
1710.04584	Towards Scalable Spectral Clustering via Spectrum-Preserving Sparsification	The eigendeomposition of nearest-neighbor (NN) graph Laplacian matrices is the main computational bottleneck in spectral clustering. In this work, we introduce a highly-scalable, spectrum-preserving graph sparsification algorithm that enables to build ultra-sparse NN (u-NN) graphs with guaranteed preservation of the or...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	82,500
2204.04216	Learning Trajectory-Aware Transformer for Video Super-Resolution	Video super-resolution (VSR) aims to restore a sequence of high-resolution (HR) frames from their low-resolution (LR) counterparts. Although some progress has been made, there are grand challenges to effectively utilize temporal dependency in entire video sequences. Existing approaches usually align and aggregate video...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	290,576
1302.6957	Ensemble Sparse Models for Image Analysis	Sparse representations with learned dictionaries have been successful in several image analysis applications. In this paper, we propose and analyze the framework of ensemble sparse models, and demonstrate their utility in image restoration and unsupervised clustering. The proposed ensemble model approximates the data a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	22,492
2012.11936	Knowledge Graphs Evolution and Preservation -- A Technical Report from ISWS 2019	One of the grand challenges discussed during the Dagstuhl Seminar "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web" and described in its report is that of a: "Public FAIR Knowledge Graph of Everything: We increasingly see the creation of knowledge graphs that capture information about ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	212,782
2004.12762	Fitness Landscape Analysis of Dimensionally-Aware Genetic Programming Featuring Feynman Equations	Genetic programming is an often-used technique for symbolic regression: finding symbolic expressions that match data from an unknown function. To make the symbolic regression more efficient, one can also use dimensionally-aware genetic programming that constrains the physical units of the equation. Nevertheless, there ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	174,343
2111.05203	Footstep Adjustment for Biped Push Recovery on Slippery Surfaces	Despite extensive studies on motion stabilization of bipeds, they still suffer from the lack of disturbance coping capability on slippery surfaces. In this paper, a novel controller for stabilizing a bipedal motion in its sagittal plane is developed with regard to the surface friction limitations. By taking into accoun...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	265,723
2111.10912	Johnson Coverage Hypothesis: Inapproximability of k-means and k-median in L_p metrics	K-median and k-means are the two most popular objectives for clustering algorithms. Despite intensive effort, a good understanding of the approximability of these objectives, particularly in $\ell_p$-metrics, remains a major open problem. In this paper, we significantly improve upon the hardness of approximation factor...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	267,484
2104.05160	Feature Decomposition and Reconstruction Learning for Effective Facial Expression Recognition	In this paper, we propose a novel Feature Decomposition and Reconstruction Learning (FDRL) method for effective facial expression recognition. We view the expression information as the combination of the shared information (expression similarities) across different expressions and the unique information (expression-spe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	229,617
1807.00454	Multi-Stage Complex Contagions in Random Multiplex Networks	Complex contagion models have been developed to understand a wide range of social phenomena such as adoption of cultural fads, the diffusion of belief, norms, and innovations in social networks, and the rise of collective action to join a riot. Most existing works focus on contagions where individuals' states are repre...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	101,839
2004.03627	TypeNet: Scaling up Keystroke Biometrics	We study the suitability of keystroke dynamics to authenticate 100K users typing free-text. For this, we first analyze to what extent our method based on a Siamese Recurrent Neural Network (RNN) is able to authenticate users when the amount of data per user is scarce, a common scenario in free-text keystroke authentica...	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	171,623
2412.00034	Data-Driven Prescriptive Analytics Applications: A Comprehensive Survey	Prescriptive Analytics (PSA), an emerging business analytics field suggesting concrete options for solving business problems, has seen an increasing amount of interest after more than a decade of multidisciplinary research. This paper is a comprehensive survey of existing applications within PSA in terms of their use c...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	512,451
2111.06426	A Robust Mean-field Game of Boltzmann-Vlasov-like Traffic Flow	Historically, traffic modelling approaches have taken either a particle-like (microscopic) approach, or a gas-like (meso- or macroscopic) approach. Until recently with the introduction of mean-field games to the controls community, there has not been a rigorous framework to facilitate passage between controls for the m...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	266,072
2211.10643	Downscaled Representation Matters: Improving Image Rescaling with Collaborative Downscaled Images	Deep networks have achieved great success in image rescaling (IR) task that seeks to learn the optimal downscaled representations, i.e., low-resolution (LR) images, to reconstruct the original high-resolution (HR) images. Compared with super-resolution methods that consider a fixed downscaling scheme, e.g., bicubic, IR...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	331,380
2409.12632	Counterfactual Explanations for Clustering Models	Clustering algorithms rely on complex optimisation processes that may be difficult to comprehend, especially for individuals who lack technical expertise. While many explainable artificial intelligence techniques exist for supervised machine learning, unsupervised learning -- and clustering in particular -- has been la...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	489,663
2306.04806	Autonomous Capability Assessment of Sequential Decision-Making Systems in Stochastic Settings (Extended Version)	It is essential for users to understand what their AI systems can and can't do in order to use them safely. However, the problem of enabling users to assess AI systems with sequential decision-making (SDM) capabilities is relatively understudied. This paper presents a new approach for modeling the capabilities of black...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	371,904
2210.15559	Robust Monocular Localization of Drones by Adapting Domain Maps to Depth Prediction Inaccuracies	We present a novel monocular localization framework by jointly training deep learning-based depth prediction and Bayesian filtering-based pose reasoning. The proposed cross-modal framework significantly outperforms deep learning-only predictions with respect to model scalability and tolerance to environmental variation...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	327,005
2402.13270	Global Tropical Cyclone Intensity Forecasting with Multi-modal Multi-scale Causal Autoregressive Model	Accurate forecasting of Tropical cyclone (TC) intensity is crucial for formulating disaster risk reduction strategies. Current methods predominantly rely on limited spatiotemporal information from ERA5 data and neglect the causal relationships between these physical variables, failing to fully capture the spatial and t...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	431,180
2112.01984	Fixed-Gain AF Relaying for RF-THz Wireless System over $\alpha$-$\kappa$-$\mu$ Shadowed and $\alpha$-$\mu$ Channels	Recent research investigates the decode-and-forward (DF) relaying for mixed radio frequency (RF) and terahertz (THz) wireless links with zero-boresight pointing errors. In this letter, we analyze the performance of a fixed-gain amplify-and-forward (AF) relaying for the RF-THz link to interface the access network on the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	269,694
2005.04354	Exact Asymptotics for Learning Tree-Structured Graphical Models with Side Information: Noiseless and Noisy Samples	Given side information that an Ising tree-structured graphical model is homogeneous and has no external field, we derive the exact asymptotics of learning its structure from independently drawn samples. Our results, which leverage the use of probabilistic tools from the theory of strong large deviations, refine the lar...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	176,436
2404.11357	Detector Collapse: Physical-World Backdooring Object Detection to Catastrophic Overload or Blindness in Autonomous Driving	Object detection tasks, crucial in safety-critical systems like autonomous driving, focus on pinpointing object locations. These detectors are known to be susceptible to backdoor attacks. However, existing backdoor techniques have primarily been adapted from classification tasks, overlooking deeper vulnerabilities spec...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	447,479
2007.15342	The optimality of syntactic dependency distances	It is often stated that human languages, as other biological systems, are shaped by cost-cutting pressures but, to what extent? Attempts to quantify the degree of optimality of languages by means of an optimality score have been scarce and focused mostly on English. Here we recast the problem of the optimality of the w...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	189,647
2409.11884	Recent Advances in OOD Detection: Problems and Approaches	Out-of-distribution (OOD) detection aims to detect test samples outside the training category space, which is an essential component in building reliable machine learning systems. Existing reviews on OOD detection primarily focus on method taxonomy, surveying the field by categorizing various approaches. However, many ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	489,353
2401.01054	Elastic Multi-Gradient Descent for Parallel Continual Learning	The goal of Continual Learning (CL) is to continuously learn from new data streams and accomplish the corresponding tasks. Previously studied CL assumes that data are given in sequence nose-to-tail for different tasks, thus indeed belonging to Serial Continual Learning (SCL). This paper studies the novel paradigm of Pa...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	419,205
2008.07730	Parallel Extraction of Long-term Trends and Short-term Fluctuation Framework for Multivariate Time Series Forecasting	Multivariate time series forecasting is widely used in various fields. Reasonable prediction results can assist people in planning and decision-making, generate benefits and avoid risks. Normally, there are two characteristics of time series, that is, long-term trend and short-term fluctuation. For example, stock price...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	192,205
2202.08703	Robust Frequency Constrained UC Using Data Driven Logistic Regression for Island Power Systems	In the current practice of short-term power scheduling, online power reserves are used to address generation mismatches and contingencies. Neither online inertia nor the speed of the committed units is considered in the scheduling process. With the increasing injection of uncertain renewable energy sources, this practi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	280,965
2104.03058	Optimizing Memory Efficiency of Graph Neural Networks on Edge Computing Platforms	Graph neural networks (GNN) have achieved state-of-the-art performance on various industrial tasks. However, the poor efficiency of GNN inference and frequent Out-Of-Memory (OOM) problem limit the successful application of GNN on edge computing platforms. To tackle these problems, a feature decomposition approach is pr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	228,954
cs/0407047	Channel-Independent and Sensor-Independent Stimulus Representations	This paper shows how a machine, which observes stimuli through an uncharacterized, uncalibrated channel and sensor, can glean machine-independent information (i.e., channel- and sensor-independent information) about the stimuli. First, we demonstrate that a machine defines a specific coordinate system on the stimulus s...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	538,276
2409.14083	SURf: Teaching Large Vision-Language Models to Selectively Utilize Retrieved Information	Large Vision-Language Models (LVLMs) have become pivotal at the intersection of computer vision and natural language processing. However, the full potential of LVLMs Retrieval-Augmented Generation (RAG) capabilities remains underutilized. Existing works either focus solely on the text modality or are limited to specifi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	490,315
2311.06554	PGODE: Towards High-quality System Dynamics Modeling	This paper studies the problem of modeling multi-agent dynamical systems, where agents could interact mutually to influence their behaviors. Recent research predominantly uses geometric graphs to depict these mutual interactions, which are then captured by powerful graph neural networks (GNNs). However, predicting inte...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	406,987
1512.05868	On Voting and Facility Location	We study mechanisms for candidate selection that seek to minimize the social cost, where voters and candidates are associated with points in some underlying metric space. The social cost of a candidate is the sum of its distances to each voter. Some of our work assumes that these points can be modeled on a real line, b...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	50,265
1901.11074	A Convolutional Neural Network for the Automatic Diagnosis of Collagen VI related Muscular Dystrophies	The development of machine learning systems for the diagnosis of rare diseases is challenging mainly due the lack of data to study them. Despite this challenge, this paper proposes a system for the Computer Aided Diagnosis (CAD) of low-prevalence, congenital muscular dystrophies from confocal microscopy images. The pro...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	120,159
2004.08582	BiFNet: Bidirectional Fusion Network for Road Segmentation	Multi-sensor fusion-based road segmentation plays an important role in the intelligent driving system since it provides a drivable area. The existing mainstream fusion method is mainly to feature fusion in the image space domain which causes the perspective compression of the road and damages the performance of the dis...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	173,107
2309.13130	Insights from an OTTR-centric Ontology Engineering Methodology	OTTR is a language for representing ontology modeling patterns, which enables to build ontologies or knowledge bases by instantiating templates. Thereby, particularities of the ontological representation language are hidden from the domain experts, and it enables ontology engineers to, to some extent, separate the proc...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	394,067
2205.03513	Digital Twin Framework for Time to Failure Forecasting of Wind Turbine Gearbox: A Concept	Wind turbine is a complex machine with its rotating and non-rotating equipment being sensitive to faults. Due to increased wear and tear, the maintenance aspect of a wind turbine is of critical importance. Unexpected failure of wind turbine components can lead to increased O\&M costs which ultimately reduces effective ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	295,304
2012.02994	Attention-Driven Dynamic Graph Convolutional Network for Multi-Label Image Recognition	Recent studies often exploit Graph Convolutional Network (GCN) to model label dependencies to improve recognition accuracy for multi-label image recognition. However, constructing a graph by counting the label co-occurrence possibilities of the training data may degrade model generalizability, especially when there exi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	209,943
2412.19876	WiSER-X: Wireless Signals-based Efficient Decentralized Multi-Robot Exploration without Explicit Information Exchange	We introduce a Wireless Signal based Efficient multi-Robot eXploration (WiSER-X) algorithm applicable to a decentralized team of robots exploring an unknown environment with communication bandwidth constraints. WiSER-X relies only on local inter-robot relative position estimates, that can be obtained by exchanging sign...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	521,010
1105.2864	The Rate-Distortion Function for Product of Two Sources with Side-Information at Decoders	This paper investigates a lossy source coding problem in which two decoders can access their side-information respectively. The correlated sources are a product of two component correlated sources, and we exclusively investigate the case such that each component is degraded. We show the rate-distortion function for tha...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	10,368
2301.12995	FedFA: Federated Feature Augmentation	Federated learning is a distributed paradigm that allows multiple parties to collaboratively train deep models without exchanging the raw data. However, the data distribution among clients is naturally non-i.i.d., which leads to severe degradation of the learnt model. The primary goal of this paper is to develop a robu...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	342,749
2402.16749	MISC: Ultra-low Bitrate Image Semantic Compression Driven by Large Multimodal Model	With the evolution of storage and communication protocols, ultra-low bitrate image compression has become a highly demanding topic. However, existing compression algorithms must sacrifice either consistency with the ground truth or perceptual quality at ultra-low bitrate. In recent years, the rapid development of the L...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	432,678
0812.1780	On the Energy Efficiency of Orthogonal Signaling	In this paper, transmission over the additive white Gaussian noise (AWGN) channel, and coherent and noncoherent fading channels using M-ary orthogonal frequency-shift keying (FSK) or on-off frequency-shift keying (OOFSK) is considered. The receiver is assumed to perform hard-decision detection. In this setting, energy ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	2,771

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