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
2111.01582	LMdiff: A Visual Diff Tool to Compare Language Models	While different language models are ubiquitous in NLP, it is hard to contrast their outputs and identify which contexts one can handle better than the other. To address this question, we introduce LMdiff, a tool that visually compares probability distributions of two models that differ, e.g., through finetuning, distil...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	264,598
2301.08454	Integrated Planning of Multi-energy Grids: Concepts and Challenges	In order to meet ever-stricter climate targets and achieve the eventual decarbonization of the energy supply of German industrial metropolises, the focus is on gradually phasing out nuclear power, then coal and gas combined with the increased use of renewable energy sources and employing hydrogen as a clean energy carr...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	341,207
2401.06785	Human-Instruction-Free LLM Self-Alignment with Limited Samples	Aligning large language models (LLMs) with human values is a vital task for LLM practitioners. Current alignment techniques have several limitations: (1) requiring a large amount of annotated data; (2) demanding heavy human involvement; (3) lacking a systematic mechanism to continuously improve. In this work, we study ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	421,280
2305.17021	GLOBE-CE: A Translation-Based Approach for Global Counterfactual Explanations	Counterfactual explanations have been widely studied in explainability, with a range of application dependent methods prominent in fairness, recourse and model understanding. The major shortcoming associated with these methods, however, is their inability to provide explanations beyond the local or instance-level. Whil...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	368,377
2406.13612	On Computation of Approximate Solutions to Large-Scale Backstepping Kernel Equations via Continuum Approximation	We provide two methods for computation of continuum backstepping kernels that arise in control of continua (ensembles) of linear hyperbolic PDEs and which can approximate backstepping kernels arising in control of a large-scale, PDE system counterpart (with computational complexity that does not grow with the number of...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	465,918
1804.05427	White matter fiber analysis using kernel dictionary learning and sparsity priors	Diffusion magnetic resonance imaging, a non-invasive tool to infer white matter fiber connections, produces a large number of streamlines containing a wealth of information on structural connectivity. The size of these tractography outputs makes further analyses complex, creating a need for methods to group streamlines...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	95,071
1412.6464	Simplified firefly algorithm for 2D image key-points search	In order to identify an object, human eyes firstly search the field of view for points or areas which have particular properties. These properties are used to recognise an image or an object. Then this process could be taken as a model to develop computer algorithms for images identification. This paper proposes the id...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	true	false	false	38,635
1905.04041	Intelligent User Association for Symbiotic Radio Networks using Deep Reinforcement Learning	In this paper, we are interested in symbiotic radio networks, in which an Internet-of-Things (IoT) network parasitizes in a primary network to achieve spectrum-, energy-, and infrastructure-efficient communications. Specifically, the BS serves multiple cellular users using time division multiple access (TDMA) and each ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	130,351
1903.09513	Process Mining of Programmable Logic Controllers: Input/Output Event Logs	This paper presents an approach to model an unknown Ladder Logic based Programmable Logic Controller (PLC) program consisting of Boolean logic and counters using Process Mining techniques. First, we tap the inputs and outputs of a PLC to create a data flow log. Second, we propose a method to translate the obtained data...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	125,074
2409.15710	Autotuning Bipedal Locomotion MPC with GRFM-Net for Efficient Sim-to-Real Transfer	Bipedal locomotion control is essential for humanoid robots to navigate complex, human-centric environments. While optimization-based control designs are popular for integrating sophisticated models of humanoid robots, they often require labor-intensive manual tuning. In this work, we address the challenges of paramete...	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	false	false	491,024
cs/0405019	Hybrid Fuzzy-Linear Programming Approach for Multi Criteria Decision Making Problems	The purpose of this paper is to point to the usefulness of applying a linear mathematical formulation of fuzzy multiple criteria objective decision methods in organising business activities. In this respect fuzzy parameters of linear programming are modelled by preference-based membership functions. This paper begins w...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	538,181
2001.06268	Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network	Recent studies in image classification have demonstrated a variety of techniques for improving the performance of Convolutional Neural Networks (CNNs). However, attempts to combine existing techniques to create a practical model are still uncommon. In this study, we carry out extensive experiments to validate that care...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	160,761
2309.13962	Egocentric RGB+Depth Action Recognition in Industry-Like Settings	Action recognition from an egocentric viewpoint is a crucial perception task in robotics and enables a wide range of human-robot interactions. While most computer vision approaches prioritize the RGB camera, the Depth modality - which can further amplify the subtleties of actions from an egocentric perspective - remain...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	394,423
1802.08369	Missing Data Reconstruction in Remote Sensing image with a Unified Spatial-Temporal-Spectral Deep Convolutional Neural Network	Because of the internal malfunction of satellite sensors and poor atmospheric conditions such as thick cloud, the acquired remote sensing data often suffer from missing information, i.e., the data usability is greatly reduced. In this paper, a novel method of missing information reconstruction in remote sensing images ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	91,088
2502.06186	Learning the Frequency Dynamics of the Power System Using Higher-order Dynamic Mode Decomposition	The increasing penetration of renewable energy sources, characterised by low inertia and intermittent disturbances, presents substantial challenges to power system stability. As critical indicators of system stability, frequency dynamics and associated oscillatory phenomena have attracted significant research attention...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	531,972
2202.02925	Benchmarking Deep Models for Salient Object Detection	In recent years, deep network-based methods have continuously refreshed state-of-the-art performance on Salient Object Detection (SOD) task. However, the performance discrepancy caused by different implementation details may conceal the real progress in this task. Making an impartial comparison is required for future r...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	279,003
1307.7286	A Review of Machine Learning based Anomaly Detection Techniques	Intrusion detection is so much popular since the last two decades where intrusion is attempted to break into or misuse the system. It is mainly of two types based on the intrusions, first is Misuse or signature based detection and the other is Anomaly detection. In this paper Machine learning based methods which are on...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	26,086
1507.00814	Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models	Achieving efficient and scalable exploration in complex domains poses a major challenge in reinforcement learning. While Bayesian and PAC-MDP approaches to the exploration problem offer strong formal guarantees, they are often impractical in higher dimensions due to their reliance on enumerating the state-action space....	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	44,789
2001.01027	The Radial Point Interpolation Mixed Collocation (RPIMC) Method for the Solution of Transient Diffusion Problems	The Radial Point Interpolation Mixed Collocation (RPIMC) method is proposed in this paper for transient analysis of diffusion problems. RPIMC is an efficient purely meshless method where the solution of the field variable is obtained through collocation. The field function and its gradient are both interpolated (mixed ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	159,380
2312.02308	AdsorbRL: Deep Multi-Objective Reinforcement Learning for Inverse Catalysts Design	A central challenge of the clean energy transition is the development of catalysts for low-emissions technologies. Recent advances in Machine Learning for quantum chemistry drastically accelerate the computation of catalytic activity descriptors such as adsorption energies. Here we introduce AdsorbRL, a Deep Reinforcem...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	412,811
1905.10830	Feature Map Transform Coding for Energy-Efficient CNN Inference	Convolutional neural networks (CNNs) achieve state-of-the-art accuracy in a variety of tasks in computer vision and beyond. One of the major obstacles hindering the ubiquitous use of CNNs for inference on low-power edge devices is their high computational complexity and memory bandwidth requirements. The latter often d...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	132,212
2011.08363	Vis-CRF, A Classical Receptive Field Model for VISION	Over the last decade, a variety of new neurophysiological experiments have led to new insights as to how, when and where retinal processing takes place, and the nature of the retinal representation encoding sent to the cortex for further processing. Based on these neurobiological discoveries, in our previous work, we p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	206,846
2106.04565	Translate, then Parse! A strong baseline for Cross-Lingual AMR Parsing	In cross-lingual Abstract Meaning Representation (AMR) parsing, researchers develop models that project sentences from various languages onto their AMRs to capture their essential semantic structures: given a sentence in any language, we aim to capture its core semantic content through concepts connected by manifold ty...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	239,779
1709.03019	Classifying Unordered Feature Sets with Convolutional Deep Averaging Networks	Unordered feature sets are a nonstandard data structure that traditional neural networks are incapable of addressing in a principled manner. Providing a concatenation of features in an arbitrary order may lead to the learning of spurious patterns or biases that do not actually exist. Another complication is introduced ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	80,388
1910.08942	Autonomous Industrial Management via Reinforcement Learning: Self-Learning Agents for Decision-Making -- A Review	Industry has always been in the pursuit of becoming more economically efficient and the current focus has been to reduce human labour using modern technologies. Even with cutting edge technologies, which range from packaging robots to AI for fault detection, there is still some ambiguity on the aims of some new systems...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	150,023
2411.07956	Commissioning An All-Sky Infrared Camera Array for Detection Of Airborne Objects	To date there is little publicly available scientific data on Unidentified Aerial Phenomena (UAP) whose properties and kinematics purportedly reside outside the performance envelope of known phenomena. To address this deficiency, the Galileo Project is designing, building, and commissioning a multi-modal ground-based o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	507,732
2405.01919	Channel Orthogonalization in Panel-Based LIS	Large intelligent surface (LIS) has gained momentum as a potential 6G-enabling technology that expands the benefits of massive multiple-input multiple-output (MIMO). On the other hand, orthogonal space-division multiplexing (OSDM) may give a promising direction for efficient exploitation of the spatial resources, analo...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	451,558
1711.06370	Parallel Attention: A Unified Framework for Visual Object Discovery through Dialogs and Queries	Recognising objects according to a pre-defined fixed set of class labels has been well studied in the Computer Vision. There are a great many practical applications where the subjects that may be of interest are not known beforehand, or so easily delineated, however. In many of these cases natural language dialog is a ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	84,754
2105.10129	A Novel 3D-UNet Deep Learning Framework Based on High-Dimensional Bilateral Grid for Edge Consistent Single Image Depth Estimation	The task of predicting smooth and edge-consistent depth maps is notoriously difficult for single image depth estimation. This paper proposes a novel Bilateral Grid based 3D convolutional neural network, dubbed as 3DBG-UNet, that parameterizes high dimensional feature space by encoding compact 3D bilateral grids with UN...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	236,281
2005.02126	Falsification of Cyber-Physical Systems with Robustness-Guided Black-Box Checking	For exhaustive formal verification, industrial-scale cyber-physical systems (CPSs) are often too large and complex, and lightweight alternatives (e.g., monitoring and testing) have attracted the attention of both industrial practitioners and academic researchers. Falsification is one popular testing method of CPSs util...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	175,767
2005.09379	Staying True to Your Word: (How) Can Attention Become Explanation?	The attention mechanism has quickly become ubiquitous in NLP. In addition to improving performance of models, attention has been widely used as a glimpse into the inner workings of NLP models. The latter aspect has in the recent years become a common topic of discussion, most notably in work of Jain and Wallace, 2019; ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	177,912
2410.01239	Replacement Learning: Training Vision Tasks with Fewer Learnable Parameters	Traditional end-to-end deep learning models often enhance feature representation and overall performance by increasing the depth and complexity of the network during training. However, this approach inevitably introduces issues of parameter redundancy and resource inefficiency, especially in deeper networks. While exis...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	493,671
1909.03044	Deep learning with sentence embeddings pre-trained on biomedical corpora improves the performance of finding similar sentences in electronic medical records	Capturing sentence semantics plays a vital role in a range of text mining applications. Despite continuous efforts on the development of related datasets and models in the general domain, both datasets and models are limited in biomedical and clinical domains. The BioCreative/OHNLP organizers have made the first attemp...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	144,355
2405.16728	Towards Multi-Task Multi-Modal Models: A Video Generative Perspective	Advancements in language foundation models have primarily fueled the recent surge in artificial intelligence. In contrast, generative learning of non-textual modalities, especially videos, significantly trails behind language modeling. This thesis chronicles our endeavor to build multi-task models for generating videos...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	true	457,569
1607.03255	A Variational Model for Joint Motion Estimation and Image Reconstruction	The aim of this paper is to derive and analyze a variational model for the joint estimation of motion and reconstruction of image sequences, which is based on a time-continuous Eulerian motion model. The model can be set up in terms of the continuity equation or the brightness constancy equation. The analysis in this p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	58,478
1912.04950	HyperCon: Image-To-Video Model Transfer for Video-To-Video Translation Tasks	Video-to-video translation is more difficult than image-to-image translation due to the temporal consistency problem that, if unaddressed, leads to distracting flickering effects. Although video models designed from scratch produce temporally consistent results, training them to match the vast visual knowledge captured...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	156,951
2406.19564	Voices Unheard: NLP Resources and Models for Yor\`ub\'a Regional Dialects	Yor\`ub\'a an African language with roughly 47 million speakers encompasses a continuum with several dialects. Recent efforts to develop NLP technologies for African languages have focused on their standard dialects, resulting in disparities for dialects and varieties for which there are little to no resources or tools...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	468,466
2309.11875	Stochastic stiffness identification and response estimation of Timoshenko beams via physics-informed Gaussian processes	Machine learning models trained with structural health monitoring data have become a powerful tool for system identification. This paper presents a physics-informed Gaussian process (GP) model for Timoshenko beam elements. The model is constructed as a multi-output GP with covariance and cross-covariance kernels analyt...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	393,574
2501.07531	Evaluating Agent-based Program Repair at Google	Agent-based program repair offers to automatically resolve complex bugs end-to-end by combining the planning, tool use, and code generation abilities of modern LLMs. Recent work has explored the use of agent-based repair approaches on the popular open-source SWE-Bench, a collection of bugs from highly-rated GitHub Pyth...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	524,426
2406.16714	AutoDetect: Towards a Unified Framework for Automated Weakness Detection in Large Language Models	Although Large Language Models (LLMs) are becoming increasingly powerful, they still exhibit significant but subtle weaknesses, such as mistakes in instruction-following or coding tasks. As these unexpected errors could lead to severe consequences in practical deployments, it is crucial to investigate the limitations w...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	467,243
2501.08096	Hybrid Action Based Reinforcement Learning for Multi-Objective Compatible Autonomous Driving	Reinforcement Learning (RL) has shown excellent performance in solving decision-making and control problems of autonomous driving, which is increasingly applied in diverse driving scenarios. However, driving is a multi-attribute problem, leading to challenges in achieving multi-objective compatibility for current RL me...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	true	524,628
1905.04720	Rotation Invariant Householder Parameterization for Bayesian PCA	We consider probabilistic PCA and related factor models from a Bayesian perspective. These models are in general not identifiable as the likelihood has a rotational symmetry. This gives rise to complicated posterior distributions with continuous subspaces of equal density and thus hinders efficiency of inference as wel...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	130,544
2007.09461	Controllability of reaction systems	Controlling a dynamical system is the ability of changing its configuration arbitrarily through a suitable choice of inputs. It is a very well studied concept in control theory, with wide ranging applications in medicine, biology, social sciences, engineering. We introduce in this article the concept of controllability...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	187,954
1904.01133	Filling Factors of Sunspots in SODISM Images	Received: 1st December 2018; Accepted: 18th February 2019; Published: 1st April 2019 Abstract: The calculated filling factors (FFs) for a feature reflect the fraction of the solar disc covered by that feature, and the assignment of reference synthetic spectra. In this paper, the FFs, specified as a function of radial p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	126,060
2107.10030	Differentiable Feature Selection, a Reparameterization Approach	We consider the task of feature selection for reconstruction which consists in choosing a small subset of features from which whole data instances can be reconstructed. This is of particular importance in several contexts involving for example costly physical measurements, sensor placement or information compression. T...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	247,199
2306.10664	Object Topological Character Acquisition by Inductive Learning	Understanding the shape and structure of objects is undoubtedly extremely important for object recognition, but the most common pattern recognition method currently used is machine learning, which often requires a large number of training data. The problem is that this kind of object-oriented learning lacks a priori kn...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	374,313
1512.04087	True Online Temporal-Difference Learning	The temporal-difference methods TD($\lambda$) and Sarsa($\lambda$) form a core part of modern reinforcement learning. Their appeal comes from their good performance, low computational cost, and their simple interpretation, given by their forward view. Recently, new versions of these methods were introduced, called true...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	50,098
2303.01471	Quantum Hamiltonian Descent	Gradient descent is a fundamental algorithm in both theory and practice for continuous optimization. Identifying its quantum counterpart would be appealing to both theoretical and practical quantum applications. A conventional approach to quantum speedups in optimization relies on the quantum acceleration of intermedia...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	348,980
2502.07978	A Survey of In-Context Reinforcement Learning	Reinforcement learning (RL) agents typically optimize their policies by performing expensive backward passes to update their network parameters. However, some agents can solve new tasks without updating any parameters by simply conditioning on additional context such as their action-observation histories. This paper su...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	532,844
1905.13136	Job Recommendation through Progression of Job Selection	Job recommendation has traditionally been treated as a filter-based match or as a recommendation based on the features of jobs and candidates as discrete entities. In this paper, we introduce a methodology where we leverage the progression of job selection by candidates using machine learning. Additionally, our recomme...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	133,004
0809.2687	Frequent itemsets mining for database auto-administration	With the wide development of databases in general and data warehouses in particular, it is important to reduce the tasks that a database administrator must perform manually. The aim of auto-administrative systems is to administrate and adapt themselves automatically without loss (or even with a gain) in performance. Th...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	2,352
2311.11759	Unveiling the Unseen Potential of Graph Learning through MLPs: Effective Graph Learners Using Propagation-Embracing MLPs	Recent studies attempted to utilize multilayer perceptrons (MLPs) to solve semi-supervised node classification on graphs, by training a student MLP by knowledge distillation (KD) from a teacher graph neural network (GNN). While previous studies have focused mostly on training the student MLP by matching the output prob...	false	false	false	true	true	false	true	false	false	true	false	false	false	false	false	true	false	false	409,064
2310.01508	CODA: Temporal Domain Generalization via Concept Drift Simulator	In real-world applications, machine learning models often become obsolete due to shifts in the joint distribution arising from underlying temporal trends, a phenomenon known as the "concept drift". Existing works propose model-specific strategies to achieve temporal generalization in the near-future domain. However, th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	396,452
2403.04149	MAP: MAsk-Pruning for Source-Free Model Intellectual Property Protection	Deep learning has achieved remarkable progress in various applications, heightening the importance of safeguarding the intellectual property (IP) of well-trained models. It entails not only authorizing usage but also ensuring the deployment of models in authorized data domains, i.e., making models exclusive to certain ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	435,477
2105.10880	RtFPS: An Interactive Map that Visualizes and Predicts Wildfires in the US	Climate change has largely impacted our daily lives. As one of its consequences, we are experiencing more wildfires. In the year 2020, wildfires burned a record number of 8,888,297 acres in the US. To awaken people's attention to climate change, and to visualize the current risk of wildfires, We developed RtFPS, "Real-...	true	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	236,527
2003.04742	Rainy screens: Collecting rainy datasets, indoors	Acquisition of data with adverse conditions in robotics is a cumbersome task due to the difficulty in guaranteeing proper ground truth and synchronising with desired weather conditions. In this paper, we present a simple method - recording a high resolution screen - for generating diverse rainy images from existing cle...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	167,647
1608.02026	Photometric Bundle Adjustment for Vision-Based SLAM	We propose a novel algorithm for the joint refinement of structure and motion parameters from image data directly without relying on fixed and known correspondences. In contrast to traditional bundle adjustment (BA) where the optimal parameters are determined by minimizing the reprojection error using tracked features,...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	59,500
2211.15508	Self Supervised Clustering of Traffic Scenes using Graph Representations	Examining graphs for similarity is a well-known challenge, but one that is mandatory for grouping graphs together. We present a data-driven method to cluster traffic scenes that is self-supervised, i.e. without manual labelling. We leverage the semantic scene graph model to create a generic graph embedding of the traff...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	333,299
2210.07338	Reinforcement Learning with Unbiased Policy Evaluation and Linear Function Approximation	We provide performance guarantees for a variant of simulation-based policy iteration for controlling Markov decision processes that involves the use of stochastic approximation algorithms along with state-of-the-art techniques that are useful for very large MDPs, including lookahead, function approximation, and gradien...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	323,660
2203.13125	Intelligent Systematic Investment Agent: an ensemble of deep learning and evolutionary strategies	Machine learning driven trading strategies have garnered a lot of interest over the past few years. There is, however, limited consensus on the ideal approach for the development of such trading strategies. Further, most literature has focused on trading strategies for short-term trading, with little or no focus on str...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	true	false	false	287,516
2010.12574	Online Semi-Supervised Learning with Bandit Feedback	We formulate a new problem at the intersectionof semi-supervised learning and contextual bandits,motivated by several applications including clini-cal trials and ad recommendations. We demonstratehow Graph Convolutional Network (GCN), a semi-supervised learning approach, can be adjusted tothe new problem formulation. W...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	202,747
1911.08621	Open Cross-Domain Visual Search	This paper addresses cross-domain visual search, where visual queries retrieve category samples from a different domain. For example, we may want to sketch an airplane and retrieve photographs of airplanes. Despite considerable progress, the search occurs in a closed setting between two pre-defined domains. In this pap...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	154,245
1010.5529	Belief Propagation based MIMO Detection Operating on Quantized Channel Output	In multiple-antenna communications, as bandwidth and modulation order increase, system components must work with demanding tolerances. In particular, high resolution and high sampling rate analog-to-digital converters (ADCs) are often prohibitively challenging to design. Therefore ADCs for such applications should be l...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	8,036
2011.02408	Which Minimizer Does My Neural Network Converge To?	The loss surface of an overparameterized neural network (NN) possesses many global minima of zero training error. We explain how common variants of the standard NN training procedure change the minimizer obtained. First, we make explicit how the size of the initialization of a strongly overparameterized NN affects the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	204,923
2406.11802	PhyBench: A Physical Commonsense Benchmark for Evaluating Text-to-Image Models	Text-to-image (T2I) models have made substantial progress in generating images from textual prompts. However, they frequently fail to produce images consistent with physical commonsense, a vital capability for applications in world simulation and everyday tasks. Current T2I evaluation benchmarks focus on metrics such a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	465,065
1911.04948	EntropyDB: A Probabilistic Approach to Approximate Query Processing	We present EntropyDB, an interactive data exploration system that uses a probabilistic approach to generate a small, query-able summary of a dataset. Departing from traditional summarization techniques, we use the Principle of Maximum Entropy to generate a probabilistic representation of the data that can be used to gi...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	153,124
1906.00041	Table2Vec: Neural Word and Entity Embeddings for Table Population and Retrieval	Tables contain valuable knowledge in a structured form. We employ neural language modeling approaches to embed tabular data into vector spaces. Specifically, we consider different table elements, such caption, column headings, and cells, for training word and entity embeddings. These embeddings are then utilized in thr...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	133,241
2108.04740	Semantics-STGCNN: A Semantics-guided Spatial-Temporal Graph Convolutional Network for Multi-class Trajectory Prediction	Predicting the movement trajectories of multiple classes of road users in real-world scenarios is a challenging task due to the diverse trajectory patterns. While recent works of pedestrian trajectory prediction successfully modelled the influence of surrounding neighbours based on the relative distances, they are inef...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	250,100
1812.01738	Multiview Cross-supervision for Semantic Segmentation	This paper presents a semi-supervised learning framework for a customized semantic segmentation task using multiview image streams. A key challenge of the customized task lies in the limited accessibility of the labeled data due to the requirement of prohibitive manual annotation effort. We hypothesize that it is possi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	115,598
2308.00980	Grasp Stability Assessment Through Attention-Guided Cross-Modality Fusion and Transfer Learning	Extensive research has been conducted on assessing grasp stability, a crucial prerequisite for achieving optimal grasping strategies, including the minimum force grasping policy. However, existing works employ basic feature-level fusion techniques to combine visual and tactile modalities, resulting in the inadequate ut...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	383,100
2407.10226	Addressing Domain Discrepancy: A Dual-branch Collaborative Model to Unsupervised Dehazing	Although synthetic data can alleviate acquisition challenges in image dehazing tasks, it also introduces the problem of domain bias when dealing with small-scale data. This paper proposes a novel dual-branch collaborative unpaired dehazing model (DCM-dehaze) to address this issue. The proposed method consists of two co...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	472,890
2408.17129	Controllable Edge-Type-Specific Interpretation in Multi-Relational Graph Neural Networks for Drug Response Prediction	Graph Neural Networks have been widely applied in critical decision-making areas that demand interpretable predictions, leading to the flourishing development of interpretability algorithms. However, current graph interpretability algorithms tend to emphasize generality and often overlook biological significance, there...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	484,585
2306.17738	The Bridge between Xsens Motion-Capture and Robot Operating System (ROS): Enabling Robots with Online 3D Human Motion Tracking	This document introduces the bridge between the leading inertial motion-capture systems for 3D human tracking and the most used robotics software framework. 3D kinematic data provided by Xsens are translated into ROS messages to make them usable by robots and a Unified Robotics Description Format (URDF) model of the hu...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	376,794
2010.13632	Black-box density function estimation using recursive partitioning	We present a novel approach to Bayesian inference and general Bayesian computation that is defined through a sequential decision loop. Our method defines a recursive partitioning of the sample space. It neither relies on gradients nor requires any problem-specific tuning, and is asymptotically exact for any density fun...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	203,199
2402.11530	Efficient Multimodal Learning from Data-centric Perspective	Multimodal Large Language Models (MLLMs) have demonstrated notable capabilities in general visual understanding and reasoning tasks. However, their deployment is hindered by substantial computational costs in both training and inference, limiting accessibility to the broader research and user communities. A straightfor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	430,442
2502.06023	Dual Caption Preference Optimization for Diffusion Models	Recent advancements in human preference optimization, originally developed for Large Language Models (LLMs), have shown significant potential in improving text-to-image diffusion models. These methods aim to learn the distribution of preferred samples while distinguishing them from less preferred ones. However, existin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	531,885
2010.08684	Example-Driven Intent Prediction with Observers	A key challenge of dialog systems research is to effectively and efficiently adapt to new domains. A scalable paradigm for adaptation necessitates the development of generalizable models that perform well in few-shot settings. In this paper, we focus on the intent classification problem which aims to identify user inte...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	201,260
2304.14300	Learning Absorption Rates in Glucose-Insulin Dynamics from Meal Covariates	Traditional models of glucose-insulin dynamics rely on heuristic parameterizations chosen to fit observations within a laboratory setting. However, these models cannot describe glucose dynamics in daily life. One source of failure is in their descriptions of glucose absorption rates after meal events. A meal's macronut...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	360,890
2403.04526	Hyperspectral unmixing for Raman spectroscopy via physics-constrained autoencoders	Raman spectroscopy is widely used across scientific domains to characterize the chemical composition of samples in a non-destructive, label-free manner. Many applications entail the unmixing of signals from mixtures of molecular species to identify the individual components present and their proportions, yet convention...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	435,633
2502.01787	The Effects of Enterprise Social Media on Communication Networks	Enterprise social media platforms (ESMPs) are web-based platforms with standard social media functionality, e.g., communicating with others, posting links and files, liking content, etc., yet all users are part of the same company. The first contribution of this work is the use of a difference-in-differences analysis o...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	530,032
2006.00842	LFTag: A Scalable Visual Fiducial System with Low Spatial Frequency	Visual fiducial systems are a key component of many robotics and AR/VR applications for 6-DOF monocular relative pose estimation and target identification. This paper presents LFTag, a visual fiducial system based on topological detection and relative position data encoding which optimizes data density within spatial f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	179,587
1910.03496	Fake news detection using Deep Learning	The evolution of the information and communication technologies has dramatically increased the number of people with access to the Internet, which has changed the way the information is consumed. As a consequence of the above, fake news have become one of the major concerns because its potential to destabilize governme...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	148,510
2411.07042	Minion: A Technology Probe for Resolving Value Conflicts through Expert-Driven and User-Driven Strategies in AI Companion Applications	AI companions based on large language models can role-play and converse very naturally. When value conflicts arise between the AI companion and the user, it may offend or upset the user. Yet, little research has examined such conflicts. We first conducted a formative study that analyzed 151 user complaints about confli...	true	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	507,365
2411.17783	KACDP: A Highly Interpretable Credit Default Prediction Model	In the field of finance, the prediction of individual credit default is of vital importance. However, existing methods face problems such as insufficient interpretability and transparency as well as limited performance when dealing with high-dimensional and nonlinear data. To address these issues, this paper introduces...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	511,603
2309.13294	MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo	Significant strides have been made in enhancing the accuracy of Multi-View Stereo (MVS)-based 3D reconstruction. However, untextured areas with unstable photometric consistency often remain incompletely reconstructed. In this paper, we propose a resilient and effective multi-view stereo approach (MP-MVS). We design a m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	394,145
cs/0702149	Coupling Control and Human-Centered Automation in Mathematical Models of Complex Systems	In this paper we analyze mathematically how human factors can be effectively incorporated into the analysis and control of complex systems. As an example, we focus our discussion around one of the key problems in the Intelligent Transportation Systems (ITS) theory and practice, the problem of speed control, considered ...	true	true	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	540,195
2203.06041	Embedding Earth: Self-supervised contrastive pre-training for dense land cover classification	In training machine learning models for land cover semantic segmentation there is a stark contrast between the availability of satellite imagery to be used as inputs and ground truth data to enable supervised learning. While thousands of new satellite images become freely available on a daily basis, getting ground trut...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	284,996
2411.13260	Paying more attention to local contrast: improving infrared small target detection performance via prior knowledge	The data-driven method for infrared small target detection (IRSTD) has achieved promising results. However, due to the small scale of infrared small target datasets and the limited number of pixels occupied by the targets themselves, it is a challenging task for deep learning methods to directly learn from these sample...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	509,733
2005.11770	Longitudinal Deep Kernel Gaussian Process Regression	Gaussian processes offer an attractive framework for predictive modeling from longitudinal data, i.e., irregularly sampled, sparse observations from a set of individuals over time. However, such methods have two key shortcomings: (i) They rely on ad hoc heuristics or expensive trial and error to choose the effective ke...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	178,570
1901.11376	Learning of High Dengue Incidence with Clustering and FP-Growth Algorithm using WHO Historical Data	This paper applies FP-Growth algorithm in mining fuzzy association rules for a prediction system of dengue. The system mines its rules through input of historic predictor variables for dengue. The rules will be used to build a rule-based classifier to predict the dengue incidence for the next month for the years 2001-2...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	120,234
2411.12239	A Control Lyapunov Function Approach to Event-Triggered Parameterized Control for Discrete-Time Linear Systems	This paper proposes an event-triggered parameterized control method using a control Lyapunov function approach for discrete time linear systems with external disturbances. In this control method, each control input to the plant is a linear combination of a fixed set of linearly independent scalar functions. The control...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	509,346
1207.1417	The DLR Hierarchy of Approximate Inference	We propose a hierarchy for approximate inference based on the Dobrushin, Lanford, Ruelle (DLR) equations. This hierarchy includes existing algorithms, such as belief propagation, and also motivates novel algorithms such as factorized neighbors (FN) algorithms and variants of mean field (MF) algorithms. In particular, w...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	17,297
2206.06847	On the Finite-Time Performance of the Knowledge Gradient Algorithm	The knowledge gradient (KG) algorithm is a popular and effective algorithm for the best arm identification (BAI) problem. Due to the complex calculation of KG, theoretical analysis of this algorithm is difficult, and existing results are mostly about the asymptotic performance of it, e.g., consistency, asymptotic sampl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	302,523
2107.04265	Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation	In recent years, formal methods of privacy protection such as differential privacy (DP), capable of deployment to data-driven tasks such as machine learning (ML), have emerged. Reconciling large-scale ML with the closed-form reasoning required for the principled analysis of individual privacy loss requires the introduc...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	245,404
2408.00210	A Prior Embedding-Driven Architecture for Long Distance Blind Iris Recognition	Blind iris images, which result from unknown degradation during the process of iris recognition at long distances, often lead to decreased iris recognition rates. Currently, little existing literature offers a solution to this problem. In response, we propose a prior embedding-driven architecture for long distance blin...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	477,742
2402.16383	Self Supervised Correlation-based Permutations for Multi-View Clustering	Fusing information from different modalities can enhance data analysis tasks, including clustering. However, existing multi-view clustering (MVC) solutions are limited to specific domains or rely on a suboptimal and computationally demanding two-stage procedure of representation and clustering. We propose an end-to-end...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	432,548
1702.07543	Embedding Knowledge Graphs Based on Transitivity and Antisymmetry of Rules	Representation learning of knowledge graphs encodes entities and relation types into a continuous low-dimensional vector space, learns embeddings of entities and relation types. Most existing methods only concentrate on knowledge triples, ignoring logic rules which contain rich background knowledge. Although there has ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	68,803
2407.02877	Resource Allocation Design for Next-Generation Multiple Access: A Tutorial Overview	Multiple access is the cornerstone technology for each generation of wireless cellular networks and resource allocation design plays a crucial role in multiple access. In this paper, we present a comprehensive tutorial overview for junior researchers in this field, aiming to offer a foundational guide for resource allo...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	469,924
2402.19473	Retrieval-Augmented Generation for AI-Generated Content: A Survey	Advancements in model algorithms, the growth of foundational models, and access to high-quality datasets have propelled the evolution of Artificial Intelligence Generated Content (AIGC). Despite its notable successes, AIGC still faces hurdles such as updating knowledge, handling long-tail data, mitigating data leakage,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	433,819
2408.10113	Enhancing Reinforcement Learning Through Guided Search	With the aim of improving performance in Markov Decision Problem in an Off-Policy setting, we suggest taking inspiration from what is done in Offline Reinforcement Learning (RL). In Offline RL, it is a common practice during policy learning to maintain proximity to a reference policy to mitigate uncertainty, reduce pot...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	481,719

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.