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
2002.07528	A Computationally Efficient Neural Network Invariant to the Action of Symmetry Subgroups	We introduce a method to design a computationally efficient $G$-invariant neural network that approximates functions invariant to the action of a given permutation subgroup $G \leq S_n$ of the symmetric group on input data. The key element of the proposed network architecture is a new $G$-invariant transformation modul...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	164,500
2312.09611	Capturing Dynamics in Online Public Discourse: A Case Study of Universal Basic Income Discussions on Reddit	Societal change is often driven by shifts in public opinion. As citizens evolve in their norms, beliefs, and values, public policies change too. While traditional opinion polling and surveys can outline the broad strokes of whether public opinion on a particular topic is changing, they usually cannot capture the full m...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	415,813
2303.10608	A model is worth tens of thousands of examples	Traditional signal processing methods relying on mathematical data generation models have been cast aside in favour of deep neural networks, which require vast amounts of data. Since the theoretical sample complexity is nearly impossible to evaluate, these amounts of examples are usually estimated with crude rules of t...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	352,518
2501.11252	Constant Optimization Driven Database System Testing	Logic bugs are bugs that can cause database management systems (DBMSs) to silently produce incorrect results for given queries. Such bugs are severe, because they can easily be overlooked by both developers and users, and can cause applications that rely on the DBMSs to malfunction. In this work, we propose Constant-Op...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	525,852
2009.01438	Tasks Integrated Networks: Joint Detection and Retrieval for Image Search	The traditional object retrieval task aims to learn a discriminative feature representation with intra-similarity and inter-dissimilarity, which supposes that the objects in an image are manually or automatically pre-cropped exactly. However, in many real-world searching scenarios (e.g., video surveillance), the object...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	194,301
2405.16325	SLoPe: Double-Pruned Sparse Plus Lazy Low-Rank Adapter Pretraining of LLMs	We propose SLoPe, a Double-Pruned Sparse Plus Lazy Low-rank Adapter Pretraining method for LLMs that improves the accuracy of sparse LLMs while accelerating their pretraining and inference and reducing their memory footprint. Sparse pretraining of LLMs reduces the accuracy of the model, to overcome this, prior work use...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	457,359
1906.08083	Linear Complexity of A Family of Binary $pq^2$-periodic Sequences From Euler Quotients	We first introduce a family of binary $pq^2$-periodic sequences based on the Euler quotients modulo $pq$, where $p$ and $q$ are two distinct odd primes and $p$ divides $q-1$. The minimal polynomials and linear complexities are determined for the proposed sequences provided that $2^{q-1} \not\equiv 1 \mod{q^2}.$ The res...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	135,772
1711.01380	Joint Power Allocation and Beamforming for Non-Orthogonal Multiple Access (NOMA) in 5G Millimeter-Wave Communications	In this paper we explore non-orthogonal multiple access (NOMA) in millimeter-wave (mmWave) communications (mmWave-NOMA). In particular, we consider a typical problem, i.e., maximization of the sum rate of a 2-user mmWave-NOMA system. In this problem, we need to find the beamforming vector to steer towards the two users...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	83,872
2307.07099	Controllable Data Augmentation for Few-Shot Text Mining with Chain-of-Thought Attribute Manipulation	Prompting large language models (LLMs) for data augmentation has recently become a common practice in few-shot NLP tasks. In this paper, we propose Chain-of-Thought Attribute Manipulation (CoTAM), a novel approach that generates new data from existing examples by only tweaking in the user-provided, task-specific attrib...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	379,283
2311.08113	Understanding learning from EEG data: Combining machine learning and feature engineering based on hidden Markov models and mixed models	Theta oscillations, ranging from 4-8 Hz, play a significant role in spatial learning and memory functions during navigation tasks. Frontal theta oscillations are thought to play an important role in spatial navigation and memory. Electroencephalography (EEG) datasets are very complex, making any changes in the neural s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	407,594
2203.15850	Fault Detection and Isolation of Uncertain Nonlinear Parabolic PDE Systems	This paper proposes a novel fault detection and isolation (FDI) scheme for distributed parameter systems modeled by a class of parabolic partial differential equations (PDEs) with nonlinear uncertain dynamics. A key feature of the proposed FDI scheme is its capability of dealing with the effects of system uncertainties...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	288,558
1804.04849	The unreasonable effectiveness of the forget gate	Given the success of the gated recurrent unit, a natural question is whether all the gates of the long short-term memory (LSTM) network are necessary. Previous research has shown that the forget gate is one of the most important gates in the LSTM. Here we show that a forget-gate-only version of the LSTM with chrono-ini...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	94,951
2007.06324	TrustNet: Learning from Trusted Data Against (A)symmetric Label Noise	Robustness to label noise is a critical property for weakly-supervised classifiers trained on massive datasets. Robustness to label noise is a critical property for weakly-supervised classifiers trained on massive datasets. In this paper, we first derive analytical bound for any given noise patterns. Based on the insig...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	186,983
2001.08681	Bayesian estimates of transmission line outage rates that consider line dependencies	Transmission line outage rates are fundamental to power system reliability analysis. Line outages are infrequent, occurring only about once a year, so outage data are limited. We propose a Bayesian hierarchical model that leverages line dependencies to better estimate outage rates of individual transmission lines from ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	161,355
1012.0009	Time-Varying Graphs and Dynamic Networks	The past few years have seen intensive research efforts carried out in some apparently unrelated areas of dynamic systems -- delay-tolerant networks, opportunistic-mobility networks, social networks -- obtaining closely related insights. Indeed, the concepts discovered in these investigations can be viewed as parts of ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	8,373
2412.14119	Learning and Reconstructing Conflicts in O-RAN: A Graph Neural Network Approach	The Open Radio Access Network (O-RAN) architecture enables the deployment of third-party applications on the RAN Intelligent Controllers (RICs). However, the operation of third-party applications in the Near Real-Time RIC (Near-RT RIC), known as xApps, may result in conflicting interactions. Each xApp can independently...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	518,579
1607.04833	Belief propagation decoding of quantum channels by passing quantum messages	Belief propagation is a powerful tool in statistical physics, machine learning, and modern coding theory. As a decoding method, it is ubiquitous in classical error correction and has also been applied to stabilizer-based quantum error correction. The algorithm works by passing messages between nodes of the factor graph...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	58,676
2105.03170	FedGL: Federated Graph Learning Framework with Global Self-Supervision	Graph data are ubiquitous in the real world. Graph learning (GL) tries to mine and analyze graph data so that valuable information can be discovered. Existing GL methods are designed for centralized scenarios. However, in practical scenarios, graph data are usually distributed in different organizations, i.e., the curs...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	234,066
2002.08772	Set2Graph: Learning Graphs From Sets	Many problems in machine learning can be cast as learning functions from sets to graphs, or more generally to hypergraphs; in short, Set2Graph functions. Examples include clustering, learning vertex and edge features on graphs, and learning features on triplets in a collection. A natural approach for building Set2Graph...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	164,857
2401.07074	Detachment Problem -- Application in Prevention of Information Leakage in Stock Markets	In this paper, we introduce the Detachment Problem. It can be seen as a generalized Vaccination Problem. The aim is to optimally cut the individuals' ties to circles that connect them to others, to minimize the overall information transfer in a social network. When an individual is isolated from a particular circle, it...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	421,410
2411.02385	How Far is Video Generation from World Model: A Physical Law Perspective	OpenAI's Sora highlights the potential of video generation for developing world models that adhere to fundamental physical laws. However, the ability of video generation models to discover such laws purely from visual data without human priors can be questioned. A world model learning the true law should give predictio...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	505,465
2302.10756	Unsupervised Seismic Footprint Removal With Physical Prior Augmented Deep Autoencoder	Seismic acquisition footprints appear as stably faint and dim structures and emerge fully spatially coherent, causing inevitable damage to useful signals during the suppression process. Various footprint removal methods, including filtering and sparse representation (SR), have been reported to attain promising results ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	346,928
2301.04545	AdaPoinTr: Diverse Point Cloud Completion with Adaptive Geometry-Aware Transformers	In this paper, we present a new method that reformulates point cloud completion as a set-to-set translation problem and design a new model, called PoinTr, which adopts a Transformer encoder-decoder architecture for point cloud completion. By representing the point cloud as a set of unordered groups of points with posit...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	340,096
2012.03234	Amortized Q-learning with Model-based Action Proposals for Autonomous Driving on Highways	Well-established optimization-based methods can guarantee an optimal trajectory for a short optimization horizon, typically no longer than a few seconds. As a result, choosing the optimal trajectory for this short horizon may still result in a sub-optimal long-term solution. At the same time, the resulting short-term t...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	210,042
2403.09975	Skeleton-Based Human Action Recognition with Noisy Labels	Understanding human actions from body poses is critical for assistive robots sharing space with humans in order to make informed and safe decisions about the next interaction. However, precise temporal localization and annotation of activity sequences is time-consuming and the resulting labels are often noisy. If not e...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	437,983
2405.04664	Proximal Policy Optimization with Adaptive Exploration	Proximal Policy Optimization with Adaptive Exploration (axPPO) is introduced as a novel learning algorithm. This paper investigates the exploration-exploitation tradeoff within the context of reinforcement learning and aims to contribute new insights into reinforcement learning algorithm design. The proposed adaptive e...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	452,632
1709.05581	MultiNet: Multi-Modal Multi-Task Learning for Autonomous Driving	Autonomous driving requires operation in different behavioral modes ranging from lane following and intersection crossing to turning and stopping. However, most existing deep learning approaches to autonomous driving do not consider the behavioral mode in the training strategy. This paper describes a technique for lear...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	80,908
2301.04650	Geometry-biased Transformers for Novel View Synthesis	We tackle the task of synthesizing novel views of an object given a few input images and associated camera viewpoints. Our work is inspired by recent 'geometry-free' approaches where multi-view images are encoded as a (global) set-latent representation, which is then used to predict the color for arbitrary query rays. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	340,132
2309.10431	Sample-adaptive Augmentation for Point Cloud Recognition Against Real-world Corruptions	Robust 3D perception under corruption has become an essential task for the realm of 3D vision. While current data augmentation techniques usually perform random transformations on all point cloud objects in an offline way and ignore the structure of the samples, resulting in over-or-under enhancement. In this work, we ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	393,009
2207.08466	What does Transformer learn about source code?	In the field of source code processing, the transformer-based representation models have shown great powerfulness and have achieved state-of-the-art (SOTA) performance in many tasks. Although the transformer models process the sequential source code, pieces of evidence show that they may capture the structural informat...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	308,600
1301.2342	A Linear Time Algorithm for the Feasibility of Pebble Motion on Graphs	Given a connected, undirected, simple graph $G = (V, E)$ and $p \le \|V\|$ pebbles labeled $1,..., p$, a configuration of these $p$ pebbles is an injective map assigning the pebbles to vertices of $G$. Let $S$ and $D$ be two such configurations. From a configuration, pebbles can move on $G$ as follows: In each step, at m...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	20,997
2108.00320	StudyMe: A New Mobile App for User-Centric N-of-1 Trials	N-of-1 trials are multi-crossover self-experiments that allow individuals to systematically evaluate the effect of interventions on their personal health goals. Although several tools for N-of-1 trials exist, none support non-experts in conducting their own user-centric trials. In this study we present StudyMe, an open...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	248,670
2502.06877	WirelessGPT: A Generative Pre-trained Multi-task Learning Framework for Wireless Communication	This paper introduces WirelessGPT, a pioneering foundation model specifically designed for multi-task learning in wireless communication and sensing. Specifically, WirelessGPT leverages large-scale wireless channel datasets for unsupervised pretraining and extracting universal channel representations, which captures co...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	532,317
2006.11070	HPRA: Hyperedge Prediction using Resource Allocation	Many real-world systems involve higher-order interactions and thus demand complex models such as hypergraphs. For instance, a research article could have multiple collaborating authors, and therefore the co-authorship network is best represented as a hypergraph. In this work, we focus on the problem of hyperedge predic...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	183,094
1505.06311	Tracking Human Mobility using WiFi signals	We study six months of human mobility data, including WiFi and GPS traces recorded with high temporal resolution, and find that time series of WiFi scans contain a strong latent location signal. In fact, due to inherent stability and low entropy of human mobility, it is possible to assign location to WiFi access points...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	43,408
2404.08691	Enhancing Adaptive Video Streaming through Fuzzy Logic-Based Content Recommendation Systems: A Comprehensive Review and Future Directions	As the demand for high-quality video content continues to rise, adaptive video streaming plays a pivotal role in delivering an optimal viewing experience. However, traditional content recommendation systems face challenges in dynamically adapting to users' preferences, content features, and contextual information. This...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	446,356
1908.02589	How weaponizing disinformation can bring down a city's power grid	Social technologies have made it possible to propagate disinformation and manipulate the masses at an unprecedented scale. This is particularly alarming from a security perspective, as humans have proven to be the weakest link when protecting critical infrastructure in general, and the power grid in particular. Here, w...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	141,043
2101.05136	Leveraging Structured Biological Knowledge for Counterfactual Inference: a Case Study of Viral Pathogenesis	Counterfactual inference is a useful tool for comparing outcomes of interventions on complex systems. It requires us to represent the system in form of a structural causal model, complete with a causal diagram, probabilistic assumptions on exogenous variables, and functional assignments. Specifying such models can be e...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	215,342
2012.05462	Cold-start Sequential Recommendation via Meta Learner	This paper explores meta-learning in sequential recommendation to alleviate the item cold-start problem. Sequential recommendation aims to capture user's dynamic preferences based on historical behavior sequences and acts as a key component of most online recommendation scenarios. However, most previous methods have tr...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	210,793
1609.02228	Learning to learn with backpropagation of Hebbian plasticity	Hebbian plasticity is a powerful principle that allows biological brains to learn from their lifetime experience. By contrast, artificial neural networks trained with backpropagation generally have fixed connection weights that do not change once training is complete. While recent methods can endow neural networks with...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	60,706
1706.04318	Hierarchical Gaussian Descriptors with Application to Person Re-Identification	Describing the color and textural information of a person image is one of the most crucial aspects of person re-identification (re-id). In this paper, we present novel meta-descriptors based on a hierarchical distribution of pixel features. Although hierarchical covariance descriptors have been successfully applied to ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	75,324
1412.3247	Towards Robot-independent Manipulation Behavior Description	In this paper we present a workflow to design and control robot manipulation behavior. To remain independent from particular robot hardware and an explicit area of application, an embedded domain specific language (eDSL) is used to describe the particular robot and a controller network that drives the robot. We make us...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	38,280
2111.10372	Resistance-Time Co-Modulated PointNet for Temporal Super-Resolution Simulation of Blood Vessel Flows	In this paper, a novel deep learning framework is proposed for temporal super-resolution simulation of blood vessel flows, in which a high-temporal-resolution time-varying blood vessel flow simulation is generated from a low-temporal-resolution flow simulation result. In our framework, point-cloud is used to represent ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	267,300
2412.17254	Enhancing Multi-Text Long Video Generation Consistency without Tuning: Time-Frequency Analysis, Prompt Alignment, and Theory	Despite the considerable progress achieved in the long video generation problem, there is still significant room to improve the consistency of the videos, particularly in terms of smoothness and transitions between scenes. We address these issues to enhance the consistency and coherence of videos generated with either ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	519,892
2406.04578	SC2: Towards Enhancing Content Preservation and Style Consistency in Long Text Style Transfer	Text style transfer (TST) aims to vary the style polarity of text while preserving the semantic content. Although recent advancements have demonstrated remarkable progress in short TST, it remains a relatively straightforward task with limited practical applications. The more comprehensive long TST task presents two ch...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	461,740
2305.15003	Feasible Action-Space Reduction as a Metric of Causal Responsibility in Multi-Agent Spatial Interactions	Modelling causal responsibility in multi-agent spatial interactions is crucial for safety and efficiency of interactions of humans with autonomous agents. However, current formal metrics and models of responsibility either lack grounding in ethical and philosophical concepts of responsibility, or cannot be applied to s...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	367,386
2308.07279	A Robust Image Forensic Framework Utilizing Multi-Colorspace Enriched Vision Transformer for Distinguishing Natural and Computer-Generated Images	The digital image forensics based research works in literature classifying natural and computer generated images primarily focuses on binary tasks. These tasks typically involve the classification of natural images versus computer graphics images only or natural images versus GAN generated images only, but not natural ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	385,453
1411.7973	Bus Travel Time Predictions Using Additive Models	Many factors can affect the predictability of public bus services such as traffic, weather and local events. Other aspects, such as day of week or hour of day, may influence bus travel times as well, either directly or in conjunction with other variables. However, the exact nature of such relationships between travel t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	37,982
1808.09016	Review Helpfulness Assessment based on Convolutional Neural Network	In this paper we describe the implementation of a convolutional neural network (CNN) used to assess online review helpfulness. To our knowledge, this is the first use of this architecture to address this problem. We explore the impact of two related factors impacting CNN performance: different word embedding initializa...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	106,086
2306.14511	TaylorPDENet: Learning PDEs from non-grid Data	Modeling data obtained from dynamical systems has gained attention in recent years as a challenging task for machine learning models. Previous approaches assume the measurements to be distributed on a grid. However, for real-world applications like weather prediction, the observations are taken from arbitrary locations...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	375,709
2409.10669	Realistic Extreme Behavior Generation for Improved AV Testing	This work introduces a framework to diagnose the strengths and shortcomings of Autonomous Vehicle (AV) collision avoidance technology with synthetic yet realistic potential collision scenarios adapted from real-world, collision-free data. Our framework generates counterfactual collisions with diverse crash properties, ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	488,835
1310.7442	Ranking basic belief assignments in decision making under uncertain environment	Dempster-Shafer theory (D-S theory) is widely used in decision making under the uncertain environment. Ranking basic belief assignments (BBAs) now is an open issue. Existing evidence distance measures cannot rank the BBAs in the situations when the propositions have their own ranking order or their inherent measure of ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	28,037
2305.15115	Semantic-Enhanced Differentiable Search Index Inspired by Learning Strategies	Recently, a new paradigm called Differentiable Search Index (DSI) has been proposed for document retrieval, wherein a sequence-to-sequence model is learned to directly map queries to relevant document identifiers. The key idea behind DSI is to fully parameterize traditional ``index-retrieve'' pipelines within a single ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	367,463
2312.11934	Identification of Causal Structure with Latent Variables Based on Higher Order Cumulants	Causal discovery with latent variables is a crucial but challenging task. Despite the emergence of numerous methods aimed at addressing this challenge, they are not fully identified to the structure that two observed variables are influenced by one latent variable and there might be a directed edge in between. Interest...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	416,786
2008.06220	Kernel Methods for Cooperative Multi-Agent Contextual Bandits	Cooperative multi-agent decision making involves a group of agents cooperatively solving learning problems while communicating over a network with delays. In this paper, we consider the kernelised contextual bandit problem, where the reward obtained by an agent is an arbitrary linear function of the contexts' images in...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	191,735
2408.01612	Data-Driven Machine Learning Approaches for Predicting In-Hospital Sepsis Mortality	Sepsis is a severe condition responsible for many deaths in the United States and worldwide, making accurate prediction of outcomes crucial for timely and effective treatment. Previous studies employing machine learning faced limitations in feature selection and model interpretability, reducing their clinical applicabi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	478,299
2410.06321	An Algorithm for Distributed Computation of Reachable Sets for Multi-Agent Systems	In this paper, we consider the problem of distributed reachable set computation for multi-agent systems (MASs) interacting over an undirected, stationary graph. A full state-feedback control input for such MASs depends no only on the current agent's state, but also of its neighbors. However, in most MAS applications, t...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	496,143
2312.00099	Online Influence Maximization: Concept and Algorithm	In this survey, we offer an extensive overview of the Online Influence Maximization (IM) problem by covering both theoretical aspects and practical applications. For the integrity of the article and because the online algorithm takes an offline oracle as a subroutine, we first make a clear definition of the Offline IM ...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	411,913
1712.00552	An Enhanced LMMSE Channel Estimation under High Speed Railway Scenarios	With the rapid deployment of the high speed railway (HSR), the wireless communication in HSR has been one of the indispensable scenarios in the fifth generation (5G) communications. In order to improve the performance of the orthogonal frequency division multiplexing (OFDM) system in the HSR scenarios, we propose an en...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	85,923
2407.01355	Hyperspectral Pansharpening: Critical Review, Tools and Future Perspectives	Hyperspectral pansharpening consists of fusing a high-resolution panchromatic band and a low-resolution hyperspectral image to obtain a new image with high resolution in both the spatial and spectral domains. These remote sensing products are valuable for a wide range of applications, driving ever growing research effo...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	469,259
1203.0096	Joint Estimation of Angle and Delay of Radio Wave Arrival under Multiplicative Noise Environment	We propose a novel technique for joint estimation of angle and delay of radio wave arrival in a multipath mobile communication channel using knowledge of the transmitted pulse shape function. Employing an array of sensors to sample the radio received signal, and subsequent array signal processing can provide the charac...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	14,674
2110.09005	Unsupervised Learned Kalman Filtering	In this paper we adapt KalmanNet, which is a recently pro-posed deep neural network (DNN)-aided system whose architecture follows the operation of the model-based Kalman filter (KF), to learn its mapping in an unsupervised manner, i.e., without requiring ground-truth states. The unsupervised adaptation is achieved by e...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	261,644
2112.01609	Probabilistic Tracking with Deep Factors	In many applications of computer vision it is important to accurately estimate the trajectory of an object over time by fusing data from a number of sources, of which 2D and 3D imagery is only one. In this paper, we show how to use a deep feature encoding in conjunction with generative densities over the features in a ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	269,548
2406.12384	VRSBench: A Versatile Vision-Language Benchmark Dataset for Remote Sensing Image Understanding	We introduce a new benchmark designed to advance the development of general-purpose, large-scale vision-language models for remote sensing images. Although several vision-language datasets in remote sensing have been proposed to pursue this goal, existing datasets are typically tailored to single tasks, lack detailed o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	465,377
1909.08181	Self-boosted Time-series Forecasting with Multi-task and Multi-view Learning	A robust model for time series forecasting is highly important in many domains, including but not limited to financial forecast, air temperature and electricity consumption. To improve forecasting performance, traditional approaches usually require additional feature sets. However, adding more feature sets from differe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	145,891
2409.16444	Artificial Intelligence for Secured Information Systems in Smart Cities: Collaborative IoT Computing with Deep Reinforcement Learning and Blockchain	The accelerated expansion of the Internet of Things (IoT) has raised critical challenges associated with privacy, security, and data integrity, specifically in infrastructures such as smart cities or smart manufacturing. Blockchain technology provides immutable, scalable, and decentralized solutions to address these ch...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	491,343
1707.02591	Flexible human-robot cooperation models for assisted shop-floor tasks	The Industry 4.0 paradigm emphasizes the crucial benefits that collaborative robots, i.e., robots able to work alongside and together with humans, could bring to the whole production process. In this context, an enabling technology yet unreached is the design of flexible robots able to deal at all levels with humans' i...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	76,730
1901.00150	Accelerated MM Algorithms for Ranking Scores Inference from Comparison Data	In this paper, we study a popular method for inference of the Bradley-Terry model parameters, namely the MM algorithm, for maximum likelihood estimation and maximum a posteriori probability estimation. This class of models includes the Bradley-Terry model of paired comparisons, the Rao-Kupper model of paired comparison...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	117,704
1709.04553	MOLTE: a Modular Optimal Learning Testing Environment	We address the relative paucity of empirical testing of learning algorithms (of any type) by introducing a new public-domain, Modular, Optimal Learning Testing Environment (MOLTE) for Bayesian ranking and selection problem, stochastic bandits or sequential experimental design problems. The Matlab-based simulator allows...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	80,684
2202.08774	mmWave Communications for Indoor Dense Spaces: Ray-Tracing Based Channel Characterization and Performance Comparison	In this paper, the indoor dense space (IDS) channel at 28 GHz is characterized through extensive Ray-Tracing (RT) simulations. We consider IDS as a specific type of indoor environment with confined geometry and packed with humans, such as aircraft cabins and train wagons. Based on RT simulations, we characterize path l...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	280,981
2109.05173	Making Table Understanding Work in Practice	Understanding the semantics of tables at scale is crucial for tasks like data integration, preparation, and search. Table understanding methods aim at detecting a table's topic, semantic column types, column relations, or entities. With the rise of deep learning, powerful models have been developed for these tasks with...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	254,686
1705.02304	Deep Speaker: an End-to-End Neural Speaker Embedding System	We present Deep Speaker, a neural speaker embedding system that maps utterances to a hypersphere where speaker similarity is measured by cosine similarity. The embeddings generated by Deep Speaker can be used for many tasks, including speaker identification, verification, and clustering. We experiment with ResCNN and G...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	72,968
2107.11517	Crosslink-Net: Double-branch Encoder Segmentation Network via Fusing Vertical and Horizontal Convolutions	Accurate image segmentation plays a crucial role in medical image analysis, yet it faces great challenges of various shapes, diverse sizes, and blurry boundaries. To address these difficulties, square kernel-based encoder-decoder architecture has been proposed and widely used, but its performance remains still unsatisf...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	247,610
2306.07104	Unveiling the Hessian's Connection to the Decision Boundary	Understanding the properties of well-generalizing minima is at the heart of deep learning research. On the one hand, the generalization of neural networks has been connected to the decision boundary complexity, which is hard to study in the high-dimensional input space. Conversely, the flatness of a minimum has become ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	372,880
2106.15844	Bounded rationality for relaxing best response and mutual consistency: The Quantal Hierarchy model of decision-making	While game theory has been transformative for decision-making, the assumptions made can be overly restrictive in certain instances. In this work, we investigate some of the underlying assumptions of rationality, such as mutual consistency and best response, and consider ways to relax these assumptions using concepts fr...	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	true	243,892
2501.03026	Putnam's Critical and Explanatory Tendencies Interpreted from a Machine Learning Perspective	Making sense of theory choice in normal and across extraordinary science is central to philosophy of science. The emergence of machine learning models has the potential to act as a wrench in the gears of current debates. In this paper, I will attempt to reconstruct the main movements that lead to and came out of Putnam...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	522,734
1801.02563	Information Theoretic Security for Side-Channel Attacks to the Shannon Cipher System	We study side-channel attacks for the Shannon cipher system. To pose side channel-attacks to the Shannon cipher system, we regard them as a signal estimation via encoded data from two distributed sensors. This can be formulated as the one helper source coding problem posed and investigated by Ahlswede, K\"orner(1975), ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	87,942
1907.12900	Slot Based Image Augmentation System for Object Detection	Object Detection has been a significant topic in computer vision. As the continuous development of Deep Learning, many advanced academic and industrial outcomes are established on localising and classifying the target objects, such as instance segmentation, video tracking and robotic vision. As the core concept of Deep...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	140,229
2208.09703	SnowFormer: Context Interaction Transformer with Scale-awareness for Single Image Desnowing	Due to various and complicated snow degradations, single image desnowing is a challenging image restoration task. As prior arts can not handle it ideally, we propose a novel transformer, SnowFormer, which explores efficient cross-attentions to build local-global context interaction across patches and surpasses existing...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	313,805
2411.08320	Responsible AI in Construction Safety: Systematic Evaluation of Large Language Models and Prompt Engineering	Construction remains one of the most hazardous sectors. Recent advancements in AI, particularly Large Language Models (LLMs), offer promising opportunities for enhancing workplace safety. However, responsible integration of LLMs requires systematic evaluation, as deploying them without understanding their capabilities ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	507,844
2201.10444	AggMatch: Aggregating Pseudo Labels for Semi-Supervised Learning	Semi-supervised learning (SSL) has recently proven to be an effective paradigm for leveraging a huge amount of unlabeled data while mitigating the reliance on large labeled data. Conventional methods focused on extracting a pseudo label from individual unlabeled data sample and thus they mostly struggled to handle inac...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	276,996
2310.12274	An Image is Worth Multiple Words: Discovering Object Level Concepts using Multi-Concept Prompt Learning	Textural Inversion, a prompt learning method, learns a singular text embedding for a new "word" to represent image style and appearance, allowing it to be integrated into natural language sentences to generate novel synthesised images. However, identifying multiple unknown object-level concepts within one scene remains...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	true	400,955
2103.05706	A sampling criterion for constrained Bayesian optimization with uncertainties	We consider the problem of chance constrained optimization where it is sought to optimize a function and satisfy constraints, both of which are affected by uncertainties. The real world declinations of this problem are particularly challenging because of their inherent computational cost. To tackle such problems, we ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	224,059
1906.08598	Companion Surface of Danger Cylinder and its Role in Solution Variation of P3P Problem	Traditionally the danger cylinder is intimately related to the solution stability in P3P problem. In this work, we show that the danger cylinder is also closely related to the multiple-solution phenomenon. More specifically, we show when the optical center lies on the danger cylinder, of the 3 possible P3P solutions, i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	135,915
2304.05979	NaviSTAR: Socially Aware Robot Navigation with Hybrid Spatio-Temporal Graph Transformer and Preference Learning	Developing robotic technologies for use in human society requires ensuring the safety of robots' navigation behaviors while adhering to pedestrians' expectations and social norms. However, maintaining real-time communication between robots and pedestrians to avoid collisions can be challenging. To address these challen...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	357,803
1005.4877	Set-Monotonicity Implies Kelly-Strategyproofness	This paper studies the strategic manipulation of set-valued social choice functions according to Kelly's preference extension, which prescribes that one set of alternatives is preferred to another if and only if all elements of the former are preferred to all elements of the latter. It is shown that set-monotonicity---...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	6,575
1304.1514	A Decision-Theoretic Model for Using Scientific Data	Many Artificial Intelligence systems depend on the agent's updating its beliefs about the world on the basis of experience. Experiments constitute one type of experience, so scientific methodology offers a natural environment for examining the issues attendant to using this class of evidence. This paper presents a fram...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	23,547
1909.11813	LAVAE: Disentangling Location and Appearance	We propose a probabilistic generative model for unsupervised learning of structured, interpretable, object-based representations of visual scenes. We use amortized variational inference to train the generative model end-to-end. The learned representations of object location and appearance are fully disentangled, and ob...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	146,919
2305.07497	Dynamically Conservative Self-Driving Planner for Long-Tail Cases	Self-driving vehicles (SDVs) are becoming reality but still suffer from "long-tail" challenges during natural driving: the SDVs will continually encounter rare, safety-critical cases that may not be included in the dataset they were trained. Some safety-assurance planners solve this problem by being conservative in all...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	363,920
1811.05397	Algorithms for Optimal AC Power Flow in the Presence of Renewable Sources	This chapter presents recent solutions to the optimal power flow (OPF) problem in the presence of renewable energy sources (RES), {such} as solar photo-voltaic and wind generation. After introducing the original formulation of the problem, arising from the combination of economic dispatch and power flow, we provide a b...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	113,307
1204.2356	Self-Adaptive Surrogate-Assisted Covariance Matrix Adaptation Evolution Strategy	This paper presents a novel mechanism to adapt surrogate-assisted population-based algorithms. This mechanism is applied to ACM-ES, a recently proposed surrogate-assisted variant of CMA-ES. The resulting algorithm, saACM-ES, adjusts online the lifelength of the current surrogate model (the number of CMA-ES generations ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	15,405
2303.01506	Understanding and Unifying Fourteen Attribution Methods with Taylor Interactions	Various attribution methods have been developed to explain deep neural networks (DNNs) by inferring the attribution/importance/contribution score of each input variable to the final output. However, existing attribution methods are often built upon different heuristics. There remains a lack of a unified theoretical und...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	348,998
2402.04423	Smart Pipe System for a Shipyard 4.0	As a result of the progressive implantation of the Industry 4.0 paradigm, many industries are experimenting a revolution that shipyards cannot ignore. Therefore, the application of the principles of Industry 4.0 to shipyards are leading to the creation of Shipyards 4.0. Due to this, Navantia, one of the 10 largest ship...	false	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	427,445
1604.01745	Distributed Synthesis of State-Dependent Switching Control	We present a correct-by-design method of state-dependent control synthesis for linear discrete-time switching systems. Given an objective region R of the state space, the method builds a capture set S and a control which steers any element of S into R. The method works by iterated backward reachability from R. More pre...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	54,235
2211.02243	Mixline: A Hybrid Reinforcement Learning Framework for Long-horizon Bimanual Coffee Stirring Task	Bimanual activities like coffee stirring, which require coordination of dual arms, are common in daily life and intractable to learn by robots. Adopting reinforcement learning to learn these tasks is a promising topic since it enables the robot to explore how dual arms coordinate together to accomplish the same task. H...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	328,520
1604.07671	A Generic Transformation to Enable Optimal Repair in MDS Codes for Distributed Storage Systems	We propose a generic transformation that can convert any nonbinary $(n=k+r,k)$ maximum distance separable (MDS) code into another $(n,k)$ MDS code over the same field such that 1) some arbitrarily chosen $r$ nodes have the optimal repair bandwidth and the optimal rebuilding access, 2) for the remaining $k$ nodes, the n...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	55,120
2406.12403	PDSS: A Privacy-Preserving Framework for Step-by-Step Distillation of Large Language Models	In the context of real-world applications, leveraging large language models (LLMs) for domain-specific tasks often faces two major challenges: domain-specific knowledge privacy and constrained resources. To address these issues, we propose PDSS, a privacy-preserving framework for step-by-step distillation of LLMs. PDSS...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	465,386
1604.08934	An expressive dissimilarity measure for relational clustering using neighbourhood trees	Clustering is an underspecified task: there are no universal criteria for what makes a good clustering. This is especially true for relational data, where similarity can be based on the features of individuals, the relationships between them, or a mix of both. Existing methods for relational clustering have strong and ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	55,277
1404.7170	Temporal stability of network partitions	We present a method to find the best temporal partition at any time-scale and rank the relevance of partitions found at different time-scales. This method is based on random walkers coevolving with the network and as such constitutes a generalization of partition stability to the case of temporal networks. We show that...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	32,669
2204.09658	Generative Design Ideation: A Natural Language Generation Approach	This paper aims to explore a generative approach for knowledge-based design ideation by applying the latest pre-trained language models in artificial intelligence (AI). Specifically, a method of fine-tuning the generative pre-trained transformer using the USPTO patent database is proposed. The AI-generated ideas are no...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	292,517

Subsets and Splits

No community queries yet

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