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
2306.14905	PRISMA-DFLLM: An Extension of PRISMA for Systematic Literature Reviews using Domain-specific Finetuned Large Language Models	With the proliferation of open-sourced Large Language Models (LLMs) and efficient finetuning techniques, we are on the cusp of the emergence of numerous domain-specific LLMs that have been finetuned for expertise across specialized fields and applications for which the current general-purpose LLMs are unsuitable. In ac...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	375,858
1905.03239	Generative Model with Dynamic Linear Flow	Flow-based generative models are a family of exact log-likelihood models with tractable sampling and latent-variable inference, hence conceptually attractive for modeling complex distributions. However, flow-based models are limited by density estimation performance issues as compared to state-of-the-art autoregressive...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	130,156
1704.00102	Gradient Flows in Uncertainty Propagation and Filtering of Linear Gaussian Systems	The purpose of this work is mostly expository and aims to elucidate the Jordan-Kinderlehrer-Otto (JKO) scheme for uncertainty propagation, and a variant, the Laugesen-Mehta-Meyn-Raginsky (LMMR) scheme for filtering. We point out that these variational schemes can be understood as proximal operators in the space of dens...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	71,023
2112.13319	Quantum Algorithm for the Shortest Superstring Problem	In this paper, we consider the ``Shortest Superstring Problem''(SSP) or the ``Shortest Common Superstring Problem''(SCS). The problem is as follows. For a positive integer $n$, a sequence of n strings $S=(s^1,\dots,s^n)$ is given. We should construct the shortest string $t$ (we call it superstring) that contains each s...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	273,207
2307.04780	Comparison of Point Cloud and Image-based Models for Calorimeter Fast Simulation	Score based generative models are a new class of generative models that have been shown to accurately generate high dimensional calorimeter datasets. Recent advances in generative models have used images with 3D voxels to represent and model complex calorimeter showers. Point clouds, however, are likely a more natural ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	378,519
1903.00117	A Sketch Based 3D Shape Retrieval Approach Based on Efficient Deep Point-to-Subspace Metric Learning	A sketch based 3D shape retrieval	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	122,947
2211.13264	Distilling Knowledge from Self-Supervised Teacher by Embedding Graph Alignment	Recent advances have indicated the strengths of self-supervised pre-training for improving representation learning on downstream tasks. Existing works often utilize self-supervised pre-trained models by fine-tuning on downstream tasks. However, fine-tuning does not generalize to the case when one needs to build a custo...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	332,412
1909.00031	Interactive Task and Concept Learning from Natural Language Instructions and GUI Demonstrations	Natural language programming is a promising approach to enable end users to instruct new tasks for intelligent agents. However, our formative study found that end users would often use unclear, ambiguous or vague concepts when naturally instructing tasks in natural language, especially when specifying conditionals. Exi...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	143,500
2402.07445	Top-$K$ ranking with a monotone adversary	In this paper, we address the top-$K$ ranking problem with a monotone adversary. We consider the scenario where a comparison graph is randomly generated and the adversary is allowed to add arbitrary edges. The statistician's goal is then to accurately identify the top-$K$ preferred items based on pairwise comparisons d...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	428,723
2310.09040	Optimal Scheduling of Electric Vehicle Charging with Deep Reinforcement Learning considering End Users Flexibility	The rapid growth of decentralized energy resources and especially Electric Vehicles (EV), that are expected to increase sharply over the next decade, will put further stress on existing power distribution networks, increasing the need for higher system reliability and flexibility. In an attempt to avoid unnecessary net...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	399,633
2406.14902	Zero-one laws for events with positional symmetries	We use an information-theoretic argument due to O'Connell (2000) to prove that every sufficiently symmetric event concerning a countably infinite family of independent and identically distributed random variables is deterministic (i.e., has a probability of either 0 or 1). The i.i.d. condition can be relaxed. This resu...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	466,527
1808.02911	A Case Study on the Impact of Similarity Measure on Information Retrieval based Software Engineering Tasks	Information Retrieval (IR) plays a pivotal role in diverse Software Engineering (SE) tasks, e.g., bug localization and triaging, code retrieval, requirements analysis, etc. The choice of similarity measure is the core component of an IR technique. The performance of any IR method critically depends on selecting an appr...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	104,847
2105.10668	Runtime Enforcement of Programmable Logic Controllers	With the advent of Industry 4.0, industrial facilities and critical infrastructures are transforming into an ecosystem of heterogeneous physical and cyber components, such as programmable logic controllers, increasingly interconnected and therefore exposed to cyber-physical attacks, i.e., security breaches in cyberspac...	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	true	236,463
2502.01477	Position: Empowering Time Series Reasoning with Multimodal LLMs	Understanding time series data is crucial for multiple real-world applications. While large language models (LLMs) show promise in time series tasks, current approaches often rely on numerical data alone, overlooking the multimodal nature of time-dependent information, such as textual descriptions, visual data, and aud...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	529,873
2407.20197	Learning Random Numbers to Realize Appendable Memory System for Artificial Intelligence to Acquire New Knowledge after Deployment	In this study, we developed a learning method for constructing a neural network system capable of memorizing data and recalling it without parameter updates. The system we built using this method is called the Appendable Memory system. The Appendable Memory system enables an artificial intelligence (AI) to acquire new ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	477,081
2104.08781	Monte Carlo Elites: Quality-Diversity Selection as a Multi-Armed Bandit Problem	A core challenge of evolutionary search is the need to balance between exploration of the search space and exploitation of highly fit regions. Quality-diversity search has explicitly walked this tightrope between a population's diversity and its quality. This paper extends a popular quality-diversity search algorithm, ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	230,976
1207.6180	A Unified Approach of Observability Analysis for Airborne SLAM	Observability is a key aspect of the state estimation problem of SLAM, However, the dimension and variables of SLAM system might be changed with new features, to which little attention is paid in the previous work. In this paper, a unified approach of observability analysis for SLAM system is provided, whether the dime...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	17,771
2412.04413	Efficient Task Grouping Through Samplewise Optimisation Landscape Analysis	Shared training approaches, such as multi-task learning (MTL) and gradient-based meta-learning, are widely used in various machine learning applications, but they often suffer from negative transfer, leading to performance degradation in specific tasks. While several optimisation techniques have been developed to mitig...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	514,390
1001.2806	MIMO Gaussian Broadcast Channels with Confidential and Common Messages	This paper considers the problem of secret communication over a two-receiver multiple-input multiple-output (MIMO) Gaussian broadcast channel. The transmitter has two independent, confidential messages and a common message. Each of the confidential messages is intended for one of the receivers but needs to be kept perf...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	5,419
2406.06064	6DMA Enhanced Wireless Network with Flexible Antenna Position and Rotation: Opportunities and Challenges	6DMA (six-dimensional movable antenna) is a new and revolutionizing technology that fully exploits the wireless channel spatial variation at the transmitter/receiver by flexibly adjusting the three-dimensional (3D) positions and 3D rotations of distributed antennas/antenna surfaces (arrays). In this article, we provide...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	462,426
2209.11003	Predicting pairwise preferences between TTS audio stimuli using parallel ratings data and anti-symmetric twin neural networks	Automatically predicting the outcome of subjective listening tests is a challenging task. Ratings may vary from person to person even if preferences are consistent across listeners. While previous work has focused on predicting listeners' ratings (mean opinion scores) of individual stimuli, we focus on the simpler task...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	319,045
2309.00618	Short-Term Stock Price Forecasting using exogenous variables and Machine Learning Algorithms	Creating accurate predictions in the stock market has always been a significant challenge in finance. With the rise of machine learning as the next level in the forecasting area, this research paper compares four machine learning models and their accuracy in forecasting three well-known stocks traded in the NYSE in the...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	389,360
1805.07569	Reliable counting of weakly labeled concepts by a single spiking neuron model	Making an informed, correct and quick decision can be life-saving. It's crucial for animals during an escape behaviour or for autonomous cars during driving. The decision can be complex and may involve an assessment of the amount of threats present and the nature of each threat. Thus, we should expect early sensory pro...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	97,872
2308.01927	MultiEM: Efficient and Effective Unsupervised Multi-Table Entity Matching	Entity Matching (EM), which aims to identify all entity pairs referring to the same real-world entity from relational tables, is one of the most important tasks in real-world data management systems. Due to the labeling process of EM being extremely labor-intensive, unsupervised EM is more applicable than supervised EM...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	false	383,419
2308.02065	On the Biometric Capacity of Generative Face Models	There has been tremendous progress in generating realistic faces with high fidelity over the past few years. Despite this progress, a crucial question remains unanswered: "Given a generative face model, how many unique identities can it generate?" In other words, what is the biometric capacity of the generative face mo...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	383,477
2401.16330	Digital requirements engineering with an INCOSE-derived SysML meta-model	Traditional requirements engineering tools do not readily access the SysML-defined system architecture model, often resulting in ad-hoc duplication of model elements that lacks the connectivity and expressive detail possible in a SysML-defined model. Without that model connectivity, requirement quality can suffer due t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	424,781
2311.10610	A Poincar\'e Inequality and Consistency Results for Signal Sampling on Large Graphs	Large-scale graph machine learning is challenging as the complexity of learning models scales with the graph size. Subsampling the graph is a viable alternative, but sampling on graphs is nontrivial as graphs are non-Euclidean. Existing graph sampling techniques require not only computing the spectra of large matrices ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	408,585
2010.03019	Global Self-Attention Networks for Image Recognition	Recently, a series of works in computer vision have shown promising results on various image and video understanding tasks using self-attention. However, due to the quadratic computational and memory complexities of self-attention, these works either apply attention only to low-resolution feature maps in later stages o...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	199,238
1906.10414	Learning Feature Embeddings for Discriminant Model based Tracking	After observing that the features used in most online discriminatively trained trackers are not optimal, in this paper, we propose a novel and effective architecture to learn optimal feature embeddings for online discriminative tracking. Our method, called DCFST, integrates the solver of a discriminant model that is di...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	136,430
1611.08212	Interference alignment for downlink cellular networks: Joint scheduling and precoding	Interference Alignment (IA) is technique that, in a large sense, makes use of the increasing signal dimensions available in the system through MIMO and OFDM technologies in order to globally reduce the interference suffered by users in a network. In this paper, we address the problem of downlink cellular networks, the ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	64,463
1507.04050	Reducing Complexity in Next-Generation MU-MIMO Systems	Recently, several advanced multi-antenna radio communications technologies have emerged to meet the increased capacity demands in wireless multi-user networks. Despite their great potential, the extent of these techniques' practical applicability still remains questionable, since they have to face either backhaul limit...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	45,129
2407.12408	Towards Revisiting Visual Place Recognition for Joining Submaps in Multimap SLAM	Visual SLAM is a key technology for many autonomous systems. However, tracking loss can lead to the creation of disjoint submaps in multimap SLAM systems like ORB-SLAM3. Because of that, these systems employ submap merging strategies. As we show, these strategies are not always successful. In this paper, we investigate...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	473,916
2010.09600	Drug Repurposing for COVID-19 via Knowledge Graph Completion	Objective: To discover candidate drugs to repurpose for COVID-19 using literature-derived knowledge and knowledge graph completion methods. Methods: We propose a novel, integrative, and neural network-based literature-based discovery (LBD) approach to identify drug candidates from both PubMed and COVID-19-focused resea...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	201,607
2203.12827	Sparse Instance Activation for Real-Time Instance Segmentation	In this paper, we propose a conceptually novel, efficient, and fully convolutional framework for real-time instance segmentation. Previously, most instance segmentation methods heavily rely on object detection and perform mask prediction based on bounding boxes or dense centers. In contrast, we propose a sparse set of ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	287,405
2305.13632	Detecting and Mitigating Hallucinations in Multilingual Summarisation	Hallucinations pose a significant challenge to the reliability of neural models for abstractive summarisation. While automatically generated summaries may be fluent, they often lack faithfulness to the original document. This issue becomes even more pronounced in low-resource settings, such as cross-lingual transfer. W...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	366,592
2012.15075	Human Evaluation of Spoken vs. Visual Explanations for Open-Domain QA	While research on explaining predictions of open-domain QA systems (ODQA) to users is gaining momentum, most works have failed to evaluate the extent to which explanations improve user trust. While few works evaluate explanations using user studies, they employ settings that may deviate from the end-user's usage in-the...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	213,689
cmp-lg/9407013	The Acquisition of a Lexicon from Paired Phoneme Sequences and Semantic Representations	We present an algorithm that acquires words (pairings of phonological forms and semantic representations) from larger utterances of unsegmented phoneme sequences and semantic representations. The algorithm maintains from utterance to utterance only a single coherent dictionary, and learns in the presence of homonymy, s...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,132
2106.14269	Deep Learning for Technical Document Classification	In large technology companies, the requirements for managing and organizing technical documents created by engineers and managers have increased dramatically in recent years, which has led to a higher demand for more scalable, accurate, and automated document classification. Prior studies have only focused on processin...	false	false	false	false	false	true	true	false	false	false	false	true	false	false	false	false	false	false	243,347
2206.04835	Communication Efficient Distributed Learning for Kernelized Contextual Bandits	We tackle the communication efficiency challenge of learning kernelized contextual bandits in a distributed setting. Despite the recent advances in communication-efficient distributed bandit learning, existing solutions are restricted to simple models like multi-armed bandits and linear bandits, which hamper their prac...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	301,790
2407.04075	Sparsest Models Elude Pruning: An Expos\'e of Pruning's Current Capabilities	Pruning has emerged as a promising approach for compressing large-scale models, yet its effectiveness in recovering the sparsest of models has not yet been explored. We conducted an extensive series of 485,838 experiments, applying a range of state-of-the-art pruning algorithms to a synthetic dataset we created, named ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	470,417
1606.06154	Closed Form Fractional Integration and Differentiation via Real Exponentially Spaced Pole-Zero Pairs	We derive closed-form expressions for the poles and zeros of approximate fractional integrator/differentiator filters, which correspond to spectral roll-off filters having any desired log-log slope to a controllable degree of accuracy over any bandwidth. The filters can be described as a uniform exponential distributio...	false	true	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	57,537
2210.10300	Dense but Efficient VideoQA for Intricate Compositional Reasoning	It is well known that most of the conventional video question answering (VideoQA) datasets consist of easy questions requiring simple reasoning processes. However, long videos inevitably contain complex and compositional semantic structures along with the spatio-temporal axis, which requires a model to understand the c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	324,865
2006.11905	Feel The Music: Automatically Generating A Dance For An Input Song	We present a general computational approach that enables a machine to generate a dance for any input music. We encode intuitive, flexible heuristics for what a 'good' dance is: the structure of the dance should align with the structure of the music. This flexibility allows the agent to discover creative dances. Human s...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	183,405
1208.0562	Learning the Interference Graph of a Wireless Network	A key challenge in wireless networking is the management of interference between transmissions. Identifying which transmitters interfere with each other is a crucial first step. In this paper we cast the task of estimating the a wireless interference environment as a graph learning problem. Nodes represent transmitters...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	17,922
2305.00210	ShipHullGAN: A generic parametric modeller for ship hull design using deep convolutional generative model	In this work, we introduce ShipHullGAN, a generic parametric modeller built using deep convolutional generative adversarial networks (GANs) for the versatile representation and generation of ship hulls. At a high level, the new model intends to address the current conservatism in the parametric ship design paradigm, wh...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	361,253
2103.11089	Dependency Graph-to-String Statistical Machine Translation	We present graph-based translation models which translate source graphs into target strings. Source graphs are constructed from dependency trees with extra links so that non-syntactic phrases are connected. Inspired by phrase-based models, we first introduce a translation model which segments a graph into a sequence of...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	225,663
1409.4320	Self-Dictionary Sparse Regression for Hyperspectral Unmixing: Greedy Pursuit and Pure Pixel Search are Related	This paper considers a recently emerged hyperspectral unmixing formulation based on sparse regression of a self-dictionary multiple measurement vector (SD-MMV) model, wherein the measured hyperspectral pixels are used as the dictionary. Operating under the pure pixel assumption, this SD-MMV formalism is special in that...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	36,059
2008.01540	The world as a neural network	We discuss a possibility that the entire universe on its most fundamental level is a neural network. We identify two different types of dynamical degrees of freedom: "trainable" variables (e.g. bias vector or weight matrix) and "hidden" variables (e.g. state vector of neurons). We first consider stochastic evolution of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	190,359
1906.09434	Intelligent Reflecting Surface for Downlink Non-Orthogonal Multiple Access Networks	Intelligent reflecting surface (IRS) has recently been recognized as a promising technology to enhance the energy and spectrum efficiency of wireless networks by controlling the wireless medium with the configurable electromagnetic materials. In this paper, we consider the downlink transmit power minimization problem f...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	136,154
1905.11137	Learning to Detect and Retrieve Objects from Unlabeled Videos	Learning an object detector or retrieval requires a large data set with manual annotations. Such data sets are expensive and time consuming to create and therefore difficult to obtain on a large scale. In this work, we propose to exploit the natural correlation in narrations and the visual presence of objects in video,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	132,341
2308.10036	Semi-Supervised Anomaly Detection for the Determination of Vehicle Hijacking Tweets	In South Africa, there is an ever-growing issue of vehicle hijackings. This leads to travellers constantly being in fear of becoming a victim to such an incident. This work presents a new semi-supervised approach to using tweets to identify hijacking incidents by using unsupervised anomaly detection algorithms. Tweets ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	386,542
2412.11827	Hyperparametric Robust and Dynamic Influence Maximization	We study the problem of robust influence maximization in dynamic diffusion networks. In line with recent works, we consider the scenario where the network can undergo insertion and removal of nodes and edges, in discrete time steps, and the influence weights are determined by the features of the corresponding nodes and...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	false	517,601
2101.00395	Image-based Textile Decoding	A textile fabric consists of countless parallel vertical yarns (warps) and horizontal yarns (wefts). While common looms can weave repetitive patterns, Jacquard looms can weave the patterns without repetition restrictions. A pattern in which the warps and wefts cross on a grid is defined in a binary matrix. The binary m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	214,071
2408.02777	DUST: A Framework for Data-Driven Density Steering	We consider the problem of data-driven stochastic optimal control of an unknown LTI dynamical system. Assuming the process noise is normally distributed, we pose the problem of steering the state's mean and covariance to a target normal distribution, under noisy data collected from the underlying system, a problem comm...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	478,758
2410.09676	Uncovering Attacks and Defenses in Secure Aggregation for Federated Deep Learning	Federated learning enables the collaborative learning of a global model on diverse data, preserving data locality and eliminating the need to transfer user data to a central server. However, data privacy remains vulnerable, as attacks can target user training data by exploiting the updates sent by users during each lea...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	497,713
2012.00900	Deploying deep learning in OpenFOAM with TensorFlow	We outline the development of a data science module within OpenFOAM which allows for the in-situ deployment of trained deep learning architectures for general-purpose predictive tasks. This module is constructed with the TensorFlow C API and is integrated into OpenFOAM as an application that may be linked at run time. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	209,266
2111.06979	Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception	Adversarial examples are often cited by neuroscientists and machine learning researchers as an example of how computational models diverge from biological sensory systems. Recent work has proposed adding biologically-inspired components to visual neural networks as a way to improve their adversarial robustness. One sur...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	266,236
2110.13376	Task-Specific Dependency-based Word Embedding Methods	Two task-specific dependency-based word embedding methods are proposed for text classification in this work. In contrast with universal word embedding methods that work for generic tasks, we design task-specific word embedding methods to offer better performance in a specific task. Our methods follow the PPMI matrix fa...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	263,154
1902.03112	Towards autonomous ocean observing systems using Miniature Underwater Gliders with UAV deployment and recovery capabilities	This paper presents preliminary results towards the development of an autonomous ocean observing system using Miniature Underwater Gliders (MUGs) that can operate with the support of Unmanned Aerial Vehicles (UAVs) and Unmanned Surface Vessels (USVs) for deployment, recovery, battery charging, and communication relay. ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	121,028
2203.05151	Frequency-driven Imperceptible Adversarial Attack on Semantic Similarity	Current adversarial attack research reveals the vulnerability of learning-based classifiers against carefully crafted perturbations. However, most existing attack methods have inherent limitations in cross-dataset generalization as they rely on a classification layer with a closed set of categories. Furthermore, the pe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	284,725
2408.06996	Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds	The manifold hypothesis says that natural high-dimensional data is actually supported on or around a low-dimensional manifold. Recent success of statistical and learning-based methods empirically supports this hypothesis, due to outperforming classical statistical intuition in very high dimensions. A natural step for a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	480,417
2204.05422	SATA: Sparsity-Aware Training Accelerator for Spiking Neural Networks	Spiking Neural Networks (SNNs) have gained huge attention as a potential energy-efficient alternative to conventional Artificial Neural Networks (ANNs) due to their inherent high-sparsity activation. Recently, SNNs with backpropagation through time (BPTT) have achieved a higher accuracy result on image recognition task...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	291,010
2107.01733	Toward Increased Airspace Safety: Quadrotor Guidance for Targeting Aerial Objects	As the market for commercially available unmanned aerial vehicles (UAVs) booms, there is an increasing number of small, teleoperated or autonomous aircraft found in protected or sensitive airspace. Existing solutions for removal of these aircraft are either military-grade and too disruptive for domestic use, or compose...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	244,578
2312.00358	Impact of Data Augmentation on QCNNs	In recent years, Classical Convolutional Neural Networks (CNNs) have been applied for image recognition successfully. Quantum Convolutional Neural Networks (QCNNs) are proposed as a novel generalization to CNNs by using quantum mechanisms. The quantum mechanisms lead to an efficient training process in QCNNs by reducin...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	412,022
2411.09996	Building 6G Radio Foundation Models with Transformer Architectures	Foundation deep learning (DL) models are general models, designed to learn general, robust and adaptable representations of their target modality, enabling finetuning across a range of downstream tasks. These models are pretrained on large, unlabeled datasets using self-supervised learning (SSL). Foundation models have...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	508,448
2304.04023	Attack-Augmentation Mixing-Contrastive Skeletal Representation Learning	Contrastive learning, relying on effective positive and negative sample pairs, is beneficial to learn informative skeleton representations in unsupervised skeleton-based action recognition. To achieve these positive and negative pairs, existing weak/strong data augmentation methods have to randomly change the appearanc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	357,041
1109.3804	Quantum Hypothesis Testing and Non-Equilibrium Statistical Mechanics	We extend the mathematical theory of quantum hypothesis testing to the general $W^*$-algebraic setting and explore its relation with recent developments in non-equilibrium quantum statistical mechanics. In particular, we relate the large deviation principle for the full counting statistics of entropy flow to quantum hy...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	12,216
1902.07422	Mexican Hat Wavelet Kernel ELM for Multiclass Classification	Kernel extreme learning machine (KELM) is a novel feedforward neural network, which is widely used in classification problems. To some extent, it solves the existing problems of the invalid nodes and the large computational complexity in ELM. However, the traditional KELM classifier usually has a low test accuracy when...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	121,981
2308.10453	DOMINO++: Domain-aware Loss Regularization for Deep Learning Generalizability	Out-of-distribution (OOD) generalization poses a serious challenge for modern deep learning (DL). OOD data consists of test data that is significantly different from the model's training data. DL models that perform well on in-domain test data could struggle on OOD data. Overcoming this discrepancy is essential to the ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	386,737
2310.20561	Predictive Control for Autonomous Driving with Uncertain, Multi-modal Predictions	We propose a Stochastic MPC (SMPC) formulation for path planning with autonomous vehicles in scenarios involving multiple agents with multi-modal predictions. The multi-modal predictions capture the uncertainty of urban driving in distinct modes/maneuvers (e.g., yield, keep speed) and driving trajectories (e.g., speed,...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	404,435
2203.09580	Surface Defect Detection and Evaluation for Marine Vessels using Multi-Stage Deep Learning	Detecting and evaluating surface coating defects is important for marine vessel maintenance. Currently, the assessment is carried out manually by qualified inspectors using international standards and their own experience. Automating the processes is highly challenging because of the high level of variation in vessel t...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	286,198
1802.07544	Personal research information system. About developing the methods for searching patent analogs of invention	The article describes information model and the method for searching patent analogs for Personal Research Information System.	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	90,916
2102.08302	Robust multi-rate predictive control using multi-step prediction models learned from data	This note extends a recently proposed algorithm for model identification and robust MPC of asymptotically stable, linear time-invariant systems subject to process and measurement disturbances. Independent output predictors for different steps ahead are estimated with Set Membership methods. It is here shown that the co...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	220,401
1702.07006	Synthesising Dynamic Textures using Convolutional Neural Networks	Here we present a parametric model for dynamic textures. The model is based on spatiotemporal summary statistics computed from the feature representations of a Convolutional Neural Network (CNN) trained on object recognition. We demonstrate how the model can be used to synthesise new samples of dynamic textures and to ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	68,712
2006.01486	On the existence of the stabilizing solution of generalized Riccati equations arising in zero sum stochastic difference games: The time-varying case	In this paper, a large class of time-varying Riccati equations arising in stochastic dynamic games is considered. The problem of the existence and uniqueness of some globally defined solution, namely the bounded and stabilizing solution, is investigated. As an application of the obtained existence results, we address i...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	179,793
1710.01990	r-Robustness and (r,s)-Robustness of Circulant Graphs	There has been recent growing interest in graph theoretical properties known as r- and (r,s)-robustness. These properties serve as sufficient conditions guaranteeing the success of certain consensus algorithms in networks with misbehaving agents present. Due to the complexity of determining the robustness for an arbitr...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	82,089
1909.01779	Approximating two value functions instead of one: towards characterizing a new family of Deep Reinforcement Learning algorithms	This paper makes one step forward towards characterizing a new family of \textit{model-free} Deep Reinforcement Learning (DRL) algorithms. The aim of these algorithms is to jointly learn an approximation of the state-value function ($V$), alongside an approximation of the state-action value function ($Q$). Our analysis...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	144,001
2212.04030	Analysis of Deep Learning Architectures and Efficacy of Detecting Forest Fires	The aim of this research is to review the state of computer vision as applied to combatting forest fires. My motivation to research this topic comes from the urgency with which new participants and stakeholders require guidance in this field. One of these new stakeholder groups are practitioners of machine learning tha...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	335,297
2104.14654	Adversarial Inverse Reinforcement Learning for Mean Field Games	Mean field games (MFGs) provide a mathematically tractable framework for modelling large-scale multi-agent systems by leveraging mean field theory to simplify interactions among agents. It enables applying inverse reinforcement learning (IRL) to predict behaviours of large populations by recovering reward signals from ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	232,890
2112.14476	ADAPQUEST: A Software for Web-Based Adaptive Questionnaires based on Bayesian Networks	We introduce ADAPQUEST, a software tool written in Java for the development of adaptive questionnaires based on Bayesian networks. Adaptiveness is intended here as the dynamical choice of the question sequence on the basis of an evolving model of the skill level of the test taker. Bayesian networks offer a flexible and...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	273,544
1912.02796	Architecting Safety Supervisors for High Levels of Automated Driving	The complexity of automated driving poses challenges for providing safety assurance. Focusing on the architecting of an Autonomous Driving Intelligence (ADI), i.e. the computational intelligence, sensors and communication needed for high levels of automated driving, we investigate so called safety supervisors that comp...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	156,438
2007.11318	Multi-Spectral Facial Biometrics in Access Control	This study demonstrates how facial biometrics, acquired using multi-spectral sensors, such as RGB, depth, and infrared, assist the data accumulation in the process of authorizing users of automated and semi-automated access systems. This data serves the purposes of person authentication, as well as facial temperature e...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	188,521
2104.07538	Street-Map Based Validation of Semantic Segmentation in Autonomous Driving	Artificial intelligence for autonomous driving must meet strict requirements on safety and robustness, which motivates the thorough validation of learned models. However, current validation approaches mostly require ground truth data and are thus both cost-intensive and limited in their applicability. We propose to ove...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	230,456
2410.09283	Comparative Analysis of Static and Contextual Embeddings for Analyzing Semantic Changes in Medieval Latin Charters	The Norman Conquest of 1066 C.E. brought profound transformations to England's administrative, societal, and linguistic practices. The DEEDS (Documents of Early England Data Set) database offers a unique opportunity to explore these changes by examining shifts in word meanings within a vast collection of Medieval Latin...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	497,513
2010.07290	XPDNet for MRI Reconstruction: an application to the 2020 fastMRI challenge	We present a new neural network, the XPDNet, for MRI reconstruction from periodically under-sampled multi-coil data. We inform the design of this network by taking best practices from MRI reconstruction and computer vision. We show that this network can achieve state-of-the-art reconstruction results, as shown by its r...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	200,766
2311.10862	Formal concept analysis for evaluating intrinsic dimension of a natural language	Some results of a computational experiment for determining the intrinsic dimension of linguistic varieties for the Bengali and Russian languages are presented. At the same time, both sets of words and sets of bigrams in these languages were considered separately. The method used to solve this problem was based on forma...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	408,695
2203.02432	Improving \textit{Tug-of-War} sketch using Control-Variates method	Computing space-efficient summary, or \textit{a.k.a. sketches}, of large data, is a central problem in the streaming algorithm. Such sketches are used to answer \textit{post-hoc} queries in several data analytics tasks. The algorithm for computing sketches typically requires to be fast, accurate, and space-efficient. A...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	283,741
1708.04167	Strange Attractor for Efficient Polar Code Design	This paper presents a definition of a construction for long polar codes. Recently, we know that partial order is a universal property of the construction with a sublinear complexity for polar codes. In order to describe the partial order, addition and left-swap operators are only defined as universal up to now. In this...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	78,894
1811.02363	Fast High-Dimensional Bilateral and Nonlocal Means Filtering	Existing fast algorithms for bilateral and nonlocal means filtering mostly work with grayscale images. They cannot easily be extended to high-dimensional data such as color and hyperspectral images, patch-based data, flow-fields, etc. In this paper, we propose a fast algorithm for high-dimensional bilateral and nonloca...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	112,573
1703.06045	Approximation Complexity of Maximum A Posteriori Inference in Sum-Product Networks	We discuss the computational complexity of approximating maximum a posteriori inference in sum-product networks. We first show NP-hardness in trees of height two by a reduction from maximum independent set; this implies non-approximability within a sublinear factor. We show that this is a tight bound, as we can find an...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	70,167
1805.00330	Real-Time Human Detection as an Edge Service Enabled by a Lightweight CNN	Edge computing allows more computing tasks to take place on the decentralized nodes at the edge of networks. Today many delay sensitive, mission-critical applications can leverage these edge devices to reduce the time delay or even to enable real time, online decision making thanks to their onsite presence. Human objec...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	96,418
1910.06552	Improved Generalization Bounds of Group Invariant / Equivariant Deep Networks via Quotient Feature Spaces	Numerous invariant (or equivariant) neural networks have succeeded in handling invariant data such as point clouds and graphs. However, a generalization theory for the neural networks has not been well developed, because several essential factors for the theory, such as network size and margin distribution, are not dee...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	149,374
2411.13757	GenBFA: An Evolutionary Optimization Approach to Bit-Flip Attacks on LLMs	Large Language Models (LLMs) have revolutionized natural language processing (NLP), excelling in tasks like text generation and summarization. However, their increasing adoption in mission-critical applications raises concerns about hardware-based threats, particularly bit-flip attacks (BFAs). BFAs, enabled by fault in...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	509,906
2409.01627	Dynamic Guidance Adversarial Distillation with Enhanced Teacher Knowledge	In the realm of Adversarial Distillation (AD), strategic and precise knowledge transfer from an adversarially robust teacher model to a less robust student model is paramount. Our Dynamic Guidance Adversarial Distillation (DGAD) framework directly tackles the challenge of differential sample importance, with a keen foc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	485,416
1308.6709	Distributed H-infinity Tracking Control for Discrete-Time Multi-Agent Systems with a High-Dimensional Leader	This paper considers the distributed H-infinity leader-following tracking problem for a class of discrete time multi-agent systems with a high-dimensional dynamic leader. It is assumed that output information about the leader is only available to designated followers, and the dynamics of the followers are subject to pe...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	26,740
2401.10539	Quality-Diversity Algorithms Can Provably Be Helpful for Optimization	Quality-Diversity (QD) algorithms are a new type of Evolutionary Algorithms (EAs), aiming to find a set of high-performing, yet diverse solutions. They have found many successful applications in reinforcement learning and robotics, helping improve the robustness in complex environments. Furthermore, they often empirica...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	422,681
1503.05079	Learning Models for Following Natural Language Directions in Unknown Environments	Natural language offers an intuitive and flexible means for humans to communicate with the robots that we will increasingly work alongside in our homes and workplaces. Recent advancements have given rise to robots that are able to interpret natural language manipulation and navigation commands, but these methods requir...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	41,209
2403.06185	Quantized Constant-Envelope Waveform Design for Massive MIMO DFRC Systems	Both dual-functional radar-communication (DFRC) and massive multiple-input multiple-output (MIMO) have been recognized as enabling technologies for 6G wireless networks. This paper considers the advanced waveform design for hardware-efficient massive MIMO DFRC systems. Specifically, the transmit waveform is imposed wit...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	436,338
1512.05726	Semi-supervised Question Retrieval with Gated Convolutions	Question answering forums are rapidly growing in size with no effective automated ability to refer to and reuse answers already available for previous posted questions. In this paper, we develop a methodology for finding semantically related questions. The task is difficult since 1) key pieces of information are often ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	50,253
2110.15722	ICDM 2020 Knowledge Graph Contest: Consumer Event-Cause Extraction	Consumer Event-Cause Extraction, the task aimed at extracting the potential causes behind certain events in the text, has gained much attention in recent years due to its wide applications. The ICDM 2020 conference sets up an evaluation competition that aims to extract events and the causes of the extracted events with...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	263,976

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