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
1806.03539	Computational Complexity of Motion Planning of a Robot through Simple Gadgets	We initiate a general theory for analyzing the complexity of motion planning of a single robot through a graph of "gadgets", each with their own state, set of locations, and allowed traversals between locations that can depend on and change the state. This type of setup is common to many robot motion planning hardness ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	100,020
2310.05727	The Program Testing Ability of Large Language Models for Code	Recent development of large language models (LLMs) for code like CodeX and CodeT5+ demonstrates tremendous promise in achieving code intelligence. Their ability of synthesizing code that completes a program for performing a pre-defined task has been intensively tested and verified on benchmark datasets including HumanE...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	true	398,270
2108.07917	Classification of Abnormal Hand Movement for Aiding in Autism Detection: Machine Learning Study	A formal autism diagnosis can be an inefficient and lengthy process. Families may wait months or longer before receiving a diagnosis for their child despite evidence that earlier intervention leads to better treatment outcomes. Digital technologies which detect the presence of behaviors related to autism can scale acce...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	251,060
2312.08891	High-Dimensional Bayesian Optimisation with Large-Scale Constraints -- An Application to Aeroelastic Tailoring	Design optimisation potentially leads to lightweight aircraft structures with lower environmental impact. Due to the high number of design variables and constraints, these problems are ordinarily solved using gradient-based optimisation methods, leading to a local solution in the design space while the global space is ...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	415,505
2408.10495	How Well Do Large Language Models Serve as End-to-End Secure Code Producers?	The rapid advancement of large language models (LLMs) such as GPT-4 has revolutionized the landscape of software engineering, positioning these models at the core of modern development practices. As we anticipate these models to evolve into the primary and trustworthy tools used in software development, ensuring the se...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	481,875
1911.10783	Financial Event Extraction Using Wikipedia-Based Weak Supervision	Extraction of financial and economic events from text has previously been done mostly using rule-based methods, with more recent works employing machine learning techniques. This work is in line with this latter approach, leveraging relevant Wikipedia sections to extract weak labels for sentences describing economic ev...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	154,946
2103.07905	Bangla Handwritten Digit Recognition and Generation	Handwritten digit or numeral recognition is one of the classical issues in the area of pattern recognition and has seen tremendous advancement because of the recent wide availability of computing resources. Plentiful works have already done on English, Arabic, Chinese, Japanese handwritten script. Some work on Bangla a...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	224,731
2305.16508	Most Neural Networks Are Almost Learnable	We present a PTAS for learning random constant-depth networks. We show that for any fixed $\epsilon>0$ and depth $i$, there is a poly-time algorithm that for any distribution on $\sqrt{d} \cdot \mathbb{S}^{d-1}$ learns random Xavier networks of depth $i$, up to an additive error of $\epsilon$. The algorithm runs in tim...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	368,121
1404.6000	Robust and computationally feasible community detection in the presence of arbitrary outlier nodes	Community detection, which aims to cluster $N$ nodes in a given graph into $r$ distinct groups based on the observed undirected edges, is an important problem in network data analysis. In this paper, the popular stochastic block model (SBM) is extended to the generalized stochastic block model (GSBM) that allows for ad...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	32,548
2107.04074	Accelerating Spherical k-Means	Spherical k-means is a widely used clustering algorithm for sparse and high-dimensional data such as document vectors. While several improvements and accelerations have been introduced for the original k-means algorithm, not all easily translate to the spherical variant: Many acceleration techniques, such as the algori...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	245,340
2110.02623	Is An Image Worth Five Sentences? A New Look into Semantics for Image-Text Matching	The task of image-text matching aims to map representations from different modalities into a common joint visual-textual embedding. However, the most widely used datasets for this task, MSCOCO and Flickr30K, are actually image captioning datasets that offer a very limited set of relationships between images and sentenc...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	259,188
2311.05161	Enhancing Computation Efficiency in Large Language Models through Weight and Activation Quantization	Large Language Models (LLMs) are proficient in natural language processing tasks, but their deployment is often restricted by extensive parameter sizes and computational demands. This paper focuses on post-training quantization (PTQ) in LLMs, specifically 4-bit weight and 8-bit activation (W4A8) quantization, to enhanc...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	406,497
1907.11367	Data Aggregation Techniques for Internet of Things	The goal of this dissertation is to design efficient data aggregation frameworks for massive IoT networks in different scenarios to support the proper functioning of IoT analytics layer. This dissertation includes modern algorithmic frameworks such as non convex optimization, machine learning, stochastic matrix perturb...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	139,830
2309.10171	Specification-Driven Video Search via Foundation Models and Formal Verification	The increasing abundance of video data enables users to search for events of interest, e.g., emergency incidents. Meanwhile, it raises new concerns, such as the need for preserving privacy. Existing approaches to video search require either manual inspection or a deep learning model with massive training. We develop a ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	392,888
1706.08088	Efficient and accurate monitoring of the depth information in a Wireless Multimedia Sensor Network based surveillance	Wireless Multimedia Sensor Network (WMSN) is a promising technology capturing rich multimedia data like audio and video, which can be useful to monitor an environment under surveillance. However, many scenarios in real time monitoring requires 3D depth information. In this research work, we propose to use the disparity...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	75,937
2408.00764	AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generation	Large Language Model-based agents have garnered significant attention and are becoming increasingly popular. Furthermore, planning ability is a crucial component of an LLM-based agent, which generally entails achieving a desired goal from an initial state. This paper investigates enhancing the planning abilities of LLM...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	477,965
1911.10290	Scalable sim-to-real transfer of soft robot designs	The manual design of soft robots and their controllers is notoriously challenging, but it could be augmented---or, in some cases, entirely replaced---by automated design tools. Machine learning algorithms can automatically propose, test, and refine designs in simulation, and the most promising ones can then be manufact...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	154,779
1905.05376	Dimensionality Reduction for Tukey Regression	We give the first dimensionality reduction methods for the overconstrained Tukey regression problem. The Tukey loss function $\\|y\\|_M = \sum_i M(y_i)$ has $M(y_i) \approx \|y_i\|^p$ for residual errors $y_i$ smaller than a prescribed threshold $\tau$, but $M(y_i)$ becomes constant for errors $\|y_i\| > \tau$. Our results d...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	130,704
1807.11348	Learning Adaptive Discriminative Correlation Filters via Temporal Consistency Preserving Spatial Feature Selection for Robust Visual Tracking	With efficient appearance learning models, Discriminative Correlation Filter (DCF) has been proven to be very successful in recent video object tracking benchmarks and competitions. However, the existing DCF paradigm suffers from two major issues, i.e., spatial boundary effect and temporal filter degradation. To mitiga...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	104,162
2203.07728	Securing the Classification of COVID-19 in Chest X-ray Images: A Privacy-Preserving Deep Learning Approach	Deep learning (DL) is being increasingly utilized in healthcare-related fields due to its outstanding efficiency. However, we have to keep the individual health data used by DL models private and secure. Protecting data and preserving the privacy of individuals has become an increasingly prevalent issue. The gap betwee...	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	285,539
cs/0308032	Evaluation of text data mining for database curation: lessons learned from the KDD Challenge Cup	MOTIVATION: The biological literature is a major repository of knowledge. Many biological databases draw much of their content from a careful curation of this literature. However, as the volume of literature increases, the burden of curation increases. Text mining may provide useful tools to assist in the curation proc...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	537,967
1806.07555	Stagewise Safe Bayesian Optimization with Gaussian Processes	Enforcing safety is a key aspect of many problems pertaining to sequential decision making under uncertainty, which require the decisions made at every step to be both informative of the optimal decision and also safe. For example, we value both efficacy and comfort in medical therapy, and efficiency and safety in robo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	100,960
1907.11065	DropAttention: A Regularization Method for Fully-Connected Self-Attention Networks	Variants dropout methods have been designed for the fully-connected layer, convolutional layer and recurrent layer in neural networks, and shown to be effective to avoid overfitting. As an appealing alternative to recurrent and convolutional layers, the fully-connected self-attention layer surprisingly lacks a specific...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	139,771
1910.06591	SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference	We present a modern scalable reinforcement learning agent called SEED (Scalable, Efficient Deep-RL). By effectively utilizing modern accelerators, we show that it is not only possible to train on millions of frames per second but also to lower the cost of experiments compared to current methods. We achieve this with a ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	149,388
2104.11846	Joint Detection and Localization of Stealth False Data Injection Attacks in Smart Grids using Graph Neural Networks	False data injection attacks (FDIA) are a main category of cyber-attacks threatening the security of power systems. Contrary to the detection of these attacks, less attention has been paid to identifying the attacked units of the grid. To this end, this work jointly studies detecting and localizing the stealth FDIA in ...	false	false	false	false	true	false	true	false	false	false	true	false	true	false	false	false	false	false	232,033
1401.0131	System Analysis And Design For Multimedia Retrieval Systems	Due to the extensive use of information technology and the recent developments in multimedia systems, the amount of multimedia data available to users has increased exponentially. Video is an example of multimedia data as it contains several kinds of data such as text, image, meta-data, visual and audio. Content based ...	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	true	29,533
2501.05247	Online Prompt Selection for Program Synthesis	Large Language Models (LLMs) demonstrate impressive capabilities in the domain of program synthesis. This level of performance is not, however, universal across all tasks, all LLMs and all prompting styles. There are many areas where one LLM dominates, one prompting style dominates, or where calling a symbolic solver i...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	523,518
2207.02400	Chairs Can be Stood on: Overcoming Object Bias in Human-Object Interaction Detection	Detecting Human-Object Interaction (HOI) in images is an important step towards high-level visual comprehension. Existing work often shed light on improving either human and object detection, or interaction recognition. However, due to the limitation of datasets, these methods tend to fit well on frequent interactions ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	306,505
2310.02206	Chunking: Continual Learning is not just about Distribution Shift	Work on continual learning (CL) has thus far largely focused on the problems arising from shifts in the data distribution. However, CL can be decomposed into two sub-problems: (a) shifts in the data distribution, and (b) dealing with the fact that the data is split into chunks and so only a part of the data is availabl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	396,742
2311.07106	A Tutorial on Coding Methods for DNA-based Molecular Communications and Storage	Exponential increase of data has motivated advances of data storage technologies. As a promising storage media, DeoxyriboNucleic Acid (DNA) storage provides a much higher data density and superior durability, compared with state-of-the-art media. In this paper, we provide a tutorial on DNA storage and its role in molec...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	407,202
2310.17678	Spatio-Temporal Meta Contrastive Learning	Spatio-temporal prediction is crucial in numerous real-world applications, including traffic forecasting and crime prediction, which aim to improve public transportation and safety management. Many state-of-the-art models demonstrate the strong capability of spatio-temporal graph neural networks (STGNN) to capture comp...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	403,243
1910.02696	Hierarchical stochastic neighbor embedding as a tool for visualizing the encoding capability of magnetic resonance fingerprinting dictionaries	In Magnetic Resonance Fingerprinting (MRF) the quality of the estimated parameter maps depends on the encoding capability of the variable flip angle train. In this work we show how the dimensionality reduction technique Hierarchical Stochastic Neighbor Embedding (HSNE) can be used to obtain insight into the encoding ca...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	148,317
1711.04907	A Family of Constrained Adaptive filtering Algorithms Based on Logarithmic Cost	This paper introduces a novel constraint adaptive filtering algorithm based on a relative logarithmic cost function which is termed as Constrained Least Mean Logarithmic Square (CLMLS). The proposed CLMLS algorithm elegantly adjusts the cost function based on the amount of error thereby achieves better performance comp...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	84,458
1304.4652	A Health Monitoring System for Elder and Sick Persons	This paper discusses a vision based health monitoring system which would be very easy in use and deployment. Elder and sick people who are not able to talk or walk they are dependent on other human beings for their daily needs and need continuous monitoring. The developed system provides facility to the sick or elder p...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	24,022
2004.08499	Design and Control of Roller Grasper V2 for In-Hand Manipulation	The ability to perform in-hand manipulation still remains an unsolved problem; having this capability would allow robots to perform sophisticated tasks requiring repositioning and reorienting of grasped objects. In this work, we present a novel non-anthropomorphic robot grasper with the ability to manipulate objects by...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	173,074
2501.04652	Multi-task retriever fine-tuning for domain-specific and efficient RAG	Retrieval-Augmented Generation (RAG) has become ubiquitous when deploying Large Language Models (LLMs), as it can address typical limitations such as generating hallucinated or outdated information. However, when building real-world RAG applications, practical issues arise. First, the retrieved information is generally...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	523,292
1607.02296	On the evolution of cooperation under social pressure in multiplex networks	In this work, we aim to contribute to the understanding of the human pro-social behavior by studying the influence that a particular form of social pressure "being watched" has on the evolution of cooperative behavior. We study how cooperation emerge in multiplex complex topologies by analyzing a particular bidirection...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	58,326
2407.04393	Function Smoothing Regularization for Precision Factorization Machine Annealing in Continuous Variable Optimization Problems	Solving continuous variable optimization problems by factorization machine quantum annealing (FMQA) demonstrates the potential of Ising machines to be extended as a solver for integer and real optimization problems. However, the details of the Hamiltonian function surface obtained by factorization machine (FM) have bee...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	470,547
1905.01787	Creating Lightweight Object Detectors with Model Compression for Deployment on Edge Devices	To achieve lightweight object detectors for deployment on the edge devices, an effective model compression pipeline is proposed in this paper. The compression pipeline consists of automatic channel pruning for the backbone, fixed channel deletion for the branch layers and knowledge distillation for the guidance learnin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	129,817
1802.02297	3D Point Cloud Descriptors in Hand-crafted and Deep Learning Age: State-of-the-Art	The introduction of inexpensive 3D data acquisition devices has promisingly facilitated the wide availability and popularity of 3D point cloud, which attracts more attention to the effective extraction of novel 3D point cloud descriptors for accuracy of the efficiency of 3D computer vision tasks in recent years. Howeve...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	89,751
1801.02019	A Survey on Quantum Channel Capacities	Quantum information processing exploits the quantum nature of information. It offers fundamentally new solutions in the field of computer science and extends the possibilities to a level that cannot be imagined in classical communication systems. For quantum communication channels, many new capacity definitions were de...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	87,844
2501.13928	Fast3R: Towards 3D Reconstruction of 1000+ Images in One Forward Pass	Multi-view 3D reconstruction remains a core challenge in computer vision, particularly in applications requiring accurate and scalable representations across diverse perspectives. Current leading methods such as DUSt3R employ a fundamentally pairwise approach, processing images in pairs and necessitating costly global ...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	true	526,884
2104.03781	Leveraging Good Representations in Linear Contextual Bandits	The linear contextual bandit literature is mostly focused on the design of efficient learning algorithms for a given representation. However, a contextual bandit problem may admit multiple linear representations, each one with different characteristics that directly impact the regret of the learning algorithm. In parti...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	229,176
2411.01818	Shrinking the Giant : Quasi-Weightless Transformers for Low Energy Inference	Transformers are set to become ubiquitous with applications ranging from chatbots and educational assistants to visual recognition and remote sensing. However, their increasing computational and memory demands is resulting in growing energy consumption. Building models with fast and energy-efficient inference is impera...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	505,241
1708.04014	Style2Vec: Representation Learning for Fashion Items from Style Sets	With the rapid growth of online fashion market, demand for effective fashion recommendation systems has never been greater. In fashion recommendation, the ability to find items that goes well with a few other items based on style is more important than picking a single item based on the user's entire purchase history. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	78,872
2310.05804	Learning Language-guided Adaptive Hyper-modality Representation for Multimodal Sentiment Analysis	Though Multimodal Sentiment Analysis (MSA) proves effective by utilizing rich information from multiple sources (e.g., language, video, and audio), the potential sentiment-irrelevant and conflicting information across modalities may hinder the performance from being further improved. To alleviate this, we present Adapt...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	true	398,300
1101.0764	Binary Polar Code Kernels from Code Decompositions	Code decompositions (a.k.a code nestings) are used to design good binary polar code kernels. The proposed kernels are in general non-linear and show a better rate of polarization under successive cancelation decoding, than the ones suggested by Korada et al., for the same kernel dimensions. In particular, kernels of si...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	8,724
2012.06971	Syntactic representation learning for neural network based TTS with syntactic parse tree traversal	Syntactic structure of a sentence text is correlated with the prosodic structure of the speech that is crucial for improving the prosody and naturalness of a text-to-speech (TTS) system. Nowadays TTS systems usually try to incorporate syntactic structure information with manually designed features based on expert knowl...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	211,293
2307.05891	PID-Inspired Inductive Biases for Deep Reinforcement Learning in Partially Observable Control Tasks	Deep reinforcement learning (RL) has shown immense potential for learning to control systems through data alone. However, one challenge deep RL faces is that the full state of the system is often not observable. When this is the case, the policy needs to leverage the history of observations to infer the current state. ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	378,888
2409.15301	Derangetropy in Probability Distributions and Information Dynamics	We introduce derangetropy, a novel functional measure designed to characterize the dynamics of information within probability distributions. Unlike scalar measures such as Shannon entropy, derangetropy offers a functional representation that captures the dispersion of information across the entire support of a distribu...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	490,846
1807.09959	Iterative Crowd Counting	In this work, we tackle the problem of crowd counting in images. We present a Convolutional Neural Network (CNN) based density estimation approach to solve this problem. Predicting a high resolution density map in one go is a challenging task. Hence, we present a two branch CNN architecture for generating high resoluti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	103,841
1405.6293	Cross-Language Personal Name Mapping	Name matching between multiple natural languages is an important step in cross-enterprise integration applications and data mining. It is difficult to decide whether or not two syntactic values (names) from two heterogeneous data sources are alternative designation of the same semantic entity (person), this process bec...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	33,368
1812.07203	Video Trajectory Classification and Anomaly Detection Using Hybrid CNN-VAE	Classifying time series data using neural networks is a challenging problem when the length of the data varies. Video object trajectories, which are key to many of the visual surveillance applications, are often found to be of varying length. If such trajectories are used to understand the behavior (normal or anomalous...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	116,775
2404.17249	Making Better Use of Unlabelled Data in Bayesian Active Learning	Fully supervised models are predominant in Bayesian active learning. We argue that their neglect of the information present in unlabelled data harms not just predictive performance but also decisions about what data to acquire. Our proposed solution is a simple framework for semi-supervised Bayesian active learning. We...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	449,794
2209.09362	Analyzing Machine Learning Models for Credit Scoring with Explainable AI and Optimizing Investment Decisions	This paper examines two different yet related questions related to explainable AI (XAI) practices. Machine learning (ML) is increasingly important in financial services, such as pre-approval, credit underwriting, investments, and various front-end and back-end activities. Machine Learning can automatically detect non-l...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	318,477
1910.13942	Motion-Nets: 6D Tracking of Unknown Objects in Unseen Environments using RGB	In this work, we bridge the gap between recent pose estimation and tracking work to develop a powerful method for robots to track objects in their surroundings. Motion-Nets use a segmentation model to segment the scene, and separate translation and rotation models to identify the relative 6D motion of an object between...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	151,521
1902.00751	Parameter-Efficient Transfer Learning for NLP	Fine-tuning large pre-trained models is an effective transfer mechanism in NLP. However, in the presence of many downstream tasks, fine-tuning is parameter inefficient: an entire new model is required for every task. As an alternative, we propose transfer with adapter modules. Adapter modules yield a compact and extens...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	120,497
2201.08832	Occupancy Information Ratio: Infinite-Horizon, Information-Directed, Parameterized Policy Search	In this work, we propose an information-directed objective for infinite-horizon reinforcement learning (RL), called the occupancy information ratio (OIR), inspired by the information ratio objectives used in previous information-directed sampling schemes for multi-armed bandits and Markov decision processes as well as ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	276,463
2110.10996	Mean Nystr\"om Embeddings for Adaptive Compressive Learning	Compressive learning is an approach to efficient large scale learning based on sketching an entire dataset to a single mean embedding (the sketch), i.e. a vector of generalized moments. The learning task is then approximately solved as an inverse problem using an adapted parametric model. Previous works in this context...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	262,328
2111.07864	Evaluating Metrics for Bias in Word Embeddings	Over the last years, word and sentence embeddings have established as text preprocessing for all kinds of NLP tasks and improved the performances significantly. Unfortunately, it has also been shown that these embeddings inherit various kinds of biases from the training data and thereby pass on biases present in societ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	266,496
2401.10393	Natural Mitigation of Catastrophic Interference: Continual Learning in Power-Law Learning Environments	Neural networks often suffer from catastrophic interference (CI): performance on previously learned tasks drops off significantly when learning a new task. This contrasts strongly with humans, who can continually learn new tasks without appreciably forgetting previous tasks. Prior work has explored various techniques f...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	422,618
2409.12669	Enhancing Construction Site Safety: A Lightweight Convolutional Network for Effective Helmet Detection	In the realm of construction safety, the detection of personal protective equipment, such as helmets, plays a critical role in preventing workplace injuries. This paper details the development and evaluation of convolutional neural networks (CNNs) designed for the accurate classification of helmet presence on construct...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	489,676
1911.06364	MmWave Radar Point Cloud Segmentation using GMM in Multimodal Traffic Monitoring	In multimodal traffic monitoring, we gather traffic statistics for distinct transportation modes, such as pedestrians, cars and bicycles, in order to analyze and improve people's daily mobility in terms of safety and convenience. On account of its robustness to bad light and adverse weather conditions, and inherent spe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	153,520
2012.06106	EQG-RACE: Examination-Type Question Generation	Question Generation (QG) is an essential component of the automatic intelligent tutoring systems, which aims to generate high-quality questions for facilitating the reading practice and assessments. However, existing QG technologies encounter several key issues concerning the biased and unnatural language sources of da...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	210,995
1005.4496	Combining Naive Bayes and Decision Tree for Adaptive Intrusion Detection	In this paper, a new learning algorithm for adaptive network intrusion detection using naive Bayesian classifier and decision tree is presented, which performs balance detections and keeps false positives at acceptable level for different types of network attacks, and eliminates redundant attributes as well as contradi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	6,563
2102.12516	A Large-Scale, Automated Study of Language Surrounding Artificial Intelligence	This work presents a large-scale analysis of artificial intelligence (AI) and machine learning (ML) references within news articles and scientific publications between 2011 and 2019. We implement word association measurements that automatically identify shifts in language co-occurring with AI/ML and quantify the streng...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	221,746
2410.02626	Online Learning Guided Quasi-Newton Methods with Global Non-Asymptotic Convergence	In this paper, we propose a quasi-Newton method for solving smooth and monotone nonlinear equations, including unconstrained minimization and minimax optimization as special cases. For the strongly monotone setting, we establish two global convergence bounds: (i) a linear convergence rate that matches the rate of the c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	494,361
1404.6044	Harnessing Bursty Interference in Multicarrier Systems with Feedback	We study parallel symmetric 2-user interference channels when the interference is bursty and feedback is available from the respective receivers. Presence of interference in each subcarrier is modeled as a memoryless Bernoulli random state. The states across subcarriers are drawn from an arbitrary joint distribution wi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	32,556
1106.5256	Structure and Complexity in Planning with Unary Operators	Unary operator domains -- i.e., domains in which operators have a single effect -- arise naturally in many control problems. In its most general form, the problem of STRIPS planning in unary operator domains is known to be as hard as the general STRIPS planning problem -- both are PSPACE-complete. However, unary operat...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	11,002
2210.17106	Intelligent Painter: Picture Composition With Resampling Diffusion Model	Have you ever thought that you can be an intelligent painter? This means that you can paint a picture with a few expected objects in mind, or with a desirable scene. This is different from normal inpainting approaches for which the location of specific objects cannot be determined. In this paper, we present an intellig...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	327,572
2302.04999	Ablation Study on Features in Learning-based Joints Calibration of Cable-driven Surgical Robots	With worldwide implementation, millions of surgeries are assisted by surgical robots. The cable-drive mechanism on many surgical robots allows flexible, light, and compact arms and tools. However, the slack and stretch of the cables and the backlash of the gears introduce inevitable errors from motor poses to joint pos...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	344,891
2405.02574	A Data Mining-Based Dynamical Anomaly Detection Method for Integrating with an Advance Metering System	Building operations consume 30% of total power consumption and contribute 26% of global power-related emissions. Therefore, monitoring, and early detection of anomalies at the meter level are essential for residential and commercial buildings. This work investigates both supervised and unsupervised approaches and intro...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	451,816
1909.07809	Learn to Segment Organs with a Few Bounding Boxes	Semantic segmentation is an import task in the medical field to identify the exact extent and orientation of significant structures like organs and pathology. Deep neural networks can perform this task well by leveraging the information from a large well-labeled data-set. This paper aims to present a method that mitiga...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	145,780
2409.11340	OmniGen: Unified Image Generation	The emergence of Large Language Models (LLMs) has unified language generation tasks and revolutionized human-machine interaction. However, in the realm of image generation, a unified model capable of handling various tasks within a single framework remains largely unexplored. In this work, we introduce OmniGen, a new d...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	489,114
2112.12495	Polar Codes Do Not Have Many Affine Automorphisms	Polar coding solutions demonstrate excellent performance under the list decoding that is challenging to implement in hardware due to the path sorting operations. As a potential solution to this problem, permutation decoding recently became a hot research topic. However, it imposes more constraints on the code structure...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	272,976
2307.12136	Using Reinforcement Learning for the Three-Dimensional Loading Capacitated Vehicle Routing Problem	Heavy goods vehicles are vital backbones of the supply chain delivery system but also contribute significantly to carbon emissions with only 60% loading efficiency in the United Kingdom. Collaborative vehicle routing has been proposed as a solution to increase efficiency, but challenges remain to make this a possibilit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	381,150
2008.10741	Efficient Detection Of Infected Individuals using Two Stage Testing	Group testing is an efficient method for testing a large population to detect infected individuals. In this paper, we consider an efficient adaptive two stage group testing scheme. Using a straightforward analysis, we characterize the efficiency of several two stage group testing algorithms. We determine how to pick th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	193,073
2501.05904	Binary Event-Driven Spiking Transformer	Transformer-based Spiking Neural Networks (SNNs) introduce a novel event-driven self-attention paradigm that combines the high performance of Transformers with the energy efficiency of SNNs. However, the larger model size and increased computational demands of the Transformer structure limit their practicality in resou...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	523,764
2009.02251	Efficient Model-Based Collaborative Filtering with Fast Adaptive PCA	A model-based collaborative filtering (CF) approach utilizing fast adaptive randomized singular value decomposition (SVD) is proposed for the matrix completion problem in recommender system. Firstly, a fast adaptive PCA frameworkis presented which combines the fixed-precision randomized matrix factorization algorithm [...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	true	194,499
2312.00066	Exploring Factors Affecting Pedestrian Crash Severity Using TabNet: A Deep Learning Approach	This study presents the first investigation of pedestrian crash severity using the TabNet model, a novel tabular deep learning method exceptionally suited for analyzing the tabular data inherent in transportation safety research. Through the application of TabNet to a comprehensive dataset from Utah covering the years ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	411,885
2111.14493	On the Effectiveness of Neural Ensembles for Image Classification with Small Datasets	Deep neural networks represent the gold standard for image classification. However, they usually need large amounts of data to reach superior performance. In this work, we focus on image classification problems with a few labeled examples per class and improve data efficiency by using an ensemble of relatively small ne...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	268,617
2311.06362	Word Definitions from Large Language Models	Dictionary definitions are historically the arbitrator of what words mean, but this primacy has come under threat by recent progress in NLP, including word embeddings and generative models like ChatGPT. We present an exploratory study of the degree of alignment between word definitions from classical dictionaries and t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	406,906
2104.04765	Q-matrix Unaware Double JPEG Detection using DCT-Domain Deep BiLSTM Network	The double JPEG compression detection has received much attention in recent years due to its applicability as a forensic tool for the most widely used JPEG file format. Existing state-of-the-art CNN-based methods either use histograms of all the frequencies or rely on heuristics to select histograms of specific low fre...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	229,489
1906.07991	Computationally Efficient Distributed Multi-sensor Fusion with Multi-Bernoulli Filter	This paper proposes a computationally efficient algorithm for distributed fusion in a sensor network in which multi-Bernoulli (MB) filters are locally running in every sensor node for multi-target tracking. The generalized Covariance Intersection (GCI) fusion rule is employed to fuse multiple MB random finite set densi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	135,753
2103.13146	Energy-Efficient Resource Allocation in Massive MIMO-NOMA Networks with Wireless Power Transfer: A Distributed ADMM Approach	In multicell massive multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) networks, base stations (BSs) with multiple antennas deliver their radio frequency energy in the downlink, and Internet-of-Things (IoT) devices use their harvested energy to support uplink data transmission. This paper inve...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	226,406
2207.06252	Context-Consistent Semantic Image Editing with Style-Preserved Modulation	Semantic image editing utilizes local semantic label maps to generate the desired content in the edited region. A recent work borrows SPADE block to achieve semantic image editing. However, it cannot produce pleasing results due to style discrepancy between the edited region and surrounding pixels. We attribute this to...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	307,822
1407.6714	CrowdSTAR: A Social Task Routing Framework for Online Communities	The online communities available on the Web have shown to be significantly interactive and capable of collectively solving difficult tasks. Nevertheless, it is still a challenge to decide how a task should be dispatched through the network due to the high diversity of the communities and the dynamically changing expert...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	34,889
1905.05637	Randomized Adversarial Imitation Learning for Autonomous Driving	With the evolution of various advanced driver assistance system (ADAS) platforms, the design of autonomous driving system is becoming more complex and safety-critical. The autonomous driving system simultaneously activates multiple ADAS functions; and thus it is essential to coordinate various ADAS functions. This pape...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	130,775
2408.08471	Fairness Issues and Mitigations in (Differentially Private) Socio-Demographic Data Processes	Statistical agencies rely on sampling techniques to collect socio-demographic data crucial for policy-making and resource allocation. This paper shows that surveys of important societal relevance introduce sampling errors that unevenly impact group-level estimates, thereby compromising fairness in downstream decisions....	false	false	false	false	true	false	false	false	false	false	false	false	true	true	false	false	false	false	481,005
1810.08236	Semantic Integration in the Information Flow Framework	The Information Flow Framework (IFF) is a descriptive category metatheory currently under development, which is being offered as the structural aspect of the Standard Upper Ontology (SUO). The architecture of the IFF is composed of metalevels, namespaces and meta-ontologies. The main application of the IFF is instituti...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	110,782
1205.5589	Technical report: Two observations on probability distribution symmetries for randomly-projected data	In this technical report, we will make two observations concerning symmetries of the probability distribution resulting from projection of a piece of p-dimensional data onto a random m-dimensional subspace of $\mathbb{R}^p$, where m < p. In particular, we shall observe that such distributions are unchanged by reflectio...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	16,167
2212.12420	Delay Analysis of IEEE 802.11be Multi-link Operation under Finite Load	Multi-link Operation (MLO), arguably the most disruptive feature introduced in IEEE 802.11be, will cater for delay-sensitive applications by using multiple radio interfaces concurrently. In this paper, we analyze the delay distribution of MLO under non-saturated traffic. Our results show that upgrading from legacy sing...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	338,037
2312.04560	NeRFiller: Completing Scenes via Generative 3D Inpainting	We propose NeRFiller, an approach that completes missing portions of a 3D capture via generative 3D inpainting using off-the-shelf 2D visual generative models. Often parts of a captured 3D scene or object are missing due to mesh reconstruction failures or a lack of observations (e.g., contact regions, such as the botto...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	413,727
1805.12343	Least-square based recursive optimization for distance-based source localization	In this paper we study the problem of driving an agent to an unknown source whose location is estimated in real-time by a recursive optimization algorithm. The optimization criterion is subject to a least-square cost function constructed from the distance measurements to the target combined with the agent's self-odomet...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	99,152
2010.09788	Deriving Commonsense Inference Tasks from Interactive Fictions	Commonsense reasoning simulates the human ability to make presumptions about our physical world, and it is an indispensable cornerstone in building general AI systems. We propose a new commonsense reasoning dataset based on human's interactive fiction game playings as human players demonstrate plentiful and diverse com...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	201,657
1506.08244	Formation Control in Multi-Agent Systems Over Packet Dropping Links	One major challenge in implementation of formation control problems stems from the packet loss that occur in these shared communication channel. In the presence of packet loss the coordination information among agents is lost. Moreover, there is a move to use wireless channels in formation control applications. It has ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	44,588
1712.03687	FHEDN: A based on context modeling Feature Hierarchy Encoder-Decoder Network for face detection	Because of affected by weather conditions, camera pose and range, etc. Objects are usually small, blur, occluded and diverse pose in the images gathered from outdoor surveillance cameras or access control system. It is challenging and important to detect faces precisely for face recognition system in the field of publi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	86,491
2309.02084	Unsupervised Out-of-Distribution Detection by Restoring Lossy Inputs with Variational Autoencoder	Deep generative models have been demonstrated as problematic in the unsupervised out-of-distribution (OOD) detection task, where they tend to assign higher likelihoods to OOD samples. Previous studies on this issue are usually not applicable to the Variational Autoencoder (VAE). As a popular subclass of generative mode...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	389,925
2110.14867	Modeling, simulation, and optimization of a monopod hopping on yielding terrain	Legged locomotion on deformable terrain is a challenging and open robo-physics problem since the uncertainty in terrain dynamics introduced by ground deformation complicates the dynamical modelling and control methods. Moreover, learning how (e.g. what controls and mechanisms) to move efficiently and stably on soft gro...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	263,672
1306.0340	Majority-vote model on Opinion-Dependent Networks	We study a nonequilibrium model with up-down symmetry and a noise parameter $q$ known as majority-vote model of M.J. Oliveira $1992$ on opinion-dependent network or Stauffer-Hohnisch-Pittnauer networks. By Monte Carlo simulations and finite-size scaling relations the critical exponents $\beta/\nu$, $\gamma/\nu$, and $1...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	24,956

Subsets and Splits

No community queries yet

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