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
1707.06541	Discretization-free Knowledge Gradient Methods for Bayesian Optimization	This paper studies Bayesian ranking and selection (R&S) problems with correlated prior beliefs and continuous domains, i.e. Bayesian optimization (BO). Knowledge gradient methods [Frazier et al., 2008, 2009] have been widely studied for discrete R&S problems, which sample the one-step Bayes-optimal point. When used ove...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	77,442
2401.04122	From Prompt Engineering to Prompt Science With Human in the Loop	As LLMs make their way into many aspects of our lives, one place that warrants increased scrutiny with LLM usage is scientific research. Using LLMs for generating or analyzing data for research purposes is gaining popularity. But when such application is marred with ad-hoc decisions and engineering solutions, we need t...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	420,331
1711.03082	Offline signature authenticity verification through unambiguously connected skeleton segments	A method for offline signature verification is presented in this paper. It is based on the segmentation of the signature skeleton (through standard image skeletonization) into unambiguous sequences of points, or unambiguously connected skeleton segments corresponding to vectorial representations of signature portions. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	84,153
2307.01391	A New Learning Approach for Noise Reduction	Noise is a part of data whether the data is from measurement, experiment or ... A few techniques are suggested for noise reduction to improve the data quality in recent years some of which are based on wavelet, orthogonalization and neural networks. The computational cost of existing methods are more than expected and ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	377,332
2106.03723	Self-Supervised Graph Learning with Proximity-based Views and Channel Contrast	We consider graph representation learning in a self-supervised manner. Graph neural networks (GNNs) use neighborhood aggregation as a core component that results in feature smoothing among nodes in proximity. While successful in various prediction tasks, such a paradigm falls short of capturing nodes' similarities over...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	239,423
2111.00735	Calibrating Explore-Exploit Trade-off for Fair Online Learning to Rank	Online learning to rank (OL2R) has attracted great research interests in recent years, thanks to its advantages in avoiding expensive relevance labeling as required in offline supervised ranking model learning. Such a solution explores the unknowns (e.g., intentionally present selected results on top positions) to impr...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	264,320
2309.10359	Prompt, Condition, and Generate: Classification of Unsupported Claims with In-Context Learning	Unsupported and unfalsifiable claims we encounter in our daily lives can influence our view of the world. Characterizing, summarizing, and -- more generally -- making sense of such claims, however, can be challenging. In this work, we focus on fine-grained debate topics and formulate a new task of distilling, from such...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	392,977
2407.17940	Positive Text Reframing under Multi-strategy Optimization	Differing from sentiment transfer, positive reframing seeks to substitute negative perspectives with positive expressions while preserving the original meaning. With the emergence of pre-trained language models (PLMs), it is possible to achieve acceptable results by fine-tuning PLMs. Nevertheless, generating fluent, di...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	476,182
1605.01434	Performance Comparison of CP-OFDM and OQAM-OFDM Based WiFi Systems	In this contribution, a direct comparison of the Offset-QAM-OFDM (OQAM-OFDM) and the Cyclic Prefix OFDM (CP-OFDM) scheme is given for an 802.11a based system. Therefore, the chosen algorithms and choices of design are described and evaluated as a whole system in terms of bit and frame error rate (BER/FER) performance a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	55,479
2111.00178	Direct attacks using fake images in iris verification	In this contribution, the vulnerabilities of iris-based recognition systems to direct attacks are studied. A database of fake iris images has been created from real iris of the BioSec baseline database. Iris images are printed using a commercial printer and then, presented at the iris sensor. We use for our experiments...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	264,130
2312.10917	Semi-Supervised Clustering via Structural Entropy with Different Constraints	Semi-supervised clustering techniques have emerged as valuable tools for leveraging prior information in the form of constraints to improve the quality of clustering outcomes. Despite the proliferation of such methods, the ability to seamlessly integrate various types of constraints remains limited. While structural en...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	416,363
1909.09231	Chaitin's Omega and an Algorithmic Phase Transition	We consider the statistical mechanical ensemble of bit string histories that are computed by a universal Turing machine. The role of the energy is played by the program size. We show that this ensemble has a first-order phase transition at a critical temperature, at which the partition function equals Chaitin's halting...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	146,192
2012.01668	Online Forgetting Process for Linear Regression Models	Motivated by the EU's "Right To Be Forgotten" regulation, we initiate a study of statistical data deletion problems where users' data are accessible only for a limited period of time. This setting is formulated as an online supervised learning task with \textit{constant memory limit}. We propose a deletion-aware algori...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	209,486
1908.00625	Learning about spatial inequalities: Capturing the heterogeneity in the urban environment	Transportation systems can be conceptualized as an instrument of spreading people and resources over the territory, playing an important role in developing sustainable cities. The current rationale of transport provision is based on population demand, disregarding land use and socioeconomic information. To meet the cha...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	140,547
2403.05136	DeRO: Dead Reckoning Based on Radar Odometry With Accelerometers Aided for Robot Localization	In this paper, we propose a radar odometry structure that directly utilizes radar velocity measurements for dead reckoning while maintaining its ability to update estimations within the Kalman filter framework. Specifically, we employ the Doppler velocity obtained by a 4D Frequency Modulated Continuous Wave (FMCW) rada...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	435,892
2009.08330	More Embeddings, Better Sequence Labelers?	Recent work proposes a family of contextual embeddings that significantly improves the accuracy of sequence labelers over non-contextual embeddings. However, there is no definite conclusion on whether we can build better sequence labelers by combining different kinds of embeddings in various settings. In this paper, we...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	196,211
1202.2223	Performance Analysis of $\ell_1$-synthesis with Coherent Frames	Signals with sparse frame representations comprise a much more realistic model of nature than that with orthonomal bases. Studies about the signal recovery associated with such sparsity models have been one of major focuses in compressed sensing. In such settings, one important and widely used signal recovery approach ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	14,260
2110.04998	Nonparametric Functional Analysis of Generalized Linear Models Under Nonlinear Constraints	This article introduces a novel nonparametric methodology for Generalized Linear Models which combines the strengths of the binary regression and latent variable formulations for categorical data, while overcoming their disadvantages. Requiring minimal assumptions, it extends recently published parametric versions of t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	260,123
1901.00671	Une nouvelle approche de compl\'etion des valeurs manquantes dans les bases de donn\'ees	When tackling real-life datasets, it is common to face the existence of scrambled missing values within data. Considered as 'dirty data', usually it is removed during a pre-processing step. Starting from the fact that 'making up this missing data is better than throwing out it away', we present a new approach trying to...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	117,827
1409.1045	A Fuzzy Directional Distance Measure	The measure of distance between two fuzzy sets is a fundamental tool within fuzzy set theory, however, distance measures currently within the literature use a crisp value to represent the distance between fuzzy sets. A real valued distance measure is developed into a fuzzy distance measure which better reflects the unc...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	35,790
2007.00559	Index Coding in Vehicle to Vehicle Communication	Vehicle to Vehicle (V2V) communication phase is an integral part of collaborative message dissemination in vehicular ad-hoc networks (VANETs). In this work, we apply index coding techniques to reduce the number of transmissions required for data exchange. The index coding problem has a sender, which tries to meet the d...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	185,151
1406.0281	On Classification with Bags, Groups and Sets	Many classification problems can be difficult to formulate directly in terms of the traditional supervised setting, where both training and test samples are individual feature vectors. There are cases in which samples are better described by sets of feature vectors, that labels are only available for sets rather than i...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	33,545
2409.00572	The Persistent Robot Charging Problem for Long-Duration Autonomy	This paper introduces a novel formulation aimed at determining the optimal schedule for recharging a fleet of $n$ heterogeneous robots, with the primary objective of minimizing resource utilization. This study provides a foundational framework applicable to Multi-Robot Mission Planning, particularly in scenarios demand...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	484,976
1910.10826	A Safety Constrained Control Framework for UAVs in GPS Denied Environment	Unmanned aerial vehicles (UAVs) suffer from sensor drifts in GPS denied environments, which can lead to potentially dangerous situations. To avoid intolerable sensor drifts in the presence of GPS spoofing attacks, we propose a safety constrained control framework that adapts the UAV at a path re-planning level to suppo...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	150,594
2208.14403	Verifiable Obstacle Detection	Perception of obstacles remains a critical safety concern for autonomous vehicles. Real-world collisions have shown that the autonomy faults leading to fatal collisions originate from obstacle existence detection. Open source autonomous driving implementations show a perception pipeline with complex interdependent Deep...	false	false	false	false	false	false	false	true	false	false	true	true	false	false	false	false	false	false	315,315
1803.04242	Video Object Segmentation with Joint Re-identification and Attention-Aware Mask Propagation	The problem of video object segmentation can become extremely challenging when multiple instances co-exist. While each instance may exhibit large scale and pose variations, the problem is compounded when instances occlude each other causing failures in tracking. In this study, we formulate a deep recurrent network that...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	92,416
2302.04185	Efficient Joint Learning for Clinical Named Entity Recognition and Relation Extraction Using Fourier Networks: A Use Case in Adverse Drug Events	Current approaches for clinical information extraction are inefficient in terms of computational costs and memory consumption, hindering their application to process large-scale electronic health records (EHRs). We propose an efficient end-to-end model, the Joint-NER-RE-Fourier (JNRF), to jointly learn the tasks of nam...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	344,620
2408.16762	UV-free Texture Generation with Denoising and Geodesic Heat Diffusions	Seams, distortions, wasted UV space, vertex-duplication, and varying resolution over the surface are the most prominent issues of the standard UV-based texturing of meshes. These issues are particularly acute when automatic UV-unwrapping techniques are used. For this reason, instead of generating textures in automatica...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	484,441
2305.13082	Sketch-and-Project Meets Newton Method: Global $\mathcal O(k^{-2})$ Convergence with Low-Rank Updates	In this paper, we propose the first sketch-and-project Newton method with fast $\mathcal O(k^{-2})$ global convergence rate for self-concordant functions. Our method, SGN, can be viewed in three ways: i) as a sketch-and-project algorithm projecting updates of Newton method, ii) as a cubically regularized Newton ethod i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	366,338
1706.00957	Semantic Vector Encoding and Similarity Search Using Fulltext Search Engines	Vector representations and vector space modeling (VSM) play a central role in modern machine learning. We propose a novel approach to `vector similarity searching' over dense semantic representations of words and documents that can be deployed on top of traditional inverted-index-based fulltext engines, taking advantag...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	74,723
2410.18693	Unleashing Reasoning Capability of LLMs via Scalable Question Synthesis from Scratch	The availability of high-quality data is one of the most important factors in improving the reasoning capability of LLMs. Existing works have demonstrated the effectiveness of creating more instruction data from seed questions or knowledge bases. Recent research indicates that continually scaling up data synthesis from...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	501,994
2305.19598	Towards Semi-supervised Universal Graph Classification	Graph neural networks have pushed state-of-the-arts in graph classifications recently. Typically, these methods are studied within the context of supervised end-to-end training, which necessities copious task-specific labels. However, in real-world circumstances, labeled data could be limited, and there could be a mass...	false	false	false	true	true	true	true	false	false	false	false	false	false	false	false	false	false	false	369,604
1905.01686	New Item Consumption Prediction Using Deep Learning	Recommendation systems have become ubiquitous in today's online world and are an integral part of practically every e-commerce platform. While traditional recommender systems use customer history, this approach is not feasible in 'cold start' scenarios. Such scenarios include the need to produce recommendations for new...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	129,789
2009.11453	Control Policies for Recovery of Interdependent Systems After Disruptions	We examine a control problem where the states of the components of a system deteriorate after a disruption, if they are not being repaired by an entity. There exist a set of dependencies in the form of precedence constraints between the components, captured by a directed acyclic graph (DAG). The objective of the entity...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	197,173
1403.3376	Massive MIMO performance evaluation based on measured propagation data	Massive MIMO, also known as very-large MIMO or large-scale antenna systems, is a new technique that potentially can offer large network capacities in multi-user scenarios. With a massive MIMO system, we consider the case where a base station equipped with a large number of antenna elements simultaneously serves multipl...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	31,568
2501.09399	Fast Searching of Extreme Operating Conditions for Relay Protection Setting Calculation Based on Graph Neural Network and Reinforcement Learning	Searching for the Extreme Operating Conditions (EOCs) is one of the core problems of power system relay protection setting calculation. The current methods based on brute-force search, heuristic algorithms, and mathematical programming can hardly meet the requirements of today's power systems in terms of computation sp...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	525,128
2206.06960	ABCinML: Anticipatory Bias Correction in Machine Learning Applications	The idealization of a static machine-learned model, trained once and deployed forever, is not practical. As input distributions change over time, the model will not only lose accuracy, any constraints to reduce bias against a protected class may fail to work as intended. Thus, researchers have begun to explore ways to ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	302,553
1609.08286	Online Unsupervised Multi-view Feature Selection	In the era of big data, it is becoming common to have data with multiple modalities or coming from multiple sources, known as "multi-view data". Multi-view data are usually unlabeled and come from high-dimensional spaces (such as language vocabularies), unsupervised multi-view feature selection is crucial to many appli...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	61,562
2408.15082	Compact Pixelated Microstrip Forward Broadside Coupler Using Binary Particle Swarm Optimization	In this paper, a compact microstrip forward broadside coupler (MFBC) with high coupling level is proposed in the frequency band of 3.5-3.8 GHz. The coupler is composed of two parallel pixelated transmission lines. To validate the designstrategy, the proposed MFBC is fabricated and measured. The measured results demonst...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	483,791
2305.05352	A Taxonomy of Foundation Model based Systems through the Lens of Software Architecture	The recent release of large language model (LLM) based chatbots, such as ChatGPT, has attracted huge interest in foundation models. It is widely believed that foundation models will serve as the fundamental building blocks for future AI systems. As foundation models are in their early stages, the design of foundation m...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	true	363,114
2201.04487	Smoothness and continuity of cost functionals for ECG mismatch computation	The field of cardiac electrophysiology tries to abstract, describe and finally model the electrical characteristics of a heartbeat. With recent advances in cardiac electrophysiology, models have become more powerful and descriptive as ever. However, to advance to the field of inverse electrophysiological modeling, i.e....	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	275,119
2003.05728	Fixed-order strong H-infinity control of interconnected systems with time-delays	We design fixed-order strong H-infinity controllers for general time-delay systems. The designer chooses the controller order and may introduce constant time-delays in the controller. We represent the closed-loop system of the plant and the controller as delay differential algebraic equations (DDAEs). This representati...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	167,932
1511.04661	A System for Extracting Sentiment from Large-Scale Arabic Social Data	Social media data in Arabic language is becoming more and more abundant. It is a consensus that valuable information lies in social media data. Mining this data and making the process easier are gaining momentum in the industries. This paper describes an enterprise system we developed for extracting sentiment from larg...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	48,926
2412.14002	Operator Splitting for Convex Constrained Markov Decision Processes	We consider finite Markov decision processes (MDPs) with convex constraints and known dynamics. In principle, this problem is amenable to off-the-shelf convex optimization solvers, but typically this approach suffers from poor scalability. In this work, we develop a first-order algorithm, based on the Douglas-Rachford ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	518,534
1911.11502	Hearing Lips: Improving Lip Reading by Distilling Speech Recognizers	Lip reading has witnessed unparalleled development in recent years thanks to deep learning and the availability of large-scale datasets. Despite the encouraging results achieved, the performance of lip reading, unfortunately, remains inferior to the one of its counterpart speech recognition, due to the ambiguous nature...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	155,146
2005.00269	Energy-Efficient Wireless Communications with Distributed Reconfigurable Intelligent Surfaces	This paper investigates the problem of resource allocation for a wireless communication network with distributed reconfigurable intelligent surfaces (RISs). In this network, multiple RISs are spatially distributed to serve wireless users and the energy efficiency of the network is maximized by dynamically controlling t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	175,183
2310.16828	TD-MPC2: Scalable, Robust World Models for Continuous Control	TD-MPC is a model-based reinforcement learning (RL) algorithm that performs local trajectory optimization in the latent space of a learned implicit (decoder-free) world model. In this work, we present TD-MPC2: a series of improvements upon the TD-MPC algorithm. We demonstrate that TD-MPC2 improves significantly over ba...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	402,893
1603.02563	A Jamming-resilient Algorithm for Self-triggered Network Coordination	The issue of cyber-security has become ever more prevalent in the analysis and design of cyber-physical systems. In this paper, we investigate self-triggered consensus networks in the presence of communication failures caused by Denialof- Service (DoS) attacks. A general framework is considered in which the network lin...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	53,024
2002.12761	DIHARD II is Still Hard: Experimental Results and Discussions from the DKU-LENOVO Team	In this paper, we present the submitted system for the second DIHARD Speech Diarization Challenge from the DKULENOVO team. Our diarization system includes multiple modules, namely voice activity detection (VAD), segmentation, speaker embedding extraction, similarity scoring, clustering, resegmentation and overlap detec...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	166,129
2410.02203	GraphIC: A Graph-Based In-Context Example Retrieval Model for Multi-Step Reasoning	In-context learning (ICL) enables large language models (LLMs) to generalize to new tasks by incorporating a few in-context examples (ICEs) directly in the input, without updating parameters. However, the effectiveness of ICL heavily relies on the selection of ICEs, and conventional text-based embedding methods are oft...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	494,166
1906.01374	Autonomous Reinforcement Learning of Multiple Interrelated Tasks	Autonomous multiple tasks learning is a fundamental capability to develop versatile artificial agents that can act in complex environments. In real-world scenarios, tasks may be interrelated (or "hierarchical") so that a robot has to first learn to achieve some of them to set the preconditions for learning other ones. ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	133,692
2003.12093	To Tweet or Not to Tweet: Covertly Manipulating a Twitter Debate on Vaccines Using Malware-Induced Misperceptions	Trolling and social bots have been proven as powerful tactics for manipulating the public opinion and sowing discord among Twitter users. This effort requires substantial content fabrication and account coordination to evade Twitter's detection of nefarious platform use. In this paper we explore an alternative tactic f...	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	169,809
2408.13480	Towards a Converged Relational-Graph Optimization Framework	The recent ISO SQL:2023 standard adopts SQL/PGQ (Property Graph Queries), facilitating graph-like querying within relational databases. This advancement, however, underscores a significant gap in how to effectively optimize SQL/PGQ queries within relational database systems. To address this gap, we extend the foundatio...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	483,157
2210.02081	Locate before Answering: Answer Guided Question Localization for Video Question Answering	Video question answering (VideoQA) is an essential task in vision-language understanding, which has attracted numerous research attention recently. Nevertheless, existing works mostly achieve promising performances on short videos of duration within 15 seconds. For VideoQA on minute-level long-term videos, those method...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	321,516
2003.02170	HintPose	Most of the top-down pose estimation models assume that there exists only one person in a bounding box. However, the assumption is not always correct. In this technical report, we introduce two ideas, instance cue and recurrent refinement, to an existing pose estimator so that the model is able to handle detection boxe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	166,866
2407.17596	Quality Assured: Rethinking Annotation Strategies in Imaging AI	This paper does not describe a novel method. Instead, it studies an essential foundation for reliable benchmarking and ultimately real-world application of AI-based image analysis: generating high-quality reference annotations. Previous research has focused on crowdsourcing as a means of outsourcing annotations. Howeve...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	476,040
2305.09193	Easy-to-Hard Learning for Information Extraction	Information extraction (IE) systems aim to automatically extract structured information, such as named entities, relations between entities, and events, from unstructured texts. While most existing work addresses a particular IE task, universally modeling various IE tasks with one model has achieved great success recen...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	364,550
1508.00722	Multi-Label Active Learning from Crowds	Multi-label active learning is a hot topic in reducing the label cost by optimally choosing the most valuable instance to query its label from an oracle. In this paper, we consider the poolbased multi-label active learning under the crowdsourcing setting, where during the active query process, instead of resorting to a...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	45,708
1909.11765	A Multimodal Alerting System for Online Class Quality Assurance	Online 1 on 1 class is created for more personalized learning experience. It demands a large number of teaching resources, which are scarce in China. To alleviate this problem, we build a platform (marketplace), i.e., \emph{Dahai} to allow college students from top Chinese universities to register as part-time instruct...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	146,903
2305.03661	Predicting COVID-19 and pneumonia complications from admission texts	In this paper we present a novel approach to risk assessment for patients hospitalized with pneumonia or COVID-19 based on their admission reports. We applied a Longformer neural network to admission reports and other textual data available shortly after admission to compute risk scores for the patients. We used patien...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	362,470
2306.02715	Federated Deep Learning for Intrusion Detection in IoT Networks	The vast increase of Internet of Things (IoT) technologies and the ever-evolving attack vectors have increased cyber-security risks dramatically. A common approach to implementing AI-based Intrusion Detection systems (IDSs) in distributed IoT systems is in a centralised manner. However, this approach may violate data p...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	371,024
2407.19914	Sentiment Analysis of Lithuanian Online Reviews Using Large Language Models	Sentiment analysis is a widely researched area within Natural Language Processing (NLP), attracting significant interest due to the advent of automated solutions. Despite this, the task remains challenging because of the inherent complexity of languages and the subjective nature of sentiments. It is even more challengi...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	476,984
2412.07499	EDGE: Unknown-aware Multi-label Learning by Energy Distribution Gap Expansion	Multi-label Out-Of-Distribution (OOD) detection aims to discriminate the OOD samples from the multi-label In-Distribution (ID) ones. Compared with its multiclass counterpart, it is crucial to model the joint information among classes. To this end, JointEnergy, which is a representative multi-label OOD inference criteri...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	515,689
2409.19132	From Vision to Audio and Beyond: A Unified Model for Audio-Visual Representation and Generation	Video encompasses both visual and auditory data, creating a perceptually rich experience where these two modalities complement each other. As such, videos are a valuable type of media for the investigation of the interplay between audio and visual elements. Previous studies of audio-visual modalities primarily focused ...	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	492,545
1903.03697	Scalable and Congestion-aware Routing for Autonomous Mobility-on-Demand via Frank-Wolfe Optimization	We consider the problem of vehicle routing for Autonomous Mobility-on-Demand (AMoD) systems, wherein a fleet of self-driving vehicles provides on-demand mobility in a given environment. Specifically, the task it to compute routes for the vehicles (both customer-carrying and empty travelling) so that travel demand is fu...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	123,791
2408.17006	Retrieval-Augmented Natural Language Reasoning for Explainable Visual Question Answering	Visual Question Answering with Natural Language Explanation (VQA-NLE) task is challenging due to its high demand for reasoning-based inference. Recent VQA-NLE studies focus on enhancing model networks to amplify the model's reasoning capability but this approach is resource-consuming and unstable. In this work, we intr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	484,540
1802.06015	Diversity from the Topology of Citation Networks	We study transitivity in directed acyclic graphs and its usefulness in capturing nodes that act as bridges between more densely interconnected parts in such type of network. In transitively reduced citation networks degree centrality could be used as a measure of interdisciplinarity or diversity. We study the measure's...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	90,570
1902.04227	Beamwidth Control for NOMA in Hybrid mmWave Communication Systems	In this paper, we propose a beamwidth control-based non-orthogonal multiple access (NOMA) scheme for hybrid millimeter wave (mmWave) communication systems. In particular, the proposed scheme allows multiple users in one NOMA group to share the same radio frequency chain and analog beam for superposition transmission. T...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	121,292
2304.07417	Understanding and Mitigating Mental Health Misinformation on Video Sharing Platforms	Despite the ever-strong demand for mental health care globally, access to traditional mental health services remains severely limited expensive, and stifled by stigma and systemic barriers. Thus, over the last few years, young people are increasingly turning to content on video-sharing platforms (VSPs) like TikTok and ...	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	358,332
2311.06900	Symbol-Error Probability Constrained Power Minimization for Reconfigurable Intelligent Surfaces-based Passive Transmitter	This study considers a virtual multiuser multiple-input multiple-output system with PSK modulation realized via the reconfigurable intelligent surface-based passive transmitter setup. Under this framework, the study derives the formulation for the union-bound symbol-error probability, which is an upper bound on the act...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	407,124
2304.10038	Open-World Continual Learning: Unifying Novelty Detection and Continual Learning	As AI agents are increasingly used in the real open world with unknowns or novelties, they need the ability to (1) recognize objects that (a) they have learned before and (b) detect items that they have never seen or learned, and (2) learn the new items incrementally to become more and more knowledgeable and powerful. ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	359,267
2404.00629	Against The Achilles' Heel: A Survey on Red Teaming for Generative Models	Generative models are rapidly gaining popularity and being integrated into everyday applications, raising concerns over their safe use as various vulnerabilities are exposed. In light of this, the field of red teaming is undergoing fast-paced growth, highlighting the need for a comprehensive survey covering the entire ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	443,035
2502.11859	Defining and Evaluating Visual Language Models' Basic Spatial Abilities: A Perspective from Psychometrics	The Theory of Multiple Intelligences underscores the hierarchical nature of cognitive capabilities. To advance Spatial Artificial Intelligence, we pioneer a psychometric framework defining five Basic Spatial Abilities (BSAs) in Visual Language Models (VLMs): Spatial Perception, Spatial Relation, Spatial Orientation, Me...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	534,573
2411.17690	Visatronic: A Multimodal Decoder-Only Model for Speech Synthesis	In this paper, we propose a new task -- generating speech from videos of people and their transcripts (VTTS) -- to motivate new techniques for multimodal speech generation. This task generalizes the task of generating speech from cropped lip videos, and is also more complicated than the task of generating generic audio...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	511,545
2305.05460	Optimization- and AI-based approaches to academic quality quantification for transparent academic recruitment: part 1-model development	For fair academic recruitment at universities and research institutions, determination of the right measure based on globally accepted academic quality features is a highly delicate, challenging, but quite important problem to be addressed. In a series of two papers, we consider the modeling part for academic quality q...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	363,157
2107.05627	Hierarchical Neural Dynamic Policies	We tackle the problem of generalization to unseen configurations for dynamic tasks in the real world while learning from high-dimensional image input. The family of nonlinear dynamical system-based methods have successfully demonstrated dynamic robot behaviors but have difficulty in generalizing to unseen configuration...	false	false	false	false	true	false	true	true	false	false	true	true	false	false	false	false	false	false	245,840
2202.13778	Rule-based Evolutionary Bayesian Learning	In our previous work, we introduced the rule-based Bayesian Regression, a methodology that leverages two concepts: (i) Bayesian inference, for the general framework and uncertainty quantification and (ii) rule-based systems for the incorporation of expert knowledge and intuition. The resulting method creates a penalty ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	282,745
2211.11937	Genetic Algorithm for Program Synthesis	A deductive program synthesis tool takes a specification as input and derives a program that satisfies the specification. The drawback of this approach is that search spaces for such correct programs tend to be enormous, making it difficult to derive correct programs within a realistic timeout. To speed up such program...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	true	331,922
2202.13110	Optimal-er Auctions through Attention	RegretNet is a recent breakthrough in the automated design of revenue-maximizing auctions. It combines the flexibility of deep learning with the regret-based approach to relax the Incentive Compatibility (IC) constraint (that participants prefer to bid truthfully) in order to approximate optimal auctions. We propose tw...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	282,488
2102.10556	Inductive logic programming at 30	Inductive logic programming (ILP) is a form of logic-based machine learning. The goal is to induce a hypothesis (a logic program) that generalises given training examples. As ILP turns 30, we review the last decade of research. We focus on (i) new meta-level search methods, (ii) techniques for learning recursive progra...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	221,140
1901.06926	Segmentation of Lumen and External Elastic Laminae in Intravascular Ultrasound Images using Ultrasonic Backscattering Physics Initialized Multiscale Random Walks	Coronary artery disease accounts for a large number of deaths across the world and clinicians generally prefer using x-ray computed tomography or magnetic resonance imaging for localizing vascular pathologies. Interventional imaging modalities like intravascular ultrasound (IVUS) are used to adjunct diagnosis of athero...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	119,119
2110.14341	Active-LATHE: An Active Learning Algorithm for Boosting the Error Exponent for Learning Homogeneous Ising Trees	The Chow-Liu algorithm (IEEE Trans.~Inform.~Theory, 1968) has been a mainstay for the learning of tree-structured graphical models from i.i.d.\ sampled data vectors. Its theoretical properties have been well-studied and are well-understood. In this paper, we focus on the class of trees that are arguably even more funda...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	263,503
2308.04762	Tram-FL: Routing-based Model Training for Decentralized Federated Learning	In decentralized federated learning (DFL), substantial traffic from frequent inter-node communication and non-independent and identically distributed (non-IID) data challenges high-accuracy model acquisition. We propose Tram-FL, a novel DFL method, which progressively refines a global model by transferring it sequentia...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	384,546
1403.3057	Evaluation of Image Segmentation and Filtering With ANN in the Papaya Leaf	Precision agriculture is area with lack of cheap technology. The refinement of the production system brings large advantages to the producer and the use of images makes the monitoring a more cheap methodology. Macronutrients monitoring can to determine the health and vulnerability of the plant in specific stages. In th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	31,533
2005.09512	Applying Genetic Programming to Improve Interpretability in Machine Learning Models	Explainable Artificial Intelligence (or xAI) has become an important research topic in the fields of Machine Learning and Deep Learning. In this paper, we propose a Genetic Programming (GP) based approach, named Genetic Programming Explainer (GPX), to the problem of explaining decisions computed by AI systems. The meth...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	true	177,946
2402.04710	Incorporating Retrieval-based Causal Learning with Information Bottlenecks for Interpretable Graph Neural Networks	Graph Neural Networks (GNNs) have gained considerable traction for their capability to effectively process topological data, yet their interpretability remains a critical concern. Current interpretation methods are dominated by post-hoc explanations to provide a transparent and intuitive understanding of GNNs. However,...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	427,562
2303.08420	Descriptor Distillation for Efficient Multi-Robot SLAM	Performing accurate localization while maintaining the low-level communication bandwidth is an essential challenge of multi-robot simultaneous localization and mapping (MR-SLAM). In this paper, we tackle this problem by generating a compact yet discriminative feature descriptor with minimum inference time. We propose d...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	351,637
cs/0503042	Uplink User Capacity in a CDMA System with Hotspot Microcells: Effects of Finite Transmit Power and Dispersion	This paper examines the uplink user capacity in a two-tier code division multiple access (CDMA) system with hotspot microcells when user terminal power is limited and the wireless channel is finitely-dispersive. A finitely-dispersive channel causes variable fading of the signal power at the output of the RAKE receiver....	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	538,605
2411.18064	Lightweight Gaze Estimation Model Via Fusion Global Information	Deep learning-based appearance gaze estimation methods are gaining popularity due to their high accuracy and fewer constraints from the environment. However, existing high-precision models often rely on deeper networks, leading to problems such as large parameters, long training time, and slow convergence. In terms of ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	511,714
1511.00925	Do Prices Coordinate Markets?	Walrasian equilibrium prices can be said to coordinate markets: They support a welfare optimal allocation in which each buyer is buying bundle of goods that is individually most preferred. However, this clean story has two caveats. First, the prices alone are not sufficient to coordinate the market, and buyers may need...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	48,458
1807.03053	A deep learning approach for understanding natural language commands for mobile service robots	Using natural language to give instructions to robots is challenging, since natural language understanding is still largely an open problem. In this paper we address this problem by restricting our attention to commands modeled as one action, plus arguments (also known as slots). For action detection (also called inten...	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	102,416
cmp-lg/9407025	Recovering From Parser Failures: A Hybrid Statistical/Symbolic Approach	We describe an implementation of a hybrid statistical/symbolic approach to repairing parser failures in a speech-to-speech translation system. We describe a module which takes as input a fragmented parse and returns a repaired meaning representation. It negotiates with the speaker about what the complete meaning of the...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,144
1701.07981	Design Aspects of Multi-Soliton Pulses for Optical Fiber Transmission	We explain how to optimize the nonlinear spectrum of multi-soliton pulses by considering the practical constraints of transmitter, receiver, and lumped-amplified link. The optimization is applied for the experimental transmission of 2ns soliton pulses with independent on-off keying of 10 eigenvalues over 2000 km of NZ-...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	67,381
2405.09923	NTIRE 2024 Restore Any Image Model (RAIM) in the Wild Challenge	In this paper, we review the NTIRE 2024 challenge on Restore Any Image Model (RAIM) in the Wild. The RAIM challenge constructed a benchmark for image restoration in the wild, including real-world images with/without reference ground truth in various scenarios from real applications. The participants were required to re...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	454,581
1912.13139	NOMA-Aided Mobile Edge Computing via User Cooperation	Exploiting the idle computation resources of mobile devices in mobile edge computing (MEC) system can achieve both channel diversity and computing diversity as mobile devices can offload their computation tasks to nearby mobile devices in addition to MEC server embedded access point (AP). In this paper, we propose a no...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	159,011
2011.14661	TransMIA: Membership Inference Attacks Using Transfer Shadow Training	Transfer learning has been widely studied and gained increasing popularity to improve the accuracy of machine learning models by transferring some knowledge acquired in different training. However, no prior work has pointed out that transfer learning can strengthen privacy attacks on machine learning models. In this pa...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	208,851
2210.16536	Differentiable Data Augmentation for Contrastive Sentence Representation Learning	Fine-tuning a pre-trained language model via the contrastive learning framework with a large amount of unlabeled sentences or labeled sentence pairs is a common way to obtain high-quality sentence representations. Although the contrastive learning framework has shown its superiority on sentence representation learning ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	327,370
2412.00070	Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling	Recurrent stochastic configuration networks (RSCNs) have shown great potential in modelling nonlinear dynamic systems with uncertainties. This paper presents an RSCN with hybrid regularization to enhance both the learning capacity and generalization performance of the network. Given a set of temporal data, the well-kno...	false	true	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	512,472
2408.13256	How Diffusion Models Learn to Factorize and Compose	Diffusion models are capable of generating photo-realistic images that combine elements which likely do not appear together in the training set, demonstrating the ability to \textit{compositionally generalize}. Nonetheless, the precise mechanism of compositionality and how it is acquired through training remains elusiv...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	483,075
2311.11347	Large-scale Mixed Traffic Control Using Dynamic Vehicle Routing and Privacy-Preserving Crowdsourcing	Controlling and coordinating urban traffic flow through robot vehicles is emerging as a novel transportation paradigm for the future. While this approach garners growing attention from researchers and practitioners, effectively managing and coordinating large-scale mixed traffic remains a challenge. We introduce an eff...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	408,916

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