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
1703.04870	Low-complexity Location-aware Multi-user Massive MIMO Beamforming for High Speed Train Communications	Massive Multiple-input Multiple-output (MIMO) adaption is one of the primary evolving objectives for the next generation high speed train (HST) communication system. In this paper, we consider how to design an efficient low-complexity location-aware beamforming for the multi-user (MU) massive MIMO system in HST scenari...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	69,975
2305.13800	Generalizable Synthetic Image Detection via Language-guided Contrastive Learning	The heightened realism of AI-generated images can be attributed to the rapid development of synthetic models, including generative adversarial networks (GANs) and diffusion models (DMs). The malevolent use of synthetic images, such as the dissemination of fake news or the creation of fake profiles, however, raises sign...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	366,691
1905.09045	End-to-End Learned Random Walker for Seeded Image Segmentation	We present an end-to-end learned algorithm for seeded segmentation. Our method is based on the Random Walker algorithm, where we predict the edge weights of the underlying graph using a convolutional neural network. This can be interpreted as learning context-dependent diffusivities for a linear diffusion process. Besi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	131,636
2408.13448	ALIAS: DAG Learning with Efficient Unconstrained Policies	Recently, reinforcement learning (RL) has proved a promising alternative for conventional local heuristics in score-based approaches to learning directed acyclic causal graphs (DAGs) from observational data. However, the intricate acyclicity constraint still challenges the efficient exploration of the vast space of DAG...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	483,143
2410.18217	A Methodology for Transformer Ratio Adjustment in Small-Size Rotary Transformers	This study addresses a neglected challenge that has been hidden in the Rotary Transformer (RT) field: the possibility of a discrepancy between transformer ratio and turn number ratio in small-size transformers. Previous investigations have shown that in the geometry design of RTs, as well as their resonant circuit desi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	501,796
2401.13410	How to Forget Clients in Federated Online Learning to Rank?	Data protection legislation like the European Union's General Data Protection Regulation (GDPR) establishes the \textit{right to be forgotten}: a user (client) can request contributions made using their data to be removed from learned models. In this paper, we study how to remove the contributions made by a client part...	false	false	false	false	false	true	true	false	false	false	false	false	true	false	false	false	false	false	423,719
2209.06414	Behavioral Theory for Stochastic Systems? A Data-driven Journey from Willems to Wiener and Back Again	The fundamental lemma by Jan C. Willems and co-workers, which is deeply rooted in behavioral systems theory, has become one of the supporting pillars of the recent progress on data-driven control and system analysis. This tutorial-style paper combines recent insights into stochastic and descriptor-system formulations o...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	317,392
1909.13003	DualSMC: Tunneling Differentiable Filtering and Planning under Continuous POMDPs	A major difficulty of solving continuous POMDPs is to infer the multi-modal distribution of the unobserved true states and to make the planning algorithm dependent on the perceived uncertainty. We cast POMDP filtering and planning problems as two closely related Sequential Monte Carlo (SMC) processes, one over the real...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	147,290
2309.16102	Discovering Utility-driven Interval Rules	For artificial intelligence, high-utility sequential rule mining (HUSRM) is a knowledge discovery method that can reveal the associations between events in the sequences. Recently, abundant methods have been proposed to discover high-utility sequence rules. However, the existing methods are all related to point-based s...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	395,214
2206.02618	Generalized Federated Learning via Sharpness Aware Minimization	Federated Learning (FL) is a promising framework for performing privacy-preserving, distributed learning with a set of clients. However, the data distribution among clients often exhibits non-IID, i.e., distribution shift, which makes efficient optimization difficult. To tackle this problem, many FL algorithms focus on...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	300,961
2104.02279	Mobile Robot Yielding Cues for Human-Robot Spatial Interaction	Mobile robots are increasingly being deployed in public spaces such as shopping malls, airports, and urban sidewalks. Most of these robots are designed with human-aware motion planning capabilities but are not designed to communicate with pedestrians. Pedestrians encounter these robots without prior understanding of th...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	228,665
2011.09867	Exercise Hierarchical Feature Enhanced Knowledge Tracing	Knowledge tracing is a fundamental task in the computer-aid educational system. In this paper, we propose a hierarchical exercise feature enhanced knowledge tracing framework, which could enhance the ability of knowledge tracing by incorporating knowledge distribution, semantic features, and difficulty features from ex...	false	false	false	false	true	false	true	false	true	false	false	false	false	true	false	false	false	false	207,345
2109.11897	Adaptivity for clustering-based reduced-order modeling of localized history-dependent phenomena	This paper proposes a novel Adaptive Clustering-based Reduced-Order Modeling (ACROM) framework to significantly improve and extend the recent family of clustering-based reduced-order models (CROMs). This adaptive framework enables the clustering-based domain decomposition to evolve dynamically throughout the problem so...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	257,093
2007.09852	Multi-label Contrastive Predictive Coding	Variational mutual information (MI) estimators are widely used in unsupervised representation learning methods such as contrastive predictive coding (CPC). A lower bound on MI can be obtained from a multi-class classification problem, where a critic attempts to distinguish a positive sample drawn from the underlying jo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	188,084
2404.15918	Perception and Localization of Macular Degeneration Applying Convolutional Neural Network, ResNet and Grad-CAM	A well-known retinal disease that sends blurry visions to the affected patients is Macular Degeneration. This research is based on classifying the healthy and macular degeneration fundus by localizing the affected region of the fundus. A CNN architecture and CNN with ResNet architecture (ResNet50, ResNet50v2, ResNet101...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	449,284
2102.01995	Convergence Voting: From Pairwise Comparisons to Consensus	An important aspect of AI design and ethics is to create systems that reflect aggregate preferences of the society. To this end, the techniques of social choice theory are often utilized. We propose a new social choice function motivated by the PageRank algorithm. The function ranks voting options based on the Condorce...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	218,294
1606.01614	Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification	In recent years great success has been achieved in sentiment classification for English, thanks in part to the availability of copious annotated resources. Unfortunately, most languages do not enjoy such an abundance of labeled data. To tackle the sentiment classification problem in low-resource languages without adequ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	56,841
1604.02080	Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes	Information-theoretic principles for learning and acting have been proposed to solve particular classes of Markov Decision Problems. Mathematically, such approaches are governed by a variational free energy principle and allow solving MDP planning problems with information-processing constraints expressed in terms of a...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	54,286
2202.00538	The impact of removing head movements on audio-visual speech enhancement	This paper investigates the impact of head movements on audio-visual speech enhancement (AVSE). Although being a common conversational feature, head movements have been ignored by past and recent studies: they challenge today's learning-based methods as they often degrade the performance of models that are trained on c...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	278,180
2310.16450	CLEX: Continuous Length Extrapolation for Large Language Models	Transformer-based Large Language Models (LLMs) are pioneering advances in many natural language processing tasks, however, their exceptional capabilities are restricted within the preset context window of Transformer. Position Embedding (PE) scaling methods, while effective in extending the context window to a specific...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	402,736
2501.07523	Parallel Key-Value Cache Fusion for Position Invariant RAG	Recent advancements in Large Language Models (LLMs) underscore the necessity of Retrieval Augmented Generation (RAG) to leverage external information. However, LLMs are sensitive to the position of relevant information within contexts and tend to generate incorrect responses when such information is placed in the middl...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	524,423
1101.5334	SmartInt: Using Mined Attribute Dependencies to Integrate Fragmented Web Databases	Many web databases can be seen as providing partial and overlapping information about entities in the world. To answer queries effectively, we need to integrate the information about the individual entities that are fragmented over multiple sources. At first blush this is just the inverse of traditional database normal...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	8,942
2209.03714	Visual Grounding of Inter-lingual Word-Embeddings	Visual grounding of Language aims at enriching textual representations of language with multiple sources of visual knowledge such as images and videos. Although visual grounding is an area of intense research, inter-lingual aspects of visual grounding have not received much attention. The present study investigates the...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	316,574
2409.12426	UniMSF: A Unified Multi-Sensor Fusion Framework for Intelligent Transportation System Global Localization	Intelligent transportation systems (ITS) localization is of significant importance as it provides fundamental position and orientation for autonomous operations like intelligent vehicles. Integrating diverse and complementary sensors such as global navigation satellite system (GNSS) and 4D-radar can provide scalable an...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	489,584
1901.03198	On Finding Gray Pixels	We propose a novel grayness index for finding gray pixels and demonstrate its effectiveness and efficiency in illumination estimation. The grayness index, GI in short, is derived using the Dichromatic Reflection Model and is learning-free. GI allows to estimate one or multiple illumination sources in color-biased image...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	118,359
2411.08335	DEEGITS: Deep Learning based Framework for Measuring Heterogenous Traffic State in Challenging Traffic Scenarios	This paper presents DEEGITS (Deep Learning Based Heterogeneous Traffic State Measurement), a comprehensive framework that leverages state-of-the-art convolutional neural network (CNN) techniques to accurately and rapidly detect vehicles and pedestrians, as well as to measure traffic states in challenging scenarios (i.e...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	507,853
2406.18718	State-Based Automation for Time-Restricted Eating Adherence	Developing and enforcing study protocols is a foundational component of medical research. As study complexity for participant interactions increases, translating study protocols to supporting application code becomes challenging. A collaboration exists between the University of Kentucky and Arizona State University to ...	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	468,145
2106.15535	Subgroup Generalization and Fairness of Graph Neural Networks	Despite enormous successful applications of graph neural networks (GNNs), theoretical understanding of their generalization ability, especially for node-level tasks where data are not independent and identically-distributed (IID), has been sparse. The theoretical investigation of the generalization performance is benef...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	243,798
1709.01110	Distributed circular formation flight of fixed-wing aircraft with Paparazzi autopilot	In this paper we introduce the usage of guidance vector fields for the coordination and formation flight of fixed-wing aircraft. In particular, we describe in detail the technological implementation of the formation flight control for a fully distributed execution of the algorithm by employing the open-source project P...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	80,022
2303.06904	Contextually-rich human affect perception using multimodal scene information	The process of human affect understanding involves the ability to infer person specific emotional states from various sources including images, speech, and language. Affect perception from images has predominantly focused on expressions extracted from salient face crops. However, emotions perceived by humans rely on mu...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	351,045
2001.04889	Physical-Virtual Collaboration Modeling for Intra-and Inter-Station Metro Ridership Prediction	Due to the widespread applications in real-world scenarios, metro ridership prediction is a crucial but challenging task in intelligent transportation systems. However, conventional methods either ignore the topological information of metro systems or directly learn on physical topology, and cannot fully explore the pa...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	160,388
1904.09460	Data-Driven Neuron Allocation for Scale Aggregation Networks	Successful visual recognition networks benefit from aggregating information spanning from a wide range of scales. Previous research has investigated information fusion of connected layers or multiple branches in a block, seeking to strengthen the power of multi-scale representations. Despite their great successes, exis...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	128,386
2412.15402	Optimizing Photovoltaic Panel Quantity for Water Distribution Networks	The paper introduces a procedure for determining an approximation of the optimal amount of photovoltaics (PVs) for powering water distribution networks (WDNs) through grid-connected PVs. The procedure aims to find the PV amount minimizing the total expected cost of the WDN over the lifespan of the PVs. The approach fol...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	519,096
1711.05912	On Channel Reciprocity to Activate Uplink Channel Training for Downlink Wireless Transmission in Tactile Internet Applications	We determine, for the first time, the requirement on channel reciprocity to activate uplink channel training, instead of downlink channel training, to achieve a higher data rate for the downlink transmission from a multi-antenna base station to a single-antenna user. We first derive novel closed-form expressions for th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	84,672
2211.14745	Cross-domain Few-shot Segmentation with Transductive Fine-tuning	Few-shot segmentation (FSS) expects models trained on base classes to work on novel classes with the help of a few support images. However, when there exists a domain gap between the base and novel classes, the state-of-the-art FSS methods may even fail to segment simple objects. To improve their performance on unseen ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	332,976
2005.04605	Robust Tensor Decomposition for Image Representation Based on Generalized Correntropy	Traditional tensor decomposition methods, e.g., two dimensional principal component analysis and two dimensional singular value decomposition, that minimize mean square errors, are sensitive to outliers. To overcome this problem, in this paper we propose a new robust tensor decomposition method using generalized corren...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	176,517
1911.01103	Learning One-Shot Imitation from Humans without Humans	Humans can naturally learn to execute a new task by seeing it performed by other individuals once, and then reproduce it in a variety of configurations. Endowing robots with this ability of imitating humans from third person is a very immediate and natural way of teaching new tasks. Only recently, through meta-learning...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	152,017
2312.15136	Towards End-to-End Structure Solutions from Information-Compromised Diffraction Data via Generative Deep Learning	The revolution in materials in the past century was built on a knowledge of the atomic arrangements and the structure-property relationship. The sine qua non for obtaining quantitative structural information is single crystal crystallography. However, increasingly we need to solve structures in cases where the informat...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	417,884
2303.10566	Dynamical Hyperspectral Unmixing with Variational Recurrent Neural Networks	Multitemporal hyperspectral unmixing (MTHU) is a fundamental tool in the analysis of hyperspectral image sequences. It reveals the dynamical evolution of the materials (endmembers) and of their proportions (abundances) in a given scene. However, adequately accounting for the spatial and temporal variability of the endm...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	352,502
2008.11476	HipaccVX: Wedding of OpenVX and DSL-based Code Generation	Writing programs for heterogeneous platforms optimized for high performance is hard since this requires the code to be tuned at a low level with architecture-specific optimizations that are most times based on fundamentally differing programming paradigms and languages. OpenVX promises to solve this issue for computer ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	193,289
1609.09007	Unsupervised Neural Hidden Markov Models	In this work, we present the first results for neuralizing an Unsupervised Hidden Markov Model. We evaluate our approach on tag in- duction. Our approach outperforms existing generative models and is competitive with the state-of-the-art though with a simpler model easily extended to include additional context.	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	61,660
1304.1100	A Dynamic Approach to Probabilistic Inference	In this paper we present a framework for dynamically constructing Bayesian networks. We introduce the notion of a background knowledge base of schemata, which is a collection of parameterized conditional probability statements. These schemata explicitly separate the general knowledge of properties an individual may hav...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	23,453
1911.05695	Learning Representations in Reinforcement Learning:An Information Bottleneck Approach	The information bottleneck principle is an elegant and useful approach to representation learning. In this paper, we investigate the problem of representation learning in the context of reinforcement learning using the information bottleneck framework, aiming at improving the sample efficiency of the learning algorithm...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	153,338
1905.13533	Autonomous Human Activity Classification from Ego-vision Camera and Accelerometer Data	There has been significant amount of research work on human activity classification relying either on Inertial Measurement Unit (IMU) data or data from static cameras providing a third-person view. Using only IMU data limits the variety and complexity of the activities that can be detected. For instance, the sitting ac...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	133,156
2211.08201	Multiagent Rollout with Reshuffling for Warehouse Robots Path Planning	Efficiently solving path planning problems for a large number of robots is critical to the successful operation of modern warehouses. The existing approaches adopt classical shortest path algorithms to plan in environments whose cells are associated with both space and time in order to avoid collision between robots. I...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	330,521
2303.09995	Neural-prior stochastic block model	The stochastic block model (SBM) is widely studied as a benchmark for graph clustering aka community detection. In practice, graph data often come with node attributes that bear additional information about the communities. Previous works modeled such data by considering that the node attributes are generated from the ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	352,270
2310.01439	Making Friends in the Dark: Ad Hoc Teamwork Under Partial Observability	This paper introduces a formal definition of the setting of ad hoc teamwork under partial observability and proposes a first-principled model-based approach which relies only on prior knowledge and partial observations of the environment in order to perform ad hoc teamwork. We make three distinct assumptions that set i...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	396,431
2006.09902	Vision-Aided Dynamic Blockage Prediction for 6G Wireless Communication Networks	Unlocking the full potential of millimeter-wave and sub-terahertz wireless communication networks hinges on realizing unprecedented low-latency and high-reliability requirements. The challenge in meeting those requirements lies partly in the sensitivity of signals in the millimeter-wave and sub-terahertz frequency rang...	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	182,694
2201.09210	Terra: Imperative-Symbolic Co-Execution of Imperative Deep Learning Programs	Imperative programming allows users to implement their deep neural networks (DNNs) easily and has become an essential part of recent deep learning (DL) frameworks. Recently, several systems have been proposed to combine the usability of imperative programming with the optimized performance of symbolic graph execution. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	276,605
2209.09861	ESTA: An Esports Trajectory and Action Dataset	Sports, due to their global reach and impact-rich prediction tasks, are an exciting domain to deploy machine learning models. However, data from conventional sports is often unsuitable for research use due to its size, veracity, and accessibility. To address these issues, we turn to esports, a growing domain that encom...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	318,662
2310.18840	Customizing 360-Degree Panoramas through Text-to-Image Diffusion Models	Personalized text-to-image (T2I) synthesis based on diffusion models has attracted significant attention in recent research. However, existing methods primarily concentrate on customizing subjects or styles, neglecting the exploration of global geometry. In this study, we propose an approach that focuses on the customi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	403,726
1706.04872	Towards a theory of word order. Comment on "Dependency distance: a new perspective on syntactic patterns in natural language" by Haitao Liu et al	Comment on "Dependency distance: a new perspective on syntactic patterns in natural language" by Haitao Liu et al	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	75,405
2210.11942	Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning	Stackelberg equilibria arise naturally in a range of popular learning problems, such as in security games or indirect mechanism design, and have received increasing attention in the reinforcement learning literature. We present a general framework for implementing Stackelberg equilibria search as a multi-agent RL probl...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	true	325,517
2209.15197	Evaluation of taxonomic and neural embedding methods for calculating semantic similarity	Modelling semantic similarity plays a fundamental role in lexical semantic applications. A natural way of calculating semantic similarity is to access handcrafted semantic networks, but similarity prediction can also be anticipated in a distributional vector space. Similarity calculation continues to be a challenging t...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	320,508
2110.08994	CMTR: Cross-modality Transformer for Visible-infrared Person Re-identification	Visible-infrared cross-modality person re-identification is a challenging ReID task, which aims to retrieve and match the same identity's images between the heterogeneous visible and infrared modalities. Thus, the core of this task is to bridge the huge gap between these two modalities. The existing convolutional neura...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	261,640
1607.00771	OpenGeoBase: Information Centric Networking meets Spatial Database applications - Extended Version	This paper explores methodologies, advantages and challenges related to the use of Information Centric Networking (ICN) for realizing distributed spatial databases. Our findings show that the ICN functionality perfectly fits database requirements: routing-by-name can be used to dispatch queries and insertions, in-netwo...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	58,135
2412.00934	QABISAR: Query-Article Bipartite Interactions for Statutory Article Retrieval	In this paper, we introduce QABISAR, a novel framework for statutory article retrieval, to overcome the semantic mismatch problem when modeling each query-article pair in isolation, making it hard to learn representation that can effectively capture multi-faceted information. QABISAR leverages bipartite interactions be...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	512,873
2309.01855	SMPLitex: A Generative Model and Dataset for 3D Human Texture Estimation from Single Image	We propose SMPLitex, a method for estimating and manipulating the complete 3D appearance of humans captured from a single image. SMPLitex builds upon the recently proposed generative models for 2D images, and extends their use to the 3D domain through pixel-to-surface correspondences computed on the input image. To thi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	389,831
1809.02926	Probabilistic Prediction of Interactive Driving Behavior via Hierarchical Inverse Reinforcement Learning	Autonomous vehicles (AVs) are on the road. To safely and efficiently interact with other road participants, AVs have to accurately predict the behavior of surrounding vehicles and plan accordingly. Such prediction should be probabilistic, to address the uncertainties in human behavior. Such prediction should also be in...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	107,180
1501.04376	Optimal Power Allocation for Secure Communications in Large-Scale MIMO Relaying Systems	In this paper, we address the problem of optimal power allocation at the relay in two-hop secure communications. In order to solve the challenging issue of short-distance interception in secure communications, the benefit of large-scale MIMO (LS-MIMO) relaying techniques is exploited to improve the secrecy performance ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,370
2307.14605	Clustering based Point Cloud Representation Learning for 3D Analysis	Point cloud analysis (such as 3D segmentation and detection) is a challenging task, because of not only the irregular geometries of many millions of unordered points, but also the great variations caused by depth, viewpoint, occlusion, etc. Current studies put much focus on the adaption of neural networks to the comple...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	381,988
2212.07738	A large-scale and PCR-referenced vocal audio dataset for COVID-19	The UK COVID-19 Vocal Audio Dataset is designed for the training and evaluation of machine learning models that classify SARS-CoV-2 infection status or associated respiratory symptoms using vocal audio. The UK Health Security Agency recruited voluntary participants through the national Test and Trace programme and the ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	336,504
2310.11105	Generalizability of CNN Architectures for Face Morph Presentation Attack	Automatic border control systems are wide spread in modern airports worldwide. Morphing attacks on face biometrics is a serious threat that undermines the security and reliability of face recognition systems deployed in airports and border controls. Therefore, developing a robust Machine Learning (ML) system is necessa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	400,525
2204.12534	AccMPEG: Optimizing Video Encoding for Video Analytics	With more videos being recorded by edge sensors (cameras) and analyzed by computer-vision deep neural nets (DNNs), a new breed of video streaming systems has emerged, with the goal to compress and stream videos to remote servers in real time while preserving enough information to allow highly accurate inference by the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	293,507
2206.01608	Structure-Preserving Model Order Reduction for Index One Port-Hamiltonian Descriptor Systems	We develop optimization-based structure-preserving model order reduction (MOR) methods for port-Hamiltonian (pH) descriptor systems of differentiation index one. Descriptor systems in pH form permit energy-based modeling and intuitive coupling of physical systems across different physical domains, scales, and accuracie...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	300,533
2203.10335	TO-FLOW: Efficient Continuous Normalizing Flows with Temporal Optimization adjoint with Moving Speed	Continuous normalizing flows (CNFs) construct invertible mappings between an arbitrary complex distribution and an isotropic Gaussian distribution using Neural Ordinary Differential Equations (neural ODEs). It has not been tractable on large datasets due to the incremental complexity of the neural ODE training. Optimal...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	286,496
1403.5473	Image Fusion Techniques in Remote Sensing	Remote sensing image fusion is an effective way to use a large volume of data from multisensor images. Most earth satellites such as SPOT, Landsat 7, IKONOS and QuickBird provide both panchromatic (Pan) images at a higher spatial resolution and multispectral (MS) images at a lower spatial resolution and many remote sen...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	31,731
2102.10293	Discussion Tracker: Supporting Teacher Learning about Students' Collaborative Argumentation in High School Classrooms	Teaching collaborative argumentation is an advanced skill that many K-12 teachers struggle to develop. To address this, we have developed Discussion Tracker, a classroom discussion analytics system based on novel algorithms for classifying argument moves, specificity, and collaboration. Results from a classroom deploym...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	221,040
2306.13586	NetBooster: Empowering Tiny Deep Learning By Standing on the Shoulders of Deep Giants	Tiny deep learning has attracted increasing attention driven by the substantial demand for deploying deep learning on numerous intelligent Internet-of-Things devices. However, it is still challenging to unleash tiny deep learning's full potential on both large-scale datasets and downstream tasks due to the under-fittin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	375,328
2310.12243	REVAMP: Automated Simulations of Adversarial Attacks on Arbitrary Objects in Realistic Scenes	Deep Learning models, such as those used in an autonomous vehicle are vulnerable to adversarial attacks where an attacker could place an adversarial object in the environment, leading to mis-classification. Generating these adversarial objects in the digital space has been extensively studied, however successfully tran...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	400,948
2306.03481	Transition Role of Entangled Data in Quantum Machine Learning	Entanglement serves as the resource to empower quantum computing. Recent progress has highlighted its positive impact on learning quantum dynamics, wherein the integration of entanglement into quantum operations or measurements of quantum machine learning (QML) models leads to substantial reductions in training data si...	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	false	371,348
1910.07395	Offline handwritten mathematical symbol recognition utilising deep learning	This paper describes an approach for offline recognition of handwritten mathematical symbols. The process of symbol recognition in this paper includes symbol segmentation and accurate classification for over 300 classes. Many multidimensional mathematical symbols need both horizontal and vertical projection to be segme...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	149,597
1602.05546	Fault and Byzantine Tolerant Self-stabilizing Mobile Robots Gathering - Feasibility Study -	Gathering is a fundamental coordination problem in cooperative mobile robotics. In short, given a set of robots with arbitrary initial locations and no initial agreement on a global coordinate system, gathering requires that all robots, following their algorithm, reach the exact same but not predetermined location. Gat...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	52,270
2305.19981	MedNgage: A Dataset for Understanding Engagement in Patient-Nurse Conversations	Patients who effectively manage their symptoms often demonstrate higher levels of engagement in conversations and interventions with healthcare practitioners. This engagement is multifaceted, encompassing cognitive and socio-affective dimensions. Consequently, it is crucial for AI systems to understand the engagement i...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	369,760
2308.06142	CompTLL-UNet: Compressed Domain Text-Line Localization in Challenging Handwritten Documents using Deep Feature Learning from JPEG Coefficients	Automatic localization of text-lines in handwritten documents is still an open and challenging research problem. Various writing issues such as uneven spacing between the lines, oscillating and touching text, and the presence of skew become much more challenging when the case of complex handwritten document images are ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	385,044
1611.08389	Color Constancy with Derivative Colors	Information about the illuminant color is well contained in both achromatic regions and the specular components of highlight regions. In this paper, we propose a novel way to achieve color constancy by exploiting such clues. The key to our approach lies in the use of suitably extracted derivative colors, which are able...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	64,500
2212.11506	Accelerating Barnes-Hut t-SNE Algorithm by Efficient Parallelization on Multi-Core CPUs	t-SNE remains one of the most popular embedding techniques for visualizing high-dimensional data. Most standard packages of t-SNE, such as scikit-learn, use the Barnes-Hut t-SNE (BH t-SNE) algorithm for large datasets. However, existing CPU implementations of this algorithm are inefficient. In this work, we accelerate ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	337,815
1602.00975	BotOrNot: A System to Evaluate Social Bots	While most online social media accounts are controlled by humans, these platforms also host automated agents called social bots or sybil accounts. Recent literature reported on cases of social bots imitating humans to manipulate discussions, alter the popularity of users, pollute content and spread misinformation, and ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	51,640
2107.00333	Multilingual Central Repository: a Cross-lingual Framework for Developing Wordnets	Language resources are necessary for language processing,but building them is costly, involves many researches from different areas and needs constant updating. In this paper, we describe the crosslingual framework used for developing the Multilingual Central Repository (MCR), a multilingual knowledge base that include...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	244,124
2407.07461	Drantal-NeRF: Diffusion-Based Restoration for Anti-aliasing Neural Radiance Field	Aliasing artifacts in renderings produced by Neural Radiance Field (NeRF) is a long-standing but complex issue in the field of 3D implicit representation, which arises from a multitude of intricate causes and was mitigated by designing more advanced but complex scene parameterization methods before. In this paper, we p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	471,771
1605.08838	Dueling Bandits with Dependent Arms	We study dueling bandits with weak utility-based regret when preferences over arms have a total order and carry observable feature vectors. The order is assumed to be determined by these feature vectors, an unknown preference vector, and a known utility function. This structure introduces dependence between preferences...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	56,483
2207.11196	Learning to Singulate Layers of Cloth using Tactile Feedback	Robotic manipulation of cloth has applications ranging from fabrics manufacturing to handling blankets and laundry. Cloth manipulation is challenging for robots largely due to their high degrees of freedom, complex dynamics, and severe self-occlusions when in folded or crumpled configurations. Prior work on robotic man...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	309,540
2112.04882	Evaluating saliency methods on artificial data with different background types	Over the last years, many 'explainable artificial intelligence' (xAI) approaches have been developed, but these have not always been objectively evaluated. To evaluate the quality of heatmaps generated by various saliency methods, we developed a framework to generate artificial data with synthetic lesions and a known g...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	270,668
2109.01731	Acceleration Method for Learning Fine-Layered Optical Neural Networks	An optical neural network (ONN) is a promising system due to its high-speed and low-power operation. Its linear unit performs a multiplication of an input vector and a weight matrix in optical analog circuits. Among them, a circuit with a multiple-layered structure of programmable Mach-Zehnder interferometers (MZIs) ca...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	253,514
2105.14139	On a class of data-driven mixed-integer programming problems under uncertainty: a distributionally robust approach	In this study we analyze linear mixed-integer programming problems, in which the distribution of the cost vector is only observable through a finite training data set. In contrast to the related studies, we assume that the number of random observations for each component of the cost vector may vary. Then the goal is to...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	237,544
1903.01093	Differentiable Causal Computations via Delayed Trace	We investigate causal computations taking sequences of inputs to sequences of outputs where the $n$th output depends on the first $n$ inputs only. We model these in category theory via a construction taking a Cartesian category $C$ to another category $St(C)$ with a novel trace-like operation called "delayed trace", wh...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	123,194
1503.03394	New upper bounds on binary linear codes and a $\mathbb Z_4$-code with a better-than-linear Gray image	Using integer linear programming and table-lookups we prove that there is no binary linear $[1988, 12, 992]$ code. As a by-product, the non-existence of binary linear codes with the parameters $[324, 10, 160]$, $[356, 10, 176]$, $[772,11,384]$, and $[836,11,416]$ is shown. Our work is motivated by the recent construc...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	41,046
1705.10300	Effective Metrics for Multi-Robot Motion-Planning	We study the effectiveness of metrics for Multi-Robot Motion-Planning (MRMP) when using RRT-style sampling-based planners. These metrics play the crucial role of determining the nearest neighbors of configurations and in that they regulate the connectivity of the underlying roadmaps produced by the planners and other p...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	74,368
2303.09906	Discovering mesoscopic descriptions of collective movement with neural stochastic modelling	Collective motion is an ubiquitous phenomenon in nature, inspiring engineers, physicists and mathematicians to develop mathematical models and bio-inspired designs. Collective motion at small to medium group sizes ($\sim$10-1000 individuals, also called the `mesoscale'), can show nontrivial features due to stochasticit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	352,236
2209.13420	Stacking Ensemble Learning in Deep Domain Adaptation for Ophthalmic Image Classification	Domain adaptation is an attractive approach given the availability of a large amount of labeled data with similar properties but different domains. It is effective in image classification tasks where obtaining sufficient label data is challenging. We propose a novel method, named SELDA, for stacking ensemble learning v...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	319,884
1505.06792	Seeing the Forest through the Trees: Adaptive Local Exploration of Large Graphs	Visualization is a powerful paradigm for exploratory data analysis. Visualizing large graphs, however, often results in a meaningless hairball. In this paper, we propose a different approach that helps the user adaptively explore large million-node graphs from a local perspective. For nodes that the user investigates, ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	43,474
2305.08079	Stacked Intelligent Metasurfaces for Efficient Holographic MIMO Communications in 6G	The revolutionary technology of \emph{Stacked Intelligent Metasurfaces (SIM)} has been recently shown to be capable of carrying out advanced signal processing directly in the native electromagnetic (EM) wave domain. An SIM is fabricated by a sophisticated amalgam of multiple stacked metasurface layers, which may outper...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	364,155
2308.02142	Tweet Insights: A Visualization Platform to Extract Temporal Insights from Twitter	This paper introduces a large collection of time series data derived from Twitter, postprocessed using word embedding techniques, as well as specialized fine-tuned language models. This data comprises the past five years and captures changes in n-gram frequency, similarity, sentiment and topic distribution. The interfa...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	383,508
2002.03150	Surrogate Assisted Evolutionary Algorithm for Medium Scale Expensive Multi-Objective Optimisation Problems	Building a surrogate model of an objective function has shown to be effective to assist evolutionary algorithms (EAs) to solve real-world complex optimisation problems which involve either computationally expensive numerical simulations or costly physical experiments. However, their effectiveness mostly focuses on smal...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	163,154
2211.11950	UpCycling: Semi-supervised 3D Object Detection without Sharing Raw-level Unlabeled Scenes	Semi-supervised Learning (SSL) has received increasing attention in autonomous driving to reduce the enormous burden of 3D annotation. In this paper, we propose UpCycling, a novel SSL framework for 3D object detection with zero additional raw-level point cloud: learning from unlabeled de-identified intermediate feature...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	331,930
1605.00873	Queueing Stability and CSI Probing of a TDD Wireless Network with Interference Alignment	This paper characterizes the performance of interference alignment (IA) technique taking into account the dynamic traffic pattern and the probing/feedback cost. We consider a time-division duplex (TDD) system where transmitters acquire their channel state information (CSI) by decoding the pilot sequences sent by the re...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	55,398
2006.01494	Cross-Domain Imitation Learning with a Dual Structure	In this paper, we consider cross-domain imitation learning (CDIL) in which an agent in a target domain learns a policy to perform well in the target domain by observing expert demonstrations in a source domain without accessing any reward function. In order to overcome the domain difference for imitation learning, we p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	179,796
2310.14736	SAMCLR: Contrastive pre-training on complex scenes using SAM for view sampling	In Computer Vision, self-supervised contrastive learning enforces similar representations between different views of the same image. The pre-training is most often performed on image classification datasets, like ImageNet, where images mainly contain a single class of objects. However, when dealing with complex scenes ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	401,997
2209.12894	Biologically-Plausible Determinant Maximization Neural Networks for Blind Separation of Correlated Sources	Extraction of latent sources of complex stimuli is critical for making sense of the world. While the brain solves this blind source separation (BSS) problem continuously, its algorithms remain unknown. Previous work on biologically-plausible BSS algorithms assumed that observed signals are linear mixtures of statistica...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	319,701
2412.03103	MultiGO: Towards Multi-level Geometry Learning for Monocular 3D Textured Human Reconstruction	This paper investigates the research task of reconstructing the 3D clothed human body from a monocular image. Due to the inherent ambiguity of single-view input, existing approaches leverage pre-trained SMPL(-X) estimation models or generative models to provide auxiliary information for human reconstruction. However, t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	513,820

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