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
1803.01526	Blind Channel Equalization using Variational Autoencoders	A new maximum likelihood estimation approach for blind channel equalization, using variational autoencoders (VAEs), is introduced. Significant and consistent improvements in the error rate of the reconstructed symbols, compared to constant modulus equalizers, are demonstrated. In fact, for the channels that were examin...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	91,897
2210.12229	Deep Reinforcement Learning for Stabilization of Large-scale Probabilistic Boolean Networks	The ability to direct a Probabilistic Boolean Network (PBN) to a desired state is important to applications such as targeted therapeutics in cancer biology. Reinforcement Learning (RL) has been proposed as a framework that solves a discrete-time optimal control problem cast as a Markov Decision Process. We focus on an ...	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	325,640
2302.03341	The Effect of Metadata on Scientific Literature Tagging: A Cross-Field Cross-Model Study	Due to the exponential growth of scientific publications on the Web, there is a pressing need to tag each paper with fine-grained topics so that researchers can track their interested fields of study rather than drowning in the whole literature. Scientific literature tagging is beyond a pure multi-label text classifica...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	344,307
2305.00001	Feature Embedding Clustering using POCS-based Clustering Algorithm	An application of the POCS-based clustering algorithm (POCS stands for Projection Onto Convex Set), a novel clustering technique, for feature embedding clustering problems is proposed in this paper. The POCS-based clustering algorithm applies the POCS's convergence property to clustering problems and has shown competit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	361,175
2204.12793	Modern Baselines for SPARQL Semantic Parsing	In this work, we focus on the task of generating SPARQL queries from natural language questions, which can then be executed on Knowledge Graphs (KGs). We assume that gold entity and relations have been provided, and the remaining task is to arrange them in the right order along with SPARQL vocabulary, and input tokens ...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	293,605
2305.00980	Learning Structured Output Representations from Attributes using Deep Conditional Generative Models	Structured output representation is a generative task explored in computer vision that often times requires the mapping of low dimensional features to high dimensional structured outputs. Losses in complex spatial information in deterministic approaches such as Convolutional Neural Networks (CNN) lead to uncertainties ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	361,515
1809.07357	Combined Image- and World-Space Tracking in Traffic Scenes	Tracking in urban street scenes plays a central role in autonomous systems such as self-driving cars. Most of the current vision-based tracking methods perform tracking in the image domain. Other approaches, eg based on LIDAR and radar, track purely in 3D. While some vision-based tracking methods invoke 3D information ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	108,262
2405.11106	LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions	In recent years, Large Language Models (LLMs) have shown great abilities in various tasks, including question answering, arithmetic problem solving, and poem writing, among others. Although research on LLM-as-an-agent has shown that LLM can be applied to Reinforcement Learning (RL) and achieve decent results, the exten...	false	false	false	false	true	false	true	true	true	false	false	false	false	false	true	false	false	false	455,004
1312.0649	Dynamics of Trends and Attention in Chinese Social Media	There has been a tremendous rise in the growth of online social networks all over the world in recent years. It has facilitated users to generate a large amount of real-time content at an incessant rate, all competing with each other to attract enough attention and become popular trends. While Western online social net...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	28,798
1802.09477	Addressing Function Approximation Error in Actor-Critic Methods	In value-based reinforcement learning methods such as deep Q-learning, function approximation errors are known to lead to overestimated value estimates and suboptimal policies. We show that this problem persists in an actor-critic setting and propose novel mechanisms to minimize its effects on both the actor and the cr...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	91,331
2001.07442	Learning Diverse Features with Part-Level Resolution for Person Re-Identification	Learning diverse features is key to the success of person re-identification. Various part-based methods have been extensively proposed for learning local representations, which, however, are still inferior to the best-performing methods for person re-identification. This paper proposes to construct a strong lightweight...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	161,039
2306.15196	A Fully Bayesian Approach for Massive MIMO Unsourced Random Access	In this paper, we propose a novel fully Bayesian approach for the massive multiple-input multiple-output (MIMO) massive unsourced random access (URA). The payload of each user device is coded by the sparse regression codes (SPARCs) without redundant parity bits. A Bayesian model is established to capture the probabilis...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	375,946
1502.08037	Decentralized Abstractions for Feedback Interconnected Multi-Agent Systems	The purpose of this report is to define abstractions for multi-agent systems under coupled constraints. In the proposed decentralized framework, we specify a finite or countable transition system for each agent which only takes into account the discrete positions of its neighbors. The dynamics of the considered systems...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	40,640
2406.08476	RMem: Restricted Memory Banks Improve Video Object Segmentation	With recent video object segmentation (VOS) benchmarks evolving to challenging scenarios, we revisit a simple but overlooked strategy: restricting the size of memory banks. This diverges from the prevalent practice of expanding memory banks to accommodate extensive historical information. Our specially designed "memory...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	463,509
2405.17083	F-3DGS: Factorized Coordinates and Representations for 3D Gaussian Splatting	The neural radiance field (NeRF) has made significant strides in representing 3D scenes and synthesizing novel views. Despite its advancements, the high computational costs of NeRF have posed challenges for its deployment in resource-constrained environments and real-time applications. As an alternative to NeRF-like ne...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	457,760
2208.07791	Your ViT is Secretly a Hybrid Discriminative-Generative Diffusion Model	Diffusion Denoising Probability Models (DDPM) and Vision Transformer (ViT) have demonstrated significant progress in generative tasks and discriminative tasks, respectively, and thus far these models have largely been developed in their own domains. In this paper, we establish a direct connection between DDPM and ViT b...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	313,155
1809.10361	PolyShard: Coded Sharding Achieves Linearly Scaling Efficiency and Security Simultaneously	Today's blockchain designs suffer from a trilemma claiming that no blockchain system can simultaneously achieve decentralization, security, and performance scalability. For current blockchain systems, as more nodes join the network, the efficiency of the system (computation, communication, and storage) stays constant a...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	true	108,898
2312.14033	T-Eval: Evaluating the Tool Utilization Capability of Large Language Models Step by Step	Large language models (LLM) have achieved remarkable performance on various NLP tasks and are augmented by tools for broader applications. Yet, how to evaluate and analyze the tool-utilization capability of LLMs is still under-explored. In contrast to previous works that evaluate models holistically, we comprehensively...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	417,484
1805.11063	Theory and Experiments on Vector Quantized Autoencoders	Deep neural networks with discrete latent variables offer the promise of better symbolic reasoning, and learning abstractions that are more useful to new tasks. There has been a surge in interest in discrete latent variable models, however, despite several recent improvements, the training of discrete latent variable m...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	98,834
2109.06112	Beyond Isolated Utterances: Conversational Emotion Recognition	Speech emotion recognition is the task of recognizing the speaker's emotional state given a recording of their utterance. While most of the current approaches focus on inferring emotion from isolated utterances, we argue that this is not sufficient to achieve conversational emotion recognition (CER) which deals with re...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	255,053
2003.05325	Meta-learning curiosity algorithms	We hypothesize that curiosity is a mechanism found by evolution that encourages meaningful exploration early in an agent's life in order to expose it to experiences that enable it to obtain high rewards over the course of its lifetime. We formulate the problem of generating curious behavior as one of meta-learning: an ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	167,829
2012.05328	GAN "Steerability" without optimization	Recent research has shown remarkable success in revealing "steering" directions in the latent spaces of pre-trained GANs. These directions correspond to semantically meaningful image transformations e.g., shift, zoom, color manipulations), and have similar interpretable effects across all categories that the GAN can ge...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	210,741
2110.11385	Self-Initiated Open World Learning for Autonomous AI Agents	As more and more AI agents are used in practice, it is time to think about how to make these agents fully autonomous so that they can learn by themselves in a self-motivated and self-supervised manner rather than being retrained periodically on the initiation of human engineers using expanded training data. As the real...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	262,459
1908.10072	Controllable Video Captioning with POS Sequence Guidance Based on Gated Fusion Network	In this paper, we propose to guide the video caption generation with Part-of-Speech (POS) information, based on a gated fusion of multiple representations of input videos. We construct a novel gated fusion network, with one particularly designed cross-gating (CG) block, to effectively encode and fuse different types of...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	143,016
1801.09346	Representing the Insincere: Strategically Robust Proportional Representation	Proportional representation (PR) is a fundamental principle of many democracies world-wide which employ PR-based voting rules to elect their representatives. The normative properties of these voting rules however, are often only understood in the context of sincere voting. In this paper we consider PR in the presence...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	89,091
2309.16159	Adaptive Real-Time Numerical Differentiation with Variable-Rate Forgetting and Exponential Resetting	Digital PID control requires a differencing operation to implement the D gain. In order to suppress the effects of noisy data, the traditional approach is to filter the data, where the frequency response of the filter is adjusted manually based on the characteristics of the sensor noise. The present paper considers the...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	395,243
1506.00337	On Distributive Subalgebras of Qualitative Spatial and Temporal Calculi	Qualitative calculi play a central role in representing and reasoning about qualitative spatial and temporal knowledge. This paper studies distributive subalgebras of qualitative calculi, which are subalgebras in which (weak) composition distributives over nonempty intersections. It has been proven for RCC5 and RCC8 th...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	43,655
2007.04505	Towards Unsupervised Learning for Instrument Segmentation in Robotic Surgery with Cycle-Consistent Adversarial Networks	Surgical tool segmentation in endoscopic images is an important problem: it is a crucial step towards full instrument pose estimation and it is used for integration of pre- and intra-operative images into the endoscopic view. While many recent approaches based on convolutional neural networks have shown great results, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	186,372
2411.17767	Exploring Aleatoric Uncertainty in Object Detection via Vision Foundation Models	Datasets collected from the open world unavoidably suffer from various forms of randomness or noiseness, leading to the ubiquity of aleatoric (data) uncertainty. Quantifying such uncertainty is particularly pivotal for object detection, where images contain multi-scale objects with occlusion, obscureness, and even nois...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	511,592
2404.04808	MemFlow: Optical Flow Estimation and Prediction with Memory	Optical flow is a classical task that is important to the vision community. Classical optical flow estimation uses two frames as input, whilst some recent methods consider multiple frames to explicitly model long-range information. The former ones limit their ability to fully leverage temporal coherence along the video...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	444,796
2010.02556	SHERLock: Self-Supervised Hierarchical Event Representation Learning	Temporal event representations are an essential aspect of learning among humans. They allow for succinct encoding of the experiences we have through a variety of sensory inputs. Also, they are believed to be arranged hierarchically, allowing for an efficient representation of complex long-horizon experiences. Additiona...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	199,076
2412.20391	Open-Source Heterogeneous SoCs for AI: The PULP Platform Experience	Since 2013, the PULP (Parallel Ultra-Low Power) Platform project has been one of the most active and successful initiatives in designing research IPs and releasing them as open-source. Its portfolio now ranges from processor cores to network-on-chips, peripherals, SoC templates, and full hardware accelerators. In this ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	521,209
2011.14420	Improving Neural Network with Uniform Sparse Connectivity	Neural network forms the foundation of deep learning and numerous AI applications. Classical neural networks are fully connected, expensive to train and prone to overfitting. Sparse networks tend to have convoluted structure search, suboptimal performance and limited usage. We proposed the novel uniform sparse network ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	208,772
2110.03346	MSHCNet: Multi-Stream Hybridized Convolutional Networks with Mixed Statistics in Euclidean/Non-Euclidean Spaces and Its Application to Hyperspectral Image Classification	It is well known that hyperspectral images (HSI) contain rich spatial-spectral contextual information, and how to effectively combine both spectral and spatial information using DNN for HSI classification has become a new research hotspot. Compared with CNN with square kernels, GCN have exhibited exciting potential to ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	259,463
2106.13689	Semantic annotation for computational pathology: Multidisciplinary experience and best practice recommendations	Recent advances in whole slide imaging (WSI) technology have led to the development of a myriad of computer vision and artificial intelligence (AI) based diagnostic, prognostic, and predictive algorithms. Computational Pathology (CPath) offers an integrated solution to utilize information embedded in pathology WSIs bey...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	243,148
2405.00385	Variational Bayesian Methods for a Tree-Structured Stick-Breaking Process Mixture of Gaussians by Application of the Bayes Codes for Context Tree Models	The tree-structured stick-breaking process (TS-SBP) mixture model is a non-parametric Bayesian model that can represent tree-like hierarchical structures among the mixture components. For TS-SBP mixture models, only a Markov chain Monte Carlo (MCMC) method has been proposed and any variational Bayesian (VB) methods has...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	450,900
2405.18915	Towards Faithful Chain-of-Thought: Large Language Models are Bridging Reasoners	Large language models (LLMs) suffer from serious unfaithful chain-of-thought (CoT) issues. Previous work attempts to measure and explain it but lacks in-depth analysis within CoTs and does not consider the interactions among all reasoning components jointly. In this paper, we first study the CoT faithfulness issue at t...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	458,663
2401.03988	A Primer on Temporal Graph Learning	This document aims to familiarize readers with temporal graph learning (TGL) through a concept-first approach. We have systematically presented vital concepts essential for understanding the workings of a TGL framework. In addition to qualitative explanations, we have incorporated mathematical formulations where applic...	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	false	true	420,290
1204.0354	Identifying Infection Sources and Regions in Large Networks	Identifying the infection sources in a network, including the index cases that introduce a contagious disease into a population network, the servers that inject a computer virus into a computer network, or the individuals who started a rumor in a social network, plays a critical role in limiting the damage caused by th...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	15,251
2111.11133	L-Verse: Bidirectional Generation Between Image and Text	Far beyond learning long-range interactions of natural language, transformers are becoming the de-facto standard for many vision tasks with their power and scalability. Especially with cross-modal tasks between image and text, vector quantized variational autoencoders (VQ-VAEs) are widely used to make a raw RGB image i...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	267,560
2108.00316	Chest ImaGenome Dataset for Clinical Reasoning	Despite the progress in automatic detection of radiologic findings from chest X-ray (CXR) images in recent years, a quantitative evaluation of the explainability of these models is hampered by the lack of locally labeled datasets for different findings. With the exception of a few expert-labeled small-scale datasets fo...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	248,668
1901.01477	Dynamic Visualization and Fast Computation for Convex Clustering via Algorithmic Regularization	Convex clustering is a promising new approach to the classical problem of clustering, combining strong performance in empirical studies with rigorous theoretical foundations. Despite these advantages, convex clustering has not been widely adopted, due to its computationally intensive nature and its lack of compelling v...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	117,982
1502.02925	On the Finite Length Scaling of Ternary Polar Codes	The polarization process of polar codes over a ternary alphabet is studied. Recently it has been shown that the scaling of the blocklength of polar codes with prime alphabet size scales polynomially with respect to the inverse of the gap between code rate and channel capacity. However, except for the binary case, the d...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	40,100
2102.01375	Applications of Federated Learning in Smart Cities: Recent Advances, Taxonomy, and Open Challenges	Federated learning plays an important role in the process of smart cities. With the development of big data and artificial intelligence, there is a problem of data privacy protection in this process. Federated learning is capable of solving this problem. This paper starts with the current developments of federated lear...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	218,091
1503.07455	Sum Secrecy Rate in MISO Full-Duplex Wiretap Channel with Imperfect CSI	In this paper, we consider the achievable sum secrecy rate in MISO (multiple-input-single-output) {\em full-duplex} wiretap channel in the presence of a passive eavesdropper and imperfect channel state information (CSI). We assume that the users participating in full-duplex communication have multiple transmit antennas...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	41,474
2407.10888	Leveraging Multimodal CycleGAN for the Generation of Anatomically Accurate Synthetic CT Scans from MRIs	In many clinical settings, the use of both Computed Tomography (CT) and Magnetic Resonance (MRI) is necessary to pursue a thorough understanding of the patient's anatomy and to plan a suitable therapeutical strategy; this is often the case in MRI-based radiotherapy, where CT is always necessary to prepare the dose deli...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	473,174
2105.11950	Extending rational models of communication from beliefs to actions	Speakers communicate to influence their partner's beliefs and shape their actions. Belief- and action-based objectives have been explored independently in recent computational models, but it has been challenging to explicitly compare or integrate them. Indeed, we find that they are conflated in standard referential com...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	236,871
2402.17472	RAGFormer: Learning Semantic Attributes and Topological Structure for Fraud Detection	Fraud detection remains a challenging task due to the complex and deceptive nature of fraudulent activities. Current approaches primarily concentrate on learning only one perspective of the graph: either the topological structure of the graph or the attributes of individual nodes. However, we conduct empirical studies ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	433,006
1301.3584	Revisiting Natural Gradient for Deep Networks	We evaluate natural gradient, an algorithm originally proposed in Amari (1997), for learning deep models. The contributions of this paper are as follows. We show the connection between natural gradient and three other recently proposed methods for training deep models: Hessian-Free (Martens, 2010), Krylov Subspace Desc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	21,116
2201.01836	A Generalized Bootstrap Target for Value-Learning, Efficiently Combining Value and Feature Predictions	Estimating value functions is a core component of reinforcement learning algorithms. Temporal difference (TD) learning algorithms use bootstrapping, i.e. they update the value function toward a learning target using value estimates at subsequent time-steps. Alternatively, the value function can be updated toward a lear...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	274,365
1502.00762	On the Solvability of 3s/nt Sum-Network---A Region Decomposition and Weak Decentralized Code Method	We study the network coding problem of sum-networks with 3 sources and n terminals (3s/nt sum-network), for an arbitrary positive integer n, and derive a sufficient and necessary condition for the solvability of a family of so-called terminal-separable sum-network. Both the condition of terminal-separable and the solva...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,871
2301.02284	Unsupervised Broadcast News Summarization; a comparative study on Maximal Marginal Relevance (MMR) and Latent Semantic Analysis (LSA)	The methods of automatic speech summarization are classified into two groups: supervised and unsupervised methods. Supervised methods are based on a set of features, while unsupervised methods perform summarization based on a set of rules. Latent Semantic Analysis (LSA) and Maximal Marginal Relevance (MMR) are consider...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	339,460
2104.14586	Crack Semantic Segmentation using the U-Net with Full Attention Strategy	Structures suffer from the emergence of cracks, therefore, crack detection is always an issue with much concern in structural health monitoring. Along with the rapid progress of deep learning technology, image semantic segmentation, an active research field, offers another solution, which is more effective and intellig...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	232,872
1804.04888	Scalable and Interpretable One-class SVMs with Deep Learning and Random Fourier features	One-class support vector machine (OC-SVM) for a long time has been one of the most effective anomaly detection methods and extensively adopted in both research as well as industrial applications. The biggest issue for OC-SVM is yet the capability to operate with large and high-dimensional datasets due to optimization c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	94,957
2401.10254	Beyond the Frame: Single and mutilple video summarization method with user-defined length	Video smmarization is a crucial method to reduce the time of videos which reduces the spent time to watch/review a long video. This apporach has became more important as the amount of publisehed video is increasing everyday. A single or multiple videos can be summarized into a relatively short video using various of te...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	422,552
1909.10205	Low-PAPR Preamble Design for FBMC Systems	This paper presents a family of training preambles for offset QAM (OQAM) based filter-bank multi-carrier (FBMC) modulations with low peak-to-average power ratio (PAPR) property. We propose to use binary Golay sequences as FBMC preambles and analyze the maximum PAPR for different numbers of zero guard symbols. For both ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	146,478
1711.04289	Neural Natural Language Inference Models Enhanced with External Knowledge	Modeling natural language inference is a very challenging task. With the availability of large annotated data, it has recently become feasible to train complex models such as neural-network-based inference models, which have shown to achieve the state-of-the-art performance. Although there exist relatively large annota...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	84,369
1611.07917	Deep Restricted Boltzmann Networks	Building a good generative model for image has long been an important topic in computer vision and machine learning. Restricted Boltzmann machine (RBM) is one of such models that is simple but powerful. However, its restricted form also has placed heavy constraints on the models representation power and scalability. Ma...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	64,427
1510.01705	Baseband Equivalent Models and Digital Predistortion for Mitigating Dynamic Continuous-Time Perturbations in Phase-Amplitude Modulation-Demodulation Schemes (Expanded version)	We consider baseband equivalent representation of transmission circuits, in the form of a nonlinear dynamical system $\mathbf S$ in discrete time (DT) defined by a series interconnection of a phase-amplitude modulator, a nonlinear dynamical system $\mathbf F$ in continuous time (CT), and an ideal demodulator. We show t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	47,650
1502.04500	Bi-Level Image Thresholding obtained by means of Kaniadakis Entropy	In this paper we are proposing the use of Kaniadakis entropy in the bi-level thresholding of images, in the framework of a maximum entropy principle. We discuss the role of its entropic index in determining the threshold and in driving an "image transition", that is, an abrupt transition in the appearance of the corres...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	40,276
1905.11616	Polynomial Tensor Sketch for Element-wise Function of Low-Rank Matrix	This paper studies how to sketch element-wise functions of low-rank matrices. Formally, given low-rank matrix A = [Aij] and scalar non-linear function f, we aim for finding an approximated low-rank representation of the (possibly high-rank) matrix [f(Aij)]. To this end, we propose an efficient sketching-based algorithm...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	132,487
2203.00570	Towards a unified view of unsupervised non-local methods for image denoising: the NL-Ridge approach	We propose a unified view of unsupervised non-local methods for image denoising that linearily combine noisy image patches. The best methods, established in different modeling and estimation frameworks, are two-step algorithms. Leveraging Stein's unbiased risk estimate (SURE) for the first step and the "internal adapta...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	283,052
1812.08993	A Construction of Optimal Frequency Hopping Sequence Set via Combination of Multiplicative and Additive Groups of Finite Fields	In literatures, there are various constructions of frequency hopping sequence (FHS for short) sets with good Hamming correlations. Some papers employed only multiplicative groups of finite fields to construct FHS sets, while other papers implicitly used only additive groups of finite fields for construction of FHS sets...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	117,083
1207.0757	Generalized Statistical Complexity of SAR Imagery	A new generalized Statistical Complexity Measure (SCM) was proposed by Rosso et al in 2010. It is a functional that captures the notions of order/disorder and of distance to an equilibrium distribution. The former is computed by a measure of entropy, while the latter depends on the definition of a stochastic divergence...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	17,191
2206.01394	Influence Maximization in Hypergraphs	Influence maximization in complex networks, i.e., maximizing the size of influenced nodes via selecting K seed nodes for a given spreading process, has attracted great attention in recent years. However, the influence maximization problem in hypergraphs, in which the hyperedges are leveraged to represent the interactio...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	300,459
1503.08485	Fair Scheduling Policies Exploiting Multiuser Diversity in Cellular Systems with Device-to-Device Communications	We consider the resource allocation problem in cellular networks which support Device-to-Device Communications (D2D). For systems that enable D2D via only orthogonal resource sharing, we propose and analyze two resource allocation policies that guarantee access fairness among all users, while taking advantage of multi-...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	41,596
2211.14781	Architecture, Protocols, and Algorithms for Location-Aware Services in Beyond 5G Networks	The automotive and railway industries are rapidly transforming with a strong drive towards automation and digitalization, with the goal of increased convenience, safety, efficiency, and sustainability. Since assisted and fully automated automotive and train transport services increasingly rely on vehicle-to-everything ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	332,991
2110.06150	Sparsity in Partially Controllable Linear Systems	A fundamental concept in control theory is that of controllability, where any system state can be reached through an appropriate choice of control inputs. Indeed, a large body of classical and modern approaches are designed for controllable linear dynamical systems. However, in practice, we often encounter systems in w...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	260,515
1803.09617	Correlation properties of signal at mobile receiver for different propagation environments	An issue of the parameter selection in various branches of a multi-antenna receiver system determines its effectiveness. A significant effect on these parameters are correlation properties of received signals. In this paper, the assessment of the signal correlation properties for different environmental conditions is p...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	93,539
2201.02972	Performance Analysis and Power Allocation of Joint Communication and Sensing Towards Future Communication Networks	To mitigate the radar and communication frequency overlapping caused by massive devices access, we propose a novel joint communication and sensing (JCS) system in this paper, where a micro base station (MiBS) can realize target sensing and cooperative communication simultaneously. Concretely, the MiBS, as the sensing e...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	274,712
2102.02311	Causal Sufficiency and Actual Causation	Pearl opened the door to formally defining actual causation using causal models. His approach rests on two strategies: first, capturing the widespread intuition that X=x causes Y=y iff X=x is a Necessary Element of a Sufficient Set for Y=y, and second, showing that his definition gives intuitive answers on a wide set o...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	218,371
2007.09557	From Spatial Relations to Spatial Configurations	Spatial Reasoning from language is essential for natural language understanding. Supporting it requires a representation scheme that can capture spatial phenomena encountered in language as well as in images and videos. Existing spatial representations are not sufficient for describing spatial configurations used in co...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	187,996
2104.08743	Rough Sets in Graphs Using Similarity Relations	In this paper, we use theory of rough set to study graphs using the concept of orbits. We investigate the indiscernibility partitions and approximations of graphs induced by orbits of graphs. We also study rough membership functions, essential sets, discernibility matrix and their relationships for graphs.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	230,953
2010.11092	Stacking Neural Network Models for Automatic Short Answer Scoring	Automatic short answer scoring is one of the text classification problems to assess students' answers during exams automatically. Several challenges can arise in making an automatic short answer scoring system, one of which is the quantity and quality of the data. The data labeling process is not easy because it requir...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	202,122
1803.10405	A Sherman-Morrison-Woodbury Identity for Rank Augmenting Matrices with Application to Centering	Matrices of the form $\bf{A} + (\bf{V}_1 + \bf{W}_1)\bf{G}(\bf{V}_2 + \bf{W}_2)^*$ are considered where $\bf{A}$ is a $singular$ $\ell \times \ell$ matrix and $\bf{G}$ is a nonsingular $k \times k$ matrix, $k \le \ell$. Let the columns of $\bf{V}_1$ be in the column space of $\bf{A}$ and the columns of $\bf{W}_1$ be or...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	93,695
1910.04797	CompareNet: Anatomical Segmentation Network with Deep Non-local Label Fusion	Label propagation is a popular technique for anatomical segmentation. In this work, we propose a novel deep framework for label propagation based on non-local label fusion. Our framework, named CompareNet, incorporates subnets for both extracting discriminating features, and learning the similarity measure, which lead ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	148,862
2405.13536	Attention Mechanisms Don't Learn Additive Models: Rethinking Feature Importance for Transformers	We address the critical challenge of applying feature attribution methods to the transformer architecture, which dominates current applications in natural language processing and beyond. Traditional attribution methods to explainable AI (XAI) explicitly or implicitly rely on linear or additive surrogate models to quant...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	455,975
2104.09461	Entropy-based Optimization via A* Algorithm for Parking Space Recommendation	This paper addresses the path planning problems for recommending parking spaces, given the difficulties of identifying the most optimal route to vacant parking spaces and the shortest time to leave the parking space. Our optimization approach is based on the entropy method and realized by the A* algorithm. Experiments ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	231,249
0905.0564	Selective Cooperative Relaying over Time-Varying Channels	In selective cooperative relaying only a single relay out of the set of available relays is activated, hence the available power and bandwidth resources are efficiently utilized. However, implementing selective cooperative relaying in time-varying channels may cause frequent relay switchings that deteriorate the overal...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	3,637
1009.3243	The "Unfriending" Problem: The Consequences of Homophily in Friendship Retention for Causal Estimates of Social Influence	An increasing number of scholars are using longitudinal social network data to try to obtain estimates of peer or social influence effects. These data may provide additional statistical leverage, but they can introduce new inferential problems. In particular, while the confounding effects of homophily in friendship for...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	7,564
2309.04849	Speech Emotion Recognition with Distilled Prosodic and Linguistic Affect Representations	We propose EmoDistill, a novel speech emotion recognition (SER) framework that leverages cross-modal knowledge distillation during training to learn strong linguistic and prosodic representations of emotion from speech. During inference, our method only uses a stream of speech signals to perform unimodal SER thus reduc...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	390,877
2201.06811	Tutela: An Open-Source Tool for Assessing User-Privacy on Ethereum and Tornado Cash	A common misconception among blockchain users is that pseudonymity guarantees privacy. The reality is almost the opposite. Every transaction one makes is recorded on a public ledger and reveals information about one's identity. Mixers, such as Tornado Cash, were developed to preserve privacy through "mixing" transactio...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	275,840
2108.09130	ReGenMorph: Visibly Realistic GAN Generated Face Morphing Attacks by Attack Re-generation	Face morphing attacks aim at creating face images that are verifiable to be the face of multiple identities, which can lead to building faulty identity links in operations like border checks. While creating a morphed face detector (MFD), training on all possible attack types is essential to achieve good detection perfo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	251,505
2110.05280	Multi-institutional Validation of Two-Streamed Deep Learning Method for Automated Delineation of Esophageal Gross Tumor Volume using planning-CT and FDG-PETCT	Background: The current clinical workflow for esophageal gross tumor volume (GTV) contouring relies on manual delineation of high labor-costs and interuser variability. Purpose: To validate the clinical applicability of a deep learning (DL) multi-modality esophageal GTV contouring model, developed at 1 institution wher...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	260,226
2408.05699	MacFormer: Semantic Segmentation with Fine Object Boundaries	Semantic segmentation involves assigning a specific category to each pixel in an image. While Vision Transformer-based models have made significant progress, current semantic segmentation methods often struggle with precise predictions in localized areas like object boundaries. To tackle this challenge, we introduce a ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	479,895
2305.05760	Reducing the Cost of Cycle-Time Tuning for Real-World Policy Optimization	Continuous-time reinforcement learning tasks commonly use discrete steps of fixed cycle times for actions. As practitioners need to choose the action-cycle time for a given task, a significant concern is whether the hyper-parameters of the learning algorithm need to be re-tuned for each choice of the cycle time, which ...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	363,267
1808.09374	A Tree-based Decoder for Neural Machine Translation	Recent advances in Neural Machine Translation (NMT) show that adding syntactic information to NMT systems can improve the quality of their translations. Most existing work utilizes some specific types of linguistically-inspired tree structures, like constituency and dependency parse trees. This is often done via a stan...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	106,172
1211.6827	Additive-State-Decomposition-Based Tracking Control for TORA Benchmark	In this paper, a new control scheme, called additive state decomposition based tracking control, is proposed to solve the tracking (rejection) problem for rotational position of the TORA (a nonlinear nonminimum phase system). By the additive state decomposition, the tracking (rejection) task for the considered nonlinea...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	20,009
1911.06312	Predicting sparse circle maps from their dynamics	The problem of identifying a dynamical system from its dynamics is of great importance for many applications. Recently it has been suggested to impose sparsity models for improved recovery performance. In this paper, we provide recovery guarantees for such a scenario. More precisely, we show that ergodic systems on the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	153,510
2307.03716	SAR: Generalization of Physiological Agility and Dexterity via Synergistic Action Representation	Learning effective continuous control policies in high-dimensional systems, including musculoskeletal agents, remains a significant challenge. Over the course of biological evolution, organisms have developed robust mechanisms for overcoming this complexity to learn highly sophisticated strategies for motor control. Wh...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	378,126
2107.06677	Hybrid Model and Data Driven Algorithm for Online Learning of Any-to-Any Path Loss Maps	Learning any-to-any (A2A) path loss maps, where the objective is the reconstruction of path loss between any two given points in a map, might be a key enabler for many applications that rely on device-to-device (D2D) communication. Such applications include machine-type communications (MTC) or vehicle-to-vehicle (V2V) ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	246,164
2312.16190	Hawkes-based cryptocurrency forecasting via Limit Order Book data	Accurately forecasting the direction of financial returns poses a formidable challenge, given the inherent unpredictability of financial time series. The task becomes even more arduous when applied to cryptocurrency returns, given the chaotic and intricately complex nature of crypto markets. In this study, we present a...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	418,299
2308.13279	Hyperbolic Random Forests	Hyperbolic space is becoming a popular choice for representing data due to the hierarchical structure - whether implicit or explicit - of many real-world datasets. Along with it comes a need for algorithms capable of solving fundamental tasks, such as classification, in hyperbolic space. Recently, multiple papers have ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	387,855
2110.13883	Estimating Mutual Information via Geodesic $k$NN	Estimating mutual information (MI) between two continuous random variables $X$ and $Y$ allows to capture non-linear dependencies between them, non-parametrically. As such, MI estimation lies at the core of many data science applications. Yet, robustly estimating MI for high-dimensional $X$ and $Y$ is still an open rese...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	263,339
2201.06459	A Novel Framework to Jointly Compress and Index Remote Sensing Images for Efficient Content-Based Retrieval	Remote sensing (RS) images are usually stored in compressed format to reduce the storage size of the archives. Thus, existing content-based image retrieval (CBIR) systems in RS require decoding images before applying CBIR (which is computationally demanding in the case of large-scale CBIR problems). To address this pro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	275,731
2410.07865	Synergizing Morphological Computation and Generative Design: Automatic Synthesis of Tendon-Driven Grippers	Robots' behavior and performance are determined both by hardware and software. The design process of robotic systems is a complex journey that involves multiple phases. Throughout this process, the aim is to tackle various criteria simultaneously, even though they often contradict each other. The ultimate goal is to un...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	496,837
2408.11289	HMT-UNet: A hybird Mamba-Transformer Vision UNet for Medical Image Segmentation	In the field of medical image segmentation, models based on both CNN and Transformer have been thoroughly investigated. However, CNNs have limited modeling capabilities for long-range dependencies, making it challenging to exploit the semantic information within images fully. On the other hand, the quadratic computatio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	482,216
1505.02142	Porting HTM Models to the Heidelberg Neuromorphic Computing Platform	Hierarchical Temporal Memory (HTM) is a computational theory of machine intelligence based on a detailed study of the neocortex. The Heidelberg Neuromorphic Computing Platform, developed as part of the Human Brain Project (HBP), is a mixed-signal (analog and digital) large-scale platform for modeling networks of spikin...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	42,928
2402.13028	Heterogeneous Graph Reasoning for Fact Checking over Texts and Tables	Fact checking aims to predict claim veracity by reasoning over multiple evidence pieces. It usually involves evidence retrieval and veracity reasoning. In this paper, we focus on the latter, reasoning over unstructured text and structured table information. Previous works have primarily relied on fine-tuning pretrained...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	431,087
2312.00681	Applicability of Blockchain Technology in Avionics Systems	Blockchain technology, within its fast widespread and superiority demonstrated by recent studies, can be also used as an informatic tool for solving various aviation problems. Aviation electronics (avionics) systems stand out as the application area of informatics methods in solving aviation problems or providing diffe...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	412,136

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