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
2104.11320	Federated Double Deep Q-learning for Joint Delay and Energy Minimization in IoT networks	In this paper, we propose a federated deep reinforcement learning framework to solve a multi-objective optimization problem, where we consider minimizing the expected long-term task completion delay and energy consumption of IoT devices. This is done by optimizing offloading decisions, computation resource allocation, ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	231,876
1511.03125	Virtual-MIMO-Boosted Information Propagation on Highways	In vehicular communications, traffic-related information should be spread over the network as quickly as possible to maintain a safer transportation system. This motivates us to develop more efficient information propagation schemes. In this paper, we propose a novel virtual-MIMO-enabled information dissemination schem...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	48,720
1812.06300	Analysis of the $(\mu/\mu_I,\lambda)$-$\sigma$-Self-Adaptation Evolution Strategy with Repair by Projection Applied to a Conically Constrained Problem	A theoretical performance analysis of the $(\mu/\mu_I,\lambda)$-$\sigma$-Self-Adaptation Evolution Strategy ($\sigma$SA-ES) is presented considering a conically constrained problem. Infeasible offspring are repaired using projection onto the boundary of the feasibility region. Closed-form approximations are used for th...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	116,583
1811.03581	Decidability in Robot Manipulation Planning	Consider the problem of planning collision-free motion of $n$ objects in the plane movable through contact with a robot that can autonomously translate in the plane and that can move a maximum of $m \leq n$ objects simultaneously. This represents the abstract formulation of a manipulation planning problem that is prove...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	112,878
cs/0611054	How Random is a Coin Toss? Bayesian Inference and the Symbolic Dynamics of Deterministic Chaos	Symbolic dynamics has proven to be an invaluable tool in analyzing the mechanisms that lead to unpredictability and random behavior in nonlinear dynamical systems. Surprisingly, a discrete partition of continuous state space can produce a coarse-grained description of the behavior that accurately describes the invarian...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	539,871
1506.04834	Tree-structured composition in neural networks without tree-structured architectures	Tree-structured neural networks encode a particular tree geometry for a sentence in the network design. However, these models have at best only slightly outperformed simpler sequence-based models. We hypothesize that neural sequence models like LSTMs are in fact able to discover and implicitly use recursive composition...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	44,220
1412.1185	The Entropy of Attention and Popularity in YouTube Videos	The vast majority of YouTube videos never become popular, languishing in obscurity with few views, no likes, and no comments. We use information theoretical measures based on entropy to examine how time series distributions of common measures of popularity in videos from YouTube's "Trending videos" and "Most recent" vi...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	38,079
2307.07920	A structural study of Big Tech firm-switching of inventors in the post-recession era	Complex systems research and network science have recently been used to provide novel insights into economic phenomena such as patenting behavior and innovation in firms. Several studies have found that increased mobility of inventors, manifested through firm switching or transitioning, is associated with increased ove...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	379,590
2410.20541	Data-driven Analysis of T-Product-based Dynamical Systems	A wide variety of data can be represented using third-order tensors, spanning applications in chemometrics, psychometrics, and image processing. However, traditional data-driven frameworks are not naturally equipped to process tensors without first unfolding or flattening the data, which can result in a loss of crucial...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	502,857
2304.04300	Class-Imbalanced Learning on Graphs: A Survey	The rapid advancement in data-driven research has increased the demand for effective graph data analysis. However, real-world data often exhibits class imbalance, leading to poor performance of machine learning models. To overcome this challenge, class-imbalanced learning on graphs (CILG) has emerged as a promising sol...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	357,168
2007.02509	On the weight and density bounds of polynomial threshold functions	In this report, we show that all n-variable Boolean function can be represented as polynomial threshold functions (PTF) with at most $0.75 \times 2^n$ non-zero integer coefficients and give an upper bound on the absolute value of these coefficients. To our knowledge this provides the best known bound on both the PTF de...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	185,770
2008.03781	SemEval-2020 Task 8: Memotion Analysis -- The Visuo-Lingual Metaphor!	Information on social media comprises of various modalities such as textual, visual and audio. NLP and Computer Vision communities often leverage only one prominent modality in isolation to study social media. However, the computational processing of Internet memes needs a hybrid approach. The growing ubiquity of Inter...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	191,026
2103.06498	3D Human Pose, Shape and Texture from Low-Resolution Images and Videos	3D human pose and shape estimation from monocular images has been an active research area in computer vision. Existing deep learning methods for this task rely on high-resolution input, which however, is not always available in many scenarios such as video surveillance and sports broadcasting. Two common approaches to ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	224,320
2203.04476	Part-level Action Parsing via a Pose-guided Coarse-to-Fine Framework	Action recognition from videos, i.e., classifying a video into one of the pre-defined action types, has been a popular topic in the communities of artificial intelligence, multimedia, and signal processing. However, existing methods usually consider an input video as a whole and learn models, e.g., Convolutional Neural...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	284,487
1712.04965	Model Predictive Control for Autonomous Driving Based on Time Scaled Collision Cone	In this paper, we present a Model Predictive Control (MPC) framework based on path velocity decomposition paradigm for autonomous driving. The optimization underlying the MPC has a two layer structure wherein first, an appropriate path is computed for the vehicle followed by the computation of optimal forward velocity ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	86,675
1507.01384	The method of artificial systems	This document is written with the intention to describe in detail a method and means by which a computer program can reason about the world and in so doing, increase its analogue to a living system. As the literature is rife and it is apparent we, as scientists and engineers, have not found the solution, this document ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	44,864
2311.05651	On Mergable Coresets for Polytope Distance	We show that a constant-size constant-error coreset for polytope distance is simple to maintain under merges of coresets. However, increasing the size cannot improve the error bound significantly beyond that constant.	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	406,656
2112.05612	Decentralized Spectrum Access System: Vision, Challenges, and a Blockchain Solution	Spectrum access system (SAS) is widely considered the de facto solution to coordinating dynamic spectrum sharing (DSS) and protecting incumbent users. The current SAS paradigm prescribed by the FCC for the CBRS band and standardized by the WInnForum follows a centralized service model in that a spectrum user subscribes...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	270,896
2208.01191	Implicit Two-Tower Policies	We present a new class of structured reinforcement learning policy-architectures, Implicit Two-Tower (ITT) policies, where the actions are chosen based on the attention scores of their learnable latent representations with those of the input states. By explicitly disentangling action from state processing in the policy...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	311,095
2102.00523	Co-Seg: An Image Segmentation Framework Against Label Corruption	Supervised deep learning performance is heavily tied to the availability of high-quality labels for training. Neural networks can gradually overfit corrupted labels if directly trained on noisy datasets, leading to severe performance degradation at test time. In this paper, we propose a novel deep learning framework, n...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	217,815
2109.00675	FLASHE: Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning	Homomorphic encryption (HE) is a promising privacy-preserving technique for cross-silo federated learning (FL), where organizations perform collaborative model training on decentralized data. Despite the strong privacy guarantee, general HE schemes result in significant computation and communication overhead. Prior wor...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	253,189
1805.08551	Robust Model Predictive Control for Autonomous Vehicles/Self Driving Cars	A robust Model Predictive Control (MPC) approach for controlling front steering of an autonomous vehicle is presented in this paper. We present various approaches to increase the robustness of model predictive control by using weight tuning, a successive on-line linearization of a nonlinear vehicle model to track posit...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	98,171
1402.3511	A Clockwork RNN	Sequence prediction and classification are ubiquitous and challenging problems in machine learning that can require identifying complex dependencies between temporally distant inputs. Recurrent Neural Networks (RNNs) have the ability, in theory, to cope with these temporal dependencies by virtue of the short-term memor...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	30,881
2210.08287	Linear Scalarization for Byzantine-robust learning on non-IID data	In this work we study the problem of Byzantine-robust learning when data among clients is heterogeneous. We focus on poisoning attacks targeting the convergence of SGD. Although this problem has received great attention; the main Byzantine defenses rely on the IID assumption causing them to fail when data distribution ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	324,078
2307.01158	Theory of Mind as Intrinsic Motivation for Multi-Agent Reinforcement Learning	The ability to model the mental states of others is crucial to human social intelligence, and can offer similar benefits to artificial agents with respect to the social dynamics induced in multi-agent settings. We present a method of grounding semantically meaningful, human-interpretable beliefs within policies modeled...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	377,250
2312.03131	Heterogeneous radio access with multiple latency targets	Since the advent of ultra-reliable and low-latency communications (URLLC), the requirements of low-latency applications tend to be completely characterized by a single pre-defined latency-reliability target. That is, operation is optimal whenever the pre-defined latency threshold is met but the system is assumed to be ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	413,145
2310.10765	BiomedJourney: Counterfactual Biomedical Image Generation by Instruction-Learning from Multimodal Patient Journeys	Rapid progress has been made in instruction-learning for image editing with natural-language instruction, as exemplified by InstructPix2Pix. In biomedicine, such methods can be applied to counterfactual image generation, which helps differentiate causal structure from spurious correlation and facilitate robust image in...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	400,376
2005.06653	Structured Query-Based Image Retrieval Using Scene Graphs	A structured query can capture the complexity of object interactions (e.g. 'woman rides motorcycle') unlike single objects (e.g. 'woman' or 'motorcycle'). Retrieval using structured queries therefore is much more useful than single object retrieval, but a much more challenging problem. In this paper we present a method...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	177,071
2202.08926	On Guiding Visual Attention with Language Specification	While real world challenges typically define visual categories with language words or phrases, most visual classification methods define categories with numerical indices. However, the language specification of the classes provides an especially useful prior for biased and noisy datasets, where it can help disambiguate...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	281,027
2011.01788	Loss Bounds for Approximate Influence-Based Abstraction	Sequential decision making techniques hold great promise to improve the performance of many real-world systems, but computational complexity hampers their principled application. Influence-based abstraction aims to gain leverage by modeling local subproblems together with the 'influence' that the rest of the system exe...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	204,706
2408.15857	What is YOLOv8: An In-Depth Exploration of the Internal Features of the Next-Generation Object Detector	This study presents a detailed analysis of the YOLOv8 object detection model, focusing on its architecture, training techniques, and performance improvements over previous iterations like YOLOv5. Key innovations, including the CSPNet backbone for enhanced feature extraction, the FPN+PAN neck for superior multi-scale ob...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	484,100
2311.11210	HiH: A Multi-modal Hierarchy in Hierarchy Network for Unconstrained Gait Recognition	Gait recognition has achieved promising advances in controlled settings, yet it significantly struggles in unconstrained environments due to challenges such as view changes, occlusions, and varying walking speeds. Additionally, efforts to fuse multiple modalities often face limited improvements because of cross-modalit...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	408,852
2409.19600	An Unbiased Risk Estimator for Partial Label Learning with Augmented Classes	Partial Label Learning (PLL) is a typical weakly supervised learning task, which assumes each training instance is annotated with a set of candidate labels containing the ground-truth label. Recent PLL methods adopt identification-based disambiguation to alleviate the influence of false positive labels and achieve prom...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	492,762
2205.02277	Improved error bounds for the distance distribution of Reed-Solomon codes	We use the generating function approach to derive simple expressions for the factorial moments of the distance distribution over Reed-Solomon codes. We obtain better upper bounds for the error term of a counting formula given by Li and Wan, which gives nontrivial estimates on the number of polynomials over finite field...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	294,887
2407.06324	B'MOJO: Hybrid State Space Realizations of Foundation Models with Eidetic and Fading Memory	We describe a family of architectures to support transductive inference by allowing memory to grow to a finite but a-priori unknown bound while making efficient use of finite resources for inference. Current architectures use such resources to represent data either eidetically over a finite span ("context" in Transform...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	471,358
2109.10052	Stepmothers are mean and academics are pretentious: What do pretrained language models learn about you?	In this paper, we investigate what types of stereotypical information are captured by pretrained language models. We present the first dataset comprising stereotypical attributes of a range of social groups and propose a method to elicit stereotypes encoded by pretrained language models in an unsupervised fashion. More...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	256,492
1806.08764	Learning Traffic Flow Dynamics using Random Fields	This paper presents a mesoscopic traffic flow model that explicitly describes the spatio-temporal evolution of the probability distributions of vehicle trajectories. The dynamics are represented by a sequence of factor graphs, which enable learning of traffic dynamics from limited Lagrangian measurements using an effic...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	101,216
1705.00349	Network Inspection for Detecting Strategic Attacks	This article studies a problem of strategic network inspection, in which a defender (agency) is tasked with detecting the presence of multiple attacks in the network. An inspection strategy entails monitoring the network components, possibly in a randomized manner, using a given number of detectors. We formulate the ne...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	72,663
2202.04488	CRAT-Pred: Vehicle Trajectory Prediction with Crystal Graph Convolutional Neural Networks and Multi-Head Self-Attention	Predicting the motion of surrounding vehicles is essential for autonomous vehicles, as it governs their own motion plan. Current state-of-the-art vehicle prediction models heavily rely on map information. In reality, however, this information is not always available. We therefore propose CRAT-Pred, a multi-modal and no...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	279,566
2203.10249	Learning-by-Narrating: Narrative Pre-Training for Zero-Shot Dialogue Comprehension	Comprehending a dialogue requires a model to capture diverse kinds of key information in the utterances, which are either scattered around or implicitly implied in different turns of conversations. Therefore, dialogue comprehension requires diverse capabilities such as paraphrasing, summarizing, and commonsense reasoni...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	286,459
2010.00638	Tabular GANs for uneven distribution	GANs are well known for success in the realistic image generation. However, they can be applied in tabular data generation as well. We will review and examine some recent papers about tabular GANs in action. We will generate data to make train distribution bring closer to the test. Then compare model performance traine...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	198,343
2106.15083	ElephantBook: A Semi-Automated Human-in-the-Loop System for Elephant Re-Identification	African elephants are vital to their ecosystems, but their populations are threatened by a rise in human-elephant conflict and poaching. Monitoring population dynamics is essential in conservation efforts; however, tracking elephants is a difficult task, usually relying on the invasive and sometimes dangerous placement...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	243,603
2101.05913	Supervised Transfer Learning at Scale for Medical Imaging	Transfer learning is a standard technique to improve performance on tasks with limited data. However, for medical imaging, the value of transfer learning is less clear. This is likely due to the large domain mismatch between the usual natural-image pre-training (e.g. ImageNet) and medical images. However, recent advanc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	215,547
2103.11136	Comprehensive Analysis of Continuously Variable Series Reactor Using G-C Framework	Continuously Variable Series Reactor (CVSR) has the ability to regulate the reactance of an ac circuit using the magnetizing characteristics of its ferromagnetic core, shared by an ac and a dc winding to control power flow, damp oscillations and limit fault currents. In order to understand and utilize a CVSR in the pow...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	225,683
2107.00114	QuickFlex: a Fast Algorithm for Flexible Region Construction for the TSO-DSO Coordination	Most of the new technological changes in power systems are expected to take place in distribution grids. The enormous potential for distribution flexibility could meet the transmission system's needs, changing the paradigm of generator-centric energy and ancillary services provided to a demand-centric one, by placing m...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	244,042
2209.14364	Semantic Segmentation of Vegetation in Remote Sensing Imagery Using Deep Learning	In recent years, the geospatial industry has been developing at a steady pace. This growth implies the addition of satellite constellations that produce a copious supply of satellite imagery and other Remote Sensing data on a daily basis. Sometimes, this information, even if in some cases we are referring to publicly a...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	320,217
1902.00541	The Efficacy of SHIELD under Different Threat Models	In this appraisal paper, we evaluate the efficacy of SHIELD, a compression-based defense framework for countering adversarial attacks on image classification models, which was published at KDD 2018. Here, we consider alternative threat models not studied in the original work, where we assume that an adaptive adversary ...	false	false	false	false	true	false	true	false	false	false	false	true	true	false	false	false	false	false	120,424
2311.02369	TACNET: Temporal Audio Source Counting Network	In this paper, we introduce the Temporal Audio Source Counting Network (TaCNet), an innovative architecture that addresses limitations in audio source counting tasks. TaCNet operates directly on raw audio inputs, eliminating complex preprocessing steps and simplifying the workflow. Notably, it excels in real-time speak...	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	405,413
2412.17845	Polymer/paper-based double touch mode capacitive pressure sensing element for wireless control of robotic arm	In this work, a large area, low cost and flexible polymer/paper-based double touch mode capacitive pressure sensor is demonstrated. Garage fabrication processes are used which only require cutting, taping and assembly of aluminum (Al) coated polyimide (PI) foil, PI tape and double-sided scotch tape. The presented press...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	520,146
1806.00548	A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models	We consider the problem of including additional knowledge in estimating sparse Gaussian graphical models (sGGMs) from aggregated samples, arising often in bioinformatics and neuroimaging applications. Previous joint sGGM estimators either fail to use existing knowledge or cannot scale-up to many tasks (large $K$) under...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	99,329
1511.04066	Properly Learning Poisson Binomial Distributions in Almost Polynomial Time	We give an algorithm for properly learning Poisson binomial distributions. A Poisson binomial distribution (PBD) of order $n$ is the discrete probability distribution of the sum of $n$ mutually independent Bernoulli random variables. Given $\widetilde{O}(1/\epsilon^2)$ samples from an unknown PBD $\mathbf{p}$, our algo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	48,838
2007.01290	Provably Efficient Neural Estimation of Structural Equation Model: An Adversarial Approach	Structural equation models (SEMs) are widely used in sciences, ranging from economics to psychology, to uncover causal relationships underlying a complex system under consideration and estimate structural parameters of interest. We study estimation in a class of generalized SEMs where the object of interest is defined ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	185,385
1703.03714	Applying the Wizard-of-Oz Technique to Multimodal Human-Robot Dialogue	Our overall program objective is to provide more natural ways for soldiers to interact and communicate with robots, much like how soldiers communicate with other soldiers today. We describe how the Wizard-of-Oz (WOz) method can be applied to multimodal human-robot dialogue in a collaborative exploration task. While the...	true	false	false	false	true	false	false	true	true	false	false	false	false	false	false	false	false	false	69,770
1810.04714	Training Generative Adversarial Networks with Binary Neurons by End-to-end Backpropagation	We propose the BinaryGAN, a novel generative adversarial network (GAN) that uses binary neurons at the output layer of the generator. We employ the sigmoid-adjusted straight-through estimators to estimate the gradients for the binary neurons and train the whole network by end-to-end backpropogation. The proposed model ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	110,091
1811.03305	BAR: Bayesian Activity Recognition using variational inference	Uncertainty estimation in deep neural networks is essential for designing reliable and robust AI systems. Applications such as video surveillance for identifying suspicious activities are designed with deep neural networks (DNNs), but DNNs do not provide uncertainty estimates. Capturing reliable uncertainty estimates i...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	112,808
2011.03164	Learning Power Control for Cellular Systems with Heterogeneous Graph Neural Network	Optimizing power control in multi-cell cellular networks with deep learning enables such a non-convex problem to be implemented in real-time. When channels are time-varying, the deep neural networks (DNNs) need to be re-trained frequently, which calls for low training complexity. To reduce the number of training sample...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	205,156
1803.05588	Deep Adaptive Attention for Joint Facial Action Unit Detection and Face Alignment	Facial action unit (AU) detection and face alignment are two highly correlated tasks since facial landmarks can provide precise AU locations to facilitate the extraction of meaningful local features for AU detection. Most existing AU detection works often treat face alignment as a preprocessing and handle the two tasks...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	92,663
2103.10390	Challenges of 3D Surface Reconstruction in Capsule Endoscopy	Essential for improving the accuracy and reliability of bowel cancer screening, three-dimensional (3D) surface reconstruction using capsule endoscopy (CE) images remains challenging due to CE hardware and software limitations. This report generally focuses on challenges associated with 3D visualization and specifically...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	225,440
2104.09798	CoDR: Computation and Data Reuse Aware CNN Accelerator	Computation and Data Reuse is critical for the resource-limited Convolutional Neural Network (CNN) accelerators. This paper presents Universal Computation Reuse to exploit weight sparsity, repetition, and similarity simultaneously in a convolutional layer. Moreover, CoDR decreases the cost of weight memory access by pr...	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	true	false	true	231,360
2309.08030	AV2Wav: Diffusion-Based Re-synthesis from Continuous Self-supervised Features for Audio-Visual Speech Enhancement	Speech enhancement systems are typically trained using pairs of clean and noisy speech. In audio-visual speech enhancement (AVSE), there is not as much ground-truth clean data available; most audio-visual datasets are collected in real-world environments with background noise and reverberation, hampering the developmen...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	392,004
2112.12616	Deep Filtering with DNN, CNN and RNN	This paper is about a deep learning approach for linear and nonlinear filtering. The idea is to train a neural network with Monte Carlo samples generated from a nominal dynamic model. Then the network weights are applied to Monte Carlo samples from an actual dynamic model. A main focus of this paper is on the deep filt...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	273,016
1402.2071	Attribute Dependencies for Data with Grades	This paper examines attribute dependencies in data that involve grades, such as a grade to which an object is red or a grade to which two objects are similar. We thus extend the classical agenda by allowing graded, or fuzzy, attributes instead of Boolean attributes in case of attribute implications, and allowing approx...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	30,750
2202.04499	Lightweight Jet Reconstruction and Identification as an Object Detection Task	We apply object detection techniques based on deep convolutional blocks to end-to-end jet identification and reconstruction tasks encountered at the CERN Large Hadron Collider (LHC). Collision events produced at the LHC and represented as an image composed of calorimeter and tracker cells are given as an input to a Sin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	279,570
1704.05973	Call Attention to Rumors: Deep Attention Based Recurrent Neural Networks for Early Rumor Detection	The proliferation of social media in communication and information dissemination has made it an ideal platform for spreading rumors. Automatically debunking rumors at their stage of diffusion is known as \textit{early rumor detection}, which refers to dealing with sequential posts regarding disputed factual claims with...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	72,102
1311.3198	Sound, Complete and Minimal UCQ-Rewriting for Existential Rules	We address the issue of Ontology-Based Data Access, with ontologies represented in the framework of existential rules, also known as Datalog+/-. A well-known approach involves rewriting the query using ontological knowledge. We focus here on the basic rewriting technique which consists of rewriting the initial query in...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	28,390
2501.11870	Coarse-to-Fine Lightweight Meta-Embedding for ID-Based Recommendation	The state-of-the-art recommendation systems have shifted the attention to efficient recommendation, e.g., on-device recommendation, under memory constraints. To this end, the existing methods either focused on the lightweight embeddings for both users and items, or involved on-device systems enjoying the compact embedd...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	526,071
2409.16938	Generative Object Insertion in Gaussian Splatting with a Multi-View Diffusion Model	Generating and inserting new objects into 3D content is a compelling approach for achieving versatile scene recreation. Existing methods, which rely on SDS optimization or single-view inpainting, often struggle to produce high-quality results. To address this, we propose a novel method for object insertion in 3D conten...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	491,582
1811.11127	Unprocessing Images for Learned Raw Denoising	Machine learning techniques work best when the data used for training resembles the data used for evaluation. This holds true for learned single-image denoising algorithms, which are applied to real raw camera sensor readings but, due to practical constraints, are often trained on synthetic image data. Though it is und...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	114,688
2405.19864	Out-of-distribution Reject Option Method for Dataset Shift Problem in Early Disease Onset Prediction	Machine learning is increasingly used to predict lifestyle-related disease onset using health and medical data. However, the prediction effectiveness is hindered by dataset shift, which involves discrepancies in data distribution between the training and testing datasets, misclassifying out-of-distribution (OOD) data. ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	459,099
1510.07905	Defect Detection Techniques for Airbag Production Sewing Stages	Airbags are subject to strict quality control in order to ensure passengers safety. The quality of fabric and sewing thread influence the final product and therefore, sewing defects must be early and accurately detected, in order to remove the item from production. Airbag seams assembly can take various forms, using li...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	48,242
2205.12012	Analysing the Greek Parliament Records with Emotion Classification	In this project, we tackle emotion classification for the Greek language, presenting and releasing a new dataset in Greek. We fine-tune and assess Transformer-based masked language models that were pre-trained on monolingual and multilingual resources, and we present the results per emotion and by aggregating at the se...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	298,374
1512.08571	Structured Pruning of Deep Convolutional Neural Networks	Real time application of deep learning algorithms is often hindered by high computational complexity and frequent memory accesses. Network pruning is a promising technique to solve this problem. However, pruning usually results in irregular network connections that not only demand extra representation efforts but also ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	50,528
1802.03638	Beyond Markov Logic: Efficient Mining of Prediction Rules in Large Graphs	Graph representations of large knowledge bases may comprise billions of edges. Usually built upon human-generated ontologies, several knowledge bases do not feature declared ontological rules and are far from being complete. Current rule mining approaches rely on schemata or store the graph in-memory, which can be unfe...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	90,027
2405.09197	Parallel and Proximal Constrained Linear-Quadratic Methods for Real-Time Nonlinear MPC	Recent strides in nonlinear model predictive control (NMPC) underscore a dependence on numerical advancements to efficiently and accurately solve large-scale problems. Given the substantial number of variables characterizing typical whole-body optimal control (OC) problems - often numbering in the thousands - exploitin...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	454,325
2207.14500	A Transfer Learning-Based Approach to Marine Vessel Re-Identification	Marine vessel re-identification technology is an important component of intelligent shipping systems and an important part of the visual perception tasks required for marine surveillance. However, unlike the situation on land, the maritime environment is complex and variable with fewer samples, and it is more difficult...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	310,609
2002.02220	Toward good families of codes from towers of surfaces	We introduce in this article a new method to estimate the minimum distance of codes from algebraic surfaces. This lower bound is generic, i.e. can be applied to any surface, and turns out to be ``liftable'' under finite morphisms, paving the way toward the construction of good codes from towers of surfaces. In the same...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	162,867
2307.06125	Learning Hierarchical Interactive Multi-Object Search for Mobile Manipulation	Existing object-search approaches enable robots to search through free pathways, however, robots operating in unstructured human-centered environments frequently also have to manipulate the environment to their needs. In this work, we introduce a novel interactive multi-object search task in which a robot has to open d...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	378,976
2012.12403	Performance Analysis of Adaptive Dynamic Tube MPC	Model predictive control (MPC) is an effective method for control of constrained systems but is susceptible to the external disturbances and modeling error often encountered in real-world applications. To address these issues, techniques such as Tube MPC (TMPC) utilize an ancillary offline-generated robust controller t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	212,916
2309.04960	SdCT-GAN: Reconstructing CT from Biplanar X-Rays with Self-driven Generative Adversarial Networks	Computed Tomography (CT) is a medical imaging modality that can generate more informative 3D images than 2D X-rays. However, this advantage comes at the expense of more radiation exposure, higher costs, and longer acquisition time. Hence, the reconstruction of 3D CT images using a limited number of 2D X-rays has gained...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	390,909
2108.06078	Piecewise Linear De-skewing for LiDAR Inertial Odometry	Light detection and ranging (LiDAR) on a moving agent could suffer from motion distortion due to simultaneous rotation of the LiDAR and fast movement of the agent. An accurate piecewise linear de skewing algorithm is proposed to correct the motion distortions for LiDAR inertial odometry (LIO) using high frequency motio...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	250,495
1512.00932	The Indian Spontaneous Expression Database for Emotion Recognition	Automatic recognition of spontaneous facial expressions is a major challenge in the field of affective computing. Head rotation, face pose, illumination variation, occlusion etc. are the attributes that increase the complexity of recognition of spontaneous expressions in practical applications. Effective recognition of...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	49,757
1910.10831	Variational Predictive Information Bottleneck	In classic papers, Zellner demonstrated that Bayesian inference could be derived as the solution to an information theoretic functional. Below we derive a generalized form of this functional as a variational lower bound of a predictive information bottleneck objective. This generalized functional encompasses most moder...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	150,595
2501.11351	Automatic Labelling & Semantic Segmentation with 4D Radar Tensors	In this paper, an automatic labelling process is presented for automotive datasets, leveraging on complementary information from LiDAR and camera. The generated labels are then used as ground truth with the corresponding 4D radar data as inputs to a proposed semantic segmentation network, to associate a class label to ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	525,895
2010.02012	Deep Representational Similarity Learning for analyzing neural signatures in task-based fMRI dataset	Similarity analysis is one of the crucial steps in most fMRI studies. Representational Similarity Analysis (RSA) can measure similarities of neural signatures generated by different cognitive states. This paper develops Deep Representational Similarity Learning (DRSL), a deep extension of RSA that is appropriate for an...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	198,879
2404.03414	Can Small Language Models Help Large Language Models Reason Better?: LM-Guided Chain-of-Thought	We introduce a novel framework, LM-Guided CoT, that leverages a lightweight (i.e., <1B) language model (LM) for guiding a black-box large (i.e., >10B) LM in reasoning tasks. Specifically, the lightweight LM first generates a rationale for each input instance. The Frozen large LM is then prompted to predict a task outpu...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	444,246
2311.11533	Event Camera Data Dense Pre-training	This paper introduces a self-supervised learning framework designed for pre-training neural networks tailored to dense prediction tasks using event camera data. Our approach utilizes solely event data for training. Transferring achievements from dense RGB pre-training directly to event camera data yields subpar perform...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	408,980
2408.01293	Underwater Object Detection Enhancement via Channel Stabilization	The complex marine environment exacerbates the challenges of object detection manifold. Marine trash endangers the aquatic ecosystem, presenting a persistent challenge. Accurate detection of marine deposits is crucial for mitigating this harm. Our work addresses underwater object detection by enhancing image quality an...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	478,174
1907.12122	It's All About The Scale -- Efficient Text Detection Using Adaptive Scaling	"Text can appear anywhere". This property requires us to carefully process all the pixels in an image in order to accurately localize all text instances. In particular, for the more difficult task of localizing small text regions, many methods use an enlarged image or even several rescaled ones as their input. This sig...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	140,039
2111.11862	Inferring User Facial Affect in Work-like Settings	Unlike the six basic emotions of happiness, sadness, fear, anger, disgust and surprise, modelling and predicting dimensional affect in terms of valence (positivity - negativity) and arousal (intensity) has proven to be more flexible, applicable and useful for naturalistic and real-world settings. In this paper, we aim ...	true	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	267,800
2306.05390	HQ-50K: A Large-scale, High-quality Dataset for Image Restoration	This paper introduces a new large-scale image restoration dataset, called HQ-50K, which contains 50,000 high-quality images with rich texture details and semantic diversity. We analyze existing image restoration datasets from five different perspectives, including data scale, resolution, compression rates, texture deta...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	372,174
1207.2714	Clustering based approach extracting collocations	The following study presents a collocation extraction approach based on clustering technique. This study uses a combination of several classical measures which cover all aspects of a given corpus then it suggests separating bigrams found in the corpus in several disjoint groups according to the probability of presence ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	17,412
2305.14361	Criticality Analysis: Bio-inspired Nonlinear Data Representation	The representation of arbitrary data in a biological system is one of the most elusive elements of biological information processing. The often logarithmic nature of information in amplitude and frequency presented to biosystems prevents simple encapsulation of the information contained in the input. Criticality Analys...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	366,991
2105.01714	Drifting Features: Detection and evaluation in the context of automatic RRLs identification in VVV	As most of the modern astronomical sky surveys produce data faster than humans can analyze it, Machine Learning (ML) has become a central tool in Astronomy. Modern ML methods can be characterized as highly resistant to some experimental errors. However, small changes on the data over long distances or long periods of t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	233,597
1805.03545	Solving Sudoku with Ant Colony Optimisation	In this paper we present a new Ant Colony Optimisation-based algorithm for Sudoku, which out-performs existing methods on large instances. Our method includes a novel anti-stagnation operator, which we call Best Value Evaporation.	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	97,069
2305.13119	Ambiguity Meets Uncertainty: Investigating Uncertainty Estimation for Word Sense Disambiguation	Word sense disambiguation (WSD), which aims to determine an appropriate sense for a target word given its context, is crucial for natural language understanding. Existing supervised methods treat WSD as a classification task and have achieved remarkable performance. However, they ignore uncertainty estimation (UE) in t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	366,357
2111.04798	TAGLETS: A System for Automatic Semi-Supervised Learning with Auxiliary Data	Machine learning practitioners often have access to a spectrum of data: labeled data for the target task (which is often limited), unlabeled data, and auxiliary data, the many available labeled datasets for other tasks. We describe TAGLETS, a system built to study techniques for automatically exploiting all three types...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	265,593
2010.11981	A novel auction system for selecting advertisements in Real-Time bidding	Real-Time Bidding is a new Internet advertising system that has become very popular in recent years. This system works like a global auction where advertisers bid to display their impressions in the publishers' ad slots. The most popular system to select which advertiser wins each auction is the Generalized second-pric...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	true	202,500
1908.02947	Graph Node Embeddings using Domain-Aware Biased Random Walks	The recent proliferation of publicly available graph-structured data has sparked an interest in machine learning algorithms for graph data. Since most traditional machine learning algorithms assume data to be tabular, embedding algorithms for mapping graph data to real-valued vector spaces has become an active area of ...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	141,123
1708.08994	Clustering Patients with Tensor Decomposition	In this paper we present a method for the unsupervised clustering of high-dimensional binary data, with a special focus on electronic healthcare records. We present a robust and efficient heuristic to face this problem using tensor decomposition. We present the reasons why this approach is preferable for tasks such as ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	79,711
2502.11565	STARS-Enabled Full-Duplex Two-Way mMIMO System Under Spatially-Correlated Channels	\underline{S}imultaneous \underline{t}ransmitting \underline{a}nd \underline{r}eflecting \underline{s}urface (STARS)-assisted systems have emerged to fill this gap by providing $ 360^{\circ}$ wireless coverage. In parallel, full-duplex (FD) communication offers a higher achievable rate through efficient spectrum util...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	534,444

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