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
2007.11899	Harnessing spatial homogeneity of neuroimaging data: patch individual filter layers for CNNs	Neuroimaging data, e.g. obtained from magnetic resonance imaging (MRI), is comparably homogeneous due to (1) the uniform structure of the brain and (2) additional efforts to spatially normalize the data to a standard template using linear and non-linear transformations. Convolutional neural networks (CNNs), in contrast...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	188,674
1811.00217	META-DES.Oracle: Meta-learning and feature selection for ensemble selection	The key issue in Dynamic Ensemble Selection (DES) is defining a suitable criterion for calculating the classifiers' competence. There are several criteria available to measure the level of competence of base classifiers, such as local accuracy estimates and ranking. However, using only one criterion may lead to a poor ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	112,036
1103.0795	Decimation-Enhanced Finite Alphabet Iterative Decoders for LDPC codes on the BSC	Finite alphabet iterative decoders (FAID) with multilevel messages that can surpass BP in the error floor region for LDPC codes on the BSC were previously proposed. In this paper, we propose decimation-enhanced decoders. The technique of decimation which is incorporated into the message update rule, involves fixing cer...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	9,472
1401.7486	Use HMM and KNN for classifying corneal data	These days to gain classification system with high accuracy that can classify complicated pattern are so useful in medicine and industry. In this article a process for getting the best classifier for Lasik data is suggested. However at first it's been tried to find the best line and curve by this classifier in order to...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	30,461
1909.11024	Evaluating the Impacts of Transmission Expansion on Sub-Synchronous Resonance Risk	While transmission expansions are planned to have positive impact on reliability of power grids, they could increase the risk and severity of some of the detrimental incidents in power grid mainly by virtue of changing system configuration, consequently electrical distance. This paper aims to evaluate and quantify the ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	146,692
2211.06637	Modular Clinical Decision Support Networks (MoDN) -- Updatable, Interpretable, and Portable Predictions for Evolving Clinical Environments	Data-driven Clinical Decision Support Systems (CDSS) have the potential to improve and standardise care with personalised probabilistic guidance. However, the size of data required necessitates collaborative learning from analogous CDSS's, which are often unsharable or imperfectly interoperable (IIO), meaning their fea...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	329,963
2010.02123	Lifelong Language Knowledge Distillation	It is challenging to perform lifelong language learning (LLL) on a stream of different tasks without any performance degradation comparing to the multi-task counterparts. To address this issue, we present Lifelong Language Knowledge Distillation (L2KD), a simple but efficient method that can be easily applied to existi...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	198,910
2207.02442	Transformers are Adaptable Task Planners	Every home is different, and every person likes things done in their particular way. Therefore, home robots of the future need to both reason about the sequential nature of day-to-day tasks and generalize to user's preferences. To this end, we propose a Transformer Task Planner(TTP) that learns high-level actions from ...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	306,521
2501.14970	AI-driven Wireless Positioning: Fundamentals, Standards, State-of-the-art, and Challenges	Wireless positioning technologies hold significant value for applications in autonomous driving, extended reality (XR), unmanned aerial vehicles (UAVs), and more. With the advancement of artificial intelligence (AI), leveraging AI to enhance positioning accuracy and robustness has emerged as a field full of potential. ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	527,340
1909.06418	Towards A Robot Explanation System: A Survey and Our Approach to State Summarization, Storage and Querying, and Human Interface	As robot systems become more ubiquitous, developing understandable robot systems becomes increasingly important in order to build trust. In this paper, we present an approach to developing a holistic robot explanation system, which consists of three interconnected components: state summarization, storage and querying, ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	145,364
2109.05802	PyProD: A Machine Learning-Friendly Platform for Protection Analytics in Distribution Systems	This paper introduces PyProD, a Python-based machine learning (ML)-compatible test-bed for evaluating the efficacy of protection schemes in electric distribution grids. This testbed is designed to bridge the gap between conventional power distribution grid analysis and growing capability of ML-based decision making alg...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	254,957
2502.13114	The influence of motion features in temporal perception	This paper examines the role of manner-of-motion verbs in shaping subjective temporal perception and emotional resonance. Through four complementary studies, we explore how these verbs influence the conceptualization of time, examining their use in literal and metaphorical (temporal) contexts. Our findings reveal that ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	535,207
2307.01053	ENGAGE: Explanation Guided Data Augmentation for Graph Representation Learning	The recent contrastive learning methods, due to their effectiveness in representation learning, have been widely applied to modeling graph data. Random perturbation is widely used to build contrastive views for graph data, which however, could accidentally break graph structures and lead to suboptimal performance. In a...	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	false	377,218
2108.00728	Complexity of the LTI system trajectory boundedness problem	We study the algorithmic complexity of the problem of deciding whether a Linear Time Invariant dynamical system with rational coefficients has bounded trajectories. Despite its ubiquitous and elementary nature in Systems and Control, it turns out that this question is quite intricate, and, to the best of our knowledge,...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	248,815
2312.03203	Feature 3DGS: Supercharging 3D Gaussian Splatting to Enable Distilled Feature Fields	3D scene representations have gained immense popularity in recent years. Methods that use Neural Radiance fields are versatile for traditional tasks such as novel view synthesis. In recent times, some work has emerged that aims to extend the functionality of NeRF beyond view synthesis, for semantically aware tasks such...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	413,166
2303.15167	Prompt-Guided Zero-Shot Anomaly Action Recognition using Pretrained Deep Skeleton Features	This study investigates unsupervised anomaly action recognition, which identifies video-level abnormal-human-behavior events in an unsupervised manner without abnormal samples, and simultaneously addresses three limitations in the conventional skeleton-based approaches: target domain-dependent DNN training, robustness ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	354,388
1510.02923	On 1-Laplacian Elliptic Equations Modeling Magnetic Resonance Image Rician Denoising	Modeling magnitude Magnetic Resonance Images (MRI) rician denoising in a Bayesian or generalized Tikhonov framework using Total Variation (TV) leads naturally to the consideration of nonlinear elliptic equations. These involve the so called $1$-Laplacian operator and special care is needed to properly formulate the pro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	47,779
1806.10128	Leveraging Disease Progression Learning for Medical Image Recognition	Unlike natural images, medical images often have intrinsic characteristics that can be leveraged for neural network learning. For example, images that belong to different stages of a disease may continuously follow a certain progression pattern. In this paper, we propose a novel method that leverages disease progressio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	101,489
2403.18098	GPTs and Language Barrier: A Cross-Lingual Legal QA Examination	In this paper, we explore the application of Generative Pre-trained Transformers (GPTs) in cross-lingual legal Question-Answering (QA) systems using the COLIEE Task 4 dataset. In the COLIEE Task 4, given a statement and a set of related legal articles that serve as context, the objective is to determine whether the sta...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	441,758
2307.12033	Self-Supervised and Semi-Supervised Polyp Segmentation using Synthetic Data	Early detection of colorectal polyps is of utmost importance for their treatment and for colorectal cancer prevention. Computer vision techniques have the potential to aid professionals in the diagnosis stage, where colonoscopies are manually carried out to examine the entirety of the patient's colon. The main challeng...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	381,116
2309.11530	Robust fake-post detection against real-coloring adversaries	The viral propagation of fake posts on online social networks (OSNs) has become an alarming concern. The paper aims to design control mechanisms for fake post detection while negligibly affecting the propagation of real posts. Towards this, a warning mechanism based on crowd-signals was recently proposed, where all use...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	393,445
1905.10971	An Empirical Study on Post-processing Methods for Word Embeddings	Word embeddings learnt from large corpora have been adopted in various applications in natural language processing and served as the general input representations to learning systems. Recently, a series of post-processing methods have been proposed to boost the performance of word embeddings on similarity comparison an...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	132,283
2305.00666	Part Aware Contrastive Learning for Self-Supervised Action Recognition	In recent years, remarkable results have been achieved in self-supervised action recognition using skeleton sequences with contrastive learning. It has been observed that the semantic distinction of human action features is often represented by local body parts, such as legs or hands, which are advantageous for skeleto...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	361,417
2410.02932	Intrinsic Evaluation of RAG Systems for Deep-Logic Questions	We introduce the Overall Performance Index (OPI), an intrinsic metric to evaluate retrieval-augmented generation (RAG) mechanisms for applications involving deep-logic queries. OPI is computed as the harmonic mean of two key metrics: the Logical-Relation Correctness Ratio and the average of BERT embedding similarity sc...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	494,527
2304.03516	Generative Recommendation: Towards Next-generation Recommender Paradigm	Recommender systems typically retrieve items from an item corpus for personalized recommendations. However, such a retrieval-based recommender paradigm faces two limitations: 1) the human-generated items in the corpus might fail to satisfy the users' diverse information needs, and 2) users usually adjust the recommenda...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	356,843
1904.04702	Modeling Corruption in Eventually-Consistent Graph Databases	We present a model and analysis of an eventually consistent graph database where loosely cooperating servers accept concurrent updates to a partitioned, distributed graph. The model is high-fidelity and preserves design choices from contemporary graph database management systems. To explore the problem space, we use tw...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	127,101
2311.02294	LLMs grasp morality in concept	Work in AI ethics and fairness has made much progress in regulating LLMs to reflect certain values, such as fairness, truth, and diversity. However, it has taken the problem of how LLMs might 'mean' anything at all for granted. Without addressing this, it is not clear what imbuing LLMs with such values even means. In r...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	405,377
1707.01155	Stochastic, Distributed and Federated Optimization for Machine Learning	We study optimization algorithms for the finite sum problems frequently arising in machine learning applications. First, we propose novel variants of stochastic gradient descent with a variance reduction property that enables linear convergence for strongly convex objectives. Second, we study distributed setting, in wh...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	76,478
2305.15557	Non-Parametric Learning of Stochastic Differential Equations with Non-asymptotic Fast Rates of Convergence	We propose a novel non-parametric learning paradigm for the identification of drift and diffusion coefficients of multi-dimensional non-linear stochastic differential equations, which relies upon discrete-time observations of the state. The key idea essentially consists of fitting a RKHS-based approximation of the corr...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	367,658
2104.12822	Recommending Burgers based on Pizza Preferences: Addressing Data Sparsity with a Product of Experts	In this paper, we describe a method to tackle data sparsity and create recommendations in domains with limited knowledge about user preferences. We expand the variational autoencoder collaborative filtering from a single-domain to a multi-domain setting. The intuition is that user-item interactions in a source domain c...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	232,320
2110.06682	Color Counting for Fashion, Art, and Design	Color modelling and extraction is an important topic in fashion, art, and design. Recommender systems, color-based retrieval, decorating, and fashion design can benefit from color extraction tools. Research has shown that modeling color so that it can be automatically analyzed and / or extracted is a difficult task. Un...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	260,710
2004.14010	Counting of Grapevine Berries in Images via Semantic Segmentation using Convolutional Neural Networks	The extraction of phenotypic traits is often very time and labour intensive. Especially the investigation in viticulture is restricted to an on-site analysis due to the perennial nature of grapevine. Traditionally skilled experts examine small samples and extrapolate the results to a whole plot. Thereby different grape...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	174,750
2203.12178	Unifying Motion Deblurring and Frame Interpolation with Events	Slow shutter speed and long exposure time of frame-based cameras often cause visual blur and loss of inter-frame information, degenerating the overall quality of captured videos. To this end, we present a unified framework of event-based motion deblurring and frame interpolation for blurry video enhancement, where the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	287,166
2205.14380	Deep Deconfounded Content-based Tag Recommendation for UGC with Causal Intervention	Traditional content-based tag recommender systems directly learn the association between user-generated content (UGC) and tags based on collected UGC-tag pairs. However, since a UGC uploader simultaneously creates the UGC and selects the corresponding tags, her personal preference inevitably biases the tag selections, ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	299,345
2008.12678	Comparison Between Genetic Fuzzy Methodology and Q-learning for Collaborative Control Design	A comparison between two machine learning approaches viz., Genetic Fuzzy Methodology and Q-learning, is presented in this paper. The approaches are used to model controllers for a set of collaborative robots that need to work together to bring an object to a target position. The robots are fixed and are attached to the...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	193,646
2111.06825	Alleviating the transit timing variation bias in transit surveys. I. RIVERS: Method and detection of a pair of resonant super-Earths around Kepler-1705	Transit timing variations (TTVs) can provide useful information for systems observed by transit, as they allow us to put constraints on the masses and eccentricities of the observed planets, or even to constrain the existence of non-transiting companions. However, TTVs can also act as a detection bias that can prevent ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	266,186
2309.07412	Advancing Regular Language Reasoning in Linear Recurrent Neural Networks	In recent studies, linear recurrent neural networks (LRNNs) have achieved Transformer-level performance in natural language and long-range modeling, while offering rapid parallel training and constant inference cost. With the resurgence of interest in LRNNs, we study whether they can learn the hidden rules in training ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	391,770
1702.06690	Experiment, Modeling, and Analysis of Wireless-Powered Sensor Network for Energy Neutral Power Management	In this paper, we provide a comprehensive system model of a wireless-powered sensor network (WPSN) based on experimental results on a real-life testbed. In the WPSN, a sensor node is wirelessly powered by the RF energy transfer from a dedicated RF power source. We define the behavior of each component comprising the WP...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	68,653
2209.08570	Bumpless Topology Transition	The topology transition problem of transmission networks is becoming increasingly crucial with topological flexibility more widely leveraged to promote high renewable penetration. This paper proposes a novel methodology to address this problem. Aiming at achieving a bumpless topology transition regarding both static an...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	318,174
2407.03007	What Affects the Stability of Tool Learning? An Empirical Study on the Robustness of Tool Learning Frameworks	Tool learning methods have enhanced the ability of large language models (LLMs) to interact with real-world applications. Many existing works fine-tune LLMs or design prompts to enable LLMs to select appropriate tools and correctly invoke them to meet user requirements. However, it is observed in previous works that th...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	469,984
1412.1265	Deeply learned face representations are sparse, selective, and robust	This paper designs a high-performance deep convolutional network (DeepID2+) for face recognition. It is learned with the identification-verification supervisory signal. By increasing the dimension of hidden representations and adding supervision to early convolutional layers, DeepID2+ achieves new state-of-the-art on L...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	38,090
1408.1549	Real-Time Human-Computer Interaction Based on Face and Hand Gesture Recognition	At the present time, hand gestures recognition system could be used as a more expected and useable approach for human computer interaction. Automatic hand gesture recognition system provides us a new tactic for interactive with the virtual environment. In this paper, a face and hand gesture recognition system which is ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	35,187
2407.05643	Revisiting XL-MIMO Channel Estimation: When Dual-Wideband Effects Meet Near Field	The deployment of extremely large antenna arrays (ELAAs) and operation at higher frequency bands in wideband extremely large-scale multiple-input-multiple-output (XL-MIMO) systems introduce significant near-field effects, such as spherical wavefront propagation and spatially non-stationary (SnS) properties. Combined wi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	471,068
2211.17179	Investigation of Proper Orthogonal Decomposition for Echo State Networks	Echo State Networks (ESN) are a type of Recurrent Neural Network that yields promising results in representing time series and nonlinear dynamic systems. Although they are equipped with a very efficient training procedure, Reservoir Computing strategies, such as the ESN, require high-order networks, i.e., many neurons,...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	333,887
1909.03108	High Resolution Medical Image Analysis with Spatial Partitioning	Medical images such as 3D computerized tomography (CT) scans and pathology images, have hundreds of millions or billions of voxels/pixels. It is infeasible to train CNN models directly on such high resolution images, because neural activations of a single image do not fit in the memory of a single GPU/TPU, and naive da...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	144,375
2502.05145	From Restless to Contextual: A Thresholding Bandit Approach to Improve Finite-horizon Performance	Online restless bandits extend classic contextual bandits by incorporating state transitions and budget constraints, representing each agent as a Markov Decision Process (MDP). This framework is crucial for finite-horizon strategic resource allocation, optimizing limited costly interventions for long-term benefits. How...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	531,458
2409.09144	PrimeDepth: Efficient Monocular Depth Estimation with a Stable Diffusion Preimage	This work addresses the task of zero-shot monocular depth estimation. A recent advance in this field has been the idea of utilising Text-to-Image foundation models, such as Stable Diffusion. Foundation models provide a rich and generic image representation, and therefore, little training data is required to reformulate...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	488,195
2103.10474	Dynamic Model for Query-Document Expansion towards Improving Retrieval Relevance	Getting relevant information from search engines has been the heart of research works in information retrieval. Query expansion is a retrieval technique that has been studied and proved to yield positive results in relevance. Users are required to express their queries as a shortlist of words, sentences, or questions. ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	225,461
2302.08231	3M3D: Multi-view, Multi-path, Multi-representation for 3D Object Detection	3D visual perception tasks based on multi-camera images are essential for autonomous driving systems. Latest work in this field performs 3D object detection by leveraging multi-view images as an input and iteratively enhancing object queries (object proposals) by cross-attending multi-view features. However, individual...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	345,992
2205.02979	Explaining the Effectiveness of Multi-Task Learning for Efficient Knowledge Extraction from Spine MRI Reports	Pretrained Transformer based models finetuned on domain specific corpora have changed the landscape of NLP. However, training or fine-tuning these models for individual tasks can be time consuming and resource intensive. Thus, a lot of current research is focused on using transformers for multi-task learning (Raffel et...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	295,135
1604.08201	Interpretable Deep Neural Networks for Single-Trial EEG Classification	Background: In cognitive neuroscience the potential of Deep Neural Networks (DNNs) for solving complex classification tasks is yet to be fully exploited. The most limiting factor is that DNNs as notorious 'black boxes' do not provide insight into neurophysiological phenomena underlying a decision. Layer-wise Relevance ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	55,182
1409.8332	Continuous-Time Consensus under Non-Instantaneous Reciprocity	We consider continuous-time consensus systems whose interactions satisfy a form or reciprocity that is not instantaneous, but happens over time. We show that these systems have certain desirable properties: They always converge independently of the specific interactions taking place and there exist simple conditions on...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	36,404
1808.04576	Automatic Airway Segmentation in chest CT using Convolutional Neural Networks	Segmentation of the airway tree from chest computed tomography (CT) images is critical for quantitative assessment of airway diseases including bronchiectasis and chronic obstructive pulmonary disease (COPD). However, obtaining an accurate segmentation of airways from CT scans is difficult due to the high complexity of...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	105,185
2312.17517	Embedded feature selection in LSTM networks with multi-objective evolutionary ensemble learning for time series forecasting	Time series forecasting plays a crucial role in diverse fields, necessitating the development of robust models that can effectively handle complex temporal patterns. In this article, we present a novel feature selection method embedded in Long Short-Term Memory networks, leveraging a multi-objective evolutionary algori...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	418,779
2408.05228	Beyond the Neural Fog: Interpretable Learning for AC Optimal Power Flow	The AC optimal power flow (AC-OPF) problem is essential for power system operations, but its non-convex nature makes it challenging to solve. A widely used simplification is the linearized DC optimal power flow (DC-OPF) problem, which can be solved to global optimality, but whose optimal solution is always infeasible i...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	479,702
2011.10034	Decentralized Task and Path Planning for Multi-Robot Systems	We consider a multi-robot system with a team of collaborative robots and multiple tasks that emerges over time. We propose a fully decentralized task and path planning (DTPP) framework consisting of a task allocation module and a localized path planning module. Each task is modeled as a Markov Decision Process (MDP) or...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	207,397
2002.07224	Evolutionary Optimization of Deep Learning Activation Functions	The choice of activation function can have a large effect on the performance of a neural network. While there have been some attempts to hand-engineer novel activation functions, the Rectified Linear Unit (ReLU) remains the most commonly-used in practice. This paper shows that evolutionary algorithms can discover novel...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	164,404
1612.01193	Optimal transport over nonlinear systems via infinitesimal generators on graphs	We present a set-oriented graph-based computational framework for continuous-time optimal transport over nonlinear dynamical systems. We recover provably optimal control laws for steering a given initial distribution in phase space to a final distribution in prescribed finite time for the case of non-autonomous nonline...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	65,030
2310.01842	SelfGraphVQA: A Self-Supervised Graph Neural Network for Scene-based Question Answering	The intersection of vision and language is of major interest due to the increased focus on seamless integration between recognition and reasoning. Scene graphs (SGs) have emerged as a useful tool for multimodal image analysis, showing impressive performance in tasks such as Visual Question Answering (VQA). In this work...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	396,601
2205.13199	Decoupled Pyramid Correlation Network for Liver Tumor Segmentation from CT images	Purpose: Automated liver tumor segmentation from Computed Tomography (CT) images is a necessary prerequisite in the interventions of hepatic abnormalities and surgery planning. However, accurate liver tumor segmentation remains challenging due to the large variability of tumor sizes and inhomogeneous texture. Recent ad...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	298,845
2304.07122	Stochastic Model Predictive Control using Initial State and Variance Interpolation	We present a Stochastic Model Predictive Control (SMPC) framework for linear systems subject to Gaussian disturbances. In order to avoid feasibility issues, we employ a recent initialization strategy, optimizing over an interpolation of the initial state between the current measurement and previous prediction. By also ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	358,234
2002.02705	Iterative Label Improvement: Robust Training by Confidence Based Filtering and Dataset Partitioning	State-of-the-art, high capacity deep neural networks not only require large amounts of labelled training data, they are also highly susceptible to label errors in this data, typically resulting in large efforts and costs and therefore limiting the applicability of deep learning. To alleviate this issue, we propose a no...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	163,004
2212.04976	Augmentation Matters: A Simple-yet-Effective Approach to Semi-supervised Semantic Segmentation	Recent studies on semi-supervised semantic segmentation (SSS) have seen fast progress. Despite their promising performance, current state-of-the-art methods tend to increasingly complex designs at the cost of introducing more network components and additional training procedures. Differently, in this work, we follow a ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	335,639
2408.00439	Rapid and Power-Aware Learned Optimization for Modular Receive Beamforming	Multiple-input multiple-output (MIMO) systems play a key role in wireless communication technologies. A widely considered approach to realize scalable MIMO systems involves architectures comprised of multiple separate modules, each with its own beamforming capability. Such models accommodate cell-free massive MIMO and ...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	477,843
2110.08480	Learning Cooperation and Online Planning Through Simulation and Graph Convolutional Network	Multi-agent Markov Decision Process (MMDP) has been an effective way of modelling sequential decision making algorithms for multi-agent cooperative environments. A number of algorithms based on centralized and decentralized planning have been developed in this domain. However, dynamically changing environment, coupled ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	261,420
2301.11562	Arbitrariness and Social Prediction: The Confounding Role of Variance in Fair Classification	Variance in predictions across different trained models is a significant, under-explored source of error in fair binary classification. In practice, the variance on some data examples is so large that decisions can be effectively arbitrary. To investigate this problem, we take an experimental approach and make four ove...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	342,196
1801.02172	Market-based Control of Air-Conditioning Loads with Switching Constraints for Providing Ancillary Services	Air-conditioning loads (ACLs) are among the most promising demand side resources for their thermal storage capacity and fast response potential. This paper adopts the principle of market-based control (MBC) for the ACLs to participate in the ancillary services. The MBC method is suitable for the control of distributed ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	87,876
1804.09873	Prospects for Theranostics in Neurosurgical Imaging: Empowering Confocal Laser Endomicroscopy Diagnostics via Deep Learning	Confocal laser endomicroscopy (CLE) is an advanced optical fluorescence imaging technology that has the potential to increase intraoperative precision, extend resection, and tailor surgery for malignant invasive brain tumors because of its subcellular dimension resolution. Despite its promising diagnostic potential, in...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	96,058
2104.14703	Adapting Coreference Resolution for Processing Violent Death Narratives	Coreference resolution is an important component in analyzing narrative text from administrative data (e.g., clinical or police sources). However, existing coreference models trained on general language corpora suffer from poor transferability due to domain gaps, especially when they are applied to gender-inclusive dat...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	232,911
2409.02490	TP-GMOT: Tracking Generic Multiple Object by Textual Prompt with Motion-Appearance Cost (MAC) SORT	While Multi-Object Tracking (MOT) has made substantial advancements, it is limited by heavy reliance on prior knowledge and limited to predefined categories. In contrast, Generic Multiple Object Tracking (GMOT), tracking multiple objects with similar appearance, requires less prior information about the targets but fac...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	485,725
1811.04697	CUNI System for the WMT18 Multimodal Translation Task	We present our submission to the WMT18 Multimodal Translation Task. The main feature of our submission is applying a self-attentive network instead of a recurrent neural network. We evaluate two methods of incorporating the visual features in the model: first, we include the image representation as another input to the...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	113,153
1705.04336	An Optimal Dimensionality Multi-shell Sampling Scheme with Accurate and Efficient Transforms for Diffusion MRI	This paper proposes a multi-shell sampling scheme and corresponding transforms for the accurate reconstruction of the diffusion signal in diffusion MRI by expansion in the spherical polar Fourier (SPF) basis. The sampling scheme uses an optimal number of samples, equal to the degrees of freedom of the band-limited diff...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	73,313
1405.1905	Asymmetrically interacting spreading dynamics on complex layered networks	The spread of disease through a physical-contact network and the spread of information about the disease on a communication network are two intimately related dynamical processes. We investigate the asymmetrical interplay between the two types of spreading dynamics, each occurring on its own layer, by focusing on the t...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	32,930
2209.10315	Analyzing Robustness of Angluin's L* Algorithm in Presence of Noise	Angluin's L* algorithm learns the minimal (complete) deterministic finite automaton (DFA) of a regular language using membership and equivalence queries. Its probabilistic approximatively correct (PAC) version substitutes an equivalence query by a large enough set of random membership queries to get a high level confid...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	318,821
2202.03807	Indy Autonomous Challenge -- Autonomous Race Cars at the Handling Limits	Motorsport has always been an enabler for technological advancement, and the same applies to the autonomous driving industry. The team TUM Auton-omous Motorsports will participate in the Indy Autonomous Challenge in Octo-ber 2021 to benchmark its self-driving software-stack by racing one out of ten autonomous Dallara A...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	279,349
1808.01940	Accurate indoor mapping using an autonomous unmanned aerial vehicle (UAV)	An autonomous indoor aerial vehicle requires reliable simul- taneous localization and mapping (SLAM), accurate flight control, and robust path planning for navigation. This paper presents a system level combination of these existing technologies for 2D navigation. An Unmanned aerial vehicle (UAV) called URSA (Unmanned ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	104,672
2408.14084	HABD: a houma alliance book ancient handwritten character recognition database	The Houma Alliance Book, one of history's earliest calligraphic examples, was unearthed in the 1970s. These artifacts were meticulously organized, reproduced, and copied by the Shanxi Provincial Institute of Cultural Relics. However, because of their ancient origins and severe ink erosion, identifying characters in the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	483,414
2308.06354	Large Language Models to Identify Social Determinants of Health in Electronic Health Records	Social determinants of health (SDoH) have an important impact on patient outcomes but are incompletely collected from the electronic health records (EHR). This study researched the ability of large language models to extract SDoH from free text in EHRs, where they are most commonly documented, and explored the role of ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	385,105
1810.13116	Matching Based Two-Timescale Resource Allocation for Cooperative D2D Communication	We consider a cooperative device-to-device (D2D) communication system, where the D2D transmitters (DTs) act as relays to assist cellular users (CUs) in exchange for the opportunities to use the licensed spectrum. To reduce the overhead, we propose a novel two-timescale resource allocation scheme, in which the pairing b...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	111,915
2410.06652	Task-oriented Time Series Imputation Evaluation via Generalized Representers	Time series analysis is widely used in many fields such as power energy, economics, and transportation, including different tasks such as forecasting, anomaly detection, classification, etc. Missing values are widely observed in these tasks, and often leading to unpredictable negative effects on existing methods, hinde...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	496,297
1707.00819	Causal Consistency of Structural Equation Models	Complex systems can be modelled at various levels of detail. Ideally, causal models of the same system should be consistent with one another in the sense that they agree in their predictions of the effects of interventions. We formalise this notion of consistency in the case of Structural Equation Models (SEMs) by intr...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	76,425
2112.08220	On the optimal consensus of crab submarines in one dimension	We consider the problem of computing the optimal meeting point of a set of N crab submarines. First, we analyze the case where the submarines are allowed any position on the real line: we provide a constructive proof of optimality and we use it to provide a linear-time algorithm to find the optimal meeting point for th...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	271,733
2010.10472	Comparison of Interactive Knowledge Base Spelling Correction Models for Low-Resource Languages	Spelling normalization for low resource languages is a challenging task because the patterns are hard to predict and large corpora are usually required to collect enough examples. This work shows a comparison of a neural model and character language models with varying amounts on target language data. Our usage scenari...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	201,893
1702.05202	A Correlation-Breaking Interleaving of Polar Codes in Concatenated Systems	It is known that the bit errors of polar codes with successive cancellation (SC) decoding are coupled. However, existing concatenation schemes of polar codes with other error correction codes rarely take this coupling effect into consideration. To achieve a better error performance of concatenated systems with polar co...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	68,369
2401.03128	Manifold-based Shapley for SAR Recognization Network Explanation	Explainable artificial intelligence (XAI) holds immense significance in enhancing the deep neural network's transparency and credibility, particularly in some risky and high-cost scenarios, like synthetic aperture radar (SAR). Shapley is a game-based explanation technique with robust mathematical foundations. However, ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	419,972
2408.03399	RHiOTS: A Framework for Evaluating Hierarchical Time Series Forecasting Algorithms	We introduce the Robustness of Hierarchically Organized Time Series (RHiOTS) framework, designed to assess the robustness of hierarchical time series forecasting models and algorithms on real-world datasets. Hierarchical time series, where lower-level forecasts must sum to upper-level ones, are prevalent in various con...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	478,997
1912.06059	Grid Search, Random Search, Genetic Algorithm: A Big Comparison for NAS	In this paper, we compare the three most popular algorithms for hyperparameter optimization (Grid Search, Random Search, and Genetic Algorithm) and attempt to use them for neural architecture search (NAS). We use these algorithms for building a convolutional neural network (search architecture). Experimental results on...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	157,255
cs/0003024	A Compiler for Ordered Logic Programs	This paper describes a system, called PLP, for compiling ordered logic programs into standard logic programs under the answer set semantics. In an ordered logic program, rules are named by unique terms, and preferences among rules are given by a set of dedicated atoms. An ordered logic program is transformed into a sec...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	537,038
2407.00115	Instance Temperature Knowledge Distillation	Knowledge distillation (KD) enhances the performance of a student network by allowing it to learn the knowledge transferred from a teacher network incrementally. Existing methods dynamically adjust the temperature to enable the student network to adapt to the varying learning difficulties at different learning stages o...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	468,731
2305.09175	Cooperative Aerial Transportation of Nonuniform Load through Quadrotors by Elastic and Flexible Cables	In this paper, first the full dynamics of aerial transportation of a rigid body with arbitrary number of quadrotors is derived. Then a control strategy is proposed to convey the nonuniform rigid body appropriately to the desired trajectory. In the dynamical model of this transportation system, not only the load is cons...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	364,543
2312.01053	End-to-End Speech-to-Text Translation: A Survey	Speech-to-text translation pertains to the task of converting speech signals in a language to text in another language. It finds its application in various domains, such as hands-free communication, dictation, video lecture transcription, and translation, to name a few. Automatic Speech Recognition (ASR), as well as Ma...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	412,289
2006.06392	Interpreting CNN for Low Complexity Learned Sub-pixel Motion Compensation in Video Coding	Deep learning has shown great potential in image and video compression tasks. However, it brings bit savings at the cost of significant increases in coding complexity, which limits its potential for implementation within practical applications. In this paper, a novel neural network-based tool is presented which improve...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	181,413
1604.00239	Tensor Representations via Kernel Linearization for Action Recognition from 3D Skeletons (Extended Version)	In this paper, we explore tensor representations that can compactly capture higher-order relationships between skeleton joints for 3D action recognition. We first define RBF kernels on 3D joint sequences, which are then linearized to form kernel descriptors. The higher-order outer-products of these kernel descriptors f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	53,997
1604.02634	Online Nonnegative Matrix Factorization with Outliers	We propose a unified and systematic framework for performing online nonnegative matrix factorization in the presence of outliers. Our framework is particularly suited to large-scale data. We propose two solvers based on projected gradient descent and the alternating direction method of multipliers. We prove that the se...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	54,362
2403.00621	AdaBoost-Based Efficient Channel Estimation and Data Detection in One-Bit Massive MIMO	The use of one-bit analog-to-digital converter (ADC) has been considered as a viable alternative to high resolution counterparts in realizing and commercializing massive multiple-input multiple-output (MIMO) systems. However, the issue of discarding the amplitude information by one-bit quantizers has to be compensated....	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	434,044
1811.04239	Near Real-Time Data Labeling Using a Depth Sensor for EMG Based Prosthetic Arms	Recognizing sEMG (Surface Electromyography) signals belonging to a particular action (e.g., lateral arm raise) automatically is a challenging task as EMG signals themselves have a lot of variation even for the same action due to several factors. To overcome this issue, there should be a proper separation which indicate...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	113,034
1511.03688	Online Principal Component Analysis in High Dimension: Which Algorithm to Choose?	In the current context of data explosion, online techniques that do not require storing all data in memory are indispensable to routinely perform tasks like principal component analysis (PCA). Recursive algorithms that update the PCA with each new observation have been studied in various fields of research and found wi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	48,784
2404.02624	Multi-Scale Spatial-Temporal Self-Attention Graph Convolutional Networks for Skeleton-based Action Recognition	Skeleton-based gesture recognition methods have achieved high success using Graph Convolutional Network (GCN). In addition, context-dependent adaptive topology as a neighborhood vertex information and attention mechanism leverages a model to better represent actions. In this paper, we propose self-attention GCN hybrid ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	443,942
1808.02870	Parkinson's Disease Assessment from a Wrist-Worn Wearable Sensor in Free-Living Conditions: Deep Ensemble Learning and Visualization	Parkinson's Disease (PD) is characterized by disorders in motor function such as freezing of gait, rest tremor, rigidity, and slowed and hyposcaled movements. Medication with dopaminergic medication may alleviate those motor symptoms, however, side-effects may include uncontrolled movements, known as dyskinesia. In thi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	104,843
2411.08195	An Explainable Machine Learning Approach for Age and Gender Estimation in Living Individuals Using Dental Biometrics	Objectives: Age and gender estimation is crucial for various applications, including forensic investigations and anthropological studies. This research aims to develop a predictive system for age and gender estimation in living individuals, leveraging dental measurements such as Coronal Height (CH), Coronal Pulp Cavity...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	507,800

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