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
2206.04246	SwinCheX: Multi-label classification on chest X-ray images with transformers	According to the considerable growth in the avail of chest X-ray images in diagnosing various diseases, as well as gathering extensive datasets, having an automated diagnosis procedure using deep neural networks has occupied the minds of experts. Most of the available methods in computer vision use a CNN backbone to ac...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	301,550
2010.11339	Voronoi Convolutional Neural Networks	In this technical report, we investigate extending convolutional neural networks to the setting where functions are not sampled in a grid pattern. We show that by treating the samples as the average of a function within a cell, we can find a natural equivalent of most layers used in CNN. We also present an algorithm fo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	202,205
2307.14098	Distributed robust secondary frequency control of inverter-based microgrids under time-varying communication delays	This paper presents a robust secondary control strategy for frequency synchronization and active power sharing for inverter-based microgrids. The problem is addressed in a multi-agent fashion where the local controllers of the distributed generators play the role of agents, and communication is affected by time-varying...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	381,813
1802.07814	Learning to Explain: An Information-Theoretic Perspective on Model Interpretation	We introduce instancewise feature selection as a methodology for model interpretation. Our method is based on learning a function to extract a subset of features that are most informative for each given example. This feature selector is trained to maximize the mutual information between selected features and the respon...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	90,963
2410.20905	Less is More: Efficient Time Series Dataset Condensation via Two-fold Modal Matching--Extended Version	The expanding instrumentation of processes throughout society with sensors yields a proliferation of time series data that may in turn enable important applications, e.g., related to transportation infrastructures or power grids. Machine-learning based methods are increasingly being used to extract value from such data...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	503,012
1905.03330	Universal Sound Separation	Recent deep learning approaches have achieved impressive performance on speech enhancement and separation tasks. However, these approaches have not been investigated for separating mixtures of arbitrary sounds of different types, a task we refer to as universal sound separation, and it is unknown how performance on spe...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	130,175
2408.13719	Count-based Novelty Exploration in Classical Planning	Count-based exploration methods are widely employed to improve the exploratory behavior of learning agents over sequential decision problems. Meanwhile, Novelty search has achieved success in Classical Planning through recording of the first, but not successive, occurrences of tuples. In order to structure the explorat...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	483,261
2108.01634	Triggering Failures: Out-Of-Distribution detection by learning from local adversarial attacks in Semantic Segmentation	In this paper, we tackle the detection of out-of-distribution (OOD) objects in semantic segmentation. By analyzing the literature, we found that current methods are either accurate or fast but not both which limits their usability in real world applications. To get the best of both aspects, we propose to mitigate the c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	249,088
1604.00253	Integrated Control/Structure Design of a Large Space Structure using Structured $\mathcal{H}_\infty$ Control	This study presents the integrated control/structure design of a Large Flexible Structure, the Extra Long Mast Observatory (ELMO). The integrated design is performed using structured $\mathcal{H}_\infty$ control tools, developing the Two-Input Two-Output Port (TITOP) model of the flexible multi-body structure and impos...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	53,998
1608.05151	Effective Multi-step Temporal-Difference Learning for Non-Linear Function Approximation	Multi-step temporal-difference (TD) learning, where the update targets contain information from multiple time steps ahead, is one of the most popular forms of TD learning for linear function approximation. The reason is that multi-step methods often yield substantially better performance than their single-step counter-...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	59,935
1907.13242	Joint Group Feature Selection and Discriminative Filter Learning for Robust Visual Object Tracking	We propose a new Group Feature Selection method for Discriminative Correlation Filters (GFS-DCF) based visual object tracking. The key innovation of the proposed method is to perform group feature selection across both channel and spatial dimensions, thus to pinpoint the structural relevance of multi-channel features t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	140,320
2103.14229	Thermal Fault Detection and Localization Framework for Large Format Batteries	Safety against thermal failures is crucial in battery systems. Real-time thermal diagnostics can be a key enabler of such safer batteries. Thermal fault diagnostics in large format pouch or prismatic cells pose additional challenges compared to cylindrical cells. These challenges arise from the fact that the temperatur...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	226,776
2211.11836	Towards Live 3D Reconstruction from Wearable Video: An Evaluation of V-SLAM, NeRF, and Videogrammetry Techniques	Mixed reality (MR) is a key technology which promises to change the future of warfare. An MR hybrid of physical outdoor environments and virtual military training will enable engagements with long distance enemies, both real and simulated. To enable this technology, a large-scale 3D model of a physical environment must...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	331,890
1409.4018	EquiNMF: Graph Regularized Multiview Nonnegative Matrix Factorization	Nonnegative matrix factorization (NMF) methods have proved to be powerful across a wide range of real-world clustering applications. Integrating multiple types of measurements for the same objects/subjects allows us to gain a deeper understanding of the data and refine the clustering. We have developed a novel Graph-re...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	36,033
2102.04132	Near-optimal Representation Learning for Linear Bandits and Linear RL	This paper studies representation learning for multi-task linear bandits and multi-task episodic RL with linear value function approximation. We first consider the setting where we play $M$ linear bandits with dimension $d$ concurrently, and these bandits share a common $k$-dimensional linear representation so that $k\...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	219,000
2205.12857	Structure Unbiased Adversarial Model for Medical Image Segmentation	Generative models have been widely proposed in image recognition to generate more images where the distribution is similar to that of the real ones. It often introduces a discriminator network to differentiate the real data from the generated ones. Such models utilise a discriminator network tasked with differentiating...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	298,727
1904.03371	Evaluating Coherence in Dialogue Systems using Entailment	Evaluating open-domain dialogue systems is difficult due to the diversity of possible correct answers. Automatic metrics such as BLEU correlate weakly with human annotations, resulting in a significant bias across different models and datasets. Some researchers resort to human judgment experimentation for assessing res...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	126,694
1811.02394	DeepChannel: Salience Estimation by Contrastive Learning for Extractive Document Summarization	We propose DeepChannel, a robust, data-efficient, and interpretable neural model for extractive document summarization. Given any document-summary pair, we estimate a salience score, which is modeled using an attention-based deep neural network, to represent the salience degree of the summary for yielding the document....	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	112,582
2301.12271	Bilateral Peer-to-Peer Energy Trading via Coalitional Games	In this paper, we propose a bilateral peer-to-peer (P2P) energy trading scheme under single-contract and multi-contract market setups, both as an assignment game, and a special class of coalitional games. {The proposed market formulation allows for efficient computation of a market equilibrium while keeping the desired...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	342,467
2207.10960	Principal Geodesic Analysis of Merge Trees (and Persistence Diagrams)	This paper presents a computational framework for the Principal Geodesic Analysis of merge trees (MT-PGA), a novel adaptation of the celebrated Principal Component Analysis (PCA) framework [87] to the Wasserstein metric space of merge trees [92]. We formulate MT-PGA computation as a constrained optimization problem, ai...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	309,460
2302.00808	ACPO: A Policy Optimization Algorithm for Average MDPs with Constraints	Reinforcement Learning (RL) for constrained MDPs (CMDPs) is an increasingly important problem for various applications. Often, the average criterion is more suitable than the discounted criterion. Yet, RL for average-CMDPs (ACMDPs) remains a challenging problem. Algorithms designed for discounted constrained RL problem...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	343,351
2402.17878	End-User Development for Human-Robot Interaction	End-user development (EUD) represents a key step towards making robotics accessible for experts and nonexperts alike. Within academia, researchers investigate novel ways that EUD tools can capture, represent, visualize, analyze, and test developer intent. At the same time, industry researchers increasingly build and sh...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	433,176
2310.20052	Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental Learning	Continual learning aims to create artificial neural networks capable of accumulating knowledge and skills through incremental training on a sequence of tasks. The main challenge of continual learning is catastrophic interference, wherein new knowledge overrides or interferes with past knowledge, leading to forgetting. ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	404,229
2406.05232	DALD: Improving Logits-based Detector without Logits from Black-box LLMs	The advent of Large Language Models (LLMs) has revolutionized text generation, producing outputs that closely mimic human writing. This blurring of lines between machine- and human-written text presents new challenges in distinguishing one from the other a task further complicated by the frequent updates and closed nat...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	462,038
2412.09058	EmbedGenius: Towards Automated Software Development for Generic Embedded IoT Systems	Embedded IoT system development is crucial for enabling seamless connectivity and functionality across a wide range of applications. However, such a complex process requires cross-domain knowledge of hardware and software and hence often necessitates direct developer involvement, making it labor-intensive, time-consumi...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	true	516,346
2405.06911	Replication Study and Benchmarking of Real-Time Object Detection Models	This work examines the reproducibility and benchmarking of state-of-the-art real-time object detection models. As object detection models are often used in real-world contexts, such as robotics, where inference time is paramount, simply measuring models' accuracy is not enough to compare them. We thus compare a large v...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	453,499
1906.08989	Data-Efficient Learning for Sim-to-Real Robotic Grasping using Deep Point Cloud Prediction Networks	Training a deep network policy for robot manipulation is notoriously costly and time consuming as it depends on collecting a significant amount of real world data. To work well in the real world, the policy needs to see many instances of the task, including various object arrangements in the scene as well as variations...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	136,038
1510.05811	Bregman storage functions for microgrid control	In this paper we contribute a theoretical framework that sheds a new light on the problem of microgrid analysis and control. The starting point is an energy function comprising the kinetic energy associated with the elements that emulate the rotating machinery and terms taking into account the reactive power stored in ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	48,053
2411.03888	Multi3Hate: Multimodal, Multilingual, and Multicultural Hate Speech Detection with Vision-Language Models	Warning: this paper contains content that may be offensive or upsetting Hate speech moderation on global platforms poses unique challenges due to the multimodal and multilingual nature of content, along with the varying cultural perceptions. How well do current vision-language models (VLMs) navigate these nuances? To...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	506,078
2406.01959	Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions	This paper explores adaptive variance reduction methods for stochastic optimization based on the STORM technique. Existing adaptive extensions of STORM rely on strong assumptions like bounded gradients and bounded function values, or suffer an additional $\mathcal{O}(\log T)$ term in the convergence rate. To address th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	460,546
2305.00304	A preferential interpretation of MultiLayer Perceptrons in a conditional logic with typicality	In this paper we investigate the relationships between a multipreferential semantics for defeasible reasoning in knowledge representation and a multilayer neural network model. Weighted knowledge bases for a simple description logic with typicality are considered under a (many-valued) ``concept-wise" multipreference se...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	true	361,290
1906.06593	Context is Key: Grammatical Error Detection with Contextual Word Representations	Grammatical error detection (GED) in non-native writing requires systems to identify a wide range of errors in text written by language learners. Error detection as a purely supervised task can be challenging, as GED datasets are limited in size and the label distributions are highly imbalanced. Contextualized word rep...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	135,348
2305.17102	GeoVLN: Learning Geometry-Enhanced Visual Representation with Slot Attention for Vision-and-Language Navigation	Most existing works solving Room-to-Room VLN problem only utilize RGB images and do not consider local context around candidate views, which lack sufficient visual cues about surrounding environment. Moreover, natural language contains complex semantic information thus its correlations with visual inputs are hard to mo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	368,412
1811.10980	Noise2Void - Learning Denoising from Single Noisy Images	The field of image denoising is currently dominated by discriminative deep learning methods that are trained on pairs of noisy input and clean target images. Recently it has been shown that such methods can also be trained without clean targets. Instead, independent pairs of noisy images can be used, in an approach kno...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	114,648
1608.07046	Transient performance analysis of zero-attracting LMS	Zero-attracting least-mean-square (ZA-LMS) algorithm has been widely used for online sparse system identification. It combines the LMS framework and $\ell_1$-norm regularization to promote sparsity, and relies on subgradient iterations. Despite the significant interest in ZA-LMS, few works analyzed its transient behavi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	60,189
1408.0102	Randomized Memetic Artificial Bee Colony Algorithm	Artificial Bee Colony (ABC) optimization algorithm is one of the recent population based probabilistic approach developed for global optimization. ABC is simple and has been showed significant improvement over other Nature Inspired Algorithms (NIAs) when tested over some standard benchmark functions and for some comple...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	35,060
1901.05219	Sentence transition matrix: An efficient approach that preserves sentence semantics	Sentence embedding is a significant research topic in the field of natural language processing (NLP). Generating sentence embedding vectors reflecting the intrinsic meaning of a sentence is a key factor to achieve an enhanced performance in various NLP tasks such as sentence classification and document summarization. T...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	118,750
1905.02479	P2SGrad: Refined Gradients for Optimizing Deep Face Models	Cosine-based softmax losses significantly improve the performance of deep face recognition networks. However, these losses always include sensitive hyper-parameters which can make training process unstable, and it is very tricky to set suitable hyper parameters for a specific dataset. This paper addresses this challeng...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	129,982
2212.09108	A Permutation-Free Kernel Independence Test	In nonparametric independence testing, we observe i.i.d.\ data $\{(X_i,Y_i)\}_{i=1}^n$, where $X \in \mathcal{X}, Y \in \mathcal{Y}$ lie in any general spaces, and we wish to test the null that $X$ is independent of $Y$. Modern test statistics such as the kernel Hilbert-Schmidt Independence Criterion (HSIC) and Distanc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	337,006
2202.04849	SAFER: Data-Efficient and Safe Reinforcement Learning via Skill Acquisition	Methods that extract policy primitives from offline demonstrations using deep generative models have shown promise at accelerating reinforcement learning(RL) for new tasks. Intuitively, these methods should also help to trainsafeRLagents because they enforce useful skills. However, we identify these techniques are not ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	279,693
2105.13659	Deception Detection in Videos using the Facial Action Coding System	Facts are important in decision making in every situation, which is why it is important to catch deceptive information before they are accepted as facts. Deception detection in videos has gained traction in recent times for its various real-life application. In our approach, we extract facial action units using the fac...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	237,371
1008.5163	Learning Multi-modal Similarity	In many applications involving multi-media data, the definition of similarity between items is integral to several key tasks, e.g., nearest-neighbor retrieval, classification, and recommendation. Data in such regimes typically exhibits multiple modalities, such as acoustic and visual content of video. Integrating such ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	7,410
1801.09546	21 Million Opportunities: A 19 Facility Investigation of Factors Affecting Hand Hygiene Compliance via Linear Predictive Models	This large-scale study, consisting of 21.3 million hand hygiene opportunities from 19 distinct facilities in 10 different states, uses linear predictive models to expose factors that may affect hand hygiene compliance. We examine the use of features such as temperature, relative humidity, influenza severity, day/night ...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	89,135
2111.08478	Spatial machine-learning model diagnostics: a model-agnostic distance-based approach	While significant progress has been made towards explaining black-box machine-learning (ML) models, there is still a distinct lack of diagnostic tools that elucidate the spatial behaviour of ML models in terms of predictive skill and variable importance. This contribution proposes spatial prediction error profiles (SPE...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	266,707
2003.06665	Complementarity in Complex Networks	In many networks, including networks of protein-protein interactions, interdisciplinary collaboration networks, and semantic networks, connections are established between nodes with complementary rather than similar properties. While complementarity is abundant in networks, we lack mathematical intuition and quantitati...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	168,188
2302.03248	Disentangled Causal Embedding With Contrastive Learning For Recommender System	Recommender systems usually rely on observed user interaction data to build personalized recommendation models, assuming that the observed data reflect user interest. However, user interacting with an item may also due to conformity, the need to follow popular items. Most previous studies neglect user's conformity and ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	344,275
2207.03072	Deep energy method in topology optimization applications	This paper explores the possibilities of applying physics-informed neural networks (PINNs) in topology optimization (TO) by introducing a fully self-supervised TO framework that is based on PINNs. This framework solves the forward elasticity problem by the deep energy method (DEM). Instead of training a separate neural...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	306,716
1809.08935	Lexical Bias In Essay Level Prediction	Automatically predicting the level of non-native English speakers given their written essays is an interesting machine learning problem. In this work I present the system "balikasg" that achieved the state-of-the-art performance in the CAp 2018 data science challenge among 14 systems. I detail the feature extraction, f...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	108,625
2405.06729	Fine-tuning Protein Language Models with Deep Mutational Scanning improves Variant Effect Prediction	Protein Language Models (PLMs) have emerged as performant and scalable tools for predicting the functional impact and clinical significance of protein-coding variants, but they still lag experimental accuracy. Here, we present a novel fine-tuning approach to improve the performance of PLMs with experimental maps of var...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	453,432
2408.04015	Image-to-LaTeX Converter for Mathematical Formulas and Text	In this project, we train a vision encoder-decoder model to generate LaTeX code from images of mathematical formulas and text. Utilizing a diverse collection of image-to-LaTeX data, we build two models: a base model with a Swin Transformer encoder and a GPT-2 decoder, trained on machine-generated images, and a fine-tun...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	479,219
2307.01381	Implicit Memory Transformer for Computationally Efficient Simultaneous Speech Translation	Simultaneous speech translation is an essential communication task difficult for humans whereby a translation is generated concurrently with oncoming speech inputs. For such a streaming task, transformers using block processing to break an input sequence into segments have achieved state-of-the-art performance at a red...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	377,326
2310.03165	Enhancing Accuracy in Deep Learning Using Random Matrix Theory	We explore the applications of random matrix theory (RMT) in the training of deep neural networks (DNNs), focusing on layer pruning that is reducing the number of DNN parameters (weights). Our numerical results show that this pruning leads to a drastic reduction of parameters while not reducing the accuracy of DNNs and...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	397,161
2006.06915	How Many Samples is a Good Initial Point Worth in Low-rank Matrix Recovery?	Given a sufficiently large amount of labeled data, the non-convex low-rank matrix recovery problem contains no spurious local minima, so a local optimization algorithm is guaranteed to converge to a global minimum starting from any initial guess. However, the actual amount of data needed by this theoretical guarantee i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,610
1603.00544	On the capacity of information processing systems	We propose and analyze a family of information processing systems, where a finite set of experts or servers are employed to extract information about a stream of incoming jobs. Each job is associated with a hidden label drawn from some prior distribution. An inspection by an expert produces a noisy outcome that depends...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	52,783
2410.01608	Computational Teaching for Driving via Multi-Task Imitation Learning	Learning motor skills for sports or performance driving is often done with professional instruction from expert human teachers, whose availability is limited. Our goal is to enable automated teaching via a learned model that interacts with the student similar to a human teacher. However, training such automated teachin...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	493,847
2406.17818	Temporal Prototype-Aware Learning for Active Voltage Control on Power Distribution Networks	Active Voltage Control (AVC) on the Power Distribution Networks (PDNs) aims to stabilize the voltage levels to ensure efficient and reliable operation of power systems. With the increasing integration of distributed energy resources, recent efforts have explored employing multi-agent reinforcement learning (MARL) techn...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	467,748
2007.04833	Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach	Recommendation models can effectively estimate underlying user interests and predict one's future behaviors by factorizing an observed user-item rating matrix into products of two sets of latent factors. However, the user-specific embedding factors can only be learned in a transductive way, making it difficult to handl...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	186,487
2401.16209	MultiMUC: Multilingual Template Filling on MUC-4	We introduce MultiMUC, the first multilingual parallel corpus for template filling, comprising translations of the classic MUC-4 template filling benchmark into five languages: Arabic, Chinese, Farsi, Korean, and Russian. We obtain automatic translations from a strong multilingual machine translation system and manuall...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	424,737
0905.2924	Colorization of Natural Images via L1 Optimization	Natural images in the colour space YUV have been observed to have a non-Gaussian, heavy tailed distribution (called 'sparse') when the filter G(U)(r) = U(r) - sum_{s \in N(r)} w{(Y)_{rs}} U(s), is applied to the chromacity channel U (and equivalently to V), where w is a weighting function constructed from the intensity...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	3,717
2004.11234	Memory and forecasting capacities of nonlinear recurrent networks	The notion of memory capacity, originally introduced for echo state and linear networks with independent inputs, is generalized to nonlinear recurrent networks with stationary but dependent inputs. The presence of dependence in the inputs makes natural the introduction of the network forecasting capacity, that measures...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	173,857
cs/0412076	Clustering Techniques for Marbles Classification	Automatic marbles classification based on their visual appearance is an important industrial issue. However, there is no definitive solution to the problem mainly due to the presence of randomly distributed high number of different colours and its subjective evaluation by the human expert. In this paper we present a st...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	538,452
2307.02574	Semi-supervised Learning from Street-View Images and OpenStreetMap for Automatic Building Height Estimation	Accurate building height estimation is key to the automatic derivation of 3D city models from emerging big geospatial data, including Volunteered Geographical Information (VGI). However, an automatic solution for large-scale building height estimation based on low-cost VGI data is currently missing. The fast developmen...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	377,734
2405.00025	Leveraging Pre-trained CNNs for Efficient Feature Extraction in Rice Leaf Disease Classification	Rice disease classification is a critical task in agricultural research, and in this study, we rigorously evaluate the impact of integrating feature extraction methodologies within pre-trained convolutional neural networks (CNNs). Initial investigations into baseline models, devoid of feature extraction, revealed comme...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	450,774
2302.09243	A Federated Approach for Hate Speech Detection	Hate speech detection has been the subject of high research attention, due to the scale of content created on social media. In spite of the attention and the sensitive nature of the task, privacy preservation in hate speech detection has remained under-studied. The majority of research has focused on centralised machin...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	346,338
2205.14393	Relation-Specific Attentions over Entity Mentions for Enhanced Document-Level Relation Extraction	Compared with traditional sentence-level relation extraction, document-level relation extraction is a more challenging task where an entity in a document may be mentioned multiple times and associated with multiple relations. However, most methods of document-level relation extraction do not distinguish between mention...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	299,346
2303.02503	Zero-Effort Two-Factor Authentication Using Wi-Fi Radio Wave Transmission and Machine Learning	The proliferation of sensitive information being stored online highlights the pressing need for secure and efficient user authentication methods. To address this issue, this paper presents a novel zero-effort two-factor authentication (2FA) approach that combines the unique characteristics of a users environment and Ma...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	349,384
2106.02420	An Intelligent Resource Reservation for Crowdsourced Live Video Streaming Applications in Geo-Distributed Cloud Environment	Crowdsourced live video streaming (livecast) services such as Facebook Live, YouNow, Douyu and Twitch are gaining more momentum recently. Allocating the limited resources in a cost-effective manner while maximizing the Quality of Service (QoS) through real-time delivery and the provision of the appropriate representati...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	238,869
1907.01860	Encoding high-cardinality string categorical variables	Statistical models usually require vector representations of categorical variables, using for instance one-hot encoding. This strategy breaks down when the number of categories grows, as it creates high-dimensional feature vectors. Additionally, for string entries, one-hot encoding does not capture information in their...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	137,458
2005.11706	A Novel Distributed Representation of News (DRNews) for Stock Market Predictions	In this study, a novel Distributed Representation of News (DRNews) model is developed and applied in deep learning-based stock market predictions. With the merit of integrating contextual information and cross-documental knowledge, the DRNews model creates news vectors that describe both the semantic information and po...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	178,546
1605.06047	AMSOM: Adaptive Moving Self-organizing Map for Clustering and Visualization	Self-Organizing Map (SOM) is a neural network model which is used to obtain a topology-preserving mapping from the (usually high dimensional) input/feature space to an output/map space of fewer dimensions (usually two or three in order to facilitate visualization). Neurons in the output space are connected with each ot...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	56,076
1904.01882	Learning Nash Equilibria in Monotone Games	We consider multi-agent decision making where each agent's cost function depends on all agents' strategies. We propose a distributed algorithm to learn a Nash equilibrium, whereby each agent uses only obtained values of her cost function at each joint played action, lacking any information of the functional form of her...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	126,274
2102.13326	Zero-Shot Learning Based on Knowledge Sharing	Zero-Shot Learning (ZSL) is an emerging research that aims to solve the classification problems with very few training data. The present works on ZSL mainly focus on the mapping of learning semantic space to visual space. It encounters many challenges that obstruct the progress of ZSL research. First, the representatio...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	222,025
1911.01156	AAAI FSS-19: Artificial Intelligence in Government and Public Sector Proceedings	Proceedings of the AAAI Fall Symposium on Artificial Intelligence in Government and Public Sector, Arlington, Virginia, USA, November 7-8, 2019	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	152,028
2202.02550	Intelligent Reflecting Surface-Aided Spectrum Sensing for Cognitive Radio	Spectrum sensing is a key enabling technique for cognitive radio (CR), which provides essential information on the spectrum availability. However, due to severe wireless channel fading and path loss, the primary user (PU) signals received at the CR or secondary user (SU) can be practically too weak for reliable detecti...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	278,857
2305.04792	Global Update Tracking: A Decentralized Learning Algorithm for Heterogeneous Data	Decentralized learning enables the training of deep learning models over large distributed datasets generated at different locations, without the need for a central server. However, in practical scenarios, the data distribution across these devices can be significantly different, leading to a degradation in model perfo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	362,903
1710.02866	On Matching Skulls to Digital Face Images: A Preliminary Approach	Forensic application of automatically matching skull with face images is an important research area linking biometrics with practical applications in forensics. It is an opportunity for biometrics and face recognition researchers to help the law enforcement and forensic experts in giving an identity to unidentified hum...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	82,245
2312.15490	Diffusion-EXR: Controllable Review Generation for Explainable Recommendation via Diffusion Models	Denoising Diffusion Probabilistic Model (DDPM) has shown great competence in image and audio generation tasks. However, there exist few attempts to employ DDPM in the text generation, especially review generation under recommendation systems. Fueled by the predicted reviews explainability that justifies recommendations...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	418,027
2303.08120	Blind Video Deflickering by Neural Filtering with a Flawed Atlas	Many videos contain flickering artifacts. Common causes of flicker include video processing algorithms, video generation algorithms, and capturing videos under specific situations. Prior work usually requires specific guidance such as the flickering frequency, manual annotations, or extra consistent videos to remove th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	351,517
2104.05459	Developing Annotated Resources for Internal Displacement Monitoring	This paper describes in details the design and development of a novel annotation framework and of annotated resources for Internal Displacement, as the outcome of a collaboration with the Internal Displacement Monitoring Centre, aimed at improving the accuracy of their monitoring platform IDETECT. The schema includes m...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	229,737
2403.14938	On Zero-Shot Counterspeech Generation by LLMs	With the emergence of numerous Large Language Models (LLM), the usage of such models in various Natural Language Processing (NLP) applications is increasing extensively. Counterspeech generation is one such key task where efforts are made to develop generative models by fine-tuning LLMs with hatespeech - counterspeech ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	440,315
2105.02626	A First Look: Towards Explainable TextVQA Models via Visual and Textual Explanations	Explainable deep learning models are advantageous in many situations. Prior work mostly provide unimodal explanations through post-hoc approaches not part of the original system design. Explanation mechanisms also ignore useful textual information present in images. In this paper, we propose MTXNet, an end-to-end train...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	233,875
1910.13472	Locally recoverable codes on surfaces	A linear error correcting code is a subspace of a finite-dimensional space over a finite field with a fixed coordinate system. Such a code is said to be locally recoverable with locality $r$ if, for every coordinate, its value at a codeword can be deduced from the value of (certain) $r$ other coordinates of the codewor...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	151,398
2411.15839	VaLiD: Mitigating the Hallucination of Large Vision Language Models by Visual Layer Fusion Contrastive Decoding	Large Vision-Language Models (LVLMs) have demonstrated outstanding performance in multimodal task reasoning. However, they often generate responses that appear plausible yet do not accurately reflect the visual content, a phenomenon known as hallucination. Recent approaches have introduced training-free methods that mi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	510,796
2301.03368	DRL-GAN: A Hybrid Approach for Binary and Multiclass Network Intrusion Detection	Our increasingly connected world continues to face an ever-growing amount of network-based attacks. Intrusion detection systems (IDS) are an essential security technology for detecting these attacks. Although numerous machine learning-based IDS have been proposed for the detection of malicious network traffic, the majo...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	true	339,778
2310.03273	Ablation Study to Clarify the Mechanism of Object Segmentation in Multi-Object Representation Learning	Multi-object representation learning aims to represent complex real-world visual input using the composition of multiple objects. Representation learning methods have often used unsupervised learning to segment an input image into individual objects and encode these objects into each latent vector. However, it is not c...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	397,209
1910.05253	Adversarial Colorization Of Icons Based On Structure And Color Conditions	We present a system to help designers create icons that are widely used in banners, signboards, billboards, homepages, and mobile apps. Designers are tasked with drawing contours, whereas our system colorizes contours in different styles. This goal is achieved by training a dual conditional generative adversarial netwo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	149,002
1905.13340	Log-logarithmic Time Pruned Polar Coding	A pruned variant of polar coding is proposed for binary erasure channels. For sufficiently small $\varepsilon>0$, we construct a series of capacity achieving codes with block length $N=\varepsilon^{-5}$, code rate $R=\text{Capacity}-\varepsilon$, error probability $P=\varepsilon$, and encoding and decoding time complex...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	133,082
2004.14176	Development of a General Purpose Sentiment Lexicon for Igbo Language	There are publicly available general purpose sentiment lexicons in some high resource languages but very few exist in the low resource languages. This makes it difficult to directly perform sentiment analysis tasks in such languages. The objective of this work is to create a general purpose sentiment lexicon for the Ig...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	174,801
2405.04252	VAEneu: A New Avenue for VAE Application on Probabilistic Forecasting	This paper presents VAEneu, an innovative autoregressive method for multistep ahead univariate probabilistic time series forecasting. We employ the conditional VAE framework and optimize the lower bound of the predictive distribution likelihood function by adopting the Continuous Ranked Probability Score (CRPS), a stri...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	452,500
2306.04384	Multilingual Clinical NER: Translation or Cross-lingual Transfer?	Natural language tasks like Named Entity Recognition (NER) in the clinical domain on non-English texts can be very time-consuming and expensive due to the lack of annotated data. Cross-lingual transfer (CLT) is a way to circumvent this issue thanks to the ability of multilingual large language models to be fine-tuned o...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	371,725
1809.03751	Joint Spatial Division and Diversity for Massive MIMO Systems	We propose a downlink beamforming scheme that combines spatial division and orthogonal space-time block coding (OSTBC) in multi-user massive MIMO systems. The beamformer is divided into two parts: a pre-beamforming matrix to separate the users into different beams with no interference between each other, which is desig...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	107,400
2502.07734	EdgeEar: Efficient and Accurate Ear Recognition for Edge Devices	Ear recognition is a contactless and unobtrusive biometric technique with applications across various domains. However, deploying high-performing ear recognition models on resource-constrained devices is challenging, limiting their applicability and widespread adoption. This paper introduces EdgeEar, a lightweight mode...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	532,728
2210.01433	Learning to Estimate 3-D States of Deformable Linear Objects from Single-Frame Occluded Point Clouds	Accurately and robustly estimating the state of deformable linear objects (DLOs), such as ropes and wires, is crucial for DLO manipulation and other applications. However, it remains a challenging open issue due to the high dimensionality of the state space, frequent occlusions, and noises. This paper focuses on learni...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	321,262
2309.12938	Frustrated with Code Quality Issues? LLMs can Help!	As software projects progress, quality of code assumes paramount importance as it affects reliability, maintainability and security of software. For this reason, static analysis tools are used in developer workflows to flag code quality issues. However, developers need to spend extra efforts to revise their code to imp...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	393,981
2408.14823	LapisGS: Layered Progressive 3D Gaussian Splatting for Adaptive Streaming	The rise of Extended Reality (XR) requires efficient streaming of 3D online worlds, challenging current 3DGS representations to adapt to bandwidth-constrained environments. This paper proposes LapisGS, a layered 3DGS that supports adaptive streaming and progressive rendering. Our method constructs a layered structure f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	483,690
2108.06430	Hybrid Gaussian Process Modeling Applied to Economic Stochastic Model Predictive Control of Batch Processes	Nonlinear model predictive control (NMPC) is an efficient approach for the control of nonlinear multivariable dynamic systems with constraints, which however requires an accurate plant model. Plant models can often be determined from first principles, parts of the model are however difficult to derive using physical la...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	250,593
2501.07763	On the Statistical Capacity of Deep Generative Models	Deep generative models are routinely used in generating samples from complex, high-dimensional distributions. Despite their apparent successes, their statistical properties are not well understood. A common assumption is that with enough training data and sufficiently large neural networks, deep generative model sample...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	524,501
2109.08970	Temporal Knowledge Graph Completion using Box Embeddings	Knowledge graph completion is the task of inferring missing facts based on existing data in a knowledge graph. Temporal knowledge graph completion (TKGC) is an extension of this task to temporal knowledge graphs, where each fact is additionally associated with a time stamp. Current approaches for TKGC primarily build o...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	256,099
2406.02795	ArguMentor: Augmenting User Experiences with Counter-Perspectives	We encounter arguments everyday in the form of social media posts, presidential debates, news articles, and even advertisements. A ubiquitous, influential example is the opinion piece (op-ed). Opinion pieces can provide valuable perspectives, but they often represent only one side of a story, which can make readers sus...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	460,941
2406.11247	STEVE Series: Step-by-Step Construction of Agent Systems in Minecraft	Building an embodied agent system with a large language model (LLM) as its core is a promising direction. Due to the significant costs and uncontrollable factors associated with deploying and training such agents in the real world, we have decided to begin our exploration within the Minecraft environment. Our STEVE Ser...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	464,792

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.