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
1501.01697	Super-resolution MRI Using Finite Rate of Innovation Curves	We propose a two-stage algorithm for the super-resolution of MR images from their low-frequency k-space samples. In the first stage we estimate a resolution-independent mask whose zeros represent the edges of the image. This builds off recent work extending the theory of sampling signals of finite rate of innovation (F...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	39,109
1412.2226	Possible and Necessary Allocations via Sequential Mechanisms	A simple mechanism for allocating indivisible resources is sequential allocation in which agents take turns to pick items. We focus on possible and necessary allocation problems, checking whether allocations of a given form occur in some or all mechanisms for several commonly used classes of sequential allocation mecha...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	38,182
2207.12460	A comprehensive and biophysically detailed computational model of the whole human heart electromechanics	While ventricular electromechanics is extensively studied, four-chamber heart models have only been addressed recently; most of these works however neglect atrial contraction. Indeed, as atria are characterized by a complex physiology influenced by the ventricular function, developing computational models able to captu...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	310,009
2207.04003	No Time Like the Present: Effects of Language Change on Automated Comment Moderation	The spread of online hate has become a significant problem for newspapers that host comment sections. As a result, there is growing interest in using machine learning and natural language processing for (semi-) automated abusive language detection to avoid manual comment moderation costs or having to shut down comment ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	307,043
1406.6962	How good are detection proposals, really?	Current top performing Pascal VOC object detectors employ detection proposals to guide the search for objects thereby avoiding exhaustive sliding window search across images. Despite the popularity of detection proposals, it is unclear which trade-offs are made when using them during object detection. We provide an in ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	34,173
1806.00880	Disconnected Manifold Learning for Generative Adversarial Networks	Natural images may lie on a union of disjoint manifolds rather than one globally connected manifold, and this can cause several difficulties for the training of common Generative Adversarial Networks (GANs). In this work, we first show that single generator GANs are unable to correctly model a distribution supported on...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	99,421
1203.0197	Statistical Approach for Selecting Elite Ants	Applications of ACO algorithms to obtain better solutions for combinatorial optimization problems have become very popular in recent years. In ACO algorithms, group of agents repeatedly perform well defined actions and collaborate with other ants in order to accomplish the defined task. In this paper, we introduce new ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	14,679
2403.18920	CPR: Retrieval Augmented Generation for Copyright Protection	Retrieval Augmented Generation (RAG) is emerging as a flexible and robust technique to adapt models to private users data without training, to handle credit attribution, and to allow efficient machine unlearning at scale. However, RAG techniques for image generation may lead to parts of the retrieved samples being copi...	false	false	false	false	true	false	false	false	false	false	false	true	true	false	false	false	false	false	442,126
2312.15824	Self-Supervised Learning for Few-Shot Bird Sound Classification	Self-supervised learning (SSL) in audio holds significant potential across various domains, particularly in situations where abundant, unlabeled data is readily available at no cost. This is pertinent in bioacoustics, where biologists routinely collect extensive sound datasets from the natural environment. In this stud...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	418,144
2407.01789	Optimal Sample Lens Positioning in Digital Camera Systems	In contemporary imaging systems, achieving optimal auto-focus (AF) performance hinges on precise lens positioning. Extensive research has delved into refining algorithms for determining the ideal lens position across passive, active, and hybrid autofocus systems. This paper explores the mathematical intricacies and pra...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	469,448
1705.04272	Improved underwater image enhancement algorithms based on partial differential equations (PDEs)	The experimental results of improved underwater image enhancement algorithms based on partial differential equations (PDEs) are presented in this report. This second work extends the study of previous work and incorporating several improvements into the revised algorithm. Experiments show the evidence of the improvemen...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	73,301
2211.09120	AdaMAE: Adaptive Masking for Efficient Spatiotemporal Learning with Masked Autoencoders	Masked Autoencoders (MAEs) learn generalizable representations for image, text, audio, video, etc., by reconstructing masked input data from tokens of the visible data. Current MAE approaches for videos rely on random patch, tube, or frame-based masking strategies to select these tokens. This paper proposes AdaMAE, an ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	330,884
2303.11654	Mitigating climate and health impact of small-scale kiln industry using multi-spectral classifier and deep learning	Industrial air pollution has a direct health impact and is a major contributor to climate change. Small scale industries particularly bull-trench brick kilns are one of the key sources of air pollution in South Asia often creating hazardous levels of smog that is injurious to human health. To mitigate the climate and h...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	352,946
1706.09239	Scattered EXIT Charts for Finite Length LDPC Code Design	We introduce the Scattered Extrinsic Information Transfer (S-EXIT) chart as a tool for optimizing degree profiles of short length Low-Density Parity-Check (LDPC) codes under iterative decoding. As degree profile optimization is typically done in the asymptotic length regime, there is space for further improvement when ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	76,105
1804.11283	Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive Strategies	We present NEWSROOM, a summarization dataset of 1.3 million articles and summaries written by authors and editors in newsrooms of 38 major news publications. Extracted from search and social media metadata between 1998 and 2017, these high-quality summaries demonstrate high diversity of summarization styles. In particu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	96,338
2101.06092	Black-box Adversarial Attacks in Autonomous Vehicle Technology	Despite the high quality performance of the deep neural network in real-world applications, they are susceptible to minor perturbations of adversarial attacks. This is mostly undetectable to human vision. The impact of such attacks has become extremely detrimental in autonomous vehicles with real-time "safety" concerns...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	215,608
2105.02716	Noether's Learning Dynamics: Role of Symmetry Breaking in Neural Networks	In nature, symmetry governs regularities, while symmetry breaking brings texture. In artificial neural networks, symmetry has been a central design principle to efficiently capture regularities in the world, but the role of symmetry breaking is not well understood. Here, we develop a theoretical framework to study the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	233,901
2309.04725	EPA: Easy Prompt Augmentation on Large Language Models via Multiple Sources and Multiple Targets	Large language models (LLMs) have shown promising performance on various NLP tasks via task prompting. And their performance can be further improved by appending task demonstrations to the head of the prompt. And usually, a better performance can be achieved with more demonstrations. However, asking the users to write ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	390,826
2003.03570	CPM R-CNN: Calibrating Point-guided Misalignment in Object Detection	In object detection, offset-guided and point-guided regression dominate anchor-based and anchor-free method separately. Recently, point-guided approach is introduced to anchor-based method. However, we observe points predicted by this way are misaligned with matched region of proposals and score of localization, causin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	167,275
2002.06991	Learning Group Structure and Disentangled Representations of Dynamical Environments	Learning disentangled representations is a key step towards effectively discovering and modelling the underlying structure of environments. In the natural sciences, physics has found great success by describing the universe in terms of symmetry preserving transformations. Inspired by this formalism, we propose a framew...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	164,354
1206.3295	Refractor Importance Sampling	In this paper we introduce Refractor Importance Sampling (RIS), an improvement to reduce error variance in Bayesian network importance sampling propagation under evidential reasoning. We prove the existence of a collection of importance functions that are close to the optimal importance function under evidential reason...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	16,552
2105.03059	Self-paced Resistance Learning against Overfitting on Noisy Labels	Noisy labels composed of correct and corrupted ones are pervasive in practice. They might significantly deteriorate the performance of convolutional neural networks (CNNs), because CNNs are easily overfitted on corrupted labels. To address this issue, inspired by an observation, deep neural networks might first memoriz...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	234,024
2410.02103	MVGS: Multi-view-regulated Gaussian Splatting for Novel View Synthesis	Recent works in volume rendering, \textit{e.g.} NeRF and 3D Gaussian Splatting (3DGS), significantly advance the rendering quality and efficiency with the help of the learned implicit neural radiance field or 3D Gaussians. Rendering on top of an explicit representation, the vanilla 3DGS and its variants deliver real-ti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	494,104
1806.03809	Enhancing PHY Security of MISO NOMA SWIPT Systems With a Practical Non-Linear EH Model	Non-orthogonal multiple-access (NOMA) and simultaneous wireless information and power transfer (SWIPT) are promising techniques to improve spectral efficiency and energy efficiency. However, the security of NOMA SWIPT systems has not received much attention in the literature. In this paper, an artificial noise-aided be...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	100,091
2402.02150	Data-Driven Prediction of Seismic Intensity Distributions Featuring Hybrid Classification-Regression Models	Earthquakes are among the most immediate and deadly natural disasters that humans face. Accurately forecasting the extent of earthquake damage and assessing potential risks can be instrumental in saving numerous lives. In this study, we developed linear regression models capable of predicting seismic intensity distribu...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	426,409
1805.07883	How Many Samples are Needed to Estimate a Convolutional or Recurrent Neural Network?	It is widely believed that the practical success of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) owes to the fact that CNNs and RNNs use a more compact parametric representation than their Fully-Connected Neural Network (FNN) counterparts, and consequently require fewer training examples to...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	97,976
2211.07047	Language Model Classifier Aligns Better with Physician Word Sensitivity than XGBoost on Readmission Prediction	Traditional evaluation metrics for classification in natural language processing such as accuracy and area under the curve fail to differentiate between models with different predictive behaviors despite their similar performance metrics. We introduce sensitivity score, a metric that scrutinizes models' behaviors at th...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	330,105
2301.12456	Towards Verifying the Geometric Robustness of Large-scale Neural Networks	Deep neural networks (DNNs) are known to be vulnerable to adversarial geometric transformation. This paper aims to verify the robustness of large-scale DNNs against the combination of multiple geometric transformations with a provable guarantee. Given a set of transformations (e.g., rotation, scaling, etc.), we develop...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	342,533
2112.09061	Solving Inverse Problems with NerfGANs	We introduce a novel framework for solving inverse problems using NeRF-style generative models. We are interested in the problem of 3-D scene reconstruction given a single 2-D image and known camera parameters. We show that naively optimizing the latent space leads to artifacts and poor novel view rendering. We attribu...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	272,019
2501.14270	Max-Min Fairness for IRS-Assisted Secure Two-Way Communications	This paper investigates an intelligent reflective surface (IRS) assisted secure multi-user two-way communication system. The aim of this paper is to enhance the physical layer security by optimizing the minimum secrecy-rate among all user-pairs in the presence of a malicious user. The optimization problem is converted ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	527,049
2411.12747	A Survey of Financial AI: Architectures, Advances and Open Challenges	Financial AI empowers sophisticated approaches to financial market forecasting, portfolio optimization, and automated trading. This survey provides a systematic analysis of these developments across three primary dimensions: predictive models that capture complex market dynamics, decision-making frameworks that optimiz...	false	true	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	509,521
1304.3280	Channel Coding and Source Coding with Increased Partial Side Information	Let (S1,i, S2,i), distributed according to i.i.d p(s1, s2), i = 1, 2, . . . be a memoryless, correlated partial side information sequence. In this work we study channel coding and source coding problems where the partial side information (S1, S2) is available at the encoder and the decoder, respectively, and, additiona...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	23,848
1701.01796	Cyclotomic Construction of Strong External Difference Families in Finite Fields	Strong external difference family (SEDF) and its generalizations GSEDF, BGSEDF in a finite abelian group $G$ are combinatorial designs raised by Paterson and Stinson [7] in 2016 and have applications in communication theory to construct optimal strong algebraic manipulation detection codes. In this paper we firstly pre...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	66,451
1911.07570	Sparse Bayesian Multi-Task Learning of Time-Varying Massive MIMO Channels with Dynamic Filtering	Sparsity of channel in the next generation of wireless communication for massive multiple-input-multiple-output (MIMO) systems can be exploited to reduce the overhead in the training. The multitask (MT)-sparse Bayesian learning (SBL) is applied for learning time-varying sparse channels in the uplink for multi-user mass...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	153,897
1412.7990	Predicting User Engagement in Twitter with Collaborative Ranking	Collaborative Filtering (CF) is a core component of popular web-based services such as Amazon, YouTube, Netflix, and Twitter. Most applications use CF to recommend a small set of items to the user. For instance, YouTube presents to a user a list of top-n videos she would likely watch next based on her rating and viewin...	false	false	false	false	false	true	true	false	false	false	false	false	false	true	false	false	false	false	38,877
2308.10909	Global Warming In Ghana's Major Cities Based on Statistical Analysis of NASA's POWER Over 3-Decades	Global warming's impact on high temperatures in various parts of the world has raised concerns. This study investigates long-term temperature trends in four major Ghanaian cities representing distinct climatic zones. Using NASA's Prediction of Worldwide Energy Resource (POWER) data, statistical analyses assess local cl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	386,934
1801.08198	User Association and Resource Allocation in Unified NOMA Enabled Heterogeneous Ultra Dense Networks	Heterogeneous ultra dense networks (HUDNs) and non-orthogonal multiple access (NOMA) have been identified as two proposing techniques for the fifth generation (5G) mobile communication systems due to their great capabilities to enhance spectrum efficiency. This article investigates the application of NOMA techniques in...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	88,915
2407.18331	Using Bibliometrics to Detect Unconventional Authorship Practices and Examine Their Impact on Global Research Metrics, 2019-2023	Between 2019 and 2023, sixteen universities increased their research output by over fifteen times the global average, alongside significant changes in authorship dynamics (e.g., decreased first authorship, rise in hyperprolific authors, increased multi-affiliations, and increased authors per publication rate). Using bi...	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	true	476,321
2301.12649	Convergence of uncertainty estimates in Ensemble and Bayesian sparse model discovery	Sparse model identification enables nonlinear dynamical system discovery from data. However, the control of false discoveries for sparse model identification is challenging, especially in the low-data and high-noise limit. In this paper, we perform a theoretical study on ensemble sparse model discovery, which shows emp...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	342,625
2003.13084	Best Practices for Implementing FAIR Vocabularies and Ontologies on the Web	With the adoption of Semantic Web technologies, an increasing number of vocabularies and ontologies have been developed in different domains, ranging from Biology to Agronomy or Geosciences. However, many of these ontologies are still difficult to find, access and understand by researchers due to a lack of documentatio...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	true	170,100
2106.10217	Community Detection in Interval-Weighted Networks	In this paper we introduce and develop the concept of Interval-Weighted Networks (IWN), a novel approach in Social Network Analysis, where the edge weights are represented by closed intervals composed with precise information, comprehending intrinsic variability. We extend IWN for both Newman's modularity and modularit...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	241,943
2105.06067	Causal Intervention for Leveraging Popularity Bias in Recommendation	Recommender system usually faces popularity bias issues: from the data perspective, items exhibit uneven (long-tail) distribution on the interaction frequency; from the method perspective, collaborative filtering methods are prone to amplify the bias by over-recommending popular items. It is undoubtedly critical to con...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	235,010
1501.05693	Joint Channel Direction Information Quantization For Spatially Correlated 3D MIMO Channels	This paper proposes a codebook for jointly quantizing channel direction information (CDI) of spatially correlated three-dimensional (3D) multi-input-multi-output (MIMO) channels. To reduce the dimension for quantizing the CDI of large antenna arrays, we introduce a special structure to the codewords by using Tucker dec...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,513
2207.11111	Fast strategies for multi-temporal speckle reduction of Sentinel-1 GRD images	Reducing speckle and limiting the variations of the physical parameters in Synthetic Aperture Radar (SAR) images is often a key-step to fully exploit the potential of such data. Nowadays, deep learning approaches produce state of the art results in single-image SAR restoration. Nevertheless, huge multi-temporal stacks ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	309,502
2103.01292	Maximal function pooling with applications	Inspired by the Hardy-Littlewood maximal function, we propose a novel pooling strategy which is called maxfun pooling. It is presented both as a viable alternative to some of the most popular pooling functions, such as max pooling and average pooling, and as a way of interpolating between these two algorithms. We demon...	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	222,566
2209.01728	Features Fusion Framework for Multimodal Irregular Time-series Events	Some data from multiple sources can be modeled as multimodal time-series events which have different sampling frequencies, data compositions, temporal relations and characteristics. Different types of events have complex nonlinear relationships, and the time of each event is irregular. Neither the classical Recurrent N...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	315,993
2012.11325	Detecting Botnet Attacks in IoT Environments: An Optimized Machine Learning Approach	The increased reliance on the Internet and the corresponding surge in connectivity demand has led to a significant growth in Internet-of-Things (IoT) devices. The continued deployment of IoT devices has in turn led to an increase in network attacks due to the larger number of potential attack surfaces as illustrated by...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	212,601
2204.00655	Robust Neonatal Face Detection in Real-world Clinical Settings	Current face detection algorithms are extremely generalized and can obtain decent accuracy when detecting the adult faces. These approaches are insufficient when handling outlier cases, for example when trying to detect the face of a neonate infant whose face composition and expressions are relatively different than th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	289,340
2108.01644	The Devil is in the GAN: Backdoor Attacks and Defenses in Deep Generative Models	Deep Generative Models (DGMs) are a popular class of deep learning models which find widespread use because of their ability to synthesize data from complex, high-dimensional manifolds. However, even with their increasing industrial adoption, they haven't been subject to rigorous security and privacy analysis. In this ...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	249,092
1812.10113	Privacy-Preserving Collaborative Deep Learning with Unreliable Participants	With powerful parallel computing GPUs and massive user data, neural-network-based deep learning can well exert its strong power in problem modeling and solving, and has archived great success in many applications such as image classification, speech recognition and machine translation etc. While deep learning has been ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	117,295
1501.05978	Linear independence of rank 1 matrices and the dimension of *-products of codes	We show that with high probability, random rank 1 matrices over a finite field are in (linearly) general position, at least provided their shape k x l is not excessively unbalanced. This translates into saying that the dimension of the *-product of two [n, k] and [n, l] random codes is equal to min(n, kl), as one would...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,550
2303.18171	How Efficient Are Today's Continual Learning Algorithms?	Supervised Continual learning involves updating a deep neural network (DNN) from an ever-growing stream of labeled data. While most work has focused on overcoming catastrophic forgetting, one of the major motivations behind continual learning is being able to efficiently update a network with new information, rather th...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	355,487
2305.18496	Generalized equivalences between subsampling and ridge regularization	We establish precise structural and risk equivalences between subsampling and ridge regularization for ensemble ridge estimators. Specifically, we prove that linear and quadratic functionals of subsample ridge estimators, when fitted with different ridge regularization levels $\lambda$ and subsample aspect ratios $\psi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	369,110
1609.03500	Hyperspectral Unmixing with Endmember Variability using Partial Membership Latent Dirichlet Allocation	The application of Partial Membership Latent Dirichlet Allocation(PM-LDA) for hyperspectral endmember estimation and spectral unmixing is presented. PM-LDA provides a model for a hyperspectral image analysis that accounts for spectral variability and incorporates spatial information through the use of superpixel-based ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	60,891
2004.12652	Self-supervised Keypoint Correspondences for Multi-Person Pose Estimation and Tracking in Videos	Video annotation is expensive and time consuming. Consequently, datasets for multi-person pose estimation and tracking are less diverse and have more sparse annotations compared to large scale image datasets for human pose estimation. This makes it challenging to learn deep learning based models for associating keypoin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	174,311
2209.14156	TVLT: Textless Vision-Language Transformer	In this work, we present the Textless Vision-Language Transformer (TVLT), where homogeneous transformer blocks take raw visual and audio inputs for vision-and-language representation learning with minimal modality-specific design, and do not use text-specific modules such as tokenization or automatic speech recognition...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	320,160
1804.04789	Successful Nash Equilibrium Agent for a 3-Player Imperfect-Information Game	Creating strong agents for games with more than two players is a major open problem in AI. Common approaches are based on approximating game-theoretic solution concepts such as Nash equilibrium, which have strong theoretical guarantees in two-player zero-sum games, but no guarantees in non-zero-sum games or in games wi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	true	94,932
1906.09556	DAL: Dual Adversarial Learning for Dialogue Generation	In open-domain dialogue systems, generative approaches have attracted much attention for response generation. However, existing methods are heavily plagued by generating safe responses and unnatural responses. To alleviate these two problems, we propose a novel framework named Dual Adversarial Learning (DAL) for high-q...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	136,204
2309.06725	Solar-powered shape-changing origami microfliers	Using wind to disperse microfliers that fall like seeds and leaves can help automate large-scale sensor deployments. Here, we present battery-free microfliers that can change shape in mid-air to vary their dispersal distance. We design origami microfliers using bi-stable leaf-out structures and uncover an important pro...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	391,525
2012.09670	RainBench: Towards Global Precipitation Forecasting from Satellite Imagery	Extreme precipitation events, such as violent rainfall and hail storms, routinely ravage economies and livelihoods around the developing world. Climate change further aggravates this issue. Data-driven deep learning approaches could widen the access to accurate multi-day forecasts, to mitigate against such events. Howe...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	212,139
1502.00802	Algorithm for Achieving Consensus Over Conflicting Rumors: Convergence Analysis and Applications	Motivated by the large expansion in the study of social networks, this paper deals with the problem of multiple messages spreading over the same network using gossip algorithms. Given two messages distributed over some nodes of the graph, we first investigate the final distribution of the messages given an initial stat...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	39,875
2206.04307	An Autonomous Drone System with Jamming and Relative Positioning Capabilities	As the number of unauthorized operations of Unmanned Aerial Vehicles (UAVs) is rising, the implementation of a versatile counter-drone system is becoming a necessity. In this work, we develop a drone-based counter-drone system, that employs algorithms for detecting and tracking a rogue drone, in conjunction with wirele...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	301,577
2401.01786	An experimental sorting method for improving metagenomic data encoding	Minimizing data storage poses a significant challenge in large-scale metagenomic projects. In this paper, we present a new method for improving the encoding of FASTQ files generated by metagenomic sequencing. This method incorporates metagenomic classification followed by a recursive filter for clustering reads by DNA ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	419,497
1204.4928	Challenges in Complex Systems Science	FuturICT foundations are social science, complex systems science, and ICT. The main concerns and challenges in the science of complex systems in the context of FuturICT are laid out in this paper with special emphasis on the Complex Systems route to Social Sciences. This include complex systems having: many heterogeneo...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	15,622
2405.01035	LOQA: Learning with Opponent Q-Learning Awareness	In various real-world scenarios, interactions among agents often resemble the dynamics of general-sum games, where each agent strives to optimize its own utility. Despite the ubiquitous relevance of such settings, decentralized machine learning algorithms have struggled to find equilibria that maximize individual utili...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	451,193
2202.09557	Safe Control Synthesis with Uncertain Dynamics and Constraints	This paper considers safe control synthesis for dynamical systems with either probabilistic or worst-case uncertainty in both the dynamics model and the safety constraints. We formulate novel probabilistic and robust (worst-case) control Lyapunov function (CLF) and control barrier function (CBF) constraints that take i...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	281,243
2211.12713	Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles	Attack Ensemble (AE), which combines multiple attacks together, provides a reliable way to evaluate adversarial robustness. In practice, AEs are often constructed and tuned by human experts, which however tends to be sub-optimal and time-consuming. In this work, we present AutoAE, a conceptually simple approach for aut...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	true	false	false	332,207
1808.02201	Holistic 3D Scene Parsing and Reconstruction from a Single RGB Image	We propose a computational framework to jointly parse a single RGB image and reconstruct a holistic 3D configuration composed by a set of CAD models using a stochastic grammar model. Specifically, we introduce a Holistic Scene Grammar (HSG) to represent the 3D scene structure, which characterizes a joint distribution o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	104,726
2404.11449	AI-Enhanced Cognitive Behavioral Therapy: Deep Learning and Large Language Models for Extracting Cognitive Pathways from Social Media Texts	Cognitive Behavioral Therapy (CBT) is an effective technique for addressing the irrational thoughts stemming from mental illnesses, but it necessitates precise identification of cognitive pathways to be successfully implemented in patient care. In current society, individuals frequently express negative emotions on soc...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	447,501
1809.01479	UKP-Athene: Multi-Sentence Textual Entailment for Claim Verification	The Fact Extraction and VERification (FEVER) shared task was launched to support the development of systems able to verify claims by extracting supporting or refuting facts from raw text. The shared task organizers provide a large-scale dataset for the consecutive steps involved in claim verification, in particular, do...	false	false	false	false	true	true	true	false	true	false	false	false	false	false	false	false	false	false	106,815
2112.00694	Label-Free Model Evaluation with Semi-Structured Dataset Representations	Label-free model evaluation, or AutoEval, estimates model accuracy on unlabeled test sets, and is critical for understanding model behaviors in various unseen environments. In the absence of image labels, based on dataset representations, we estimate model performance for AutoEval with regression. On the one hand, imag...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	269,213
2208.08861	Deep Billboards towards Lossless Real2Sim in Virtual Reality	An aspirational goal for virtual reality (VR) is to bring in a rich diversity of real world objects losslessly. Existing VR applications often convert objects into explicit 3D models with meshes or point clouds, which allow fast interactive rendering but also severely limit its quality and the types of supported object...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	313,507
2209.02190	A Multitask Deep Learning Model for Parsing Bridge Elements and Segmenting Defect in Bridge Inspection Images	The vast network of bridges in the United States raises a high requirement for maintenance and rehabilitation. The massive cost of manual visual inspection to assess bridge conditions is a burden to some extent. Advanced robots have been leveraged to automate inspection data collection. Automating the segmentations of ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	316,128
2306.11393	The Cultivated Practices of Text-to-Image Generation	Humankind is entering a novel creative era in which anybody can synthesize digital information using generative artificial intelligence (AI). Text-to-image generation, in particular, has become vastly popular and millions of practitioners produce AI-generated images and AI art online. This chapter first gives an overvi...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	374,580
1206.4648	Two-Manifold Problems with Applications to Nonlinear System Identification	Recently, there has been much interest in spectral approaches to learning manifolds---so-called kernel eigenmap methods. These methods have had some successes, but their applicability is limited because they are not robust to noise. To address this limitation, we look at two-manifold problems, in which we simultaneousl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	16,699
2203.13847	Cluster Algebras: Network Science and Machine Learning	Cluster algebras have recently become an important player in mathematics and physics. In this work, we investigate them through the lens of modern data science, specifically with techniques from network science and machine learning. Network analysis methods are applied to the exchange graphs for cluster algebras of var...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	287,773
1810.12114	Quantum Entanglement in Corpuses of Documents	We show that data collected from corpuses of documents violate the Clauser-Horne-Shimony-Holt version of Bell's inequality (CHSH inequality) and therefore indicate the presence of quantum entanglement in their structure. We obtain this result by considering two concepts and their combination and coincidence operations ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	111,683
2111.03137	Big-Step-Little-Step: Efficient Gradient Methods for Objectives with Multiple Scales	We provide new gradient-based methods for efficiently solving a broad class of ill-conditioned optimization problems. We consider the problem of minimizing a function $f : \mathbb{R}^d \rightarrow \mathbb{R}$ which is implicitly decomposable as the sum of $m$ unknown non-interacting smooth, strongly convex functions an...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	265,062
2106.04873	AutoFT: Automatic Fine-Tune for Parameters Transfer Learning in Click-Through Rate Prediction	Recommender systems are often asked to serve multiple recommendation scenarios or domains. Fine-tuning a pre-trained CTR model from source domains and adapting it to a target domain allows knowledge transferring. However, optimizing all the parameters of the pre-trained network may result in over-fitting if the target ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	239,885
2306.14525	ParameterNet: Parameters Are All You Need	The large-scale visual pretraining has significantly improve the performance of large vision models. However, we observe the \emph{low FLOPs pitfall} that the existing low-FLOPs models cannot benefit from large-scale pretraining. In this paper, we introduce a novel design principle, termed ParameterNet, aimed at augmen...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	375,716
2410.08355	Metalic: Meta-Learning In-Context with Protein Language Models	Predicting the biophysical and functional properties of proteins is essential for in silico protein design. Machine learning has emerged as a promising technique for such prediction tasks. However, the relative scarcity of in vitro annotations means that these models often have little, or no, specific data on the desir...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	497,074
2411.00632	PCoTTA: Continual Test-Time Adaptation for Multi-Task Point Cloud Understanding	In this paper, we present PCoTTA, an innovative, pioneering framework for Continual Test-Time Adaptation (CoTTA) in multi-task point cloud understanding, enhancing the model's transferability towards the continually changing target domain. We introduce a multi-task setting for PCoTTA, which is practical and realistic, ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	504,679
2008.03674	A Flexible Pipeline for the Optimization of CSG Trees	CSG trees are an intuitive, yet powerful technique for the representation of geometry using a combination of Boolean set-operations and geometric primitives. In general, there exists an infinite number of trees all describing the same 3D solid. However, some trees are optimal regarding the number of used operations, th...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	190,991
2305.10061	Rethinking Boundary Discontinuity Problem for Oriented Object Detection	Oriented object detection has been developed rapidly in the past few years, where rotation equivariance is crucial for detectors to predict rotated boxes. It is expected that the prediction can maintain the corresponding rotation when objects rotate, but severe mutation in angular prediction is sometimes observed when ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	364,894
2312.10321	LLM-SQL-Solver: Can LLMs Determine SQL Equivalence?	Judging the equivalence between two SQL queries is a fundamental problem with many practical applications in data management and SQL generation (i.e., evaluating the quality of generated SQL queries in text-to-SQL task). While the research community has reasoned about SQL equivalence for decades, it poses considerable ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	416,110
2305.05054	Dreams Are More "Predictable'' Than You Think	A consistent body of evidence suggests that dream reports significantly vary from other types of textual transcripts with respect to semantic content. Furthermore, it appears to be a widespread belief in the dream/sleep research community that dream reports constitute rather ``unique'' strings of text. This might be a ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	362,981
2012.12654	A deep learning-based ODE solver for chemical kinetics	Developing efficient and accurate algorithms for chemistry integration is a challenging task due to its strong stiffness and high dimensionality. The current work presents a deep learning-based numerical method called DeepCombustion0.0 to solve stiff ordinary differential equation systems. The homogeneous autoignition ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	213,009
2405.12616	Towards Using Fast Embedded Model Predictive Control for Human-Aware Predictive Robot Navigation	Predictive planning is a key capability for robots to efficiently and safely navigate populated environments. Particularly in densely crowded scenes, with uncertain human motion predictions, predictive path planning, and control can become expensive to compute in real time due to the curse of dimensionality. With the g...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	455,592
2406.12074	COMMUNITY-CROSS-INSTRUCT: Unsupervised Instruction Generation for Aligning Large Language Models to Online Communities	Social scientists use surveys to probe the opinions and beliefs of populations, but these methods are slow, costly, and prone to biases. Recent advances in large language models (LLMs) enable the creating of computational representations or "digital twins" of populations that generate human-like responses mimicking the...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	465,212
2005.00572	Exploring Pre-training with Alignments for RNN Transducer based End-to-End Speech Recognition	Recently, the recurrent neural network transducer (RNN-T) architecture has become an emerging trend in end-to-end automatic speech recognition research due to its advantages of being capable for online streaming speech recognition. However, RNN-T training is made difficult by the huge memory requirements, and complicat...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	175,277
2004.13073	A Novel Attention-based Aggregation Function to Combine Vision and Language	The joint understanding of vision and language has been recently gaining a lot of attention in both the Computer Vision and Natural Language Processing communities, with the emergence of tasks such as image captioning, image-text matching, and visual question answering. As both images and text can be encoded as sets or...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	174,430
1612.05536	A new cut-based genetic algorithm for graph partitioning applied to cell formation	Cell formation is a critical step in the design of cellular manufacturing systems. Recently, it was tackled using a cut-based-graph-partitioning model. This model meets real-life production systems requirements as it uses the actual amount of product flows, it looks for the suitable number of cells, and it takes into a...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	65,696
1603.00427	A Nonlinear Adaptive Filter Based on the Model of Simple Multilinear Functionals	Nonlinear adaptive filtering allows for modeling of some additional aspects of a general system and usually relies on highly complex algorithms, such as those based on the Volterra series. Through the use of the Kronecker product and some basic facts of tensor algebra, we propose a simple model of nonlinearity, one tha...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	52,772
2310.16360	A Comprehensive Review of AI-enabled Unmanned Aerial Vehicle: Trends, Vision , and Challenges	In recent years, the combination of artificial intelligence (AI) and unmanned aerial vehicles (UAVs) has brought about advancements in various areas. This comprehensive analysis explores the changing landscape of AI-powered UAVs and friendly computing in their applications. It covers emerging trends, futuristic visions...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	402,693
2303.17972	$\varepsilon$ K\'U <MASK>: Integrating Yor\`ub\'a cultural greetings into machine translation	This paper investigates the performance of massively multilingual neural machine translation (NMT) systems in translating Yor\`ub\'a greetings ($\varepsilon$ k\'u [MASK]), which are a big part of Yor\`ub\'a language and culture, into English. To evaluate these models, we present IkiniYor\`ub\'a, a Yor\`ub\'a-English tr...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	355,420
2501.08672	GS-LIVO: Real-Time LiDAR, Inertial, and Visual Multi-sensor Fused Odometry with Gaussian Mapping	In recent years, 3D Gaussian splatting (3D-GS) has emerged as a novel scene representation approach. However, existing vision-only 3D-GS methods often rely on hand-crafted heuristics for point-cloud densification and face challenges in handling occlusions and high GPU memory and computation consumption. LiDAR-Inertial-...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	524,867
2209.01947	MO2: Model-Based Offline Options	The ability to discover useful behaviours from past experience and transfer them to new tasks is considered a core component of natural embodied intelligence. Inspired by neuroscience, discovering behaviours that switch at bottleneck states have been long sought after for inducing plans of minimum description length ac...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	316,057
1602.05312	Density-based Denoising of Point Cloud	Point cloud source data for surface reconstruction is usually contaminated with noise and outliers. To overcome this deficiency, a density-based point cloud denoising method is presented to remove outliers and noisy points. First, particle-swam optimization technique is employed for automatically approximating optimal ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	52,239
2109.13438	Not Only Domain Randomization: Universal Policy with Embedding System Identification	Domain randomization (DR) cannot provide optimal policies for adapting the learning agent to the dynamics of the environment, although it can generalize sub-optimal policies to work in a transferred domain. In this paper, we present Universal Policy with Embedding System Identification (UPESI) as an implicit system ide...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	257,635
2209.07509	Random initialisations performing above chance and how to find them	Neural networks trained with stochastic gradient descent (SGD) starting from different random initialisations typically find functionally very similar solutions, raising the question of whether there are meaningful differences between different SGD solutions. Entezari et al.\ recently conjectured that despite different...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	317,771

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