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
1806.01817	Perturbative Neural Networks	Convolutional neural networks are witnessing wide adoption in computer vision systems with numerous applications across a range of visual recognition tasks. Much of this progress is fueled through advances in convolutional neural network architectures and learning algorithms even as the basic premise of a convolutional...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	99,643
2101.03252	Synthetic Glacier SAR Image Generation from Arbitrary Masks Using Pix2Pix Algorithm	Supervised machine learning requires a large amount of labeled data to achieve proper test results. However, generating accurately labeled segmentation maps on remote sensing imagery, including images from synthetic aperture radar (SAR), is tedious and highly subjective. In this work, we propose to alleviate the issue ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	214,866
2406.01126	TCMBench: A Comprehensive Benchmark for Evaluating Large Language Models in Traditional Chinese Medicine	Large language models (LLMs) have performed remarkably well in various natural language processing tasks by benchmarking, including in the Western medical domain. However, the professional evaluation benchmarks for LLMs have yet to be covered in the traditional Chinese medicine(TCM) domain, which has a profound history...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	460,180
2409.06699	A study on Deep Convolutional Neural Networks, Transfer Learning and Ensemble Model for Breast Cancer Detection	In deep learning, transfer learning and ensemble models have shown promise in improving computer-aided disease diagnosis. However, applying the transfer learning and ensemble model is still relatively limited. Moreover, the ensemble model's development is ad-hoc, overlooks redundant layers, and suffers from imbalanced ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	487,229
2208.01354	Distributed Sum-Rate Maximization of Cellular Communications with Multiple Reconfigurable Intelligent Surfaces	The technology of Reconfigurable Intelligent Surfaces (RISs) has lately attracted considerable interest from both academia and industry as a low-cost solution for coverage extension and signal propagation control. In this paper, we study the downlink of a multi-cell wideband communication system comprising single-anten...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	311,138
2402.07038	Nonlinear Modes as a Tool for Comparing the Mathematical Structure of Dynamic Models of Soft Robots	Continuum soft robots are nonlinear mechanical systems with theoretically infinite degrees of freedom (DoFs) that exhibit complex behaviors. Achieving motor intelligence under dynamic conditions necessitates the development of control-oriented reduced-order models (ROMs), which employ as few DoFs as possible while stil...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	428,544
2502.12862	RobotIQ: Empowering Mobile Robots with Human-Level Planning for Real-World Execution	This paper introduces RobotIQ, a framework that empowers mobile robots with human-level planning capabilities, enabling seamless communication via natural language instructions through any Large Language Model. The proposed framework is designed in the ROS architecture and aims to bridge the gap between humans and robo...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	535,085
2210.05313	Memory transformers for full context and high-resolution 3D Medical Segmentation	Transformer models achieve state-of-the-art results for image segmentation. However, achieving long-range attention, necessary to capture global context, with high-resolution 3D images is a fundamental challenge. This paper introduces the Full resolutIoN mEmory (FINE) transformer to overcome this issue. The core idea b...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	322,801
2104.02687	Strumming to the Beat: Audio-Conditioned Contrastive Video Textures	We introduce a non-parametric approach for infinite video texture synthesis using a representation learned via contrastive learning. We take inspiration from Video Textures, which showed that plausible new videos could be generated from a single one by stitching its frames together in a novel yet consistent order. This...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	228,815
2304.02859	MULLER: Multilayer Laplacian Resizer for Vision	Image resizing operation is a fundamental preprocessing module in modern computer vision. Throughout the deep learning revolution, researchers have overlooked the potential of alternative resizing methods beyond the commonly used resizers that are readily available, such as nearest-neighbors, bilinear, and bicubic. The...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	356,583
2408.09240	RepControlNet: ControlNet Reparameterization	With the wide application of diffusion model, the high cost of inference resources has became an important bottleneck for its universal application. Controllable generation, such as ControlNet, is one of the key research directions of diffusion model, and the research related to inference acceleration and model compres...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	481,347
2106.03158	Transferring Knowledge from Text to Video: Zero-Shot Anticipation for Procedural Actions	Can we teach a robot to recognize and make predictions for activities that it has never seen before? We tackle this problem by learning models for video from text. This paper presents a hierarchical model that generalizes instructional knowledge from large-scale text corpora and transfers the knowledge to video. Given ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	239,203
2408.14342	Dual-Domain CLIP-Assisted Residual Optimization Perception Model for Metal Artifact Reduction	Metal artifacts in computed tomography (CT) imaging pose significant challenges to accurate clinical diagnosis. The presence of high-density metallic implants results in artifacts that deteriorate image quality, manifesting in the forms of streaking, blurring, or beam hardening effects, etc. Nowadays, various deep lear...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	483,500
2010.05546	How to Hijack Twitter: Online Polarisation Strategies of Germany's Political Far-Right	With a network approach, we examine the case of the German far-right party Alternative f\"ur Deutschland (AfD) and their potential use of a "hashjacking" strategy. Our findings suggest that right-wing politicians (and their supporters/retweeters) actively and effectively polarise the discourse not just by using their o...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	200,181
2406.01658	Proxy Denoising for Source-Free Domain Adaptation	Source-free Domain Adaptation (SFDA) aims to adapt a pre-trained source model to an unlabeled target domain with no access to the source data. Inspired by the success of pre-trained large vision-language (ViL) models in many other applications, the latest SFDA methods have also validated the benefit of ViL models by le...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	460,425
2304.09085	Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased Recommendations	Recommender systems are seen as an effective tool to address information overload, but it is widely known that the presence of various biases makes direct training on large-scale observational data result in sub-optimal prediction performance. In contrast, unbiased ratings obtained from randomized controlled trials or ...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	358,930
2409.17750	Are Transformers in Pre-trained LM A Good ASR Encoder? An Empirical Study	In this study, we delve into the efficacy of transformers within pre-trained language models (PLMs) when repurposed as encoders for Automatic Speech Recognition (ASR). Our underlying hypothesis posits that, despite being initially trained on text-based corpora, these transformers possess a remarkable capacity to extrac...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	491,965
1901.09097	Driver Distraction Identification with an Ensemble of Convolutional Neural Networks	The World Health Organization (WHO) reported 1.25 million deaths yearly due to road traffic accidents worldwide and the number has been continuously increasing over the last few years. Nearly fifth of these accidents are caused by distracted drivers. Existing work of distracted driver detection is concerned with a smal...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	119,646
2202.01100	Exact Privacy Analysis of the Gaussian Sparse Histogram Mechanism	Sparse histogram methods can be useful for returning differentially private counts of items in large or infinite histograms, large group-by queries, and more generally, releasing a set of statistics with sufficient item counts. We consider the Gaussian version of the sparse histogram mechanism and study the exact $\eps...	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	278,366
2211.01357	Quasi-Newton Steps for Efficient Online Exp-Concave Optimization	The aim of this paper is to design computationally-efficient and optimal algorithms for the online and stochastic exp-concave optimization settings. Typical algorithms for these settings, such as the Online Newton Step (ONS), can guarantee a $O(d\ln T)$ bound on their regret after $T$ rounds, where $d$ is the dimension...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	328,203
2204.11097	The SCORE normalization, especially for highly heterogeneous network and text data	SCORE was introduced as a spectral approach to network community detection. Since many networks have severe degree heterogeneity, the ordinary spectral clustering (OSC) approach to community detection may perform unsatisfactorily. SCORE alleviates the effect of degree heterogeneity by introducing a new normalization id...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	293,031
1503.05619	3-D Statistical Channel Model for Millimeter-Wave Outdoor Mobile Broadband Communications	This paper presents an omnidirectional spatial and temporal 3-dimensional statistical channel model for 28 GHz dense urban non-line of sight environments. The channel model is developed from 28 GHz ultrawideband propagation measurements obtained with a 400 megachips per second broadband sliding correlator channel sound...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	41,262
1902.03854	Stratified communities in complex business networks	This paper presents a new definition of the community structure of a network, which takes also into account how communities are stratified. In particular, we extend the standard concept of clustering coefficient and provide the local $l$-adjacency clustering coefficient of a node $i$. We define it as an opportunely wei...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	121,213
cs/0201009	The performance of the batch learner algorithm	We analyze completely the convergence speed of the \emph{batch learning algorithm}, and compare its speed to that of the memoryless learning algorithm and of learning with memory. We show that the batch learning algorithm is never worse than the memoryless learning algorithm (at least asymptotically). Its performance \...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	537,481
2406.14522	Learning thresholds lead to stable language coexistence	We introduce a language competition model that is based on the Abrams-Strogatz model and incorporates the effects of memory and learning in the language shift dynamics. On a coarse grained time scale, the effects of memory and learning can be expressed as thresholds on the speakers fractions of the competing languages....	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	466,350
2005.07404	Think Too Fast Nor Too Slow: The Computational Trade-off Between Planning And Reinforcement Learning	Planning and reinforcement learning are two key approaches to sequential decision making. Multi-step approximate real-time dynamic programming, a recently successful algorithm class of which AlphaZero [Silver et al., 2018] is an example, combines both by nesting planning within a learning loop. However, the combination...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	177,272
1502.00979	Further Properties of Wireless Channel Capacity	Future wireless communication calls for exploration of more efficient use of wireless channel capacity to meet the increasing demand on higher data rate and less latency. However, while the ergodic capacity and instantaneous capacity of a wireless channel have been extensively studied, they are in many cases not suffic...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,892
2211.17014	An Interpretable Hybrid Predictive Model of COVID-19 Cases using Autoregressive Model and LSTM	The Coronavirus Disease 2019 (COVID-19) has a profound impact on global health and economy, making it crucial to build accurate and interpretable data-driven predictive models for COVID-19 cases to improve policy making. The extremely large scale of the pandemic and the intrinsically changing transmission characteristi...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	333,828
1304.3847	Proceedings of the Twelfth Conference on Uncertainty in Artificial Intelligence (1996)	This is the Proceedings of the Twelfth Conference on Uncertainty in Artificial Intelligence, which was held in Portland, OR, August 1-4, 1996	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	23,937
2403.16536	VMRNN: Integrating Vision Mamba and LSTM for Efficient and Accurate Spatiotemporal Forecasting	Combining CNNs or ViTs, with RNNs for spatiotemporal forecasting, has yielded unparalleled results in predicting temporal and spatial dynamics. However, modeling extensive global information remains a formidable challenge; CNNs are limited by their narrow receptive fields, and ViTs struggle with the intensive computati...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	441,093
2405.20260	Ancillary Services Provision by Cross-Voltage-Level Power Flow Control using Flexibility Regions	The large-scale integration of distributed renewable energy sources into the electricity grid requires the investigation of new methods to ensure stability. For example, Active Distribution Networks (ADNs) can be used at (sub-) transmission levels for emergency operation, provided robust and efficient control is availa...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	459,263
2406.13363	Evaluating Structural Generalization in Neural Machine Translation	Compositional generalization refers to the ability to generalize to novel combinations of previously observed words and syntactic structures. Since it is regarded as a desired property of neural models, recent work has assessed compositional generalization in machine translation as well as semantic parsing. However, pr...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	465,820
2105.04646	Deeply-Debiased Off-Policy Interval Estimation	Off-policy evaluation learns a target policy's value with a historical dataset generated by a different behavior policy. In addition to a point estimate, many applications would benefit significantly from having a confidence interval (CI) that quantifies the uncertainty of the point estimate. In this paper, we propose ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	234,567
2410.18148	Deep Autoencoder with SVD-Like Convergence and Flat Minima	Representation learning for high-dimensional, complex physical systems aims to identify a low-dimensional intrinsic latent space, which is crucial for reduced-order modeling and modal analysis. To overcome the well-known Kolmogorov barrier, deep autoencoders (AEs) have been introduced in recent years, but they often su...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	501,776
1711.02132	Weighted Transformer Network for Machine Translation	State-of-the-art results on neural machine translation often use attentional sequence-to-sequence models with some form of convolution or recursion. Vaswani et al. (2017) propose a new architecture that avoids recurrence and convolution completely. Instead, it uses only self-attention and feed-forward layers. While the...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	84,008
2304.10145	Can ChatGPT Reproduce Human-Generated Labels? A Study of Social Computing Tasks	The release of ChatGPT has uncovered a range of possibilities whereby large language models (LLMs) can substitute human intelligence. In this paper, we seek to understand whether ChatGPT has the potential to reproduce human-generated label annotations in social computing tasks. Such an achievement could significantly r...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	359,307
1707.00748	Cluster synchronization of diffusively-coupled nonlinear systems: A contraction based approach	Finding the conditions that foster synchronization in networked oscillatory systems is critical to understanding a wide range of biological and mechanical systems. However, the conditions proved in the literature for synchronization in nonlinear systems with linear coupling, such as has been used to model neuronal netw...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	76,403
2010.07261	Learning Improvised Chatbots from Adversarial Modifications of Natural Language Feedback	The ubiquitous nature of chatbots and their interaction with users generate an enormous amount of data. Can we improve chatbots using this data? A self-feeding chatbot improves itself by asking natural language feedback when a user is dissatisfied with its response and uses this feedback as an additional training sampl...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	200,757
2308.12213	CLIPN for Zero-Shot OOD Detection: Teaching CLIP to Say No	Out-of-distribution (OOD) detection refers to training the model on an in-distribution (ID) dataset to classify whether the input images come from unknown classes. Considerable effort has been invested in designing various OOD detection methods based on either convolutional neural networks or transformers. However, zer...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	387,457
2306.13421	Retrieval-Pretrained Transformer: Long-range Language Modeling with Self-retrieval	Retrieval-augmented language models (LMs) have received much attention recently. However, typically the retriever is not trained jointly as a native component of the LM, but added post-hoc to an already-pretrained LM, which limits the ability of the LM and the retriever to adapt to one another. In this work, we propose...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	375,273
1904.09324	Mask-Predict: Parallel Decoding of Conditional Masked Language Models	Most machine translation systems generate text autoregressively from left to right. We, instead, use a masked language modeling objective to train a model to predict any subset of the target words, conditioned on both the input text and a partially masked target translation. This approach allows for efficient iterative...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	128,342
2502.11486	Anti-Degeneracy Scheme for Lidar SLAM based on Particle Filter in Geometry Feature-Less Environments	Simultaneous localization and mapping (SLAM) based on particle filtering has been extensively employed in indoor scenarios due to its high efficiency. However, in geometry feature-less scenes, the accuracy is severely reduced due to lack of constraints. In this article, we propose an anti-degeneracy system based on dee...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	534,402
2402.08902	Auto-Encoding Bayesian Inverse Games	When multiple agents interact in a common environment, each agent's actions impact others' future decisions, and noncooperative dynamic games naturally capture this coupling. In interactive motion planning, however, agents typically do not have access to a complete model of the game, e.g., due to unknown objectives of ...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	true	false	false	true	429,284
2305.03970	NER-to-MRC: Named-Entity Recognition Completely Solving as Machine Reading Comprehension	Named-entity recognition (NER) detects texts with predefined semantic labels and is an essential building block for natural language processing (NLP). Notably, recent NER research focuses on utilizing massive extra data, including pre-training corpora and incorporating search engines. However, these methods suffer from...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	362,584
1807.01827	Learning Theory and Algorithms for Revenue Management in Sponsored Search	Online advertisement is the main source of revenue for Internet business. Advertisers are typically ranked according to a score that takes into account their bids and potential click-through rates(eCTR). Generally, the likelihood that a user clicks on an ad is often modeled by optimizing for the click through rates rat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	102,139
2409.13964	Adaptive bias for dissensus in nonlinear opinion dynamics with application to evolutionary division of labor games	This paper addresses the problem of adaptively controlling the bias parameter in nonlinear opinion dynamics (NOD) to allocate agents into groups of arbitrary sizes for the purpose of maximizing collective rewards. In previous work, an algorithm based on the coupling of NOD with an multi-objective behavior optimization ...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	490,257
1507.07115	SINR Constrained Beamforming for a MIMO Multi-user Downlink System	Consider a multi-input multi-output (MIMO) downlink multi-user channel. A well-studied problem in such system is the design of linear beamformers for power minimization with the quality of service (QoS) constraints. The most representative algorithms for solving this class of problems are the so-called MMSE-SOCP algori...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	45,448
2211.07814	Extending the Neural Additive Model for Survival Analysis with EHR Data	With increasing interest in applying machine learning to develop healthcare solutions, there is a desire to create interpretable deep learning models for survival analysis. In this paper, we extend the Neural Additive Model (NAM) by incorporating pairwise feature interaction networks and equip these models with loss fu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	330,374
2404.15806	Where to Mask: Structure-Guided Masking for Graph Masked Autoencoders	Graph masked autoencoders (GMAE) have emerged as a significant advancement in self-supervised pre-training for graph-structured data. Previous GMAE models primarily utilize a straightforward random masking strategy for nodes or edges during training. However, this strategy fails to consider the varying significance of ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	449,248
2401.17591	Multi-Agent Phase-Balancing around Polar Curves with Bounded Trajectories: An Experimental Study using Crazyflies and MoCap System	In this experimental work, we implement the control design from our earlier work on a swarm of Crazyflie 2.1 quad-copters by deriving the original control in terms of variables that are available to the user in this practical system. A suitable model is developed using the Crazyswarm2 package within ROS2 to facilitate ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	425,249
2407.12442	ClearCLIP: Decomposing CLIP Representations for Dense Vision-Language Inference	Despite the success of large-scale pretrained Vision-Language Models (VLMs) especially CLIP in various open-vocabulary tasks, their application to semantic segmentation remains challenging, producing noisy segmentation maps with mis-segmented regions. In this paper, we carefully re-investigate the architecture of CLIP,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	473,931
2103.02252	An Attention Based Neural Network for Code Switching Detection: English & Roman Urdu	Code-switching is a common phenomenon among people with diverse lingual background and is widely used on the internet for communication purposes. In this paper, we present a Recurrent Neural Network combined with the Attention Model for Language Identification in Code-Switched Data in English and low resource Roman Urd...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	222,902
2111.00444	Finite-Time Capacity: Making Exceed-Shannon Possible?	Shannon-Hartley theorem can accurately calculate the channel capacity when the signal observation time is infinite. However, the calculation of finite-time capacity, which remains unknown, is essential for guiding the design of practical communication systems. In this paper, we investigate the capacity between two corr...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	264,222
2411.05088	Findings of the IWSLT 2024 Evaluation Campaign	This paper reports on the shared tasks organized by the 21st IWSLT Conference. The shared tasks address 7 scientific challenges in spoken language translation: simultaneous and offline translation, automatic subtitling and dubbing, speech-to-speech translation, dialect and low-resource speech translation, and Indic lan...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	506,546
2110.09741	Trajectory Prediction with Linguistic Representations	Language allows humans to build mental models that interpret what is happening around them resulting in more accurate long-term predictions. We present a novel trajectory prediction model that uses linguistic intermediate representations to forecast trajectories, and is trained using trajectory samples with partially-a...	false	false	false	false	true	false	true	true	true	false	false	false	false	false	false	false	false	false	261,905
2303.10243	Safety-Critical Control for Systems with Impulsive Actuators and Dwell Time Constraints	This paper presents extensions of control barrier function (CBF) and control Lyapunov function (CLF) theory to systems wherein all actuators cause impulsive changes to the state trajectory, and can only be used again after a minimum dwell time has elapsed. These rules define a hybrid system, wherein the controller must...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	352,362
2206.15138	DFGC 2022: The Second DeepFake Game Competition	This paper presents the summary report on our DFGC 2022 competition. The DeepFake is rapidly evolving, and realistic face-swaps are becoming more deceptive and difficult to detect. On the contrary, methods for detecting DeepFakes are also improving. There is a two-party game between DeepFake creators and defenders. Thi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	305,497
2004.14117	Supervised MPC control of large-scale electricity networks via clustering methods	This paper describes a control approach for large-scale electricity networks, with the goal of efficiently coordinating distributed generators to balance unexpected load variations with respect to nominal forecasts. To mitigate the difficulties due to the size of the problem, the proposed methodology is divided in two ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	174,781
2012.05609	Retinex-inspired Unrolling with Cooperative Prior Architecture Search for Low-light Image Enhancement	Low-light image enhancement plays very important roles in low-level vision field. Recent works have built a large variety of deep learning models to address this task. However, these approaches mostly rely on significant architecture engineering and suffer from high computational burden. In this paper, we propose a new...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	210,837
2105.01747	Information Complexity and Generalization Bounds	We present a unifying picture of PAC-Bayesian and mutual information-based upper bounds on the generalization error of randomized learning algorithms. As we show, Tong Zhang's information exponential inequality (IEI) gives a general recipe for constructing bounds of both flavors. We show that several important results ...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	233,606
1501.01797	Inference for Generalized Linear Models via Alternating Directions and Bethe Free Energy Minimization	Generalized Linear Models (GLMs), where a random vector $\mathbf{x}$ is observed through a noisy, possibly nonlinear, function of a linear transform $\mathbf{z}=\mathbf{Ax}$ arise in a range of applications in nonlinear filtering and regression. Approximate Message Passing (AMP) methods, based on loopy belief propagati...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,124
2402.12767	When and How: Learning Identifiable Latent States for Nonstationary Time Series Forecasting	Temporal distribution shifts are ubiquitous in time series data. One of the most popular methods assumes that the temporal distribution shift occurs uniformly to disentangle the stationary and nonstationary dependencies. But this assumption is difficult to meet, as we do not know when the distribution shifts occur. To ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	430,987
2005.06586	Tropical Data Science	Phylogenomics is a new field which applies to tools in phylogenetics to genome data. Due to a new technology and increasing amount of data, we face new challenges to analyze them over a space of phylogenetic trees. Because a space of phylogenetic trees with a fixed set of labels on leaves is not Euclidean, we cannot si...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	177,035
2103.13887	Adversarial Imitation Learning with Trajectorial Augmentation and Correction	Deep Imitation Learning requires a large number of expert demonstrations, which are not always easy to obtain, especially for complex tasks. A way to overcome this shortage of labels is through data augmentation. However, this cannot be easily applied to control tasks due to the sequential nature of the problem. In thi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	226,656
2501.16357	EVolutionary Independent DEtermiNistiC Explanation	The widespread use of artificial intelligence deep neural networks in fields such as medicine and engineering necessitates understanding their decision-making processes. Current explainability methods often produce inconsistent results and struggle to highlight essential signals influencing model inferences. This paper...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	527,926
2001.08680	Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch Normalization	The fundamental difficulty in person re-identification (ReID) lies in learning the correspondence among individual cameras. It strongly demands costly inter-camera annotations, yet the trained models are not guaranteed to transfer well to previously unseen cameras. These problems significantly limit the application of ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	161,354
1911.03233	Neural Networks for Predicting Human Interactions in Repeated Games	We consider the problem of predicting human players' actions in repeated strategic interactions. Our goal is to predict the dynamic step-by-step behavior of individual players in previously unseen games. We study the ability of neural networks to perform such predictions and the information that they require. We show o...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	152,586
2408.03140	Integration vs segregation: network analysis of interdisciplinarity in funded and unfunded research on infectious diseases	Interdisciplinary research fuels innovation. In this paper, we examine the interdisciplinarity of research output driven by funding. Considering 36 major infectious diseases, we model interdisciplinarity through temporal correlation networks based on funded and unfunded research from 1995-2022. Using hierarchical clust...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	478,907
1311.0959	Validation of a Control Algorithm for Human-like Reaching Motion using 7-DOF Arm and 19-DOF Hand-Arm Systems	This technical report gives an overview of our work on control algorithms dealing with redundant robot systems for achieving human-like motion characteristics. Previously, we developed a novel control law to exhibit human-motion characteristics in redundant robot arm systems as well as arm-trunk systems for reaching ta...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	28,197
2204.13630	Rotationally Equivariant 3D Object Detection	Rotation equivariance has recently become a strongly desired property in the 3D deep learning community. Yet most existing methods focus on equivariance regarding a global input rotation while ignoring the fact that rotation symmetry has its own spatial support. Specifically, we consider the object detection problem in...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	293,882
1904.08645	Tex2Shape: Detailed Full Human Body Geometry From a Single Image	We present a simple yet effective method to infer detailed full human body shape from only a single photograph. Our model can infer full-body shape including face, hair, and clothing including wrinkles at interactive frame-rates. Results feature details even on parts that are occluded in the input image. Our main idea ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	128,139
2302.06132	NNKGC: Improving Knowledge Graph Completion with Node Neighborhoods	Knowledge graph completion (KGC) aims to discover missing relations of query entities. Current text-based models utilize the entity name and description to infer the tail entity given the head entity and a certain relation. Existing approaches also consider the neighborhood of the head entity. However, these methods te...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	345,301
2302.00671	QMP: Q-switch Mixture of Policies for Multi-Task Behavior Sharing	Multi-task reinforcement learning (MTRL) aims to learn several tasks simultaneously for better sample efficiency than learning them separately. Traditional methods achieve this by sharing parameters or relabeled data between tasks. In this work, we introduce a new framework for sharing behavioral policies across tasks,...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	343,302
2403.18791	Object Pose Estimation via the Aggregation of Diffusion Features	Estimating the pose of objects from images is a crucial task of 3D scene understanding, and recent approaches have shown promising results on very large benchmarks. However, these methods experience a significant performance drop when dealing with unseen objects. We believe that it results from the limited generalizabi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	442,078
1904.02122	Group-wise classification approach to improve Android malicious apps detection accuracy	In the fast-growing smart devices, Android is the most popular OS, and due to its attractive features, mobility, ease of use, these devices hold sensitive information such as personal data, browsing history, shopping history, financial details, etc. Therefore, any security gap in these devices means that the informatio...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	126,335
2502.02593	Reconstructing 3D Flow from 2D Data with Diffusion Transformer	Fluid flow is a widely applied physical problem, crucial in various fields. Due to the highly nonlinear and chaotic nature of fluids, analyzing fluid-related problems is exceptionally challenging. Computational fluid dynamics (CFD) is the best tool for this analysis but involves significant computational resources, esp...	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	530,389
2209.14973	Deep Unfolding for Iterative Stripe Noise Removal	The non-uniform photoelectric response of infrared imaging systems results in fixed-pattern stripe noise being superimposed on infrared images, which severely reduces image quality. As the applications of degraded infrared images are limited, it is crucial to effectively preserve original details. Existing image destri...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	320,416
1301.2603	Robust subspace clustering	Subspace clustering refers to the task of finding a multi-subspace representation that best fits a collection of points taken from a high-dimensional space. This paper introduces an algorithm inspired by sparse subspace clustering (SSC) [In IEEE Conference on Computer Vision and Pattern Recognition, CVPR (2009) 2790-27...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	21,017
1906.07697	Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes	The goal of this paper is to design image classification systems that, after an initial multi-task training phase, can automatically adapt to new tasks encountered at test time. We introduce a conditional neural process based approach to the multi-task classification setting for this purpose, and establish connections ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	135,665
2008.04621	R-MNet: A Perceptual Adversarial Network for Image Inpainting	Facial image inpainting is a problem that is widely studied, and in recent years the introduction of Generative Adversarial Networks, has led to improvements in the field. Unfortunately some issues persists, in particular when blending the missing pixels with the visible ones. We address the problem by proposing a Wass...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	191,281
2211.08008	MORA: Improving Ensemble Robustness Evaluation with Model-Reweighing Attack	Adversarial attacks can deceive neural networks by adding tiny perturbations to their input data. Ensemble defenses, which are trained to minimize attack transferability among sub-models, offer a promising research direction to improve robustness against such attacks while maintaining a high accuracy on natural inputs....	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	330,447
2008.13381	Augmented Reality-Based Advanced Driver-Assistance System for Connected Vehicles	With the development of advanced communication technology, connected vehicles become increasingly popular in our transportation systems, which can conduct cooperative maneuvers with each other as well as road entities through vehicle-to-everything communication. A lot of research interests have been drawn to other buil...	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	193,835
2310.03514	Vocal Fold Reconstruction from Optical Velocity and Displacement Measurements	The three-dimensional reconstruction of vocal folds in medicine usually involves endoscopy and an approach to extract depth information like structured light or stereo matching of images. The resulting mesh can accurately represent the superior area of the vocal folds, while new approaches also try to reconstruct the i...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	397,312
2304.03708	Efficient automatic segmentation for multi-level pulmonary arteries: The PARSE challenge	Efficient automatic segmentation of multi-level (i.e. main and branch) pulmonary arteries (PA) in CTPA images plays a significant role in clinical applications. However, most existing methods concentrate only on main PA or branch PA segmentation separately and ignore segmentation efficiency. Besides, there is no public...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	356,914
1307.3667	Logics of formal inconsistency arising from systems of fuzzy logic	This paper proposes the meeting of fuzzy logic with paraconsistency in a very precise and foundational way. Specifically, in this paper we introduce expansions of the fuzzy logic MTL by means of primitive operators for consistency and inconsistency in the style of the so-called Logics of Formal Inconsistency (LFIs). Th...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	25,819
1410.3864	Multi-Agent Shape Formation and Tracking Inspired from a Social Foraging Dynamics	Principle of Swarm Intelligence has recently found widespread application in formation control and automated tracking by the automated multi-agent system. This article proposes an elegant and effective method inspired by foraging dynamics to produce geometric-patterns by the search agents. Starting from a random initia...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	36,742
1512.08065	Inverse Reinforcement Learning via Deep Gaussian Process	We propose a new approach to inverse reinforcement learning (IRL) based on the deep Gaussian process (deep GP) model, which is capable of learning complicated reward structures with few demonstrations. Our model stacks multiple latent GP layers to learn abstract representations of the state feature space, which is link...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	50,485
2408.05136	Cycle-Configuration: A Novel Graph-theoretic Descriptor Set for Molecular Inference	In this paper, we propose a novel family of descriptors of chemical graphs, named cycle-configuration (CC), that can be used in the standard "two-layered (2L) model" of mol-infer, a molecular inference framework based on mixed integer linear programming (MILP) and machine learning (ML). Proposed descriptors capture the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	479,670
1708.00997	Rank-metric LCD codes	In this paper, we investigate the rank-metric codes which are proposed by Delsarte and Gabidulin to be complementary dual codes. We point out the relationship between Delsarte complementary dual codes and Gabidulin complementary dual codes. In finite field $\mathbb{F}_{q}^{m}$, we construct two classes of Gabidulin LCD...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	78,316
0906.1900	How deals with discrete data for the reduction of simulation models using neural network	Simulation is useful for the evaluation of a Master Production/distribution Schedule (MPS). Also, the goal of this paper is the study of the design of a simulation model by reducing its complexity. According to theory of constraints, we want to build reduced models composed exclusively by bottlenecks and a neural netwo...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	3,860
2106.03541	Multi-agent Battery Storage Management using MPC-based Reinforcement Learning	In this paper, we present the use of Model Predictive Control (MPC) based on Reinforcement Learning (RL) to find the optimal policy for a multi-agent battery storage system. A time-varying prediction of the power price and production-demand uncertainty are considered. We focus on optimizing an economic objective cost w...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	239,359
2206.05650	Preprocessing Enhanced Image Compression for Machine Vision	Recently, more and more images are compressed and sent to the back-end devices for the machine analysis tasks~(\textit{e.g.,} object detection) instead of being purely watched by humans. However, most traditional or learned image codecs are designed to minimize the distortion of the human visual system without consider...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	302,080
2405.00433	Weight Sparsity Complements Activity Sparsity in Neuromorphic Language Models	Activity and parameter sparsity are two standard methods of making neural networks computationally more efficient. Event-based architectures such as spiking neural networks (SNNs) naturally exhibit activity sparsity, and many methods exist to sparsify their connectivity by pruning weights. While the effect of weight pr...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	450,917
2208.13830	Extracting Mathematical Concepts from Text	We investigate different systems for extracting mathematical entities from English texts in the mathematical field of category theory as a first step for constructing a mathematical knowledge graph. We consider four different term extractors and compare their results. This small experiment showcases some of the issues ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	315,147
1805.10267	Duluth UROP at SemEval-2018 Task 2: Multilingual Emoji Prediction with Ensemble Learning and Oversampling	This paper describes the Duluth UROP systems that participated in SemEval--2018 Task 2, Multilingual Emoji Prediction. We relied on a variety of ensembles made up of classifiers using Naive Bayes, Logistic Regression, and Random Forests. We used unigram and bigram features and tried to offset the skewness of the data t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	98,627
1405.2281	Proceedings of the First Workshop on Resource Awareness and Adaptivity in Multi-Core Computing (Racing 2014)	This volume contains the papers accepted at the 1st Workshop on Resource Awareness and Adaptivity in Multi-Core Computing (Racing 2014), held in Paderborn, Germany, May 29-30, 2014. Racing 2014 was co-located with the IEEE European Test Symposium (ETS).	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	32,965
1907.09104	On the Consistency among Prior, Posteriors, and Information Sets (Extended Abstract)	This paper studies implications of the consistency conditions among prior, posteriors, and information sets on introspective properties of qualitative belief induced from information sets. The main result reformulates the consistency conditions as: (i) the information sets, without any assumption, almost surely form a ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	139,266
2005.10918	CHEER: Rich Model Helps Poor Model via Knowledge Infusion	There is a growing interest in applying deep learning (DL) to healthcare, driven by the availability of data with multiple feature channels in rich-data environments (e.g., intensive care units). However, in many other practical situations, we can only access data with much fewer feature channels in a poor-data environ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	178,322
2203.06345	The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy	Vision transformers (ViTs) have gained increasing popularity as they are commonly believed to own higher modeling capacity and representation flexibility, than traditional convolutional networks. However, it is questionable whether such potential has been fully unleashed in practice, as the learned ViTs often suffer fr...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	285,078
0906.0958	On a Generalized Foster-Lyapunov Type Criterion for the Stability of Multidimensional Markov chains with Applications to the Slotted-Aloha Protocol with Finite Number of Queues	In this paper, we generalize a positive recurrence criterion for multidimensional discrete-time Markov chains over countable state spaces due to Rosberg (JAP, Vol. 17, No. 3, 1980). We revisit the stability analysis of well known slotted-Aloha protocol with finite number of queues. Under standard modeling assumptions, ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	3,832

Subsets and Splits

No community queries yet

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