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
2105.01536	Abstraction-Guided Truncations for Stationary Distributions of Markov Population Models	To understand the long-run behavior of Markov population models, the computation of the stationary distribution is often a crucial part. We propose a truncation-based approximation that employs a state-space lumping scheme, aggregating states in a grid structure. The resulting approximate stationary distribution is use...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	233,547
1411.2883	A new estimate of mutual information based measure of dependence between two variables: properties and fast implementation	This article proposes a new method to estimate an existing mutual information based dependence measure using histogram density estimates. Finding a suitable bin length for histogram is an open problem. We propose a new way of computing the bin length for histogram using a function of maximum separation between points. ...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	37,455
2406.06641	Investigation of the Impact of Economic and Social Factors on Energy Demand through Natural Language Processing	The relationship between energy demand and variables such as economic activity and weather is well established. However, this paper aims to explore the connection between energy demand and other social aspects, which receive little attention. Through the use of natural language processing on a large news corpus, we she...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	462,715
2410.23626	An Application of the Holonomic Gradient Method to the Neural Tangent Kernel	A holonomic system of linear partial differential equations is, roughly speaking, a system whose solution space is finite dimensional. A distribution that is a solution of a holonomic system is called a holonomic distribution. We give methods to numerically evaluate dual activations of holonomic activator distributions...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	504,110
1602.00177	Tracing liquid level and material boundaries in transparent vessels using the graph cut computer vision approach	Detection of boundaries of materials stored in transparent vessels is essential for identifying properties such as liquid level and phase boundaries, which are vital for controlling numerous processes in the industry and chemistry laboratory. This work presents a computer vision method for identifying the boundary of m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	51,538
2002.06282	Accurate Stress Assessment based on functional Near Infrared Spectroscopy using Deep Learning Approach	Stress is known as one of the major factors threatening human health. A large number of studies have been performed in order to either assess or relieve stress by analyzing the brain and heart-related signals. In this study, signals produced by functional Near-Infrared Spectroscopy (fNIRS) of the brain recorded from 10...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	164,139
2501.10105	Universal Actions for Enhanced Embodied Foundation Models	Training on diverse, internet-scale data is a key factor in the success of recent large foundation models. Yet, using the same recipe for building embodied agents has faced noticeable difficulties. Despite the availability of many crowd-sourced embodied datasets, their action spaces often exhibit significant heterogene...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	525,393
2310.11841	Classification Aggregation without Unanimity	A classification is a surjective mapping from a set of objects to a set of categories. A classification aggregation function aggregates every vector of classifications into a single one. We show that every citizen sovereign and independent classification aggregation function is essentially a dictatorship. This impossib...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	400,803
1805.02515	Generalized Random Gilbert-Varshamov Codes	We introduce a random coding technique for transmission over discrete memoryless channels, reminiscent of the basic construction attaining the Gilbert-Varshamov bound for codes in Hamming spaces. The code construction is based on drawing codewords recursively from a fixed type class, in such a way that a newly generate...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	96,875
2307.05620	Latent Space Perspicacity and Interpretation Enhancement (LS-PIE) Framework	Linear latent variable models such as principal component analysis (PCA), independent component analysis (ICA), canonical correlation analysis (CCA), and factor analysis (FA) identify latent directions (or loadings) either ordered or unordered. The data is then projected onto the latent directions to obtain their proje...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	378,803
2004.08878	Uncertainty-Aware Consistency Regularization for Cross-Domain Semantic Segmentation	Unsupervised domain adaptation (UDA) aims to adapt existing models of the source domain to a new target domain with only unlabeled data. Most existing methods suffer from noticeable negative transfer resulting from either the error-prone discriminator network or the unreasonable teacher model. Besides, the local region...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	173,196
2406.13493	In-Context In-Context Learning with Transformer Neural Processes	Neural processes (NPs) are a powerful family of meta-learning models that seek to approximate the posterior predictive map of the ground-truth stochastic process from which each dataset in a meta-dataset is sampled. There are many cases in which practitioners, besides having access to the dataset of interest, may also ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	465,876
1611.02062	Private Information Retrieval from Coded Databases with Colluding Servers	We present a general framework for Private Information Retrieval (PIR) from arbitrary coded databases, that allows one to adjust the rate of the scheme according to the suspected number of colluding servers. If the storage code is a generalized Reed-Solomon code of length n and dimension k, we design PIR schemes which ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	63,503
2501.03936	PPTAgent: Generating and Evaluating Presentations Beyond Text-to-Slides	Automatically generating presentations from documents is a challenging task that requires accommodating content quality, visual appeal, and structural coherence. Existing methods primarily focus on improving and evaluating the content quality in isolation, overlooking visual appeal and structural coherence, which limit...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	523,046
2012.14521	Minoration via Mixed Volumes and Cover's Problem for General Channels	We give a complete solution to an open problem of Thomas Cover in 1987 about the capacity of a relay channel in the general discrete memoryless setting without any additional assumptions. The key step in our approach is to lower bound a certain soft-max of a stochastic process by convex geometry methods, which is based...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	213,528
1511.09236	Giant component sizes in scale-free networks with power-law degrees and cutoffs	Scale-free networks arise from power-law degree distributions. Due to the finite size of real-world networks, the power law inevitably has a cutoff at some maximum degree $\Delta$. We investigate the relative size of the giant component $S$ in the large-network limit. We show that $S$ as a function of $\Delta$ increase...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	49,649
2002.11332	Structured Linear Contextual Bandits: A Sharp and Geometric Smoothed Analysis	Bandit learning algorithms typically involve the balance of exploration and exploitation. However, in many practical applications, worst-case scenarios needing systematic exploration are seldom encountered. In this work, we consider a smoothed setting for structured linear contextual bandits where the adversarial conte...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	165,680
1603.01768	Semantic Style Transfer and Turning Two-Bit Doodles into Fine Artworks	Convolutional neural networks (CNNs) have proven highly effective at image synthesis and style transfer. For most users, however, using them as tools can be a challenging task due to their unpredictable behavior that goes against common intuitions. This paper introduces a novel concept to augment such generative archit...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	52,930
1809.10421	Entropy versions of additive inequalities	The connection between inequalities in additive combinatorics and analogous versions in terms of the entropy of random variables has been extensively explored over the past few years. This paper extends a device introduced by Ruzsa in his seminal work introducing this correspondence. This extension provides a toolbox f...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	108,906
2406.00685	Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training	Adversarial training (AT) trains models using adversarial examples (AEs), which are natural images modified with specific perturbations to mislead the model. These perturbations are constrained by a predefined perturbation budget $\epsilon$ and are equally applied to each pixel within an image. However, in this paper, ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	459,980
1908.05368	Robust One-Bit Recovery via ReLU Generative Networks: Near-Optimal Statistical Rate and Global Landscape Analysis	We study the robust one-bit compressed sensing problem whose goal is to design an algorithm that faithfully recovers any sparse target vector $\theta_0\in\mathbb{R}^d$ \textit{uniformly} via $m$ quantized noisy measurements. Specifically, we consider a new framework for this problem where the sparsity is implicitly enf...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	141,696
1806.03551	An Estimation and Analysis Framework for the Rasch Model	The Rasch model is widely used for item response analysis in applications ranging from recommender systems to psychology, education, and finance. While a number of estimators have been proposed for the Rasch model over the last decades, the available analytical performance guarantees are mostly asymptotic. This paper p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	100,022
1801.09838	Multiple Accounts Detection on Facebook Using Semi-Supervised Learning on Graphs	In social networks, a single user may create multiple accounts to spread his / her opinions and to influence others, by actively comment on different news pages. It would be beneficial to both social networks and their communities, to demote such abnormal activities, and the first step is to detect those accounts. Howe...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	89,179
1402.6387	Active spline model: A shape based model-interactive segmentation	Rarely in literature a method of segmentation cares for the edit after the algorithm delivers. They provide no solution when segmentation goes wrong. We propose to formulate point distribution model in terms of centripetal-parameterized Catmull-Rom spline. Such fusion brings interactivity to model-based segmentation, s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	31,171
2105.04949	BERT is to NLP what AlexNet is to CV: Can Pre-Trained Language Models Identify Analogies?	Analogies play a central role in human commonsense reasoning. The ability to recognize analogies such as "eye is to seeing what ear is to hearing", sometimes referred to as analogical proportions, shape how we structure knowledge and understand language. Surprisingly, however, the task of identifying such analogies has...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	234,669
1906.01543	Training Neural Response Selection for Task-Oriented Dialogue Systems	Despite their popularity in the chatbot literature, retrieval-based models have had modest impact on task-oriented dialogue systems, with the main obstacle to their application being the low-data regime of most task-oriented dialogue tasks. Inspired by the recent success of pretraining in language modelling, we propose...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	133,745
2007.13881	iESC: iterative Equivalent Surface Current Approximation	A novel iterative Equivalent Surface Current (iESC) algorithm has been developed to simulate the electromagnetic scattering of electrically large dielectric objects with relatively smooth surfaces. The iESC algorithm corrects the surface currents to compensate for the electromagnetic field deviation across the dielectr...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	189,244
2112.12101	Faster indicators of dengue fever case counts using Google and Twitter	Dengue is a major threat to public health in Brazil, the world's sixth biggest country by population, with over 1.5 million cases recorded in 2019 alone. Official data on dengue case counts is delivered incrementally and, for many reasons, often subject to delays of weeks. In contrast, data on dengue-related Google sea...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	272,883
2406.00121	Empowering Visual Creativity: A Vision-Language Assistant to Image Editing Recommendations	Advances in text-based image generation and editing have revolutionized content creation, enabling users to create impressive content from imaginative text prompts. However, existing methods are not designed to work well with the oversimplified prompts that are often encountered in typical scenarios when users start th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	459,716
2107.14122	Safest Nearby Neighbor Queries in Road Networks (Full Version)	Traditional route planning and k nearest neighbors queries only consider distance or travel time and ignore road safety altogether. However, many travellers prefer to avoid risky or unpleasant road conditions such as roads with high crime rates (e.g., robberies, kidnapping, riots etc.) and bumpy roads. To facilitate sa...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	248,380
1708.07241	NNVLP: A Neural Network-Based Vietnamese Language Processing Toolkit	This paper demonstrates neural network-based toolkit namely NNVLP for essential Vietnamese language processing tasks including part-of-speech (POS) tagging, chunking, named entity recognition (NER). Our toolkit is a combination of bidirectional Long Short-Term Memory (Bi-LSTM), Convolutional Neural Network (CNN), Condi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	79,449
1402.3173	Homogenization of coupled heat and moisture transport in masonry structures including interfaces	Homogenization of a simultaneous heat and moisture flow in a masonry wall is presented in this paper. The principle objective is to examine an impact of the assumed imperfect hydraulic contact on the resulting homogenized properties. Such a contact is characterized by a certain mismatching resistance allowing us to rep...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	30,845
1302.4150	Duality in Entanglement-Assisted Quantum Error Correction	The dual of an entanglement-assisted quantum error-correcting (EAQEC) code is defined from the orthogonal group of a simplified stabilizer group. From the Poisson summation formula, this duality leads to the MacWilliams identities and linear programming bounds for EAQEC codes. We establish a table of upper and lower bo...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	22,129
2502.03356	Inverse Mixed Strategy Games with Generative Trajectory Models	Game-theoretic models are effective tools for modeling multi-agent interactions, especially when robots need to coordinate with humans. However, applying these models requires inferring their specifications from observed behaviors -- a challenging task known as the inverse game problem. Existing inverse game approaches...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	530,684
2308.08732	Recursive Detection and Analysis of Nanoparticles in Scanning Electron Microscopy Images	In this study, we present a computational framework tailored for the precise detection and comprehensive analysis of nanoparticles within scanning electron microscopy (SEM) images. The primary objective of this framework revolves around the accurate localization of nanoparticle coordinates, accompanied by secondary obj...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	386,009
2104.10330	BADet: Boundary-Aware 3D Object Detection from Point Clouds	Currently, existing state-of-the-art 3D object detectors are in two-stage paradigm. These methods typically comprise two steps: 1) Utilize a region proposal network to propose a handful of high-quality proposals in a bottom-up fashion. 2) Resize and pool the semantic features from the proposed regions to summarize RoI-...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	231,538
2011.00998	A Review On Software Defects Prediction Methods	Software quality is one of the essential aspects of a software. With increasing demand, software designs are becoming more complex, increasing the probability of software defects. Testers improve the quality of software by fixing defects. Hence the analysis of defects significantly improves software quality. The comple...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	204,447
2403.00349	Impact of Inter-Operator Interference via Reconfigurable Intelligent Surfaces	A wireless communication system is studied that operates in the presence of multiple reconfigurable intelligent surfaces (RISs). In particular, a multi-operator environment is considered where each operator utilizes an RIS to enhance its communication quality. Although out-of-band interference does not exist (since eac...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	433,951
2012.05084	DeepTalk: Vocal Style Encoding for Speaker Recognition and Speech Synthesis	Automatic speaker recognition algorithms typically characterize speech audio using short-term spectral features that encode the physiological and anatomical aspects of speech production. Such algorithms do not fully capitalize on speaker-dependent characteristics present in behavioral speech features. In this work, we ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	210,674
2406.01471	Inverse design of photonic surfaces on Inconel via multi-fidelity machine learning ensemble framework and high throughput femtosecond laser processing	We demonstrate a multi-fidelity (MF) machine learning ensemble framework for the inverse design of photonic surfaces, trained on a dataset of 11,759 samples that we fabricate using high throughput femtosecond laser processing. The MF ensemble combines an initial low fidelity model for generating design solutions, with ...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	460,333
1805.09266	Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems	Distributed machine learning (ML) is a modern computation paradigm that divides its workload into independent tasks that can be simultaneously achieved by multiple machines (i.e., agents) for better scalability. However, a typical distributed system is usually implemented with a central server that collects data statis...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	98,382
1904.03468	Deep Stacked Hierarchical Multi-patch Network for Image Deblurring	Despite deep end-to-end learning methods have shown their superiority in removing non-uniform motion blur, there still exist major challenges with the current multi-scale and scale-recurrent models: 1) Deconvolution/upsampling operations in the coarse-to-fine scheme result in expensive runtime; 2) Simply increasing the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	126,731
2412.17009	Generate to Discriminate: Expert Routing for Continual Learning	In many real-world settings, regulations and economic incentives permit the sharing of models but not data across institutional boundaries. In such scenarios, practitioners might hope to adapt models to new domains, without losing performance on previous domains (so-called catastrophic forgetting). While any single mod...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	519,794
2401.16638	Breaking Free Transformer Models: Task-specific Context Attribution Promises Improved Generalizability Without Fine-tuning Pre-trained LLMs	Fine-tuning large pre-trained language models (LLMs) on particular datasets is a commonly employed strategy in Natural Language Processing (NLP) classification tasks. However, this approach usually results in a loss of models generalizability. In this paper, we present a framework that allows for maintaining generaliza...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	424,912
2210.16915	Imitating Opponent to Win: Adversarial Policy Imitation Learning in Two-player Competitive Games	Recent research on vulnerabilities of deep reinforcement learning (RL) has shown that adversarial policies adopted by an adversary agent can influence a target RL agent (victim agent) to perform poorly in a multi-agent environment. In existing studies, adversarial policies are directly trained based on experiences of i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	327,499
1707.01203	Estimating the Fundamental Limits is Easier than Achieving the Fundamental Limits	We show through case studies that it is easier to estimate the fundamental limits of data processing than to construct explicit algorithms to achieve those limits. Focusing on binary classification, data compression, and prediction under logarithmic loss, we show that in the finite space setting, when it is possible to...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	76,489
2106.03820	Accurate Shapley Values for explaining tree-based models	Shapley Values (SV) are widely used in explainable AI, but their estimation and interpretation can be challenging, leading to inaccurate inferences and explanations. As a starting point, we remind an invariance principle for SV and derive the correct approach for computing the SV of categorical variables that are parti...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	239,471
0810.4884	The adaptability of physiological systems optimizes performance: new directions in augmentation	This paper contributes to the human-machine interface community in two ways: as a critique of the closed-loop AC (augmented cognition) approach, and as a way to introduce concepts from complex systems and systems physiology into the field. Of particular relevance is a comparison of the inverted-U (or Gaussian) model of...	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	2,566
2205.04612	Reconfigurable Robots for Scaling Reef Restoration	Coral reefs are under increasing threat from the impacts of climate change. Whilst current restoration approaches are effective, they require significant human involvement and equipment, and have limited deployment scale. Harvesting wild coral spawn from mass spawning events, rearing them to the larval stage and releas...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	295,689
1911.06928	Generalized Maximum Causal Entropy for Inverse Reinforcement Learning	We consider the problem of learning from demonstrated trajectories with inverse reinforcement learning (IRL). Motivated by a limitation of the classical maximum entropy model in capturing the structure of the network of states, we propose an IRL model based on a generalized version of the causal entropy maximization pr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	153,658
2311.07840	Enabling Decision-Support Systems through Automated Cell Tower Detection	Cell phone coverage and high-speed service gaps persist in rural areas in sub-Saharan Africa, impacting public access to mobile-based financial, educational, and humanitarian services. Improving maps of telecommunications infrastructure can help inform strategies to eliminate gaps in mobile coverage. Deep neural networ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	407,488
2302.13539	Finding Support Examples for In-Context Learning	Additionally, the strong dependency among in-context examples makes it an NP-hard combinatorial optimization problem and enumerating all permutations is infeasible. Hence we propose LENS, a fiLter-thEN-Search method to tackle this challenge in two stages: First we filter the dataset to obtain informative in-context exa...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	347,983
1312.3168	Semantic Types, Lexical Sorts and Classifiers	We propose a cognitively and linguistically motivated set of sorts for lexical semantics in a compositional setting: the classifiers in languages that do have such pronouns. These sorts are needed to include lexical considerations in a semantical analyser such as Boxer or Grail. Indeed, all proposed lexical extensions ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	29,018
2310.02776	Dynamic Shuffle: An Efficient Channel Mixture Method	The redundancy of Convolutional neural networks not only depends on weights but also depends on inputs. Shuffling is an efficient operation for mixing channel information but the shuffle order is usually pre-defined. To reduce the data-dependent redundancy, we devise a dynamic shuffle module to generate data-dependent ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	396,990
2304.03297	Neural Operator Learning for Ultrasound Tomography Inversion	Neural operator learning as a means of mapping between complex function spaces has garnered significant attention in the field of computational science and engineering (CS&E). In this paper, we apply Neural operator learning to the time-of-flight ultrasound computed tomography (USCT) problem. We learn the mapping betwe...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	356,750
2211.06360	Rethinking Log Odds: Linear Probability Modelling and Expert Advice in Interpretable Machine Learning	We introduce a family of interpretable machine learning models, with two broad additions: Linearised Additive Models (LAMs) which replace the ubiquitous logistic link function in General Additive Models (GAMs); and SubscaleHedge, an expert advice algorithm for combining base models trained on subsets of features called...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	329,863
1802.04236	Buy your coffee with bitcoin: Real-world deployment of a bitcoin point of sale terminal	In this paper we discuss existing approaches for Bitcoin payments, as suitable for a small business for small-value transactions. We develop an evaluation framework utilizing security, usability, deployability criteria,, examine several existing systems, tools. Following a requirements engineering approach, we designed...	true	false	false	true	false	false	false	false	false	false	false	false	true	true	false	false	false	true	90,177
2403.06102	Coherent Temporal Synthesis for Incremental Action Segmentation	Data replay is a successful incremental learning technique for images. It prevents catastrophic forgetting by keeping a reservoir of previous data, original or synthesized, to ensure the model retains past knowledge while adapting to novel concepts. However, its application in the video domain is rudimentary, as it sim...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	436,303
2406.02309	Effects of Exponential Gaussian Distribution on (Double Sampling) Randomized Smoothing	Randomized Smoothing (RS) is currently a scalable certified defense method providing robustness certification against adversarial examples. Although significant progress has been achieved in providing defenses against $\ell_p$ adversaries, the interaction between the smoothing distribution and the robustness certificat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	460,710
1907.03885	An Intrinsic Nearest Neighbor Analysis of Neural Machine Translation Architectures	Earlier approaches indirectly studied the information captured by the hidden states of recurrent and non-recurrent neural machine translation models by feeding them into different classifiers. In this paper, we look at the encoder hidden states of both transformer and recurrent machine translation models from the neare...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	137,958
1908.00976	A local direct method for module identification in dynamic networks with correlated noise	The identification of local modules in dynamic networks with known topology has recently been addressed by formulating conditions for arriving at consistent estimates of the module dynamics, under the assumption of having disturbances that are uncorrelated over the different nodes. The conditions typically reflect the ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	140,642
1707.01659	Distributed Event-Based State Estimation for Networked Systems: An LMI-Approach	In this work, a dynamic system is controlled by multiple sensor-actuator agents, each of them commanding and observing parts of the system's input and output. The different agents sporadically exchange data with each other via a common bus network according to local event-triggering protocols. From these data, each age...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	76,579
1507.02030	Beyond Convexity: Stochastic Quasi-Convex Optimization	Stochastic convex optimization is a basic and well studied primitive in machine learning. It is well known that convex and Lipschitz functions can be minimized efficiently using Stochastic Gradient Descent (SGD). The Normalized Gradient Descent (NGD) algorithm, is an adaptation of Gradient Descent, which updates accord...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	44,933
1710.03282	Checkpoint Ensembles: Ensemble Methods from a Single Training Process	We present the checkpoint ensembles method that can learn ensemble models on a single training process. Although checkpoint ensembles can be applied to any parametric iterative learning technique, here we focus on neural networks. Neural networks' composable and simple neurons make it possible to capture many individua...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	82,299
1710.02714	Interactive Learning of State Representation through Natural Language Instruction and Explanation	One significant simplification in most previous work on robot learning is the closed-world assumption where the robot is assumed to know ahead of time a complete set of predicates describing the state of the physical world. However, robots are not likely to have a complete model of the world especially when learning a ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	82,209
2306.17485	Detection-segmentation convolutional neural network for autonomous vehicle perception	Object detection and segmentation are two core modules of an autonomous vehicle perception system. They should have high efficiency and low latency while reducing computational complexity. Currently, the most commonly used algorithms are based on deep neural networks, which guarantee high efficiency but require high-pe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	376,720
2007.07550	Group Invariant Dictionary Learning	The dictionary learning problem concerns the task of representing data as sparse linear sums drawn from a smaller collection of basic building blocks. In application domains where such techniques are deployed, we frequently encounter datasets where some form of symmetry or invariance is present. Motivated by this obser...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	187,370
2004.04396	Score-Guided Generative Adversarial Networks	We propose a Generative Adversarial Network (GAN) that introduces an evaluator module using pre-trained networks. The proposed model, called score-guided GAN (ScoreGAN), is trained with an evaluation metric for GANs, i.e., the Inception score, as a rough guide for the training of the generator. By using another pre-tra...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	171,869
2502.13480	Astra: Efficient and Money-saving Automatic Parallel Strategies Search on Heterogeneous GPUs	In this paper, we introduce an efficient and money-saving automatic parallel strategies search framework on heterogeneous GPUs: Astra. First, Astra searches for the efficiency-optimal parallel strategy in both GPU configurations search space (GPU types and GPU numbers) and parallel parameters search space. Then, Astra ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	535,385
2107.06080	Practical and Configurable Network Traffic Classification Using Probabilistic Machine Learning	Network traffic classification that is widely applicable and highly accurate is valuable for many network security and management tasks. A flexible and easily configurable classification framework is ideal, as it can be customized for use in a wide variety of networks. In this paper, we propose a highly configurable an...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	245,979
2201.04082	NOMA Beamforming in SDMA Networks: Riding on Existing Beams or Forming New Ones?	In this letter, the design of non-orthogonal multiple access (NOMA) beamforming is investigated in a spatial division multiple access (SDMA) legacy system. In particular, two popular beamforming strategies in the NOMA literature, one to use existing SDMA beams and the other to form new beams, are adopted and compared. ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	275,013
2006.15005	Resource Allocation via Graph Neural Networks in Free Space Optical Fronthaul Networks	This paper investigates the optimal resource allocation in free space optical (FSO) fronthaul networks. The optimal allocation maximizes an average weighted sum-capacity subject to power limitation and data congestion constraints. Both adaptive power assignment and node selection are considered based on the instantaneo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	184,391
2203.02102	BEATS: An Open-Source, High-Precision, Multi-Channel EEG Acquisition Tool System	Stable and accurate electroencephalogram (EEG) signal acquisition is fundamental in non-invasive brain-computer interface (BCI) technology. Commonly used EEG acquisition system's hardware and software are usually closed-source. Its inability to flexible expansion and secondary development is a major obstacle to real-ti...	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	283,631
2304.10256	Indian Sign Language Recognition Using Mediapipe Holistic	Deaf individuals confront significant communication obstacles on a daily basis. Their inability to hear makes it difficult for them to communicate with those who do not understand sign language. Moreover, it presents difficulties in educational, occupational, and social contexts. By providing alternative communication ...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	359,348
2210.17400	Max Pooling with Vision Transformers reconciles class and shape in weakly supervised semantic segmentation	Weakly Supervised Semantic Segmentation (WSSS) research has explored many directions to improve the typical pipeline CNN plus class activation maps (CAM) plus refinements, given the image-class label as the only supervision. Though the gap with the fully supervised methods is reduced, further abating the spread seems u...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	327,670
1512.02406	Learning Discrete Bayesian Networks from Continuous Data	Learning Bayesian networks from raw data can help provide insights into the relationships between variables. While real data often contains a mixture of discrete and continuous-valued variables, many Bayesian network structure learning algorithms assume all random variables are discrete. Thus, continuous variables are ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	49,934
2007.12685	Semantic Segmentation With Multi Scale Spatial Attention For Self Driving Cars	In this paper, we present a novel neural network using multi scale feature fusion at various scales for accurate and efficient semantic image segmentation. We used ResNet based feature extractor, dilated convolutional layers in downsampling part, atrous convolutional layers in the upsampling part and used concat operat...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	188,894
2011.03395	Underspecification Presents Challenges for Credibility in Modern Machine Learning	ML models often exhibit unexpectedly poor behavior when they are deployed in real-world domains. We identify underspecification as a key reason for these failures. An ML pipeline is underspecified when it can return many predictors with equivalently strong held-out performance in the training domain. Underspecification...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	205,237
2010.13753	Handgun detection using combined human pose and weapon appearance	Closed-circuit television (CCTV) systems are essential nowadays to prevent security threats or dangerous situations, in which early detection is crucial. Novel deep learning-based methods have allowed to develop automatic weapon detectors with promising results. However, these approaches are mainly based on visual weap...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	203,243
2006.12779	Density-embedding layers: a general framework for adaptive receptive fields	The effectiveness and performance of artificial neural networks, particularly for visual tasks, depends in crucial ways on the receptive field of neurons. The receptive field itself depends on the interplay between several architectural aspects, including sparsity, pooling, and activation functions. In recent literatur...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	183,707
2311.11546	Correlation-based Dual-band THz Channel Measurements and Characterization in a Laboratory	The Terahertz band, spanning from 0.1~THz to 10~THz, is envisioned as a key technology to realize ultra-high data rates in the 6G and beyond mobile communication systems, due to its abundant bandwidth resource. However, to realize THz communications, one substantial step is to fully understand the THz channels, which r...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	408,986
1807.11846	Resource Allocation in Full-Duplex Mobile-Edge Computing Systems with NOMA and Energy Harvesting	This paper considers a full-duplex (FD) mobile-edge computing (MEC) system with non-orthogonal multiple access (NOMA) and energy harvesting (EH), where one group of users simultaneously offload task data to the base station (BS) via NOMA and the BS simultaneously receive data and broadcast energy to other group of user...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	104,262
2006.08419	Spherical Motion Dynamics: Learning Dynamics of Neural Network with Normalization, Weight Decay, and SGD	In this work, we comprehensively reveal the learning dynamics of neural network with normalization, weight decay (WD), and SGD (with momentum), named as Spherical Motion Dynamics (SMD). Most related works study SMD by focusing on "effective learning rate" in "equilibrium" condition, where weight norm remains unchanged....	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	182,185
2112.03099	VocBench: A Neural Vocoder Benchmark for Speech Synthesis	Neural vocoders, used for converting the spectral representations of an audio signal to the waveforms, are a commonly used component in speech synthesis pipelines. It focuses on synthesizing waveforms from low-dimensional representation, such as Mel-Spectrograms. In recent years, different approaches have been introduc...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	270,082
1504.06761	Structural Properties of Index Coding Capacity Using Fractional Graph Theory	The capacity region of the index coding problem is characterized through the notion of confusion graph and its fractional chromatic number. Based on this multiletter characterization, several structural properties of the capacity region are established, some of which are already noted by Tahmasbi, Shahrasbi, and Gohari...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	42,448
2308.08806	Self-distillation Regularized Connectionist Temporal Classification Loss for Text Recognition: A Simple Yet Effective Approach	Text recognition methods are gaining rapid development. Some advanced techniques, e.g., powerful modules, language models, and un- and semi-supervised learning schemes, consecutively push the performance on public benchmarks forward. However, the problem of how to better optimize a text recognition model from the persp...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	386,044
2206.05741	Bootstrapping Multi-view Representations for Fake News Detection	Previous researches on multimedia fake news detection include a series of complex feature extraction and fusion networks to gather useful information from the news. However, how cross-modal consistency relates to the fidelity of news and how features from different modalities affect the decision-making are still open q...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	302,118
2310.11611	In defense of parameter sharing for model-compression	When considering a model architecture, there are several ways to reduce its memory footprint. Historically, popular approaches included selecting smaller architectures and creating sparse networks through pruning. More recently, randomized parameter-sharing (RPS) methods have gained traction for model compression at st...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	400,704
2106.13967	Exploring Temporal Context and Human Movement Dynamics for Online Action Detection in Videos	Nowadays, the interaction between humans and robots is constantly expanding, requiring more and more human motion recognition applications to operate in real time. However, most works on temporal action detection and recognition perform these tasks in offline manner, i.e. temporally segmented videos are classified as a...	true	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	243,251
2103.13613	Gaussian Guided IoU: A Better Metric for Balanced Learning on Object Detection	For most of the anchor-based detectors, Intersection over Union(IoU) is widely utilized to assign targets for the anchors during training. However, IoU pays insufficient attention to the closeness of the anchor's center to the truth box's center. This results in two problems: (1) only one anchor is assigned to most of ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	226,556
2502.01035	UASTHN: Uncertainty-Aware Deep Homography Estimation for UAV Satellite-Thermal Geo-localization	Geo-localization is an essential component of Unmanned Aerial Vehicle (UAV) navigation systems to ensure precise absolute self-localization in outdoor environments. To address the challenges of GPS signal interruptions or low illumination, Thermal Geo-localization (TG) employs aerial thermal imagery to align with refer...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	529,658
1801.00259	PolicySpace: a modeling platform	Public Policy involves proposing changes to existing practices, alternatives, new habits. Citizens and institutions react accordingly, accepting, refuting or adapting. Agent-based modeling is a tool that can enrich the policy analysis package explicitly considering dynamics, space and individual-level interactions. Thi...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	87,533
1707.00549	A new class of permutation trinomials constructed from Niho exponents	Permutation polynomials over finite fields are an interesting subject due to their important applications in the areas of mathematics and engineering. In this paper we investigate the trinomial $f(x)=x^{(p-1)q+1}+x^{pq}-x^{q+(p-1)}$ over the finite field $\mathbb{F}_{q^2}$, where $p$ is an odd prime and $q=p^k$ with $k...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	76,369
2206.13914	Dependency Parsing with Backtracking using Deep Reinforcement Learning	Greedy algorithms for NLP such as transition based parsing are prone to error propagation. One way to overcome this problem is to allow the algorithm to backtrack and explore an alternative solution in cases where new evidence contradicts the solution explored so far. In order to implement such a behavior, we use reinf...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	305,117
1712.06157	Oscillation energy based sensitivity analysis and control for multi-mode oscillation systems	This paper describes a novel approach to analyze and control systems with multi-mode oscillation problems. Traditional single dominant mode analysis fails to provide effective control actions when several modes have similar low damping ratios. This work addresses this problem by considering all modes in the formulation...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	86,842
2304.13681	Ray Conditioning: Trading Photo-consistency for Photo-realism in Multi-view Image Generation	Multi-view image generation attracts particular attention these days due to its promising 3D-related applications, e.g., image viewpoint editing. Most existing methods follow a paradigm where a 3D representation is first synthesized, and then rendered into 2D images to ensure photo-consistency across viewpoints. Howeve...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	360,668
2403.02274	NatSGD: A Dataset with Speech, Gestures, and Demonstrations for Robot Learning in Natural Human-Robot Interaction	Recent advancements in multimodal Human-Robot Interaction (HRI) datasets have highlighted the fusion of speech and gesture, expanding robots' capabilities to absorb explicit and implicit HRI insights. However, existing speech-gesture HRI datasets often focus on elementary tasks, like object pointing and pushing, reveal...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	434,750
2411.12547	S3TU-Net: Structured Convolution and Superpixel Transformer for Lung Nodule Segmentation	The irregular and challenging characteristics of lung adenocarcinoma nodules in computed tomography (CT) images complicate staging diagnosis, making accurate segmentation critical for clinicians to extract detailed lesion information. In this study, we propose a segmentation model, S3TU-Net, which integrates multi-dime...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	509,444
2406.05938	Expressive Power of Graph Neural Networks for (Mixed-Integer) Quadratic Programs	Quadratic programming (QP) is the most widely applied category of problems in nonlinear programming. Many applications require real-time/fast solutions, though not necessarily with high precision. Existing methods either involve matrix decomposition or use the preconditioned conjugate gradient method. For relatively la...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	462,358
2310.03602	Ctrl-Room: Controllable Text-to-3D Room Meshes Generation with Layout Constraints	Text-driven 3D indoor scene generation is useful for gaming, the film industry, and AR/VR applications. However, existing methods cannot faithfully capture the room layout, nor do they allow flexible editing of individual objects in the room. To address these problems, we present Ctrl-Room, which can generate convincin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	397,341

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