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
2103.14187	Beyond Low-Pass Filters: Adaptive Feature Propagation on Graphs	Graph neural networks (GNNs) have been extensively studied for prediction tasks on graphs. As pointed out by recent studies, most GNNs assume local homophily, i.e., strong similarities in local neighborhoods. This assumption however limits the generalizability power of GNNs. To address this limitation, we propose a fle...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	226,758
2206.05964	Techno Economic Modeling for Agrivoltaics: Can Agrivoltaics be more profitable than Ground mounted PV?	Agrivoltaics (AV) is a dual land-use approach to collocate solar energy generation with agriculture for preserving the terrestrial ecosystem and enabling food-energy-water synergies. Here, we present a systematic approach to model the economic performance of AV relative to standalone ground-mounted PV (GMPV) and explor...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	302,199
2403.08319	Knowledge Conflicts for LLMs: A Survey	This survey provides an in-depth analysis of knowledge conflicts for large language models (LLMs), highlighting the complex challenges they encounter when blending contextual and parametric knowledge. Our focus is on three categories of knowledge conflicts: context-memory, inter-context, and intra-memory conflict. Thes...	false	false	false	false	true	true	true	false	true	false	false	false	false	false	false	false	false	false	437,292
1903.11261	Convolution Attack on Frequency-Hopping by Full-Duplex Radios	We propose a new adversarial attack on frequency-hopping based wireless communication between two users, namely Alice and Bob. In this attack, the adversary, referred to as Eve, instantaneously modifies the transmitted signal by Alice before forwarding it to Bob within the symbol-period. We show that this attack forces...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	125,470
2312.05451	Real-time Building Energy Storage Scheduling under Electrical Load Uncertainty: A Dynamic Markov Decision Process Approach with Comprehensive Analysis of Different Pricing Policies	In response to the increasing deployment of battery storage systems for cost reduction and grid stress mitigation, this study presents the development of a new real-time Markov decision process model to efficiently schedule battery systems in buildings under electrical load uncertainty. The proposed model incorporates ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	414,090
2308.13453	Learning to Intervene on Concept Bottlenecks	While deep learning models often lack interpretability, concept bottleneck models (CBMs) provide inherent explanations via their concept representations. Moreover, they allow users to perform interventional interactions on these concepts by updating the concept values and thus correcting the predictive output of the mo...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	387,924
1906.04177	Estimating Causal Effects of Tone in Online Debates	Statistical methods applied to social media posts shed light on the dynamics of online dialogue. For example, users' wording choices predict their persuasiveness and users adopt the language patterns of other dialogue participants. In this paper, we estimate the causal effect of reply tones in debates on linguistic and...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	134,631
1906.11331	$H_{\infty}$-Control of Grid-Connected Converters: Design, Objectives and Decentralized Stability Certificates	The modern power system features high penetration of power converters due to the development of renewables, HVDC, etc. Currently, the controller design and parameter tuning of power converters heavily rely on rich engineering experience and extrapolation from a single converter system, which may lead to inferior perfor...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	136,639
2301.13856	Simplex Random Features	We present Simplex Random Features (SimRFs), a new random feature (RF) mechanism for unbiased approximation of the softmax and Gaussian kernels by geometrical correlation of random projection vectors. We prove that SimRFs provide the smallest possible mean square error (MSE) on unbiased estimates of these kernels among...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	343,058
1912.08637	Generalized Residual Ratio Thresholding	Simultaneous orthogonal matching pursuit (SOMP) and block OMP (BOMP) are two widely used techniques for sparse support recovery in multiple measurement vector (MMV) and block sparse (BS) models respectively. For optimal performance, both SOMP and BOMP require \textit{a priori} knowledge of signal sparsity or noise vari...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	157,881
2104.12277	Reranking Machine Translation Hypotheses with Structured and Web-based Language Models	In this paper, we investigate the use of linguistically motivated and computationally efficient structured language models for reranking N-best hypotheses in a statistical machine translation system. These language models, developed from Constraint Dependency Grammar parses, tightly integrate knowledge of words, morpho...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	232,160
1704.01184	On the Unreported-Profile-is-Negative Assumption for Predictive Cheminformatics	In cheminformatics, compound-target binding profiles has been a main source of data for research. For data repositories that only provide positive profiles, a popular assumption is that unreported profiles are all negative. In this paper, we caution audience not to take this assumption for granted, and present empirica...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	71,205
2112.01738	Joint User Scheduling and Beamforming Design for Multiuser MISO Downlink Systems	In multiuser communication systems, user scheduling and beamforming (US-BF) design are two fundamental problems that are usually studied separately in the existing literature. In this work, we focus on the joint US-BF design with the goal of maximizing the set cardinality of scheduled users, which is computationally ch...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	269,595
2312.00487	Explainable AI in Diagnosing and Anticipating Leukemia Using Transfer Learning Method	This research paper focuses on Acute Lymphoblastic Leukemia (ALL), a form of blood cancer prevalent in children and teenagers, characterized by the rapid proliferation of immature white blood cells (WBCs). These atypical cells can overwhelm healthy cells, leading to severe health consequences. Early and accurate detect...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	412,069
1912.04749	Efficient Differentiable Neural Architecture Search with Meta Kernels	The searching procedure of neural architecture search (NAS) is notoriously time consuming and cost prohibitive.To make the search space continuous, most existing gradient-based NAS methods relax the categorical choice of a particular operation to a softmax over all possible operations and calculate the weighted sum of ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	156,918
2408.17356	C-RADAR: A Centralized Deep Learning System for Intrusion Detection in Software Defined Networks	The popularity of Software Defined Networks (SDNs) has grown in recent years, mainly because of their ability to simplify network management and improve network flexibility. However, this also makes them vulnerable to various types of cyber attacks. SDNs work on a centralized control plane which makes them more prone t...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	484,676
2312.16141	VirtualPainting: Addressing Sparsity with Virtual Points and Distance-Aware Data Augmentation for 3D Object Detection	In recent times, there has been a notable surge in multimodal approaches that decorates raw LiDAR point clouds with camera-derived features to improve object detection performance. However, we found that these methods still grapple with the inherent sparsity of LiDAR point cloud data, primarily because fewer points are...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	418,275
2310.02456	Learning Optimal Advantage from Preferences and Mistaking it for Reward	We consider algorithms for learning reward functions from human preferences over pairs of trajectory segments, as used in reinforcement learning from human feedback (RLHF). Most recent work assumes that human preferences are generated based only upon the reward accrued within those segments, or their partial return. Re...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	396,856
2409.15019	Evaluating Synthetic Activations composed of SAE Latents in GPT-2	Sparse Auto-Encoders (SAEs) are commonly employed in mechanistic interpretability to decompose the residual stream into monosemantic SAE latents. Recent work demonstrates that perturbing a model's activations at an early layer results in a step-function-like change in the model's final layer activations. Furthermore, t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	490,724
2110.11661	UVO Challenge on Video-based Open-World Segmentation 2021: 1st Place Solution	In this report, we introduce our (pretty straightforard) two-step "detect-then-match" video instance segmentation method. The first step performs instance segmentation for each frame to get a large number of instance mask proposals. The second step is to do inter-frame instance mask matching with the help of optical fl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	262,564
2306.09424	SSL4EO-L: Datasets and Foundation Models for Landsat Imagery	The Landsat program is the longest-running Earth observation program in history, with 50+ years of data acquisition by 8 satellites. The multispectral imagery captured by sensors onboard these satellites is critical for a wide range of scientific fields. Despite the increasing popularity of deep learning and remote sen...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	373,824
1511.09368	A neurodynamic framework for local community extraction in networks	To understand the structure and organization of a large-scale social, biological or technological network, it can be helpful to describe and extract local communities or modules of the network. In this article, we develop a neurodynamic framework to describe the local communities which correspond to the stable states o...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	49,658
2007.15781	LEMMA: A Multi-view Dataset for Learning Multi-agent Multi-task Activities	Understanding and interpreting human actions is a long-standing challenge and a critical indicator of perception in artificial intelligence. However, a few imperative components of daily human activities are largely missed in prior literature, including the goal-directed actions, concurrent multi-tasks, and collaborati...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	189,755
1801.02054	Explorations in an English Poetry Corpus: A Neurocognitive Poetics Perspective	This paper describes a corpus of about 3000 English literary texts with about 250 million words extracted from the Gutenberg project that span a range of genres from both fiction and non-fiction written by more than 130 authors (e.g., Darwin, Dickens, Shakespeare). Quantitative Narrative Analysis (QNA) is used to explo...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	87,852
1408.6587	Performance Comparison Between MIMO and SISO based on Indoor Field Measurements	In this paper, we quantify performance gain achieved if SISO system is replaced with 4x4 MIMO in WLAN setting compatible with IEEE 802.11n standard. We compare throughput and power savings in MIMO by taking field measurements at various indoor locations. Measurements are validated with simulations that include differen...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	35,638
2312.07630	Building Universal Foundation Models for Medical Image Analysis with Spatially Adaptive Networks	Recent advancements in foundation models, typically trained with self-supervised learning on large-scale and diverse datasets, have shown great potential in medical image analysis. However, due to the significant spatial heterogeneity of medical imaging data, current models must tailor specific structures for different...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	415,003
2408.04315	Federated Cubic Regularized Newton Learning with Sparsification-amplified Differential Privacy	This paper investigates the use of the cubic-regularized Newton method within a federated learning framework while addressing two major concerns that commonly arise in federated learning: privacy leakage and communication bottleneck. We introduce a federated learning algorithm called Differentially Private Federated Cu...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	479,344
1306.6709	A Survey on Metric Learning for Feature Vectors and Structured Data	The need for appropriate ways to measure the distance or similarity between data is ubiquitous in machine learning, pattern recognition and data mining, but handcrafting such good metrics for specific problems is generally difficult. This has led to the emergence of metric learning, which aims at automatically learning...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	25,496
2303.15833	Complementary Domain Adaptation and Generalization for Unsupervised Continual Domain Shift Learning	Continual domain shift poses a significant challenge in real-world applications, particularly in situations where labeled data is not available for new domains. The challenge of acquiring knowledge in this problem setting is referred to as unsupervised continual domain shift learning. Existing methods for domain adapta...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	354,641
2008.01341	Appearance Consensus Driven Self-Supervised Human Mesh Recovery	We present a self-supervised human mesh recovery framework to infer human pose and shape from monocular images in the absence of any paired supervision. Recent advances have shifted the interest towards directly regressing parameters of a parametric human model by supervising them on large-scale datasets with 2D landma...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	190,284
2101.09420	Deep Anti-aliasing of Whole Focal Stack Using Slice Spectrum	The paper aims at removing the aliasing effects of the whole focal stack generated from a sparse-sampled {4D} light field, while keeping the consistency across all the focal layers. We first explore the structural characteristics embedded in the focal stack slice and its corresponding frequency-domain representation, i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	216,591
2501.10131	ACE: Anatomically Consistent Embeddings in Composition and Decomposition	Medical images acquired from standardized protocols show consistent macroscopic or microscopic anatomical structures, and these structures consist of composable/decomposable organs and tissues, but existing self-supervised learning (SSL) methods do not appreciate such composable/decomposable structure attributes inhere...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	525,404
2111.00626	Intrusion Detection using Spatial-Temporal features based on Riemannian Manifold	Network traffic data is a combination of different data bytes packets under different network protocols. These traffic packets have complex time-varying non-linear relationships. Existing state-of-the-art methods rise up to this challenge by fusing features into multiple subsets based on correlations and using hybrid c...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	264,282
1708.05512	Large Margin Learning in Set to Set Similarity Comparison for Person Re-identification	Person re-identification (Re-ID) aims at matching images of the same person across disjoint camera views, which is a challenging problem in multimedia analysis, multimedia editing and content-based media retrieval communities. The major challenge lies in how to preserve similarity of the same person across video footag...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	79,145
2004.08945	Exploring Racial Bias within Face Recognition via per-subject Adversarially-Enabled Data Augmentation	Whilst face recognition applications are becoming increasingly prevalent within our daily lives, leading approaches in the field still suffer from performance bias to the detriment of some racial profiles within society. In this study, we propose a novel adversarial derived data augmentation methodology that aims to en...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	173,216
2402.03021	Data-induced multiscale losses and efficient multirate gradient descent schemes	This paper investigates the impact of multiscale data on machine learning algorithms, particularly in the context of deep learning. A dataset is multiscale if its distribution shows large variations in scale across different directions. This paper reveals multiscale structures in the loss landscape, including its gradi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	426,828
2502.06097	NLGR: Utilizing Neighbor Lists for Generative Rerank in Personalized Recommendation Systems	Reranking plays a crucial role in modern multi-stage recommender systems by rearranging the initial ranking list. Due to the inherent challenges of combinatorial search spaces, some current research adopts an evaluator-generator paradigm, with a generator generating feasible sequences and an evaluator selecting the bes...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	531,918
2310.19240	M4LE: A Multi-Ability Multi-Range Multi-Task Multi-Domain Long-Context Evaluation Benchmark for Large Language Models	Managing long sequences has become an important and necessary feature for large language models (LLMs). However, it is still an open question of how to comprehensively and systematically evaluate the long-sequence capability of LLMs. One of the reasons is that conventional and widely-used benchmarks mainly consist of s...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	403,911
2208.03703	Granger Causality using Neural Networks	Dependence between nodes in a network is an important concept that pervades many areas including finance, politics, sociology, genomics and the brain sciences. One way to characterize dependence between components of a multivariate time series data is via Granger Causality (GC). Standard traditional approaches to GC es...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	311,871
2402.00712	ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction	Accurate prediction of climate in the subseasonal-to-seasonal scale is crucial for disaster preparedness and robust decision making amidst climate change. Yet, forecasting beyond the weather timescale is challenging because it deals with problems other than initial condition, including boundary interaction, butterfly e...	false	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	425,694
2310.09669	A Framework For Automated Dissection Along Tissue Boundary	Robotic surgery promises enhanced precision and adaptability over traditional surgical methods. It also offers the possibility of automating surgical interventions, resulting in reduced stress on the surgeon, better surgical outcomes, and lower costs. Cholecystectomy, the removal of the gallbladder, serves as an ideal ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	399,883
2409.08396	Federated One-Shot Ensemble Clustering	Cluster analysis across multiple institutions poses significant challenges due to data-sharing restrictions. To overcome these limitations, we introduce the Federated One-shot Ensemble Clustering (FONT) algorithm, a novel solution tailored for multi-site analyses under such constraints. FONT requires only a single roun...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	487,888
1303.2309	On the Performance Limits of Map-Aware Localization	Establishing bounds on the accuracy achievable by localization techniques represents a fundamental technical issue. Bounds on localization accuracy have been derived for cases in which the position of an agent is estimated on the basis of a set of observations and, possibly, of some a priori information related to them...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	22,819
2308.05602	Object Goal Navigation with Recursive Implicit Maps	Object goal navigation aims to navigate an agent to locations of a given object category in unseen environments. Classical methods explicitly build maps of environments and require extensive engineering while lacking semantic information for object-oriented exploration. On the other hand, end-to-end learning methods al...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	384,849
2412.05586	Towards Learning to Reason: Comparing LLMs with Neuro-Symbolic on Arithmetic Relations in Abstract Reasoning	This work compares large language models (LLMs) and neuro-symbolic approaches in solving Raven's progressive matrices (RPM), a visual abstract reasoning test that involves the understanding of mathematical rules such as progression or arithmetic addition. Providing the visual attributes directly as textual prompts, whi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	514,893
1106.4907	Face Identification from Manipulated Facial Images using SIFT	Editing on digital images is ubiquitous. Identification of deliberately modified facial images is a new challenge for face identification system. In this paper, we address the problem of identification of a face or person from heavily altered facial images. In this face identification problem, the input to the system i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	10,978
2110.15264	CIIA:A New Algorithm for Community Detection	In this paper, through thinking on the modularity function that measures the standard of community division, a new algorithm for dividing communities is proposed, called the Connect Intensity Iteration algorithm, or CIIA for short. In this algorithm, a new indicator is proposed.This indicator is the difference between ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	263,825
2311.15380	Grafite: Taming Adversarial Queries with Optimal Range Filters	Range filters allow checking whether a query range intersects a given set of keys with a chance of returning a false positive answer, thus generalising the functionality of Bloom filters from point to range queries. Existing practical range filters have addressed this problem heuristically, resulting in high false posi...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	410,490
2104.08261	Adaptive Robust Model Predictive Control with Matched and Unmatched Uncertainty	We propose a learning-based robust predictive control algorithm that compensates for significant uncertainty in the dynamics for a class of discrete-time systems that are nominally linear with an additive nonlinear component. Such systems commonly model the nonlinear effects of an unknown environment on a nominal syste...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	230,726
2404.09976	Diffscaler: Enhancing the Generative Prowess of Diffusion Transformers	Recently, diffusion transformers have gained wide attention with its excellent performance in text-to-image and text-to-vidoe models, emphasizing the need for transformers as backbone for diffusion models. Transformer-based models have shown better generalization capability compared to CNN-based models for general visi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	446,905
1311.1490	On Unconditionally Secure Multiparty Computation for Realizing Correlated Equilibria in Games	In game theory, a trusted mediator acting on behalf of the players can enable the attainment of correlated equilibria, which may provide better payoffs than those available from the Nash equilibria alone. We explore the approach of replacing the trusted mediator with an unconditionally secure sampling protocol that joi...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	true	28,238
1603.01250	Decision Forests, Convolutional Networks and the Models in-Between	This paper investigates the connections between two state of the art classifiers: decision forests (DFs, including decision jungles) and convolutional neural networks (CNNs). Decision forests are computationally efficient thanks to their conditional computation property (computation is confined to only a small region o...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	52,871
2410.00479	Precise Workcell Sketching from Point Clouds Using an AR Toolbox	Capturing real-world 3D spaces as point clouds is efficient and descriptive, but it comes with sensor errors and lacks object parametrization. These limitations render point clouds unsuitable for various real-world applications, such as robot programming, without extensive post-processing (e.g., outlier removal, semant...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	493,396
2012.02930	Optimizing Multiple Performance Metrics with Deep GSP Auctions for E-commerce Advertising	In e-commerce advertising, the ad platform usually relies on auction mechanisms to optimize different performance metrics, such as user experience, advertiser utility, and platform revenue. However, most of the state-of-the-art auction mechanisms only focus on optimizing a single performance metric, e.g., either social...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	true	209,919
1902.05326	Sinkhorn Divergence of Topological Signature Estimates for Time Series Classification	Distinguishing between classes of time series sampled from dynamic systems is a common challenge in systems and control engineering, for example in the context of health monitoring, fault detection, and quality control. The challenge is increased when no underlying model of a system is known, measurement noise is prese...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	121,513
2108.11535	ChessMix: Spatial Context Data Augmentation for Remote Sensing Semantic Segmentation	Labeling semantic segmentation datasets is a costly and laborious process if compared with tasks like image classification and object detection. This is especially true for remote sensing applications that not only work with extremely high spatial resolution data but also commonly require the knowledge of experts of th...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	252,202
2405.18040	Fast-FedUL: A Training-Free Federated Unlearning with Provable Skew Resilience	Federated learning (FL) has recently emerged as a compelling machine learning paradigm, prioritizing the protection of privacy for training data. The increasing demand to address issues such as ``the right to be forgotten'' and combat data poisoning attacks highlights the importance of techniques, known as \textit{unle...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	458,249
2412.06158	Is the neural tangent kernel of PINNs deep learning general partial differential equations always convergent ?	In this paper, we study the neural tangent kernel (NTK) for general partial differential equations (PDEs) based on physics-informed neural networks (PINNs). As we all know, the training of an artificial neural network can be converted to the evolution of NTK. We analyze the initialization of NTK and the convergence con...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	515,118
1909.12117	Balanced Binary Neural Networks with Gated Residual	Binary neural networks have attracted numerous attention in recent years. However, mainly due to the information loss stemming from the biased binarization, how to preserve the accuracy of networks still remains a critical issue. In this paper, we attempt to maintain the information propagated in the forward process an...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	147,028
2410.08820	Which Demographics do LLMs Default to During Annotation?	Demographics and cultural background of annotators influence the labels they assign in text annotation -- for instance, an elderly woman might find it offensive to read a message addressed to a "bro", but a male teenager might find it appropriate. It is therefore important to acknowledge label variations to not under-r...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	497,290
2412.07584	Multimodal Contextualized Support for Enhancing Video Retrieval System	Current video retrieval systems, especially those used in competitions, primarily focus on querying individual keyframes or images rather than encoding an entire clip or video segment. However, queries often describe an action or event over a series of frames, not a specific image. This results in insufficient informat...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	515,721
2404.01717	AddSR: Accelerating Diffusion-based Blind Super-Resolution with Adversarial Diffusion Distillation	Blind super-resolution methods based on stable diffusion showcase formidable generative capabilities in reconstructing clear high-resolution images with intricate details from low-resolution inputs. However, their practical applicability is often hampered by poor efficiency, stemming from the requirement of thousands o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	443,550
1603.08329	Spatially self-organized resilient networks by a distributed cooperative mechanism	The robustness of connectivity and the efficiency of paths are incompatible in many real networks. We propose a self-organization mechanism for incrementally generating onion-like networks with positive degree-degree correlations whose robustness is nearly optimal. As a spatial extension of the generation model based o...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	53,771
2407.04057	TALENT: A Tabular Analytics and Learning Toolbox	Tabular data is one of the most common data sources in machine learning. Although a wide range of classical methods demonstrate practical utilities in this field, deep learning methods on tabular data are becoming promising alternatives due to their flexibility and ability to capture complex interactions within the dat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	470,408
2304.03081	Safe MDP Planning by Learning Temporal Patterns of Undesirable Trajectories and Averting Negative Side Effects	In safe MDP planning, a cost function based on the current state and action is often used to specify safety aspects. In the real world, often the state representation used may lack sufficient fidelity to specify such safety constraints. Operating based on an incomplete model can often produce unintended negative side e...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	356,659
2412.08412	Pragmatist: Multiview Conditional Diffusion Models for High-Fidelity 3D Reconstruction from Unposed Sparse Views	Inferring 3D structures from sparse, unposed observations is challenging due to its unconstrained nature. Recent methods propose to predict implicit representations directly from unposed inputs in a data-driven manner, achieving promising results. However, these methods do not utilize geometric priors and cannot halluc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	516,075
1706.08313	A simple method for shifting local dq impedance models to a global reference frame for stability analysis	Impedance-based stability analysis in the dq-domain is a widely applied method for power electronic dominated systems. An inconvenient property with this method is that impedance models are normally referred to their own local reference frame, and need to be recalculated when referring to a global reference frame in a ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	75,975
2408.05486	Topological Blindspots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity	Topological deep learning (TDL) is a rapidly growing field that seeks to leverage topological structure in data and facilitate learning from data supported on topological objects, ranging from molecules to 3D shapes. Most TDL architectures can be unified under the framework of higher-order message-passing (HOMP), which...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	479,810
1211.1800	A Comparative study of Arabic handwritten characters invariant feature	This paper is practically interested in the unchangeable feature of Arabic handwritten character. It presents results of comparative study achieved on certain features extraction techniques of handwritten character, based on Hough transform, Fourier transform, Wavelet transform and Gabor Filter. Obtained results show t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	19,632
2405.18377	LLaMA-NAS: Efficient Neural Architecture Search for Large Language Models	The abilities of modern large language models (LLMs) in solving natural language processing, complex reasoning, sentiment analysis and other tasks have been extraordinary which has prompted their extensive adoption. Unfortunately, these abilities come with very high memory and computational costs which precludes the us...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	458,400
2101.01251	Robust Maximum Entropy Behavior Cloning	Imitation learning (IL) algorithms use expert demonstrations to learn a specific task. Most of the existing approaches assume that all expert demonstrations are reliable and trustworthy, but what if there exist some adversarial demonstrations among the given data-set? This may result in poor decision-making performance...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	214,318
1606.07365	Parallel SGD: When does averaging help?	Consider a number of workers running SGD independently on the same pool of data and averaging the models every once in a while -- a common but not well understood practice. We study model averaging as a variance-reducing mechanism and describe two ways in which the frequency of averaging affects convergence. For convex...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	57,706
2304.09526	Progressive Transfer Learning for Dexterous In-Hand Manipulation with Multi-Fingered Anthropomorphic Hand	Dexterous in-hand manipulation for a multi-fingered anthropomorphic hand is extremely difficult because of the high-dimensional state and action spaces, rich contact patterns between the fingers and objects. Even though deep reinforcement learning has made moderate progress and demonstrated its strong potential for man...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	359,082
1305.7316	A hybrid approach for semantic enrichment of MathML mathematical expressions	In this paper, we present a new approach to the semantic enrichment of mathematical expression problem. Our approach is a combination of statistical machine translation and disambiguation which makes use of surrounding text of the mathematical expressions. We first use Support Vector Machine classifier to disambiguate ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	24,895
2301.08140	Regularising disparity estimation via multi task learning with structured light reconstruction	3D reconstruction is a useful tool for surgical planning and guidance. However, the lack of available medical data stunts research and development in this field, as supervised deep learning methods for accurate disparity estimation rely heavily on large datasets containing ground truth information. Alternative approach...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	341,110
2406.10727	Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights	Given the ubiquity of graph data and its applications in diverse domains, building a Graph Foundation Model (GFM) that can work well across different graphs and tasks with a unified backbone has recently garnered significant interests. A major obstacle to achieving this goal stems from the fact that graphs from differe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	464,527
1709.07528	Defining a Lingua Franca to Open the Black Box of a Na\"ive Bayes Recommender	Many AI systems have a black box nature that makes it difficult to understand how they make their recommendations. This can be unsettling, as the designer cannot be certain how the system will respond to novelty. To penetrate our Na\"ive Bayes recommender's black box, we first asked, what do we want to know from our sy...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	81,290
1311.6243	Web-page Indexing based on the Prioritize Ontology Terms	In this world, globalization has become a basic and most popular human trend. To globalize information, people are going to publish the documents in the internet. As a result, information volume of internet has become huge. To handle that huge volume of information, Web searcher uses search engines. The Webpage indexin...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	28,639
2001.01550	Opportunities and Challenges of Deep Learning Methods for Electrocardiogram Data: A Systematic Review	Background:The electrocardiogram (ECG) is one of the most commonly used diagnostic tools in medicine and healthcare. Deep learning methods have achieved promising results on predictive healthcare tasks using ECG signals. Objective:This paper presents a systematic review of deep learning methods for ECG data from both m...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	159,507
2208.02835	Safe and Human-Like Autonomous Driving: A Predictor-Corrector Potential Game Approach	This paper proposes a novel decision-making framework for autonomous vehicles (AVs), called predictor-corrector potential game (PCPG), composed of a Predictor and a Corrector. To enable human-like reasoning and characterize agent interactions, a receding-horizon multi-player game is formulated. To address the challenge...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	311,586
2406.04041	Linear Opinion Pooling for Uncertainty Quantification on Graphs	We address the problem of uncertainty quantification for graph-structured data, or, more specifically, the problem to quantify the predictive uncertainty in (semi-supervised) node classification. Key questions in this regard concern the distinction between two different types of uncertainty, aleatoric and epistemic, an...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	461,496
2101.05792	Group Testing with a Graph Infection Spread Model	We propose a novel infection spread model based on a random connection graph which represents connections between $n$ individuals. Infection spreads via connections between individuals and this results in a probabilistic cluster formation structure as well as a non-i.i.d. (correlated) infection status for individuals. ...	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	true	215,522
2210.16386	Non-Stationary Bandits with Auto-Regressive Temporal Dependency	Traditional multi-armed bandit (MAB) frameworks, predominantly examined under stochastic or adversarial settings, often overlook the temporal dynamics inherent in many real-world applications such as recommendation systems and online advertising. This paper introduces a novel non-stationary MAB framework that captures ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	327,309
1606.03768	New Permutation Trinomials From Niho Exponents over Finite Fields with Even Characteristic	In this paper, a class of permutation trinomials of Niho type over finite fields with even characteristic is further investigated. New permutation trinomials from Niho exponents are obtained from linear fractional polynomials over finite fields, and it is shown that the presented results are the generalizations of some...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	57,142
2403.15072	Direct and Indirect Hydrogen Storage: Dynamics and Interactions in the Transition to a Renewable Energy Based System for Europe	To move towards a low-carbon society by 2050, understanding the intricate dynamics of energy systems is critical. Our study examines these interactions through the lens of hydrogen storage, dividing it into 'direct' and 'indirect' hydrogen storage. Direct hydrogen storage involves electrolysis-produced hydrogen being s...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	440,379
2003.04748	On the coexistence of competing languages	We investigate the evolution of competing languages, a subject where much previous literature suggests that the outcome is always the domination of one language over all the others. Since coexistence of languages is observed in reality, we here revisit the question of language competition, with an emphasis on uncoverin...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	167,649
1909.13101	Plasmodium Detection Using Simple CNN and Clustered GLCM Features	Malaria is a serious disease caused by the Plasmodium parasite that transmitted through the bite of a female Anopheles mosquito and invades human erythrocytes. Malaria must be recognized precisely in order to treat the patient in time and to prevent further spread of infection. The standard diagnostic technique using m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	147,326
2501.02701	Underwater Image Restoration Through a Prior Guided Hybrid Sense Approach and Extensive Benchmark Analysis	Underwater imaging grapples with challenges from light-water interactions, leading to color distortions and reduced clarity. In response to these challenges, we propose a novel Color Balance Prior \textbf{Guided} \textbf{Hyb}rid \textbf{Sens}e \textbf{U}nderwater \textbf{I}mage \textbf{R}estoration framework (\textbf{G...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	522,591
1910.02100	Social Learning in Multi Agent Multi Armed Bandits	In this paper, we introduce a distributed version of the classical stochastic Multi-Arm Bandit (MAB) problem. Our setting consists of a large number of agents $n$ that collaboratively and simultaneously solve the same instance of $K$ armed MAB to minimize the average cumulative regret over all agents. The agents can co...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	true	148,133
2307.04192	Self-Adaptive Sampling for Efficient Video Question-Answering on Image--Text Models	Video question-answering is a fundamental task in the field of video understanding. Although current vision--language models (VLMs) equipped with Video Transformers have enabled temporal modeling and yielded superior results, they are at the cost of huge computational power and thus too expensive to deploy in real-time...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	true	378,319
2502.11641	A Zero-Knowledge Proof for the Syndrome Decoding Problem in the Lee Metric	The syndrome decoding problem is one of the NP-complete problems lying at the foundation of code-based cryptography. The variant thereof where the distance between vectors is measured with respect to the Lee metric, rather than the more commonly used Hamming metric, has been analyzed recently in several works due to it...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	534,474
2105.09406	Speech & Song Emotion Recognition Using Multilayer Perceptron and Standard Vector Machine	Herein, we have compared the performance of SVM and MLP in emotion recognition using speech and song channels of the RAVDESS dataset. We have undertaken a journey to extract various audio features, identify optimal scaling strategy and hyperparameter for our models. To increase sample size, we have performed audio data...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	236,052
2310.19029	SALMA: Arabic Sense-Annotated Corpus and WSD Benchmarks	SALMA, the first Arabic sense-annotated corpus, consists of ~34K tokens, which are all sense-annotated. The corpus is annotated using two different sense inventories simultaneously (Modern and Ghani). SALMA novelty lies in how tokens and senses are associated. Instead of linking a token to only one intended sense, SALM...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	403,816
1910.12084	Detection of Adversarial Attacks and Characterization of Adversarial Subspace	Adversarial attacks have always been a serious threat for any data-driven model. In this paper, we explore subspaces of adversarial examples in unitary vector domain, and we propose a novel detector for defending our models trained for environmental sound classification. We measure chordal distance between legitimate a...	false	false	true	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	150,969
2010.12128	Accelerating Metropolis-Hastings with Lightweight Inference Compilation	In order to construct accurate proposers for Metropolis-Hastings Markov Chain Monte Carlo, we integrate ideas from probabilistic graphical models and neural networks in an open-source framework we call Lightweight Inference Compilation (LIC). LIC implements amortized inference within an open-universe declarative probab...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	202,572
2107.13216	Synthesis of Output-Feedback Controllers for Mixed Traffic Systems in Presence of Disturbances and Uncertainties	In this paper, we study mixed traffic systems that move along a single-lane ring-road or open-road. The traffic flow forms a platoon, which includes a number of heterogeneous human-driven vehicles (HDVs) together with only one connected and automated vehicle (CAV) that receives information from several neighbors. The d...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	248,136
1903.02675	A Rank-1 Sketch for Matrix Multiplicative Weights	We show that a simple randomized sketch of the matrix multiplicative weight (MMW) update enjoys (in expectation) the same regret bounds as MMW, up to a small constant factor. Unlike MMW, where every step requires full matrix exponentiation, our steps require only a single product of the form $e^A b$, which the Lanczos ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	123,544
2011.13522	Net2: A Graph Attention Network Method Customized for Pre-Placement Net Length Estimation	Net length is a key proxy metric for optimizing timing and power across various stages of a standard digital design flow. However, the bulk of net length information is not available until cell placement, and hence it is a significant challenge to explicitly consider net length optimization in design stages prior to pl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	208,501
2108.10226	ECG-Based Heart Arrhythmia Diagnosis Through Attentional Convolutional Neural Networks	Electrocardiography (ECG) signal is a highly applied measurement for individual heart condition, and much effort have been endeavored towards automatic heart arrhythmia diagnosis based on machine learning. However, traditional machine learning models require large investment of time and effort for raw data preprocessin...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	251,835
cs/0005020	Centroid-based summarization of multiple documents: sentence extraction, utility-based evaluation, and user studies	We present a multi-document summarizer, called MEAD, which generates summaries using cluster centroids produced by a topic detection and tracking system. We also describe two new techniques, based on sentence utility and subsumption, which we have applied to the evaluation of both single and multiple document summaries...	true	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	true	537,106

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