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
2305.19223	Intent-aligned AI systems deplete human agency: the need for agency foundations research in AI safety	The rapid advancement of artificial intelligence (AI) systems suggests that artificial general intelligence (AGI) systems may soon arrive. Many researchers are concerned that AIs and AGIs will harm humans via intentional misuse (AI-misuse) or through accidents (AI-accidents). In respect of AI-accidents, there is an inc...	true	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	369,430
2407.09728	Neural Operator-Based Proxy for Reservoir Simulations Considering Varying Well Settings, Locations, and Permeability Fields	Simulating Darcy flows in porous media is fundamental to understand the future flow behavior of fluids in hydrocarbon and carbon storage reservoirs. Geological models of reservoirs are often associated with high uncertainly leading to many numerical simulations for history matching and production optimization. Machine ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	472,697
2303.10891	Non-Exemplar Online Class-incremental Continual Learning via Dual-prototype Self-augment and Refinement	This paper investigates a new, practical, but challenging problem named Non-exemplar Online Class-incremental continual Learning (NO-CL), which aims to preserve the discernibility of base classes without buffering data examples and efficiently learn novel classes continuously in a single-pass (i.e., online) data stream...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	352,621
2301.11113	Finding Regions of Counterfactual Explanations via Robust Optimization	Counterfactual explanations play an important role in detecting bias and improving the explainability of data-driven classification models. A counterfactual explanation (CE) is a minimal perturbed data point for which the decision of the model changes. Most of the existing methods can only provide one CE, which may not...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	342,022
2104.04147	Artificial intelligence, human rights, democracy, and the rule of law: a primer	In September 2019, the Council of Europe's Committee of Ministers adopted the terms of reference for the Ad Hoc Committee on Artificial Intelligence (CAHAI). The CAHAI is charged with examining the feasibility and potential elements of a legal framework for the design, development, and deployment of AI systems that acc...	true	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	229,304
2003.04188	BirdNet+: End-to-End 3D Object Detection in LiDAR Bird's Eye View	On-board 3D object detection in autonomous vehicles often relies on geometry information captured by LiDAR devices. Albeit image features are typically preferred for detection, numerous approaches take only spatial data as input. Exploiting this information in inference usually involves the use of compact representatio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	167,477
2303.13101	MMFormer: Multimodal Transformer Using Multiscale Self-Attention for Remote Sensing Image Classification	To benefit the complementary information between heterogeneous data, we introduce a new Multimodal Transformer (MMFormer) for Remote Sensing (RS) image classification using Hyperspectral Image (HSI) accompanied by another source of data such as Light Detection and Ranging (LiDAR). Compared with traditional Vision Trans...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	353,548
1911.02086	Small-Footprint Keyword Spotting on Raw Audio Data with Sinc-Convolutions	Keyword Spotting (KWS) enables speech-based user interaction on smart devices. Always-on and battery-powered application scenarios for smart devices put constraints on hardware resources and power consumption, while also demanding high accuracy as well as real-time capability. Previous architectures first extracted aco...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	152,271
2402.02479	BRAIn: Bayesian Reward-conditioned Amortized Inference for natural language generation from feedback	Distribution matching methods for language model alignment such as Generation with Distributional Control (GDC) and Distributional Policy Gradient (DPG) have not received the same level of attention in reinforcement learning from human feedback (RLHF) as contrastive methods such as Sequence Likelihood Calibration (SLiC...	true	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	426,583
2204.10233	A Sandbox Tool to Bias(Stress)-Test Fairness Algorithms	Motivated by the growing importance of reducing unfairness in ML predictions, Fair-ML researchers have presented an extensive suite of algorithmic 'fairness-enhancing' remedies. Most existing algorithms, however, are agnostic to the sources of the observed unfairness. As a result, the literature currently lacks guiding...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	292,717
2212.04630	A PINN Approach to Symbolic Differential Operator Discovery with Sparse Data	Given ample experimental data from a system governed by differential equations, it is possible to use deep learning techniques to construct the underlying differential operators. In this work we perform symbolic discovery of differential operators in a situation where there is sparse experimental data. This small data ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	335,513
2410.21129	Fast Calibrated Explanations: Efficient and Uncertainty-Aware Explanations for Machine Learning Models	This paper introduces Fast Calibrated Explanations, a method designed for generating rapid, uncertainty-aware explanations for machine learning models. By incorporating perturbation techniques from ConformaSight - a global explanation framework - into the core elements of Calibrated Explanations (CE), we achieve signif...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	503,100
1801.05230	Real-time CPU-based large-scale 3D mesh reconstruction	In Robotics, especially in this era of autonomous driving, mapping is one key ability of a robot to be able to navigate through an environment, localize on it and analyze its traversability. To allow for real-time execution on constrained hardware, the map usually estimated by feature-based or semi-dense SLAM algorithm...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	88,422
2312.05153	Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference	Surrogate models are statistical or conceptual approximations for more complex simulation models. In this context, it is crucial to propagate the uncertainty induced by limited simulation budget and surrogate approximation error to predictions, inference, and subsequent decision-relevant quantities. However, quantifyin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	413,962
2211.00921	A Data-driven Case-based Reasoning in Bankruptcy Prediction	There has been intensive research regarding machine learning models for predicting bankruptcy in recent years. However, the lack of interpretability limits their growth and practical implementation. This study proposes a data-driven explainable case-based reasoning (CBR) system for bankruptcy prediction. Empirical resu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	328,055
2302.08366	Defect Transfer GAN: Diverse Defect Synthesis for Data Augmentation	Data-hunger and data-imbalance are two major pitfalls in many deep learning approaches. For example, on highly optimized production lines, defective samples are hardly acquired while non-defective samples come almost for free. The defects however often seem to resemble each other, e.g., scratches on different products ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	346,030
2501.11014	Transfer Learning Strategies for Pathological Foundation Models: A Systematic Evaluation in Brain Tumor Classification	Foundation models pretrained on large-scale pathology datasets have shown promising results across various diagnostic tasks. Here, we present a systematic evaluation of transfer learning strategies for brain tumor classification using these models. We analyzed 252 cases comprising five major tumor types: glioblastoma, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	525,754
2311.03383	Toward Reinforcement Learning-based Rectilinear Macro Placement Under Human Constraints	Macro placement is a critical phase in chip design, which becomes more intricate when involving general rectilinear macros and layout areas. Furthermore, macro placement that incorporates human-like constraints, such as design hierarchy and peripheral bias, has the potential to significantly reduce the amount of additi...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	405,831
2407.08742	Improved Robustness and Hyperparameter Selection in the Dense Associative Memory	The Dense Associative Memory generalizes the Hopfield network by allowing for sharper interaction functions. This increases the capacity of the network as an autoassociative memory as nearby learned attractors will not interfere with one another. However, the implementation of the network relies on applying large expon...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	472,295
2407.18466	A Progressive Single-Modality to Multi-Modality Classification Framework for Alzheimer's Disease Sub-type Diagnosis	The current clinical diagnosis framework of Alzheimer's disease (AD) involves multiple modalities acquired from multiple diagnosis stages, each with distinct usage and cost. Previous AD diagnosis research has predominantly focused on how to directly fuse multiple modalities for an end-to-end one-stage diagnosis, which ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	476,379
2408.13679	Segment Any Mesh: Zero-shot Mesh Part Segmentation via Lifting Segment Anything 2 to 3D	We propose Segment Any Mesh (SAMesh), a novel zero-shot method for mesh part segmentation that overcomes the limitations of shape analysis-based, learning-based, and current zero-shot approaches. SAMesh operates in two phases: multimodal rendering and 2D-to-3D lifting. In the first phase, multiview renders of the mesh ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	483,241
2411.01742	Learning from Convolution-based Unlearnable Datastes	The construction of large datasets for deep learning has raised concerns regarding unauthorized use of online data, leading to increased interest in protecting data from third-parties who want to use it for training. The Convolution-based Unlearnable DAtaset (CUDA) method aims to make data unlearnable by applying class...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	505,200
2409.18931	Social Media Bot Policies: Evaluating Passive and Active Enforcement	The emergence of Multimodal Foundation Models (MFMs) holds significant promise for transforming social media platforms. However, this advancement also introduces substantial security and ethical concerns, as it may facilitate malicious actors in the exploitation of online users. We aim to evaluate the strength of secur...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	492,461
2403.04576	A Model Hierarchy for Predicting the Flow in Stirred Tanks with Physics-Informed Neural Networks	This paper explores the potential of Physics-Informed Neural Networks (PINNs) to serve as Reduced Order Models (ROMs) for simulating the flow field within stirred tank reactors (STRs). We solve the two-dimensional stationary Navier-Stokes equations within a geometrically intricate domain and explore methodologies that ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	435,647
2108.01721	Improving Counterfactual Generation for Fair Hate Speech Detection	Bias mitigation approaches reduce models' dependence on sensitive features of data, such as social group tokens (SGTs), resulting in equal predictions across the sensitive features. In hate speech detection, however, equalizing model predictions may ignore important differences among targeted social groups, as hate spe...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	249,106
2304.03373	Training-Free Layout Control with Cross-Attention Guidance	Recent diffusion-based generators can produce high-quality images from textual prompts. However, they often disregard textual instructions that specify the spatial layout of the composition. We propose a simple approach that achieves robust layout control without the need for training or fine-tuning of the image genera...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	356,778
1711.05462	A Machine Learning Approach to Modeling Human Migration	Human migration is a type of human mobility, where a trip involves a person moving with the intention of changing their home location. Predicting human migration as accurately as possible is important in city planning applications, international trade, spread of infectious diseases, conservation planning, and public po...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	84,577
2210.04174	Grow and Merge: A Unified Framework for Continuous Categories Discovery	Although a number of studies are devoted to novel category discovery, most of them assume a static setting where both labeled and unlabeled data are given at once for finding new categories. In this work, we focus on the application scenarios where unlabeled data are continuously fed into the category discovery system....	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	322,341
1508.04333	ESDF: Ensemble Selection using Diversity and Frequency	Recently ensemble selection for consensus clustering has emerged as a research problem in Machine Intelligence. Normally consensus clustering algorithms take into account the entire ensemble of clustering, where there is a tendency of generating a very large size ensemble before computing its consensus. One can avoid c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	46,121
2212.14351	Properties of Group Fairness Metrics for Rankings	In recent years, several metrics have been developed for evaluating group fairness of rankings. Given that these metrics were developed with different application contexts and ranking algorithms in mind, it is not straightforward which metric to choose for a given scenario. In this paper, we perform a comprehensive com...	false	false	false	false	false	true	true	false	false	false	false	false	false	true	false	false	false	false	338,585
2401.08282	Nonlinear stiffness allows passive dynamic hopping for one-legged robots with an upright trunk	Template models are frequently used to simplify the control dynamics for robot hopping or running. Passive limit cycles can emerge for such systems and be exploited for energy-efficient control. A grand challenge in locomotion is trunk stabilization when the hip is offset from the center of mass (CoM). The swing phase ...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	421,837
2007.05856	Anomaly Detection-Based Unknown Face Presentation Attack Detection	Anomaly detection-based spoof attack detection is a recent development in face Presentation Attack Detection (fPAD), where a spoof detector is learned using only non-attacked images of users. These detectors are of practical importance as they are shown to generalize well to new attack types. In this paper, we present ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	186,806
2007.01851	Swoosh! Rattle! Thump! -- Actions that Sound	Truly intelligent agents need to capture the interplay of all their senses to build a rich physical understanding of their world. In robotics, we have seen tremendous progress in using visual and tactile perception; however, we have often ignored a key sense: sound. This is primarily due to the lack of data that captur...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	185,550
1610.09164	Effects of Social Ties in Knowledge Diffusion: case study on PLOS ONE	In order to capture the effects of social ties in knowledge diffusion, this paper examines the publication network that emerges from the collaboration of researchers, using citation information as means to estimate knowledge flow. For this purpose, we analyzed the papers published in the PLOS ONE journal finding strong...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	63,014
2009.04254	Cooperative Formation of Autonomous Vehicles in Mixed Traffic Flow: Beyond Platooning	Cooperative formation and control of autonomous vehicles (AVs) promise increased efficiency and safety on public roads. In mixed traffic flow consisting of AVs and human-driven vehicles (HDVs), the prevailing platooning of multiple AVs is not the only choice for cooperative formation. In this paper, we investigate how ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	194,999
2311.05332	On the Road with GPT-4V(ision): Early Explorations of Visual-Language Model on Autonomous Driving	The pursuit of autonomous driving technology hinges on the sophisticated integration of perception, decision-making, and control systems. Traditional approaches, both data-driven and rule-based, have been hindered by their inability to grasp the nuance of complex driving environments and the intentions of other road us...	false	false	false	false	true	false	false	true	true	false	false	true	false	false	false	false	false	false	406,547
1901.06082	Probabilistic symmetries and invariant neural networks	Treating neural network inputs and outputs as random variables, we characterize the structure of neural networks that can be used to model data that are invariant or equivariant under the action of a compact group. Much recent research has been devoted to encoding invariance under symmetry transformations into neural n...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	118,920
2409.18877	UniEmoX: Cross-modal Semantic-Guided Large-Scale Pretraining for Universal Scene Emotion Perception	Visual emotion analysis holds significant research value in both computer vision and psychology. However, existing methods for visual emotion analysis suffer from limited generalizability due to the ambiguity of emotion perception and the diversity of data scenarios. To tackle this issue, we introduce UniEmoX, a cross-...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	492,443
1605.08179	Discovering Causal Signals in Images	This paper establishes the existence of observable footprints that reveal the "causal dispositions" of the object categories appearing in collections of images. We achieve this goal in two steps. First, we take a learning approach to observational causal discovery, and build a classifier that achieves state-of-the-art ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	56,396
2409.17475	On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks	Heterophily, or the tendency of connected nodes in networks to have different class labels or dissimilar features, has been identified as challenging for many Graph Neural Network (GNN) models. While the challenges of applying GNNs for node classification when class labels display strong heterophily are well understood...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	491,818
1911.08581	A Configuration-Space Decomposition Scheme for Learning-based Collision Checking	Motion planning for robots of high degrees-of-freedom (DOFs) is an important problem in robotics with sampling-based methods in configuration space C as one popular solution. Recently, machine learning methods have been introduced into sampling-based motion planning methods, which train a classifier to distinguish coll...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	154,226
2403.00387	For time-invariant delay systems, global asymptotic stability does not imply uniform global attractivity	Adapting a counterexample recently proposed by J.L. Mancilla-Aguilar and H. Haimovich, we show here that, for time-delay systems, global asymptotic stability does not ensure that solutions converge uniformly to zero over bounded sets of initial states. Hence, the convergence might be arbitrarily slow even if initial st...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	433,961
1810.03237	Task-Embedded Control Networks for Few-Shot Imitation Learning	Much like humans, robots should have the ability to leverage knowledge from previously learned tasks in order to learn new tasks quickly in new and unfamiliar environments. Despite this, most robot learning approaches have focused on learning a single task, from scratch, with a limited notion of generalisation, and no ...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	109,767
2111.00316	Real-time Speaker counting in a cocktail party scenario using Attention-guided Convolutional Neural Network	Most current speech technology systems are designed to operate well even in the presence of multiple active speakers. However, most solutions assume that the number of co-current speakers is known. Unfortunately, this information might not always be available in real-world applications. In this study, we propose a real...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	264,179
2412.01330	The "LLM World of Words" English free association norms generated by large language models	Free associations have been extensively used in cognitive psychology and linguistics for studying how conceptual knowledge is organized. Recently, the potential of applying a similar approach for investigating the knowledge encoded in LLMs has emerged, specifically as a method for investigating LLM biases. However, the...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	513,066
2405.09640	Personalized Content Moderation and Emergent Outcomes	Social media platforms have implemented automated content moderation tools to preserve community norms and mitigate online hate and harassment. Recently, these platforms have started to offer Personalized Content Moderation (PCM), granting users control over moderation settings or aligning algorithms with individual us...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	454,485
2501.04169	Learning to Transfer Human Hand Skills for Robot Manipulations	We present a method for teaching dexterous manipulation tasks to robots from human hand motion demonstrations. Unlike existing approaches that solely rely on kinematics information without taking into account the plausibility of robot and object interaction, our method directly infers plausible robot manipulation actio...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	523,116
2407.20805	Multivariable Extremum Seeking Control for Dynamic Maps through Sliding Modes and Periodic Switching Function	This paper presents the design of an extremum seeking controller based on sliding modes and cyclic search for real-time optimization of non-linear multivariable dynamic systems. These systems have arbitrary relative degree, compensated by the technique of time-scaling. The resulting approach guarantees global convergen...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	477,294
2411.01119	AquaFuse: Waterbody Fusion for Physics Guided View Synthesis of Underwater Scenes	We introduce the idea of AquaFuse, a physics-based method for synthesizing waterbody properties in underwater imagery. We formulate a closed-form solution for waterbody fusion that facilitates realistic data augmentation and geometrically consistent underwater scene rendering. AquaFuse leverages the physical characteri...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	504,917
2105.08263	New LCD MDS codes of non-Reed-Solomon type	Both linear complementary dual (LCD) codes and maximum distance separable (MDS) codes have good algebraic structures, and they have interesting practical applications such as communication systems, data storage, quantum codes, and so on. So far, most of LCD MDS codes have been constructed by employing generalized Reed-...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	235,707
2411.02972	Exploring Seasonal Variability in the Context of Neural Radiance Fields for 3D Reconstruction on Satellite Imagery	In this work, the seasonal predictive capabilities of Neural Radiance Fields (NeRF) applied to satellite images are investigated. Focusing on the utilization of satellite data, the study explores how Sat-NeRF, a novel approach in computer vision, performs in predicting seasonal variations across different months. Throu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	505,740
2410.15086	Towards Safer Heuristics With XPlain	Many problems that cloud operators solve are computationally expensive, and operators often use heuristic algorithms (that are faster and scale better than optimal) to solve them more efficiently. Heuristic analyzers enable operators to find when and by how much their heuristics underperform. However, these tools do no...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	true	500,364
2209.12785	Outage Performance of Cross-Packet HARQ	As opposed to hybrid automatic repeat request with incremental redundancy (HARQ-IR) that all the resources are occupied to resend the redundant information, cross-packet HARQ (XP-HARQ) allows the introduction of new information into retransmissions to substantially exploit the remaining resources. This letter provides ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	319,658
1907.03635	Distance from the Nucleus to a Uniformly Random Point in the 0-cell and the Typical Cell of the Poisson-Voronoi Tessellation	Consider the distances $\tilde{R}_o$ and $R_o$ from the nucleus to a uniformly random point in the 0-cell and the typical cell, respectively, of the $d$-dimensional Poisson-Voronoi (PV) tessellation. The main objective of this paper is to characterize the exact distributions of $\tilde{R}_o$ and $R_o$. First, using the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	137,900
1808.06640	Adversarial Removal of Demographic Attributes from Text Data	Recent advances in Representation Learning and Adversarial Training seem to succeed in removing unwanted features from the learned representation. We show that demographic information of authors is encoded in -- and can be recovered from -- the intermediate representations learned by text-based neural classifiers. The ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	105,573
2105.13530	A BIC-based Mixture Model Defense against Data Poisoning Attacks on Classifiers	Data Poisoning (DP) is an effective attack that causes trained classifiers to misclassify their inputs. DP attacks significantly degrade a classifier's accuracy by covertly injecting attack samples into the training set. Broadly applicable to different classifier structures, without strong assumptions about the attacke...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	237,330
2106.14610	A keyword-driven approach to science	To a good extent, words can be understood as corresponding to patterns or categories that appeared in order to represent concepts and structures that are particularly important or useful in a given time and space. Words are characterized by not being completely general nor specific, in the sense that the same word can ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	243,459
2104.13494	Probability Distribution-free General Scenario Programming	This paper presents a novel solution paradigm of general optimization under both exogenous and endogenous uncertainties. This solution paradigm consists of a probability distribution (PD)-free method of obtaining deterministic equivalents and an innovative approach of scenario reduction. First, dislike the existing met...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	232,520
2112.01525	Co-domain Symmetry for Complex-Valued Deep Learning	We study complex-valued scaling as a type of symmetry natural and unique to complex-valued measurements and representations. Deep Complex Networks (DCN) extends real-valued algebra to the complex domain without addressing complex-valued scaling. SurReal takes a restrictive manifold view of complex numbers, adopting a d...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	269,515
2502.01500	Gamma/hadron separation in the TAIGA experiment with neural network methods	In this work, the ability of rare VHE gamma ray selection with neural network methods is investigated in the case when cosmic radiation flux strongly prevails (ratio up to {10^4} over the gamma radiation flux from a point source). This ratio is valid for the Crab Nebula in the TeV energy range, since the Crab is a well...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	529,882
2409.03542	Risk-based Calibration for Probabilistic Classifiers	We introduce a general iterative procedure called risk-based calibration (RC) designed to minimize the empirical risk under the 0-1 loss (empirical error) for probabilistic classifiers. These classifiers are based on modeling probability distributions, including those constructed from the joint distribution (generative...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	486,084
2207.10781	Data-Driven Stochastic AC-OPF using Gaussian Processes	In recent years, electricity generation has been responsible for more than a quarter of the greenhouse gas emissions in the US. Integrating a significant amount of renewables into a power grid is probably the most accessible way to reduce carbon emissions from power grids and slow down climate change. Unfortunately, th...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	309,378
2209.03561	Video Vision Transformers for Violence Detection	Law enforcement and city safety are significantly impacted by detecting violent incidents in surveillance systems. Although modern (smart) cameras are widely available and affordable, such technological solutions are impotent in most instances. Furthermore, personnel monitoring CCTV recordings frequently show a belated...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	316,527
2104.10067	Spherical Multi-Modal Place Recognition for Heterogeneous Sensor Systems	In this paper, we propose a robust end-to-end multi-modal pipeline for place recognition where the sensor systems can differ from the map building to the query. Our approach operates directly on images and LiDAR scans without requiring any local feature extraction modules. By projecting the sensor data onto the unit sp...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	231,452
1703.02905	Learning a Unified Control Policy for Safe Falling	Being able to fall safely is a necessary motor skill for humanoids performing highly dynamic tasks, such as running and jumping. We propose a new method to learn a policy that minimizes the maximal impulse during the fall. The optimization solves for both a discrete contact planning problem and a continuous optimal con...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	69,639
2112.01841	Reinforcement learning for options on target volatility funds	In this work we deal with the funding costs rising from hedging the risky securities underlying a target volatility strategy (TVS), a portfolio of risky assets and a risk-free one dynamically rebalanced in order to keep the realized volatility of the portfolio on a certain level. The uncertainty in the TVS risky portfo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	269,637
1804.04687	Cross-Domain Visual Recognition via Domain Adaptive Dictionary Learning	In real-world visual recognition problems, the assumption that the training data (source domain) and test data (target domain) are sampled from the same distribution is often violated. This is known as the domain adaptation problem. In this work, we propose a novel domain-adaptive dictionary learning framework for cros...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	94,913
2410.09220	M3Hop-CoT: Misogynous Meme Identification with Multimodal Multi-hop Chain-of-Thought	In recent years, there has been a significant rise in the phenomenon of hate against women on social media platforms, particularly through the use of misogynous memes. These memes often target women with subtle and obscure cues, making their detection a challenging task for automated systems. Recently, Large Language M...	false	false	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	497,488
2302.00236	Generative Adversarial Symmetry Discovery	Despite the success of equivariant neural networks in scientific applications, they require knowing the symmetry group a priori. However, it may be difficult to know which symmetry to use as an inductive bias in practice. Enforcing the wrong symmetry could even hurt the performance. In this paper, we propose a framewor...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	343,150
1912.08066	Putting Ridesharing to the Test: Efficient and Scalable Solutions and the Power of Dynamic Vehicle Relocation	We study the optimization of large-scale, real-time ridesharing systems and propose a modular design methodology, Component Algorithms for Ridesharing (CAR). We evaluate a diverse set of CARs (14 in total), focusing on the key algorithmic components of ridesharing. We take a multi-objective approach, evaluating 12 metr...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	true	157,753
2304.06798	On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence	Large pre-trained models, also known as foundation models (FMs), are trained in a task-agnostic manner on large-scale data and can be adapted to a wide range of downstream tasks by fine-tuning, few-shot, or even zero-shot learning. Despite their successes in language and vision tasks, we have yet seen an attempt to dev...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	358,105
1202.3717	PAC-Bayesian Policy Evaluation for Reinforcement Learning	Bayesian priors offer a compact yet general means of incorporating domain knowledge into many learning tasks. The correctness of the Bayesian analysis and inference, however, largely depends on accuracy and correctness of these priors. PAC-Bayesian methods overcome this problem by providing bounds that hold regardless ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	14,389
1512.08475	MRF-Based Multispectral Image Fusion Using an Adaptive Approach Based on Edge-Guided Interpolation	In interpretation of remote sensing images, it is possible that some images which are supplied by different sensors become incomprehensible. For better visual perception of these images, it is essential to operate series of pre-processing and elementary corrections and then operate a series of main processing steps for...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	50,519
1906.05894	Semantics to Space(S2S): Embedding semantics into spatial space for zero-shot verb-object query inferencing	We present a novel deep zero-shot learning (ZSL) model for inferencing human-object-interaction with verb-object (VO) query. While the previous two-stream ZSL approaches only use the semantic/textual information to be fed into the query stream, we seek to incorporate and embed the semantics into the visual representati...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	135,150
2210.14492	Provable Safe Reinforcement Learning with Binary Feedback	Safety is a crucial necessity in many applications of reinforcement learning (RL), whether robotic, automotive, or medical. Many existing approaches to safe RL rely on receiving numeric safety feedback, but in many cases this feedback can only take binary values; that is, whether an action in a given state is safe or u...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	326,571
2203.12687	Trust in AI and Its Role in the Acceptance of AI Technologies	As AI-enhanced technologies become common in a variety of domains, there is an increasing need to define and examine the trust that users have in such technologies. Given the progress in the development of AI, a correspondingly sophisticated understanding of trust in the technology is required. This paper addresses thi...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	287,360
1402.2562	\'Etude cognitive des processus de construction d'une requ\^ete dans un syst\`eme de gestion de connaissances m\'edicales	This article presents the Cogni-CISMeF project, which aims at improving medical information search in the CISMeF system (Catalog and Index of French-language health resources) by including a conversational agent to interact with the user in natural language. To study the cognitive processes involved during the informat...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	30,791
2202.00332	Activity Recognition in Assembly Tasks by Bayesian Filtering in Multi-Hypergraphs	We study sensor-based human activity recognition in manual work processes like assembly tasks. In such processes, the system states often have a rich structure, involving object properties and relations. Thus, estimating the hidden system state from sensor observations by recursive Bayesian filtering can be very challe...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	278,104
2105.02953	Recognition of handwritten MNIST digits on low-memory 2 Kb RAM Arduino board using LogNNet reservoir neural network	The presented compact algorithm for recognizing handwritten digits of the MNIST database, created on the LogNNet reservoir neural network, reaches the recognition accuracy of 82%. The algorithm was tested on a low-memory Arduino board with 2 Kb static RAM low-power microcontroller. The dependences of the accuracy and t...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	233,979
2203.01641	On generating parametrised structural data using conditional generative adversarial networks	A powerful approach, and one of the most common ones in structural health monitoring (SHM), is to use data-driven models to make predictions and inferences about structures and their condition. Such methods almost exclusively rely on the quality of the data. Within the SHM discipline, data do not always suffice to buil...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	283,460
1407.5144	Lower Bounds on the Oracle Complexity of Nonsmooth Convex Optimization via Information Theory	We present an information-theoretic approach to lower bound the oracle complexity of nonsmooth black box convex optimization, unifying previous lower bounding techniques by identifying a combinatorial problem, namely string guessing, as a single source of hardness. As a measure of complexity we use distributional oracl...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	34,753
2312.03864	Geometry Matching for Multi-Embodiment Grasping	Many existing learning-based grasping approaches concentrate on a single embodiment, provide limited generalization to higher DoF end-effectors and cannot capture a diverse set of grasp modes. We tackle the problem of grasping using multiple embodiments by learning rich geometric representations for both objects and en...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	413,461
1502.07019	Building with Drones: Accurate 3D Facade Reconstruction using MAVs	Automatic reconstruction of 3D models from images using multi-view Structure-from-Motion methods has been one of the most fruitful outcomes of computer vision. These advances combined with the growing popularity of Micro Aerial Vehicles as an autonomous imaging platform, have made 3D vision tools ubiquitous for large n...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	40,542
2008.06810	Cluster-level Feature Alignment for Person Re-identification	Instance-level alignment is widely exploited for person re-identification, e.g. spatial alignment, latent semantic alignment and triplet alignment. This paper probes another feature alignment modality, namely cluster-level feature alignment across whole dataset, where the model can see not only the sampled images in lo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	191,896
1103.4547	Canonical Dual Method for Resource Allocation and Adaptive Modulation in Uplink SC-FDMA Systems	In this paper, we study resource allocation and adaptive modulation in SC-FDMA which is adopted as the multiple access scheme for the uplink in the 3GPP-LTE standard. A sum-utility maximization (SUmax), and a joint adaptive modulation and sum-cost minimization (JAMSCmin) problems are considered. Unlike OFDMA, in additi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	9,726
2311.13921	Some Like It Small: Czech Semantic Embedding Models for Industry Applications	This article focuses on the development and evaluation of Small-sized Czech sentence embedding models. Small models are important components for real-time industry applications in resource-constrained environments. Given the limited availability of labeled Czech data, alternative approaches, including pre-training, kno...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	409,925
2107.02778	Anomaly Detection using Edge Computing in Video Surveillance System: Review	The current concept of Smart Cities influences urban planners and researchers to provide modern, secured and sustainable infrastructure and give a decent quality of life to its residents. To fulfill this need video surveillance cameras have been deployed to enhance the safety and well-being of the citizens. Despite tec...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	244,936
2405.14233	Language processing in humans and computers	Machine-learned language models have transformed everyday life: they steer us when we study, drive, manage money. They have the potential to transform our civilization. But they hallucinate. Their realities are virtual. This note provides a high-level overview of language models and outlines a low-level model of learni...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	456,324
2206.14981	Randomized Coordinate Subgradient Method for Nonsmooth Composite Optimization	Coordinate-type subgradient methods for addressing nonsmooth optimization problems are relatively underexplored due to the set-valued nature of the subdifferential. In this work, our study focuses on nonsmooth composite optimization problems, encompassing a wide class of convex and weakly convex (nonconvex nonsmooth) p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	305,442
2412.07770	From an Image to a Scene: Learning to Imagine the World from a Million 360 Videos	Three-dimensional (3D) understanding of objects and scenes play a key role in humans' ability to interact with the world and has been an active area of research in computer vision, graphics, and robotics. Large scale synthetic and object-centric 3D datasets have shown to be effective in training models that have 3D und...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	515,795
2408.09662	CusADi: A GPU Parallelization Framework for Symbolic Expressions and Optimal Control	The parallelism afforded by GPUs presents significant advantages in training controllers through reinforcement learning (RL). However, integrating model-based optimization into this process remains challenging due to the complexity of formulating and solving optimization problems across thousands of instances. In this ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	481,530
2410.22606	Testing Tensor Products of Algebraic Codes	Motivated by recent advances in locally testable codes and quantum LDPCs based on robust testability of tensor product codes, we explore the local testability of tensor products of (an abstraction of) algebraic geometry codes. Such codes are parameterized by, in addition to standard parameters such as block length $n$ ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	503,692
2211.02566	scikit-fda: A Python Package for Functional Data Analysis	The library scikit-fda is a Python package for Functional Data Analysis (FDA). It provides a comprehensive set of tools for representation, preprocessing, and exploratory analysis of functional data. The library is built upon and integrated in Python's scientific ecosystem. In particular, it conforms to the scikit-lear...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	328,615
2309.02067	Histograms of Points, Orientations, and Dynamics of Orientations Features for Hindi Online Handwritten Character Recognition	A set of features independent of character stroke direction and order variations is proposed for online handwritten character recognition. A method is developed that maps features like co-ordinates of points, orientations of strokes at points, and dynamics of orientations of strokes at points spatially as a function of...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	389,919
1703.02629	Online Learning Without Prior Information	The vast majority of optimization and online learning algorithms today require some prior information about the data (often in the form of bounds on gradients or on the optimal parameter value). When this information is not available, these algorithms require laborious manual tuning of various hyperparameters, motivati...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	69,590
2107.12744	Real-Time Activity Recognition and Intention Recognition Using a Vision-based Embedded System	With the rapid increase in digital technologies, most fields of study include recognition of human activity and intention recognition, which are essential in smart environments. In this study, we equipped the activity recognition system with the ability to recognize intentions by affecting the pace of movement of indiv...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	247,997
1807.08405	Visual Mesh: Real-time Object Detection Using Constant Sample Density	This paper proposes an enhancement of convolutional neural networks for object detection in resource-constrained robotics through a geometric input transformation called Visual Mesh. It uses object geometry to create a graph in vision space, reducing computational complexity by normalizing the pixel and feature density...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	true	103,533
2306.06945	Underwater Acoustic Target Recognition based on Smoothness-inducing Regularization and Spectrogram-based Data Augmentation	Underwater acoustic target recognition is a challenging task owing to the intricate underwater environments and limited data availability. Insufficient data can hinder the ability of recognition systems to support complex modeling, thus impeding their advancement. To improve the generalization capacity of recognition m...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	372,818
1905.10054	A Compressive Sensing Video dataset using Pixel-wise coded exposure	Manifold amount of video data gets generated every minute as we read this document, ranging from surveillance to broadcasting purposes. There are two roadblocks that restrain us from using this data as such, first being the storage which restricts us from only storing the information based on the hardware constraints. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	131,936
2306.06850	Volume-DROID: A Real-Time Implementation of Volumetric Mapping with DROID-SLAM	This paper presents Volume-DROID, a novel approach for Simultaneous Localization and Mapping (SLAM) that integrates Volumetric Mapping and Differentiable Recurrent Optimization-Inspired Design (DROID). Volume-DROID takes camera images (monocular or stereo) or frames from a video as input and combines DROID-SLAM, point ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	372,778

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