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
2403.09451	M&M: Multimodal-Multitask Model Integrating Audiovisual Cues in Cognitive Load Assessment	This paper introduces the M&M model, a novel multimodal-multitask learning framework, applied to the AVCAffe dataset for cognitive load assessment (CLA). M&M uniquely integrates audiovisual cues through a dual-pathway architecture, featuring specialized streams for audio and video inputs. A key innovation lies in its c...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	437,771
2106.02396	A Learning-based Optimal Market Bidding Strategy for Price-Maker Energy Storage	Load serving entities with storage units reach sizes and performances that can significantly impact clearing prices in electricity markets. Nevertheless, price endogeneity is rarely considered in storage bidding strategies and modeling the electricity market is a challenging task. Meanwhile, model-free reinforcement le...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	238,860
1808.05279	Measuring Human Assessed Complexity in Synthetic Aperture Sonar Imagery Using the Elo Rating System	Performance of automatic target recognition from synthetic aperture sonar data is heavily dependent on the complexity of the beamformed imagery. Several mechanisms can contribute to this, including unwanted vehicle dynamics, the bathymetry of the scene, and the presence of natural and manmade clutter. To understand the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	105,317
2109.02724	Bringing a Ruler Into the Black Box: Uncovering Feature Impact from Individual Conditional Expectation Plots	As machine learning systems become more ubiquitous, methods for understanding and interpreting these models become increasingly important. In particular, practitioners are often interested both in what features the model relies on and how the model relies on them--the feature's impact on model predictions. Prior work o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	253,831
2408.03948	A Survey of AI Reliance	Artificial intelligence (AI) systems have become an indispensable component of modern technology. However, research on human behavioral responses is lagging behind, i.e., the research into human reliance on AI advice (AI reliance). Current shortcomings in the literature include the unclear influences on AI reliance, la...	true	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	479,207
2306.13676	Modern Constraint Programming Education: Lessons for the Future	This paper details an outlook on modern constraint programming (CP) education through the lens of a CP instructor. A general overview of current CP courses and instructional methods is presented, with a focus on online and virtually-delivered courses. This is followed by a discussion of the novel approach taken to intr...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	375,356
2302.04450	Tracking Fringe and Coordinated Activity on Twitter Leading Up To the US Capitol Attack	The aftermath of the 2020 US Presidential Election witnessed an unprecedented attack on the democratic values of the country through the violent insurrection at Capitol Hill on January 6th, 2021. The attack was fueled by the proliferation of conspiracy theories and misleading claims about the integrity of the election ...	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	344,707
1910.01761	Character Feature Engineering for Japanese Word Segmentation	On word segmentation problems, machine learning architecture engineering often draws attention. The problem representation itself, however, has remained almost static as either word lattice ranking or character sequence tagging, for at least two decades. The latter of-ten shows stronger predictive power than the former...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	148,028
2007.06240	Expert Training: Task Hardness Aware Meta-Learning for Few-Shot Classification	Deep neural networks are highly effective when a large number of labeled samples are available but fail with few-shot classification tasks. Recently, meta-learning methods have received much attention, which train a meta-learner on massive additional tasks to gain the knowledge to instruct the few-shot classification. ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	186,950
2411.15245	AnyText2: Visual Text Generation and Editing With Customizable Attributes	As the text-to-image (T2I) domain progresses, generating text that seamlessly integrates with visual content has garnered significant attention. However, even with accurate text generation, the inability to control font and color can greatly limit certain applications, and this issue remains insufficiently addressed. T...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	510,525
2412.09429	From Intention To Implementation: Automating Biomedical Research via LLMs	Conventional biomedical research is increasingly labor-intensive due to the exponential growth of scientific literature and datasets. Artificial intelligence (AI), particularly Large Language Models (LLMs), has the potential to revolutionize this process by automating various steps. Still, significant challenges remain...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	true	false	false	false	516,482
1901.03447	Texture Mixer: A Network for Controllable Synthesis and Interpolation of Texture	This paper addresses the problem of interpolating visual textures. We formulate this problem by requiring (1) by-example controllability and (2) realistic and smooth interpolation among an arbitrary number of texture samples. To solve it we propose a neural network trained simultaneously on a reconstruction task and a ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	118,409
2410.06308	Quantifying Training Difficulty and Accelerating Convergence in Neural Network-Based PDE Solvers	Neural network-based methods have emerged as powerful tools for solving partial differential equations (PDEs) in scientific and engineering applications, particularly when handling complex domains or incorporating empirical data. These methods leverage neural networks as basis functions to approximate PDE solutions. Ho...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	496,138
2005.12852	3D CA model of tumor-induced angiogenesis	Tumor-induced angiogenesis is the formation of new sprouts from preexisting nearby parent blood vessels. Computationally, tumor-induced angiogenesis can be modeled using cellular automata (CA), partial differential equations, etc. In this present study, a realistic physiological approach has been made to model the proc...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	178,841
1911.09483	MUSE: Parallel Multi-Scale Attention for Sequence to Sequence Learning	In sequence to sequence learning, the self-attention mechanism proves to be highly effective, and achieves significant improvements in many tasks. However, the self-attention mechanism is not without its own flaws. Although self-attention can model extremely long dependencies, the attention in deep layers tends to over...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	154,534
2403.00473	Computer-Controlled 3D Freeform Surface Weaving	In this paper, we present a new computer-controlled weaving technology that enables the fabrication of woven structures in the shape of given 3D surfaces by using threads in non-traditional materials with high bending-stiffness, allowing for multiple applications with the resultant woven fabrics. A new weaving machine ...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	true	433,995
2405.20305	Can't make an Omelette without Breaking some Eggs: Plausible Action Anticipation using Large Video-Language Models	We introduce PlausiVL, a large video-language model for anticipating action sequences that are plausible in the real-world. While significant efforts have been made towards anticipating future actions, prior approaches do not take into account the aspect of plausibility in an action sequence. To address this limitation...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	459,281
2305.00478	Domain Agnostic Fourier Neural Operators	Fourier neural operators (FNOs) can learn highly nonlinear mappings between function spaces, and have recently become a popular tool for learning responses of complex physical systems. However, to achieve good accuracy and efficiency, FNOs rely on the Fast Fourier transform (FFT), which is restricted to modeling proble...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	361,353
2405.13080	EmInspector: Combating Backdoor Attacks in Federated Self-Supervised Learning Through Embedding Inspection	Federated self-supervised learning (FSSL) has recently emerged as a promising paradigm that enables the exploitation of clients' vast amounts of unlabeled data while preserving data privacy. While FSSL offers advantages, its susceptibility to backdoor attacks, a concern identified in traditional federated supervised le...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	455,798
1011.0234	Cascade of failures in coupled network systems with multiple support-dependent relations	We study, both analytically and numerically, the cascade of failures in two coupled network systems A and B, where multiple support-dependent relations are randomly built between nodes of networks A and B. In our model we assume that each node in one network can function only if it has at least a single support node in...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	8,086
2406.01066	Topology-Aware Dynamic Reweighting for Distribution Shifts on Graph	Graph Neural Networks (GNNs) are widely used for node classification tasks but often fail to generalize when training and test nodes come from different distributions, limiting their practicality. To overcome this, recent approaches adopt invariant learning techniques from the out-of-distribution (OOD) generalization f...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	460,153
2103.08333	Nonequilibrium in Thermodynamic Formalism: the Second Law, gases and Information Geometry	In Nonequilibrium Thermodynamics and Information Theory, the relative entropy (or, KL divergence) plays a very important role. Consider a H\"older Jacobian $J$ and the Ruelle (transfer) operator $\mathcal{L}_{\log J}.$ Two equilibrium probabilities $\mu_1$ and $\mu_2$, can interact via a discrete-time {\it Thermodynami...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	224,876
2208.10469	Formal Contracts Mitigate Social Dilemmas in Multi-Agent RL	Multi-agent Reinforcement Learning (MARL) is a powerful tool for training autonomous agents acting independently in a common environment. However, it can lead to sub-optimal behavior when individual incentives and group incentives diverge. Humans are remarkably capable at solving these social dilemmas. It is an open pr...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	true	314,073
2010.07492	NeRF++: Analyzing and Improving Neural Radiance Fields	Neural Radiance Fields (NeRF) achieve impressive view synthesis results for a variety of capture settings, including 360 capture of bounded scenes and forward-facing capture of bounded and unbounded scenes. NeRF fits multi-layer perceptrons (MLPs) representing view-invariant opacity and view-dependent color volumes to ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	200,839
2407.07917	Non-Cooperative Backdoor Attacks in Federated Learning: A New Threat Landscape	Despite the promise of Federated Learning (FL) for privacy-preserving model training on distributed data, it remains susceptible to backdoor attacks. These attacks manipulate models by embedding triggers (specific input patterns) in the training data, forcing misclassification as predefined classes during deployment. T...	false	false	false	false	true	false	true	false	false	false	false	true	true	false	false	false	false	false	471,946
2006.16055	Harnessing Adversarial Distances to Discover High-Confidence Errors	Given a deep neural network image classification model that we treat as a black box, and an unlabeled evaluation dataset, we develop an efficient strategy by which the classifier can be evaluated. Randomly sampling and labeling instances from an unlabeled evaluation dataset allows traditional performance measures like ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	184,698
2307.13240	Fashion Matrix: Editing Photos by Just Talking	The utilization of Large Language Models (LLMs) for the construction of AI systems has garnered significant attention across diverse fields. The extension of LLMs to the domain of fashion holds substantial commercial potential but also inherent challenges due to the intricate semantic interactions in fashion-related ge...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	381,522
2210.06811	On the calibration of underrepresented classes in LiDAR-based semantic segmentation	The calibration of deep learning-based perception models plays a crucial role in their reliability. Our work focuses on a class-wise evaluation of several model's confidence performance for LiDAR-based semantic segmentation with the aim of providing insights into the calibration of underrepresented classes. Those class...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	323,458
1603.06928	Performance-Oriented Association in Large Cellular Networks with Technology Diversity	The development of mobile virtual network operators, where multiple wireless technologies (e.g. 3G and 4G) or operators with non-overlapping bandwidths are pooled and shared is expected to provide enhanced service with broader coverage, without incurring additional infrastructure cost. However, their emergence poses an...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	53,565
2105.01511	Radio Communication Scenarios in 5G-Railways	With the rapid development of railways, especially high-speed railways, there is an increasingly urgent demand for new wireless communication system for railways. Taking the mature 5G technology as an opportunity, 5G-railways (5G-R) have been widely regarded as a solution to meet the diversified demands of railway wire...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	233,543
2008.06738	Reducing Sampling Error in Batch Temporal Difference Learning	Temporal difference (TD) learning is one of the main foundations of modern reinforcement learning. This paper studies the use of TD(0), a canonical TD algorithm, to estimate the value function of a given policy from a batch of data. In this batch setting, we show that TD(0) may converge to an inaccurate value function ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	191,883
2406.04032	Zero-Painter: Training-Free Layout Control for Text-to-Image Synthesis	We present Zero-Painter, a novel training-free framework for layout-conditional text-to-image synthesis that facilitates the creation of detailed and controlled imagery from textual prompts. Our method utilizes object masks and individual descriptions, coupled with a global text prompt, to generate images with high fid...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	461,491
2205.03517	AdaptiveON: Adaptive Outdoor Local Navigation Method For Stable and Reliable Actions	We present a novel outdoor navigation algorithm to generate stable and efficient actions to navigate a robot to reach a goal. We use a multi-stage training pipeline and show that our approach produces policies that result in stable and reliable robot navigation on complex terrains. Based on the Proximal Policy Optimiza...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	295,305
2208.04625	Vital node identification in hypergraphs via gravity model	Hypergraphs that can depict interactions beyond pairwise edges have emerged as an appropriate representation for modeling polyadic relations in complex systems. With the recent surge of interest in researching hypergraphs, the centrality problem has attracted abundant attention due to the challenge of how to utilize th...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	312,178
2207.05138	Towards Personalized Healthcare in Cardiac Population: The Development of a Wearable ECG Monitoring System, an ECG Lossy Compression Schema, and a ResNet-Based AF Detector	Cardiovascular diseases (CVDs) are the number one cause of death worldwide. While there is growing evidence that the atrial fibrillation (AF) has strong associations with various CVDs, this heart arrhythmia is usually diagnosed using electrocardiography (ECG) which is a risk-free, non-intrusive, and cost-efficient tool...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	307,428
1909.00141	Deep Reinforcement Learning with Distributional Semantic Rewards for Abstractive Summarization	Deep reinforcement learning (RL) has been a commonly-used strategy for the abstractive summarization task to address both the exposure bias and non-differentiable task issues. However, the conventional reward Rouge-L simply looks for exact n-grams matches between candidates and annotated references, which inevitably ma...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	true	false	false	143,538
2312.15665	A Multi-Modal Contrastive Diffusion Model for Therapeutic Peptide Generation	Therapeutic peptides represent a unique class of pharmaceutical agents crucial for the treatment of human diseases. Recently, deep generative models have exhibited remarkable potential for generating therapeutic peptides, but they only utilize sequence or structure information alone, which hinders the performance in ge...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	418,086
1503.00899	An Ant Colony Optimization Algorithm for Partitioning Graphs with Supply and Demand	In this paper we focus on finding high quality solutions for the problem of maximum partitioning of graphs with supply and demand (MPGSD). There is a growing interest for the MPGSD due to its close connection to problems appearing in the field of electrical distribution systems, especially for the optimization of self-...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	40,765
2407.14373	Adaptive State Observers of Linear Time-varying Descriptor Systems: A Parameter Estimation-Based Approach	In this paper, we apply the recently developed generalized parameter estimation-based observer design technique for state-affine systems to the practically important case of linear time-varying descriptor systems with uncertain parameters. We give simulation results of benchmark examples that illustrate the performance...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	474,760
1702.07881	On the Performance of Wireless Powered Communication With Non-linear Energy Harvesting	In this paper, we analyze the performance of a time-slotted multi-antenna wireless powered communication (WPC) system, where a wireless device first harvests radio frequency (RF) energy from a power station (PS) in the downlink to facilitate information transfer to an information receiving station (IRS) in the uplink. ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	68,858
2010.04069	Nonlinear Model Predictive Control of Permanent Magnet Synchronous Generators in DC Microgrids	A new strategy is proposed to control interior permanent magnet generators in dc microgrids interfaced through an active rectifier. The controller design is based on the decomposition of the system dynamics into slow and fast modes using singular perturbation theory. An inner current controller is developed based on ou...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	199,613
2406.11786	A Brief Survey on Leveraging Large Scale Vision Models for Enhanced Robot Grasping	Robotic grasping presents a difficult motor task in real-world scenarios, constituting a major hurdle to the deployment of capable robots across various industries. Notably, the scarcity of data makes grasping particularly challenging for learned models. Recent advancements in computer vision have witnessed a growth of...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	465,058
2002.10392	Suppressing Uncertainties for Large-Scale Facial Expression Recognition	Annotating a qualitative large-scale facial expression dataset is extremely difficult due to the uncertainties caused by ambiguous facial expressions, low-quality facial images, and the subjectiveness of annotators. These uncertainties lead to a key challenge of large-scale Facial Expression Recognition (FER) in deep l...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	165,391
2108.04378	Making Transformers Solve Compositional Tasks	Several studies have reported the inability of Transformer models to generalize compositionally, a key type of generalization in many NLP tasks such as semantic parsing. In this paper we explore the design space of Transformer models showing that the inductive biases given to the model by several design decisions signi...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	249,983
2208.02030	BPMN4sML: A BPMN Extension for Serverless Machine Learning. Technology Independent and Interoperable Modeling of Machine Learning Workflows and their Serverless Deployment Orchestration	Machine learning (ML) continues to permeate all layers of academia, industry and society. Despite its successes, mental frameworks to capture and represent machine learning workflows in a consistent and coherent manner are lacking. For instance, the de facto process modeling standard, Business Process Model and Notatio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	311,358
2204.05963	Safety in Augmented Importance Sampling: Performance Bounds for Robust MPPI	This work explores the nature of augmented importance sampling in safety-constrained model predictive control problems. When operating in a constrained environment, sampling based model predictive control and motion planning typically utilizes penalty functions or expensive optimization based control barrier algorithms...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	291,196
1610.01455	Scheduling Feasibility of Energy Management in Micro-grids Based on Significant Moment Analysis	This paper studies the operation and scheduling of electric loads in micro-grid, a highly automated and distributed cyber-physical energy system (CPES). We establish rigorous mathematical expressions for electric loads and battery banks in the micro-grid by considering their characteristics and constraints. Based on th...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	61,969
2010.06061	CADET: Debugging and Fixing Misconfigurations using Counterfactual Reasoning	Modern computing platforms are highly-configurable with thousands of interacting configurations. However, configuring these systems is challenging. Erroneous configurations can cause unexpected non-functional faults. This paper proposes CADET (short for Causal Debugging Toolkit) that enables users to identify, explain,...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	200,349
2012.04322	Quality-Diversity Optimization: a novel branch of stochastic optimization	Traditional optimization algorithms search for a single global optimum that maximizes (or minimizes) the objective function. Multimodal optimization algorithms search for the highest peaks in the search space that can be more than one. Quality-Diversity algorithms are a recent addition to the evolutionary computation t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	210,419
2210.02205	Game Theoretic Rating in N-player general-sum games with Equilibria	Rating strategies in a game is an important area of research in game theory and artificial intelligence, and can be applied to any real-world competitive or cooperative setting. Traditionally, only transitive dependencies between strategies have been used to rate strategies (e.g. Elo), however recent work has expanded ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	true	321,567
1508.03391	Reward Shaping with Recurrent Neural Networks for Speeding up On-Line Policy Learning in Spoken Dialogue Systems	Statistical spoken dialogue systems have the attractive property of being able to be optimised from data via interactions with real users. However in the reinforcement learning paradigm the dialogue manager (agent) often requires significant time to explore the state-action space to learn to behave in a desirable manne...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	45,995
2306.09992	Rewriting the Script: Adapting Text Instructions for Voice Interaction	Voice assistants have sharply risen in popularity in recent years, but their use has been limited mostly to simple applications like music, hands-free search, or control of internet-of-things devices. What would it take for voice assistants to guide people through more complex tasks? In our work, we study the limitatio...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	374,046
2312.05190	Fine Dense Alignment of Image Bursts through Camera Pose and Depth Estimation	This paper introduces a novel approach to the fine alignment of images in a burst captured by a handheld camera. In contrast to traditional techniques that estimate two-dimensional transformations between frame pairs or rely on discrete correspondences, the proposed algorithm establishes dense correspondences by optimi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	413,978
0705.2235	Response Prediction of Structural System Subject to Earthquake Motions using Artificial Neural Network	This paper uses Artificial Neural Network (ANN) models to compute response of structural system subject to Indian earthquakes at Chamoli and Uttarkashi ground motion data. The system is first trained for a single real earthquake data. The trained ANN architecture is then used to simulate earthquakes with various intens...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	247
2011.11314	Synthesizing Optical and SAR Imagery From Land Cover Maps and Auxiliary Raster Data	We synthesize both optical RGB and synthetic aperture radar (SAR) remote sensing images from land cover maps and auxiliary raster data using generative adversarial networks (GANs). In remote sensing, many types of data, such as digital elevation models (DEMs) or precipitation maps, are often not reflected in land cover...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	207,796
2405.11619	Novel Interpretable and Robust Web-based AI Platform for Phishing Email Detection	Phishing emails continue to pose a significant threat, causing financial losses and security breaches. This study addresses limitations in existing research, such as reliance on proprietary datasets and lack of real-world application, by proposing a high-performance machine learning model for email classification. Util...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	455,216
1911.00666	Progressive Sample Mining and Representation Learning for One-Shot Person Re-identification with Adversarial Samples	In this paper, we aim to tackle the one-shot person re-identification problem where only one image is labelled for each person, while other images are unlabelled. This task is challenging due to the lack of sufficient labelled training data. To tackle this problem, we propose to iteratively guess pseudo labels for the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	151,882
2305.12167	The Case Against Explainability	As artificial intelligence (AI) becomes more prevalent there is a growing demand from regulators to accompany decisions made by such systems with explanations. However, a persistent gap exists between the need to execute a meaningful right to explanation vs. the ability of Machine Learning systems to deliver on such a ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	365,870
2008.00504	Variational Filtering with Copula Models for SLAM	The ability to infer map variables and estimate pose is crucial to the operation of autonomous mobile robots. In most cases the shared dependency between these variables is modeled through a multivariate Gaussian distribution, but there are many situations where that assumption is unrealistic. Our paper shows how it is...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	190,028
1104.3161	Robust Secure Transmission in MISO Channels Based on Worst-Case Optimization	This paper studies robust transmission schemes for multiple-input single-output (MISO) wiretap channels. Both the cases of direct transmission and cooperative jamming with a helper are investigated with imperfect channel state information (CSI) for the eavesdropper links. Robust transmit covariance matrices are obtaine...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	10,004
1905.05446	D2D Assisted Beamforming for Coded Caching	Device-to-device (D2D) aided beamforming for coded caching is considered in finite signal-to-noise ratio regime. A novel beamforming scheme is proposed where the local cache content exchange among nearby users is exploited. The transmission is split into two phases: local D2D content exchange and downlink transmission....	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	130,731
1811.12035	Utilizing Complex-valued Network for Learning to Compare Image Patches	At present, the great achievements of convolutional neural network(CNN) in feature and metric learning have attracted many researchers. However, the vast majority of deep network architectures have been used to represent based on real values. The research of complex-valued networks is seldom concerned due to the absenc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	114,919
2301.08562	Latent Autoregressive Source Separation	Autoregressive models have achieved impressive results over a wide range of domains in terms of generation quality and downstream task performance. In the continuous domain, a key factor behind this success is the usage of quantized latent spaces (e.g., obtained via VQ-VAE autoencoders), which allow for dimensionality ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	341,235
1908.05024	Person Re-identification in Aerial Imagery	Nowadays, with the rapid development of consumer Unmanned Aerial Vehicles (UAVs), visual surveillance by utilizing the UAV platform has been very attractive. Most of the research works for UAV captured visual data are mainly focused on the tasks of object detection and tracking. However, limited attention has been paid...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	141,628
2303.07771	Imbalanced Domain Generalization for Robust Single Cell Classification in Hematological Cytomorphology	Accurate morphological classification of white blood cells (WBCs) is an important step in the diagnosis of leukemia, a disease in which nonfunctional blast cells accumulate in the bone marrow. Recently, deep convolutional neural networks (CNNs) have been successfully used to classify leukocytes by training them on sing...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	351,374
2405.03666	ScrewMimic: Bimanual Imitation from Human Videos with Screw Space Projection	Bimanual manipulation is a longstanding challenge in robotics due to the large number of degrees of freedom and the strict spatial and temporal synchronization required to generate meaningful behavior. Humans learn bimanual manipulation skills by watching other humans and by refining their abilities through play. In th...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	452,267
2102.02811	CrossNorm and SelfNorm for Generalization under Distribution Shifts	Traditional normalization techniques (e.g., Batch Normalization and Instance Normalization) generally and simplistically assume that training and test data follow the same distribution. As distribution shifts are inevitable in real-world applications, well-trained models with previous normalization methods can perform ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	218,530
2003.06464	LCP: A Low-Communication Parallelization Method for Fast Neural Network Inference in Image Recognition	Deep neural networks (DNNs) have inspired new studies in myriad edge applications with robots, autonomous agents, and Internet-of-things (IoT) devices. However, performing inference of DNNs in the edge is still a severe challenge, mainly because of the contradiction between the intensive resource requirements of DNNs a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	168,115
2009.03364	Adversarial attacks on deep learning models for fatty liver disease classification by modification of ultrasound image reconstruction method	Convolutional neural networks (CNNs) have achieved remarkable success in medical image analysis tasks. In ultrasound (US) imaging, CNNs have been applied to object classification, image reconstruction and tissue characterization. However, CNNs can be vulnerable to adversarial attacks, even small perturbations applied t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	194,798
1911.10454	Regularized and Smooth Double Core Tensor Factorization for Heterogeneous Data	We introduce a general tensor model suitable for data analytic tasks for {\em heterogeneous} datasets, wherein there are joint low-rank structures within groups of observations, but also discriminative structures across different groups. To capture such complex structures, a double core tensor (DCOT) factorization mode...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	154,837
2307.12898	As Time Goes By: Adding a Temporal Dimension Towards Resolving Delegations in Liquid Democracy	In recent years, the study of various models and questions related to Liquid Democracy has been of growing interest among the community of Computational Social Choice. A concern that has been raised, is that current academic literature focuses solely on static inputs, concealing a key characteristic of Liquid Democracy...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	381,416
1207.6083	Determinantal point processes for machine learning	Determinantal point processes (DPPs) are elegant probabilistic models of repulsion that arise in quantum physics and random matrix theory. In contrast to traditional structured models like Markov random fields, which become intractable and hard to approximate in the presence of negative correlations, DPPs offer efficie...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	17,762
1809.03676	Unbiasing Semantic Segmentation For Robot Perception using Synthetic Data Feature Transfer	Robot perception systems need to perform reliable image segmentation in real-time on noisy, raw perception data. State-of-the-art segmentation approaches use large CNN models and carefully constructed datasets; however, these models focus on accuracy at the cost of real-time inference. Furthermore, the standard semanti...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	107,385
2501.11246	Unlocking the Potential: A Novel Tool for Assessing Untapped Micro-Pumped Hydro Energy Storage Systems in Michigan	This study presents an innovative tool designed to unlock the potential of Michigan's lakes and dams for applications such as water resource management and renewable energy generation. Given Michigan's relatively flat landscape, the focus is on systems that could serve as micro-hydro energy storage solutions. To ensure...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	525,849
2010.04965	Scaling Guarantees for Nearest Counterfactual Explanations	Counterfactual explanations (CFE) are being widely used to explain algorithmic decisions, especially in consequential decision-making contexts (e.g., loan approval or pretrial bail). In this context, CFEs aim to provide individuals affected by an algorithmic decision with the most similar individual (i.e., nearest indi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	199,939
2502.08974	Topo2Seq: Enhanced Topology Reasoning via Topology Sequence Learning	Extracting lane topology from perspective views (PV) is crucial for planning and control in autonomous driving. This approach extracts potential drivable trajectories for self-driving vehicles without relying on high-definition (HD) maps. However, the unordered nature and weak long-range perception of the DETR-like fra...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	533,250
1912.12031	Two families of Entanglement-assisted quantum MDS codes from constacyclic codes	Entanglement-assisted quantum error correcting codes (EAQECCs) can be derived from arbitrary classical linear codes. However, it is a very difficult task to determine the number of entangled states required. In this work, using the method of the decomposition of the defining set of constacyclic codes, we construct two ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	158,736
2501.13796	PromptMono: Cross Prompting Attention for Self-Supervised Monocular Depth Estimation in Challenging Environments	Considerable efforts have been made to improve monocular depth estimation under ideal conditions. However, in challenging environments, monocular depth estimation still faces difficulties. In this paper, we introduce visual prompt learning for predicting depth across different environments within a unified model, and p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	526,827
2205.07514	Residual Local Feature Network for Efficient Super-Resolution	Deep learning based approaches has achieved great performance in single image super-resolution (SISR). However, recent advances in efficient super-resolution focus on reducing the number of parameters and FLOPs, and they aggregate more powerful features by improving feature utilization through complex layer connection ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	296,628
1912.11888	W-PoseNet: Dense Correspondence Regularized Pixel Pair Pose Regression	Solving 6D pose estimation is non-trivial to cope with intrinsic appearance and shape variation and severe inter-object occlusion, and is made more challenging in light of extrinsic large illumination changes and low quality of the acquired data under an uncontrolled environment. This paper introduces a novel pose esti...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	158,691
2405.05669	Passive Obstacle Aware Control to Follow Desired Velocities	Evaluating and updating the obstacle avoidance velocity for an autonomous robot in real-time ensures robustness against noise and disturbances. A passive damping controller can obtain the desired motion with a torque-controlled robot, which remains compliant and ensures a safe response to external perturbations. Here, ...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	453,013
1908.07144	StateLens: A Reverse Engineering Solution for Making Existing Dynamic Touchscreens Accessible	Blind people frequently encounter inaccessible dynamic touchscreens in their everyday lives that are difficult, frustrating, and often impossible to use independently. Touchscreens are often the only way to control everything from coffee machines and payment terminals, to subway ticket machines and in-flight entertainm...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	142,223
1912.06697	ViBE: Dressing for Diverse Body Shapes	Body shape plays an important role in determining what garments will best suit a given person, yet today's clothing recommendation methods take a "one shape fits all" approach. These body-agnostic vision methods and datasets are a barrier to inclusion, ill-equipped to provide good suggestions for diverse body shapes. W...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	157,400
1008.5393	Increased Capacity per Unit-Cost by Oversampling	It is demonstrated that doubling the sampling rate recovers some of the loss in capacity incurred on the bandlimited Gaussian channel with a one-bit output quantizer.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	7,430
1704.07441	Detecting English Writing Styles For Non Native Speakers	This paper presents the first attempt, up to our knowledge, to classify English writing styles on this scale with the challenge of classifying day to day language written by writers with different backgrounds covering various areas of topics.The paper proposes simple machine learning algorithms and simple to generate f...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	72,353
1906.02037	The FacT: Taming Latent Factor Models for Explainability with Factorization Trees	Latent factor models have achieved great success in personalized recommendations, but they are also notoriously difficult to explain. In this work, we integrate regression trees to guide the learning of latent factor models for recommendation, and use the learnt tree structure to explain the resulting latent factors. S...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	133,918
2004.08279	Bypassing or flying above the obstacles? A novel multi-objective UAV path planning problem	This study proposes a novel multi-objective integer programming model for a collision-free discrete drone path planning problem. Considering the possibility of bypassing obstacles or flying above them, this study aims to minimize the path length, energy consumption, and maximum path risk simultaneously. The static envi...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	173,021
1907.00329	Prediction of Small Molecule Kinase Inhibitors for Chemotherapy Using Deep Learning	The current state of cancer therapeutics has been moving away from one-size-fits-all cytotoxic chemotherapy, and towards a more individualized and specific approach involving the targeting of each tumor's genetic vulnerabilities. Different tumors, even of the same type, may be more reliant on certain cellular pathways ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	137,011
2309.14390	Early Churn Prediction from Large Scale User-Product Interaction Time Series	User churn, characterized by customers ending their relationship with a business, has profound economic consequences across various Business-to-Customer scenarios. For numerous system-to-user actions, such as promotional discounts and retention campaigns, predicting potential churners stands as a primary objective. In ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	394,592
2412.01587	Handwriting-based Automated Assessment and Grading of Degree of Handedness: A Pilot Study	Hand preference and degree of handedness (DoH) are two different aspects of human behavior which are often confused to be one. DoH is a person's inherent capability of the brain; affected by nature and nurture. In this study, we used dominant and non-dominant handwriting traits to assess DoH for the first time, on 43 s...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	513,182
2310.14963	Studying K-FAC Heuristics by Viewing Adam through a Second-Order Lens	Research into optimisation for deep learning is characterised by a tension between the computational efficiency of first-order, gradient-based methods (such as SGD and Adam) and the theoretical efficiency of second-order, curvature-based methods (such as quasi-Newton methods and K-FAC). Noting that second-order methods...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	402,101
2306.01464	Theoretical Behavior of XAI Methods in the Presence of Suppressor Variables	In recent years, the community of 'explainable artificial intelligence' (XAI) has created a vast body of methods to bridge a perceived gap between model 'complexity' and 'interpretability'. However, a concrete problem to be solved by XAI methods has not yet been formally stated. As a result, XAI methods are lacking the...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	370,471
1708.06274	This Far, No Further: Introducing Virtual Borders to Mobile Robots Using a Laser Pointer	We address the problem of controlling the workspace of a 3-DoF mobile robot. In a human-robot shared space, robots should navigate in a human-acceptable way according to the users' demands. For this purpose, we employ virtual borders, that are non-physical borders, to allow a user the restriction of the robot's workspa...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	79,297
1908.07031	Partially Observable Markov Decision Process Modelling for Assessing Hierarchies	Hierarchical clustering has been shown to be valuable in many scenarios. Despite its usefulness to many situations, there is no agreed methodology on how to properly evaluate the hierarchies produced from different techniques, particularly in the case where ground-truth labels are unavailable. This motivates us to prop...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	142,184
2012.09036	Improved StyleGAN Embedding: Where are the Good Latents?	StyleGAN is able to produce photorealistic images that are almost indistinguishable from real photos. The reverse problem of finding an embedding for a given image poses a challenge. Embeddings that reconstruct an image well are not always robust to editing operations. In this paper, we address the problem of finding a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	211,945
2404.00878	TryOn-Adapter: Efficient Fine-Grained Clothing Identity Adaptation for High-Fidelity Virtual Try-On	Virtual try-on focuses on adjusting the given clothes to fit a specific person seamlessly while avoiding any distortion of the patterns and textures of the garment. However, the clothing identity uncontrollability and training inefficiency of existing diffusion-based methods, which struggle to maintain the identity eve...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	443,142
1611.09701	Computationally Efficient Unscented Kalman Filtering Techniques for Launch Vehicle Navigation using a Space-borne GPS Receiver	The Extended Kalman Filter (EKF) is a well established technique for position and velocity estimation. However, the performance of the EKF degrades considerably in highly non-linear system applications as it requires local linearisation in its prediction stage. The Unscented Kalman Filter (UKF) was developed to address...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	64,702
2105.14995	Choose a Transformer: Fourier or Galerkin	In this paper, we apply the self-attention from the state-of-the-art Transformer in Attention Is All You Need for the first time to a data-driven operator learning problem related to partial differential equations. An effort is put together to explain the heuristics of, and to improve the efficacy of the attention mech...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	237,879
1802.04497	A Dimension-Independent discriminant between distributions	Henze-Penrose divergence is a non-parametric divergence measure that can be used to estimate a bound on the Bayes error in a binary classification problem. In this paper, we show that a cross-match statistic based on optimal weighted matching can be used to directly estimate Henze-Penrose divergence. Unlike an earlier ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	90,236
2311.00808	Mahalanobis-Aware Training for Out-of-Distribution Detection	While deep learning models have seen widespread success in controlled environments, there are still barriers to their adoption in open-world settings. One critical task for safe deployment is the detection of anomalous or out-of-distribution samples that may require human intervention. In this work, we present a novel ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	404,781

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