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
2203.00809	Instance-aware multi-object self-supervision for monocular depth prediction	This paper proposes a self-supervised monocular image-to-depth prediction framework that is trained with an end-to-end photometric loss that handles not only 6-DOF camera motion but also 6-DOF moving object instances. Self-supervision is performed by warping the images across a video sequence using depth and scene moti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	283,126
1810.06749	Optimally rotated coordinate systems for adaptive least-squares regression on sparse grids	For low-dimensional data sets with a large amount of data points, standard kernel methods are usually not feasible for regression anymore. Besides simple linear models or involved heuristic deep learning models, grid-based discretizations of larger (kernel) model classes lead to algorithms, which naturally scale linear...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	110,494
2108.12516	Few-Shot Table-to-Text Generation with Prototype Memory	Neural table-to-text generation models have achieved remarkable progress on an array of tasks. However, due to the data-hungry nature of neural models, their performances strongly rely on large-scale training examples, limiting their applicability in real-world applications. To address this, we propose a new framework:...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	252,515
1703.06554	Object category understanding via eye fixations on freehand sketches	The study of eye gaze fixations on photographic images is an active research area. In contrast, the image subcategory of freehand sketches has not received as much attention for such studies. In this paper, we analyze the results of a free-viewing gaze fixation study conducted on 3904 freehand sketches distributed acro...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	70,248
1209.6342	Sparse Ising Models with Covariates	There has been a lot of work fitting Ising models to multivariate binary data in order to understand the conditional dependency relationships between the variables. However, additional covariates are frequently recorded together with the binary data, and may influence the dependence relationships. Motivated by such a d...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	18,807
1605.04063	A construction of $q$-ary linear codes with two weights	Linear codes with a few weights are very important in coding theory and have attracted a lot of attention. In this paper, we present a construction of $q$-ary linear codes from trace and norm functions over finite fields. The weight distributions of the linear codes are determined in some cases based on Gauss sums. It ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	55,823
2206.02914	Training Subset Selection for Weak Supervision	Existing weak supervision approaches use all the data covered by weak signals to train a classifier. We show both theoretically and empirically that this is not always optimal. Intuitively, there is a tradeoff between the amount of weakly-labeled data and the precision of the weak labels. We explore this tradeoff by co...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	301,075
2109.12040	From images in the wild to video-informed image classification	Image classifiers work effectively when applied on structured images, yet they often fail when applied on images with very high visual complexity. This paper describes experiments applying state-of-the-art object classifiers toward a unique set of images in the wild with high visual complexity collected on the island o...	false	false	false	false	false	false	true	false	false	false	false	true	false	true	false	false	false	false	257,137
2410.19635	Frozen-DETR: Enhancing DETR with Image Understanding from Frozen Foundation Models	Recent vision foundation models can extract universal representations and show impressive abilities in various tasks. However, their application on object detection is largely overlooked, especially without fine-tuning them. In this work, we show that frozen foundation models can be a versatile feature enhancer, even t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	502,394
1704.00077	Geodesic Distance Histogram Feature for Video Segmentation	This paper proposes a geodesic-distance-based feature that encodes global information for improved video segmentation algorithms. The feature is a joint histogram of intensity and geodesic distances, where the geodesic distances are computed as the shortest paths between superpixels via their boundaries. We also incorp...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	71,017
2009.14786	Measuring Systematic Generalization in Neural Proof Generation with Transformers	We are interested in understanding how well Transformer language models (TLMs) can perform reasoning tasks when trained on knowledge encoded in the form of natural language. We investigate their systematic generalization abilities on a logical reasoning task in natural language, which involves reasoning over relationsh...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	198,139
2006.06320	Hypernetwork-Based Augmentation	Data augmentation is an effective technique to improve the generalization of deep neural networks. Recently, AutoAugment proposed a well-designed search space and a search algorithm that automatically finds augmentation policies in a data-driven manner. However, AutoAugment is computationally intensive. In this paper, ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	181,383
2109.02625	ERA: Entity Relationship Aware Video Summarization with Wasserstein GAN	Video summarization aims to simplify large scale video browsing by generating concise, short summaries that diver from but well represent the original video. Due to the scarcity of video annotations, recent progress for video summarization concentrates on unsupervised methods, among which the GAN based methods are most...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	253,807
2302.00518	Probabilistic Search and Track with Multiple Mobile Agents	In this paper we are interested in the task of searching and tracking multiple moving targets in a bounded surveillance area with a group of autonomous mobile agents. More specifically, we assume that targets can appear and disappear at random times inside the surveillance region and their positions are random and unkn...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	343,243
2005.10379	Hierarchical Isometry Properties of Hierarchical Measurements	A new class of measurement operators, coined hierarchical measurement operators, and prove results guaranteeing the efficient, stable and robust recovery of hierarchically structured signals from such measurements. We derive bounds on their hierarchical restricted isometry properties based on the restricted isometry co...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	178,157
2309.08375	Boosting Fair Classifier Generalization through Adaptive Priority Reweighing	With the increasing penetration of machine learning applications in critical decision-making areas, calls for algorithmic fairness are more prominent. Although there have been various modalities to improve algorithmic fairness through learning with fairness constraints, their performance does not generalize well in the...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	392,144
2104.05544	Investigating Methods to Improve Language Model Integration for Attention-based Encoder-Decoder ASR Models	Attention-based encoder-decoder (AED) models learn an implicit internal language model (ILM) from the training transcriptions. The integration with an external LM trained on much more unpaired text usually leads to better performance. A Bayesian interpretation as in the hybrid autoregressive transducer (HAT) suggests d...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	229,767
1404.1518	Nearly Optimal Minimax Tree Search?	Knuth and Moore presented a theoretical lower bound on the number of leaves that any fixed-depth minimax tree-search algorithm traversing a uniform tree must explore, the so-called minimal tree. Since real-life minimax trees are not uniform, the exact size of this tree is not known for most applications. Further, most ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	32,125
1907.11484	Multi-level Domain Adaptive learning for Cross-Domain Detection	In recent years, object detection has shown impressive results using supervised deep learning, but it remains challenging in a cross-domain environment. The variations of illumination, style, scale, and appearance in different domains can seriously affect the performance of detection models. Previous works use adversar...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	139,861
1510.06482	Triangular Alignment (TAME): A Tensor-based Approach for Higher-order Network Alignment	Network alignment has extensive applications in comparative interactomics. Traditional approaches aim to simultaneously maximize the number of conserved edges and the underlying similarity of aligned entities. We propose a novel formulation of the network alignment problem that extends topological similarity to higher-...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	48,113
2501.16373	Unveiling Discrete Clues: Superior Healthcare Predictions for Rare Diseases	Accurate healthcare prediction is essential for improving patient outcomes. Existing work primarily leverages advanced frameworks like attention or graph networks to capture the intricate collaborative (CO) signals in electronic health records. However, prediction for rare diseases remains challenging due to limited co...	false	true	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	527,938
2105.05980	DONet: Dual-Octave Network for Fast MR Image Reconstruction	Magnetic resonance (MR) image acquisition is an inherently prolonged process, whose acceleration has long been the subject of research. This is commonly achieved by obtaining multiple undersampled images, simultaneously, through parallel imaging. In this paper, we propose the Dual-Octave Network (DONet), which is capab...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	234,975
2305.18445	Intelligent gradient amplification for deep neural networks	Deep learning models offer superior performance compared to other machine learning techniques for a variety of tasks and domains, but pose their own challenges. In particular, deep learning models require larger training times as the depth of a model increases, and suffer from vanishing gradients. Several solutions add...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	369,061
2209.12602	Effects of language mismatch in automatic forensic voice comparison using deep learning embeddings	In forensic voice comparison the speaker embedding has become widely popular in the last 10 years. Most of the pretrained speaker embeddings are trained on English corpora, because it is easily accessible. Thus, language dependency can be an important factor in automatic forensic voice comparison, especially when the t...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	319,586
2307.03968	Multi-Level Power Series Solution for Large Surface and Volume Electric Field Integral Equation	In this paper, we propose a new multilevel power series solution method for solving a large surface and volume electric field integral equation based H-Matrix. The proposed solution method converges in a fixed number of iterations and is solved at each level of the H-Matrix computation.The solution method avoids the co...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	378,226
1412.6988	Universal test for Hippocratic randomness	Hippocratic randomness is defined in a similar way to Martin-Lof randomness, however it does not assume computability of the probability and the existence of universal test is not assured. We introduce the notion of approximation of probability and show the existence of the universal test (Levin-Schnorr theorem) for Hi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	38,744
1805.11653	LSTMs Exploit Linguistic Attributes of Data	While recurrent neural networks have found success in a variety of natural language processing applications, they are general models of sequential data. We investigate how the properties of natural language data affect an LSTM's ability to learn a nonlinguistic task: recalling elements from its input. We find that mode...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	98,971
2306.16707	DiffusionSTR: Diffusion Model for Scene Text Recognition	This paper presents Diffusion Model for Scene Text Recognition (DiffusionSTR), an end-to-end text recognition framework using diffusion models for recognizing text in the wild. While existing studies have viewed the scene text recognition task as an image-to-text transformation, we rethought it as a text-text one under...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	376,460
2008.04640	High-concurrency Custom-build Relational Database System's design and SQL parser design based on Turing-complete automata	Database system is an indispensable part of software projects. It plays an important role in data organization and storage. Its performance and efficiency are directly related to the performance of software. Nowadays, we have many general relational database systems that can be used in our projects, such as SQL Server,...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	191,285
2309.06388	Computational Approaches for Predicting Drug-Disease Associations: A Comprehensive Review	In recent decades, traditional drug research and development have been facing challenges such as high cost, long timelines, and high risks. To address these issues, many computational approaches have been suggested for predicting the relationship between drugs and diseases through drug repositioning, aiming to reduce t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	391,407
1701.07488	Joint Power Allocation and Beamforming for Energy-Efficient Two-Way Multi-Relay Communications	This paper considers the joint design of user power allocation and relay beamforming in relaying communications, in which multiple pairs of single-antenna users exchange information with each other via multiple-antenna relays in two time slots. All users transmit their signals to the relays in the first time slot while...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	67,300
2401.02991	GLIDE-RL: Grounded Language Instruction through DEmonstration in RL	One of the final frontiers in the development of complex human - AI collaborative systems is the ability of AI agents to comprehend the natural language and perform tasks accordingly. However, training efficient Reinforcement Learning (RL) agents grounded in natural language has been a long-standing challenge due to th...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	419,924
2305.00813	Neurosymbolic AI -- Why, What, and How	Humans interact with the environment using a combination of perception - transforming sensory inputs from their environment into symbols, and cognition - mapping symbols to knowledge about the environment for supporting abstraction, reasoning by analogy, and long-term planning. Human perception-inspired machine percept...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	361,462
2407.18716	ChatSchema: A pipeline of extracting structured information with Large Multimodal Models based on schema	Objective: This study introduces ChatSchema, an effective method for extracting and structuring information from unstructured data in medical paper reports using a combination of Large Multimodal Models (LMMs) and Optical Character Recognition (OCR) based on the schema. By integrating predefined schema, we intend to en...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	476,492
2412.05625	Can Large Language Models Help Developers with Robotic Finite State Machine Modification?	Finite state machines (FSMs) are widely used to manage robot behavior logic, particularly in real-world applications that require a high degree of reliability and structure. However, traditional manual FSM design and modification processes can be time-consuming and error-prone. We propose that large language models (LL...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	514,906
2401.08047	Incremental Extractive Opinion Summarization Using Cover Trees	Extractive opinion summarization involves automatically producing a summary of text about an entity (e.g., a product's reviews) by extracting representative sentences that capture prevalent opinions in the review set. Typically, in online marketplaces user reviews accumulate over time, and opinion summaries need to be ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	421,743
2201.05752	Moses: Efficient Exploitation of Cross-device Transferable Features for Tensor Program Optimization	Achieving efficient execution of machine learning models has attracted significant attention recently. To generate tensor programs efficiently, a key component of DNN compilers is the cost model that can predict the performance of each configuration on specific devices. However, due to the rapid emergence of hardware p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	275,478
2101.02244	User Ex Machina : Simulation as a Design Probe in Human-in-the-Loop Text Analytics	Topic models are widely used analysis techniques for clustering documents and surfacing thematic elements of text corpora. These models remain challenging to optimize and often require a "human-in-the-loop" approach where domain experts use their knowledge to steer and adjust. However, the fragility, incompleteness, an...	true	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	214,560
2107.06870	Reinforced Hybrid Genetic Algorithm for the Traveling Salesman Problem	In this paper, we propose a new method called the Reinforced Hybrid Genetic Algorithm (RHGA) for solving the famous NP-hard Traveling Salesman Problem (TSP). Specifically, we combine reinforcement learning with the well-known Edge Assembly Crossover genetic algorithm (EAX-GA) and the Lin-Kernighan-Helsgaun (LKH) local ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	246,222
2311.14997	Every latin hypercube of order 5 has transversals	We prove that for all n>1 every latin n-dimensional cube of order 5 has transversals. We find all 123 paratopy classes of layer-latin cubes of order 5 with no transversals. For each $n\geq 3$ and $q\geq 3$ we construct a (2q-2)-layer latin n-dimensional cuboid with no transversals. Moreover, we find all paratopy classe...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	410,343
2006.07695	Learning Sparse Graphons and the Generalized Kesten-Stigum Threshold	The problem of learning graphons has attracted considerable attention across several scientific communities, with significant progress over the recent years in sparser regimes. Yet, the current techniques still require diverging degrees in order to succeed with efficient algorithms in the challenging cases where the lo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,902
2302.13796	Fast Trajectory End-Point Prediction with Event Cameras for Reactive Robot Control	Prediction skills can be crucial for the success of tasks where robots have limited time to act or joints actuation power. In such a scenario, a vision system with a fixed, possibly too low, sampling rate could lead to the loss of informative points, slowing down prediction convergence and reducing the accuracy. In thi...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	348,058
1803.02578	Generating Goal-Directed Visuomotor Plans Based on Learning Using a Predictive Coding-type Deep Visuomotor Recurrent Neural Network Model	The current paper presents how a predictive coding type deep recurrent neural networks can generate vision-based goal-directed plans based on prior learning experience by examining experiment results using a real arm robot. The proposed deep recurrent neural network learns to predict visuo-proprioceptive sequences by e...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	92,091
2409.07914	InterACT: Inter-dependency Aware Action Chunking with Hierarchical Attention Transformers for Bimanual Manipulation	Bimanual manipulation presents unique challenges compared to unimanual tasks due to the complexity of coordinating two robotic arms. In this paper, we introduce InterACT: Inter-dependency aware Action Chunking with Hierarchical Attention Transformers, a novel imitation learning framework designed specifically for biman...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	487,707
2212.07719	Time-limited Balanced Truncation for Data Assimilation Problems	Balanced truncation is a well-established model order reduction method which has been applied to a variety of problems. Recently, a connection between linear Gaussian Bayesian inference problems and the system-theoretic concept of balanced truncation has been drawn. Although this connection is new, the application of b...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	336,497
1903.10693	Decomposing information into copying versus transformation	In many real-world systems, information can be transmitted in two qualitatively different ways: by copying or by transformation. Copying occurs when messages are transmitted without modification, e.g., when an offspring receives an unaltered copy of a gene from its parent. Transformation occurs when messages are modifi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	125,342
2212.00187	Five Properties of Specific Curiosity You Didn't Know Curious Machines Should Have	Curiosity for machine agents has been a focus of lively research activity. The study of human and animal curiosity, particularly specific curiosity, has unearthed several properties that would offer important benefits for machine learners, but that have not yet been well-explored in machine intelligence. In this work, ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	333,964
2310.08697	The Data Lakehouse: Data Warehousing and More	Relational Database Management Systems designed for Online Analytical Processing (RDBMS-OLAP) have been foundational to democratizing data and enabling analytical use cases such as business intelligence and reporting for many years. However, RDBMS-OLAP systems present some well-known challenges. They are primarily opti...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	399,489
1508.00784	Are You Really Hidden? Predicting Current City from Profile and Social Relationship	Privacy has become a major concern in Online Social Networks (OSNs) due to threats such as advertising spam, online stalking and identity theft. Although many users hide or do not fill out their private attributes in OSNs, prior studies point out that the hidden attributes may be inferred from some other public informa...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	45,712
1606.01077	A Fuzzy Approach to Qualification in Design Exploration for Autonomous Robots and Systems	Autonomous robots must operate in complex and changing environments subject to requirements on their behaviour. Verifying absolute satisfaction (true or false) of these requirements is challenging. Instead, we analyse requirements that admit flexible degrees of satisfaction. We analyse vague requirements using fuzzy lo...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	56,747
2310.14194	Distractor-aware Event-based Tracking	Event cameras, or dynamic vision sensors, have recently achieved success from fundamental vision tasks to high-level vision researches. Due to its ability to asynchronously capture light intensity changes, event camera has an inherent advantage to capture moving objects in challenging scenarios including objects under ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	401,752
2209.04448	Learning sparse auto-encoders for green AI image coding	Recently, convolutional auto-encoders (CAE) were introduced for image coding. They achieved performance improvements over the state-of-the-art JPEG2000 method. However, these performances were obtained using massive CAEs featuring a large number of parameters and whose training required heavy computational power.\\ In ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	316,790
1810.09304	On the k-Boundedness for Existential Rules	The chase is a fundamental tool for existential rules. Several chase variants are known, which differ on how they handle redundancies possibly caused by the introduction of nulls. Given a chase variant, the halting problem takes as input a set of existential rules and asks if this set of rules ensures the termination o...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	111,030
1809.09802	Robust Shape Estimation for 3D Deformable Object Manipulation	Existing shape estimation methods for deformable object manipulation suffer from the drawbacks of being off-line, model dependent, noise-sensitive or occlusion-sensitive, and thus are not appropriate for manipulation tasks requiring high precision. In this paper, we present a real-time shape estimation approach for aut...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	108,775
1309.5821	Undefined By Data: A Survey of Big Data Definitions	The term big data has become ubiquitous. Owing to a shared origin between academia, industry and the media there is no single unified definition, and various stakeholders provide diverse and often contradictory definitions. The lack of a consistent definition introduces ambiguity and hampers discourse relating to big d...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	27,197
2410.15521	Lying mirror	We introduce an all-optical system, termed the "lying mirror", to hide input information by transforming it into misleading, ordinary-looking patterns that effectively camouflage the underlying image data and deceive the observers. This misleading transformation is achieved through passive light-matter interactions of ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	500,585
2404.16557	Energy-Latency Manipulation of Multi-modal Large Language Models via Verbose Samples	Despite the exceptional performance of multi-modal large language models (MLLMs), their deployment requires substantial computational resources. Once malicious users induce high energy consumption and latency time (energy-latency cost), it will exhaust computational resources and harm availability of service. In this p...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	449,542
2005.07344	Resisting Crowd Occlusion and Hard Negatives for Pedestrian Detection in the Wild	Pedestrian detection has been heavily studied in the last decade due to its wide application. Despite incremental progress, crowd occlusion and hard negatives are still challenging current state-of-the-art pedestrian detectors. In this paper, we offer two approaches based on the general region-based detection framework...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	177,254
1909.03118	Trading-Off Static and Dynamic Regret in Online Least-Squares and Beyond	Recursive least-squares algorithms often use forgetting factors as a heuristic to adapt to non-stationary data streams. The first contribution of this paper rigorously characterizes the effect of forgetting factors for a class of online Newton algorithms. For exp-concave and strongly convex objectives, the algorithms a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	144,378
2205.02911	A Driver-Vehicle Model for ADS Scenario-based Testing	Scenario-based testing for automated driving systems (ADS) must be able to simulate traffic scenarios that rely on interactions with other vehicles. Although many languages for high-level scenario modelling have been proposed, they lack the features to precisely and reliably control the required micro-simulation, while...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	295,103
1712.08084	AVEID: Automatic Video System for Measuring Engagement In Dementia	Engagement in dementia is typically measured using behavior observational scales (BOS) that are tedious and involve intensive manual labor to annotate, and are therefore not easily scalable. We propose AVEID, a low cost and easy-to-use video-based engagement measurement tool to determine the engagement level of a perso...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	87,132
2203.15629	Stochastic Conservative Contextual Linear Bandits	Many physical systems have underlying safety considerations that require that the strategy deployed ensures the satisfaction of a set of constraints. Further, often we have only partial information on the state of the system. We study the problem of safe real-time decision making under uncertainty. In this paper, we fo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	288,480
2407.13881	Privacy-preserving gradient-based fair federated learning	Federated learning (FL) schemes allow multiple participants to collaboratively train neural networks without the need to directly share the underlying data.However, in early schemes, all participants eventually obtain the same model. Moreover, the aggregation is typically carried out by a third party, who obtains combi...	false	false	false	false	false	false	true	false	false	false	true	false	true	false	false	false	false	false	474,551
1809.03481	Longitudinal Safety Analysis For Heterogeneous Platoon Of Automated And Human Vehicles	With the recent advancement in environmental sensing, vehicle control and vehicle-infrastructure cooperation technologies, more and more autonomous driving companies start to put their intelligent cars into road test. But in the near future, we will face a heterogeneous traffic with both intelligent connected vehicles ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	107,338
2205.06941	Blockchain Goes Green? Part II: Characterizing the Performance and Cost of Blockchains on the Cloud and at the Edge	While state-of-the-art permissioned blockchains can achieve thousands of transactions per second on commodity hardware with x86/64 architecture, their performance when running on different architectures is not clear. The goal of this work is to characterize the performance and cost of permissioned blockchains on differ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	296,412
2003.04427	Transfer Reinforcement Learning under Unobserved Contextual Information	In this paper, we study a transfer reinforcement learning problem where the state transitions and rewards are affected by the environmental context. Specifically, we consider a demonstrator agent that has access to a context-aware policy and can generate transition and reward data based on that policy. These data const...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	167,558
2306.09462	Motion Comfort Optimization for Autonomous Vehicles: Concepts, Methods, and Techniques	This article outlines the architecture of autonomous driving and related complementary frameworks from the perspective of human comfort. The technical elements for measuring Autonomous Vehicle (AV) user comfort and psychoanalysis are listed here. At the same time, this article introduces the technology related to the s...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	373,839
2104.03775	Geometry-based Distance Decomposition for Monocular 3D Object Detection	Monocular 3D object detection is of great significance for autonomous driving but remains challenging. The core challenge is to predict the distance of objects in the absence of explicit depth information. Unlike regressing the distance as a single variable in most existing methods, we propose a novel geometry-based di...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	229,171
2402.07895	Detection of Spider Mites on Labrador Beans through Machine Learning Approaches Using Custom Datasets	Amidst growing food production demands, early plant disease detection is essential to safeguard crops; this study proposes a visual machine learning approach for plant disease detection, harnessing RGB and NIR data collected in real-world conditions through a JAI FS-1600D-10GE camera to build an RGBN dataset. A two-sta...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	428,886
2104.14029	Reducing Risk and Uncertainty of Deep Neural Networks on Diagnosing COVID-19 Infection	Effective and reliable screening of patients via Computer-Aided Diagnosis can play a crucial part in the battle against COVID-19. Most of the existing works focus on developing sophisticated methods yielding high detection performance, yet not addressing the issue of predictive uncertainty. In this work, we introduce u...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	232,682
2310.06873	A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methods	The comprehensive integration of machine learning healthcare models within clinical practice remains suboptimal, notwithstanding the proliferation of high-performing solutions reported in the literature. A predominant factor hindering widespread adoption pertains to an insufficiency of evidence affirming the reliabilit...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	398,750
1805.12064	Stochastic Deep Compressive Sensing for the Reconstruction of Diffusion Tensor Cardiac MRI	Understanding the structure of the heart at the microscopic scale of cardiomyocytes and their aggregates provides new insights into the mechanisms of heart disease and enables the investigation of effective therapeutics. Diffusion Tensor Cardiac Magnetic Resonance (DT-CMR) is a unique non-invasive technique that can re...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	99,083
1709.05038	Self-Guiding Multimodal LSTM - when we do not have a perfect training dataset for image captioning	In this paper, a self-guiding multimodal LSTM (sg-LSTM) image captioning model is proposed to handle uncontrolled imbalanced real-world image-sentence dataset. We collect FlickrNYC dataset from Flickr as our testbed with 306,165 images and the original text descriptions uploaded by the users are utilized as the ground ...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	80,771
1806.11532	TextWorld: A Learning Environment for Text-based Games	We introduce TextWorld, a sandbox learning environment for the training and evaluation of RL agents on text-based games. TextWorld is a Python library that handles interactive play-through of text games, as well as backend functions like state tracking and reward assignment. It comes with a curated list of games whose ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	101,735
2501.04477	Rethinking High-speed Image Reconstruction Framework with Spike Camera	Spike cameras, as innovative neuromorphic devices, generate continuous spike streams to capture high-speed scenes with lower bandwidth and higher dynamic range than traditional RGB cameras. However, reconstructing high-quality images from the spike input under low-light conditions remains challenging. Conventional lear...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	523,238
1411.3334	Sparse Quantum Codes from Quantum Circuits	We describe a general method for turning quantum circuits into sparse quantum subsystem codes. The idea is to turn each circuit element into a set of low-weight gauge generators that enforce the input-output relations of that circuit element. Using this prescription, we can map an arbitrary stabilizer code into a new s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	37,493
1407.8147	Stochastic Coordinate Coding and Its Application for Drosophila Gene Expression Pattern Annotation	\textit{Drosophila melanogaster} has been established as a model organism for investigating the fundamental principles of developmental gene interactions. The gene expression patterns of \textit{Drosophila melanogaster} can be documented as digital images, which are annotated with anatomical ontology terms to facilitat...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	35,010
2110.11525	Digital and Physical-World Attacks on Remote Pulse Detection	Remote photoplethysmography (rPPG) is a technique for estimating blood volume changes from reflected light without the need for a contact sensor. We present the first examples of presentation attacks in the digital and physical domains on rPPG from face video. Digital attacks are easily performed by adding imperceptibl...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	262,512
1902.03326	Architecture Compression	In this paper we propose a novel approach to model compression termed Architecture Compression. Instead of operating on the weight or filter space of the network like classical model compression methods, our approach operates on the architecture space. A 1-D CNN encoder-decoder is trained to learn a mapping from discre...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	121,070
2012.02300	Fully Convolutional Network Bootstrapped by Word Encoding and Embedding for Activity Recognition in Smart Homes	Activity recognition in smart homes is essential when we wish to propose automatic services for the inhabitants. However, it poses challenges in terms of variability of the environment, sensorimotor system, but also user habits. Therefore, endto-end systems fail at automatically extracting key features, without extensi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	209,720
2112.07909	Homography Decomposition Networks for Planar Object Tracking	Planar object tracking plays an important role in AI applications, such as robotics, visual servoing, and visual SLAM. Although the previous planar trackers work well in most scenarios, it is still a challenging task due to the rapid motion and large transformation between two consecutive frames. The essential reason b...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	271,635
2311.13199	Two-stage Synthetic Supervising and Multi-view Consistency Self-supervising based Animal 3D Reconstruction by Single Image	Pixel-aligned Implicit Function (PIFu) effectively captures subtle variations in body shape within a low-dimensional space through extensive training with human 3D scans, its application to live animals presents formidable challenges due to the difficulty of obtaining animal cooperation for 3D scanning. To address this...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	409,664
1106.5294	Set systems: order types, continuous nondeterministic deformations, and quasi-orders	By reformulating a learning process of a set system L as a game between Teacher and Learner, we define the order type of L to be the order type of the game tree, if the tree is well-founded. The features of the order type of L (dim L in symbol) are (1) We can represent any well-quasi-order (wqo for short) by the set sy...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	11,017
1611.07329	Autonomous Landing of a Multirotor Micro Air Vehicle on a High Velocity Ground Vehicle	While autonomous multirotor micro aerial vehicles (MAVs) are uniquely well suited for certain types of missions benefiting from stationary flight capabilities, their more widespread usage still faces many hurdles, due in particular to their limited range and the difficulty of fully automating their deployment and retri...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	64,340
2407.19628	Text2LiDAR: Text-guided LiDAR Point Cloud Generation via Equirectangular Transformer	The complex traffic environment and various weather conditions make the collection of LiDAR data expensive and challenging. Achieving high-quality and controllable LiDAR data generation is urgently needed, controlling with text is a common practice, but there is little research in this field. To this end, we propose Te...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	476,857
2002.06605	Fully Distributed Resilient State Estimation based on Distributed Median Solver	In this paper, we present a scheme of fully distributed resilient state estimation for linear dynamical systems under sensor attacks. The proposed state observer consists of a network of local observers, where each of them utilizes local measurements and information transmitted from the neighbors. As a fully distribute...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	164,244
2112.11909	Few-shot Multi-hop Question Answering over Knowledge Base	KBQA is a task that requires to answer questions by using semantic structured information in knowledge base. Previous work in this area has been restricted due to the lack of large semantic parsing dataset and the exponential growth of searching space with the increasing hops of relation paths. In this paper, we propos...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	272,827
2011.10679	Cost-Effective Quasi-Parallel Sensing Instrumentation for Industrial Chemical Species Tomography	Chemical Species Tomography (CST) has been widely applied for imaging of critical gas-phase parameters in industrial processes. To acquire high-fidelity images, CST is typically implemented by line-of-sight Wavelength Modulation Spectroscopy (WMS) measurements from multiple laser beams. The modulated transmission signa...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	207,580
2208.09292	UnCommonSense: Informative Negative Knowledge about Everyday Concepts	Commonsense knowledge about everyday concepts is an important asset for AI applications, such as question answering and chatbots. Recently, we have seen an increasing interest in the construction of structured commonsense knowledge bases (CSKBs). An important part of human commonsense is about properties that do not ap...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	313,651
2305.08227	DeepFilterNet: Perceptually Motivated Real-Time Speech Enhancement	Multi-frame algorithms for single-channel speech enhancement are able to take advantage from short-time correlations within the speech signal. Deep Filtering (DF) was proposed to directly estimate a complex filter in frequency domain to take advantage of these correlations. In this work, we present a real-time speech e...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	364,206
1705.01013	Quantum Mechanical Approach to Modelling Reliability of Sensor Reports	Dempster-Shafer evidence theory is wildly applied in multi-sensor data fusion. However, lots of uncertainty and interference exist in practical situation, especially in the battle field. It is still an open issue to model the reliability of sensor reports. Many methods are proposed based on the relationship among colle...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	72,782
2204.04431	A Spiking Neural Network Structure Implementing Reinforcement Learning	At present, implementation of learning mechanisms in spiking neural networks (SNN) cannot be considered as a solved scientific problem despite plenty of SNN learning algorithms proposed. It is also true for SNN implementation of reinforcement learning (RL), while RL is especially important for SNNs because of its close...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	290,655
2208.06917	MTCSNN: Multi-task Clinical Siamese Neural Network for Diabetic Retinopathy Severity Prediction	Diabetic Retinopathy (DR) has become one of the leading causes of vision impairment in working-aged people and is a severe problem worldwide. However, most of the works ignored the ordinal information of labels. In this project, we propose a novel design MTCSNN, a Multi-task Clinical Siamese Neural Network for Diabetic...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	312,865
2305.18365	What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks	Large Language Models (LLMs) with strong abilities in natural language processing tasks have emerged and have been applied in various kinds of areas such as science, finance and software engineering. However, the capability of LLMs to advance the field of chemistry remains unclear. In this paper, rather than pursuing s...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	368,987
1312.4036	Mind Your Language: Effects of Spoken Query Formulation on Retrieval Effectiveness	Voice search is becoming a popular mode for interacting with search engines. As a result, research has gone into building better voice transcription engines, interfaces, and search engines that better handle inherent verbosity of queries. However, when one considers its use by non- native speakers of English, another a...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	29,092
1602.03602	Wireless Communications with Unmanned Aerial Vehicles: Opportunities and Challenges	Wireless communication systems that include unmanned aerial vehicles (UAVs) promise to provide cost-effective wireless connectivity for devices without infrastructure coverage. Compared to terrestrial communications or those based on high-altitude platforms (HAPs), on-demand wireless systems with low-altitude UAVs are ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	52,021
2003.05882	Stackelberg Equilibria for Two-Player Network Routing Games on Parallel Networks	We consider a two-player zero-sum network routing game in which a router wants to maximize the amount of legitimate traffic that flows from a given source node to a destination node and an attacker wants to block as much legitimate traffic as possible by flooding the network with malicious traffic. We address scenarios...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	167,973
2006.06780	Tangent Space Sensitivity and Distribution of Linear Regions in ReLU Networks	Recent articles indicate that deep neural networks are efficient models for various learning problems. However they are often highly sensitive to various changes that cannot be detected by an independent observer. As our understanding of deep neural networks with traditional generalization bounds still remains incomple...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	181,549
2211.13061	A Masked Face Classification Benchmark on Low-Resolution Surveillance Images	We propose a novel image dataset focused on tiny faces wearing face masks for mask classification purposes, dubbed Small Face MASK (SF-MASK), composed of a collection made from 20k low-resolution images exported from diverse and heterogeneous datasets, ranging from 7 x 7 to 64 x 64 pixel resolution. An accurate visuali...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	332,336
2305.05486	MAUPQA: Massive Automatically-created Polish Question Answering Dataset	Recently, open-domain question answering systems have begun to rely heavily on annotated datasets to train neural passage retrievers. However, manually annotating such datasets is both difficult and time-consuming, which limits their availability for less popular languages. In this work, we experiment with several meth...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	363,170

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