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
1907.09452	Mid-price Prediction Based on Machine Learning Methods with Technical and Quantitative Indicators	Stock price prediction is a challenging task, but machine learning methods have recently been used successfully for this purpose. In this paper, we extract over 270 hand-crafted features (factors) inspired by technical and quantitative analysis and tested their validity on short-term mid-price movement prediction. We f...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	139,363
2405.09163	DVS-RG: Differential Variable Speed Limits Control using Deep Reinforcement Learning with Graph State Representation	Variable speed limit (VSL) control is an established yet challenging problem to improve freeway traffic mobility and alleviate bottlenecks by customizing speed limits at proper locations based on traffic conditions. Recent advances in deep reinforcement learning (DRL) have shown promising results in solving VSL control...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	454,318
2304.00995	Kinetostatic Optimization for Kinematic Redundancy Planning of Nimbl'Bot Robot	<jats:title>Abstract</jats:title> <jats:p>In manufacturing industry, Computer Numerical Control (CNC) machines are often preferred over Industrial Serial Robots (ISR) for machining tasks. Indeed, CNC machines offer high positioning accuracy, which leads to slight dimensional deviation on the final product. However, the...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	355,893
2104.13155	Watershed of Artificial Intelligence: Human Intelligence, Machine Intelligence, and Biological Intelligence	This article reviews the "Once learning" mechanism that was proposed 23 years ago and the subsequent successes of "One-shot learning" in image classification and "You Only Look Once - YOLO" in objective detection. Analyzing the current development of Artificial Intelligence (AI), the proposal is that AI should be clear...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	232,415
2003.06958	Vec2Face: Unveil Human Faces from their Blackbox Features in Face Recognition	Unveiling face images of a subject given his/her high-level representations extracted from a blackbox Face Recognition engine is extremely challenging. It is because the limitations of accessible information from that engine including its structure and uninterpretable extracted features. This paper presents a novel gen...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	168,276
2410.07442	Self-Supervised Learning for Real-World Object Detection: a Survey	Self-Supervised Learning (SSL) has emerged as a promising approach in computer vision, enabling networks to learn meaningful representations from large unlabeled datasets. SSL methods fall into two main categories: instance discrimination and Masked Image Modeling (MIM). While instance discrimination is fundamental to ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	496,626
2203.00952	Sketched RT3D: How to reconstruct billions of photons per second	Single-photon light detection and ranging (lidar) captures depth and intensity information of a 3D scene. Reconstructing a scene from observed photons is a challenging task due to spurious detections associated with background illumination sources. To tackle this problem, there is a plethora of 3D reconstruction algori...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	283,197
1803.01900	Style Memory: Making a Classifier Network Generative	Deep networks have shown great performance in classification tasks. However, the parameters learned by the classifier networks usually discard stylistic information of the input, in favour of information strictly relevant to classification. We introduce a network that has the capacity to do both classification and reco...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	91,954
2310.13227	ToolChain: Efficient Action Space Navigation in Large Language Models with A Search	Large language models (LLMs) have demonstrated powerful decision-making and planning capabilities in solving complicated real-world problems. LLM-based autonomous agents can interact with diverse tools (e.g., functional APIs) and generate solution plans that execute a series of API function calls in a step-by-step mann...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	401,345
2412.11095	Dynamic Graph Attention Networks for Travel Time Distribution Prediction in Urban Arterial Roads	Effective congestion management along signalized corridors is essential for improving productivity and reducing costs, with arterial travel time serving as a key performance metric. Traditional approaches, such as Coordinated Signal Timing and Adaptive Traffic Control Systems, often lack scalability and generalizabilit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	517,255
2211.01738	Analysis of a Deep Learning Model for 12-Lead ECG Classification Reveals Learned Features Similar to Diagnostic Criteria	Despite their remarkable performance, deep neural networks remain unadopted in clinical practice, which is considered to be partially due to their lack in explainability. In this work, we apply attribution methods to a pre-trained deep neural network (DNN) for 12-lead electrocardiography classification to open this "bl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	328,333
1604.03221	Leveraging Network Dynamics for Improved Link Prediction	The aim of link prediction is to forecast connections that are most likely to occur in the future, based on examples of previously observed links. A key insight is that it is useful to explicitly model network dynamics, how frequently links are created or destroyed when doing link prediction. In this paper, we introduc...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	54,459
1712.04106	Sparse Phase Retrieval via Sparse PCA Despite Model Misspecification: A Simplified and Extended Analysis	We consider the problem of high-dimensional misspecified phase retrieval. This is where we have an $s$-sparse signal vector $\mathbf{x}_*$ in $\mathbb{R}^n$, which we wish to recover using sampling vectors $\textbf{a}_1,\ldots,\textbf{a}_m$, and measurements $y_1,\ldots,y_m$, which are related by the equation $f(\left<...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	86,545
2309.13166	Invisible Watermarking for Audio Generation Diffusion Models	Diffusion models have gained prominence in the image domain for their capabilities in data generation and transformation, achieving state-of-the-art performance in various tasks in both image and audio domains. In the rapidly evolving field of audio-based machine learning, safeguarding model integrity and establishing ...	false	false	true	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	394,079
2105.11056	User-oriented Natural Human-Robot Control with Thin-Plate Splines and LRCN	We propose a real-time vision-based teleoperation approach for robotic arms that employs a single depth-based camera, exempting the user from the need for any wearable devices. By employing a natural user interface, this novel approach leverages the conventional fine-tuning control, turning it into a direct body pose c...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	236,579
2012.05197	Predicting Prostate Cancer-Specific Mortality with A.I.-based Gleason Grading	Gleason grading of prostate cancer is an important prognostic factor but suffers from poor reproducibility, particularly among non-subspecialist pathologists. Although artificial intelligence (A.I.) tools have demonstrated Gleason grading on-par with expert pathologists, it remains an open question whether A.I. grading...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	210,704
2103.04400	What If We Only Use Real Datasets for Scene Text Recognition? Toward Scene Text Recognition With Fewer Labels	Scene text recognition (STR) task has a common practice: All state-of-the-art STR models are trained on large synthetic data. In contrast to this practice, training STR models only on fewer real labels (STR with fewer labels) is important when we have to train STR models without synthetic data: for handwritten or artis...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	223,626
2109.09212	Generalized Translation and Scale Invariant Online Algorithm for Adversarial Multi-Armed Bandits	We study the adversarial multi-armed bandit problem and create a completely online algorithmic framework that is invariant under arbitrary translations and scales of the arm losses. We study the expected performance of our algorithm against a generic competition class, which makes it applicable for a wide variety of pr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	256,196
1807.11919	Efficiency, Sequenceability and Deal-Optimality in Fair Division of Indivisible Goods	In fair division of indivisible goods, using sequences of sincere choices (or picking sequences) is a natural way to allocate the objects. The idea is as follows: at each stage, a designated agent picks one object among those that remain. Another intuitive way to obtain an allocation is to give objects to agents in the...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	104,273
2004.10320	A Deep Learning System for Sentiment Analysis of Service Calls	Sentiment analysis is crucial for the advancement of artificial intelligence (AI). Sentiment understanding can help AI to replicate human language and discourse. Studying the formation and response of sentiment state from well-trained Customer Service Representatives (CSRs) can help make the interaction between humans ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	173,602
2312.09457	Functional Analytics for Document Ordering for Curriculum Development and Comprehension	We propose multiple techniques for automatic document order generation for (1) curriculum development and for (2) creation of optimal reading order for use in learning, training, and other content-sequencing applications. Such techniques could potentially be used to improve comprehension, identify areas that need expou...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	415,732
2209.05877	R-WhONet: Recalibrated Wheel Odometry Neural Network for Vehicular Positioning using Transfer Learning	This paper proposes a transfer learning approach to recalibrate our previously developed Wheel Odometry Neural Network (WhONet) for vehicle positioning in environments where Global Navigation Satellite Systems (GNSS) are unavailable. The WhONet has been shown to possess the capability to learn the uncertainties in the ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	317,234
2501.14414	SoK: What Makes Private Learning Unfair?	Differential privacy has emerged as the most studied framework for privacy-preserving machine learning. However, recent studies show that enforcing differential privacy guarantees can not only significantly degrade the utility of the model, but also amplify existing disparities in its predictive performance across demo...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	527,109
2301.10330	Off-Policy Evaluation for Action-Dependent Non-Stationary Environments	Methods for sequential decision-making are often built upon a foundational assumption that the underlying decision process is stationary. This limits the application of such methods because real-world problems are often subject to changes due to external factors (passive non-stationarity), changes induced by interactio...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	341,768
2309.05840	Self-Correlation and Cross-Correlation Learning for Few-Shot Remote Sensing Image Semantic Segmentation	Remote sensing image semantic segmentation is an important problem for remote sensing image interpretation. Although remarkable progress has been achieved, existing deep neural network methods suffer from the reliance on massive training data. Few-shot remote sensing semantic segmentation aims at learning to segment ta...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	391,212
2409.03163	CyberDep: Towards the Analysis of Cyber-Physical Power System Interdependencies Using Bayesian Networks and Temporal Data	Modern-day power systems have become increasingly cyber-physical due to the ongoing developments to the grid that include the rise of distributed energy generation and the increase of the deployment of many cyber devices for monitoring and control, such as the Supervisory Control and Data Acquisition (SCADA) system. Su...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	485,940
2308.01954	Bringing Chemistry to Scale: Loss Weight Adjustment for Multivariate Regression in Deep Learning of Thermochemical Processes	Flamelet models are widely used in computational fluid dynamics to simulate thermochemical processes in turbulent combustion. These models typically employ memory-expensive lookup tables that are predetermined and represent the combustion process to be simulated. Artificial neural networks (ANNs) offer a deep learning ...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	383,433
2309.16519	AtomSurf : Surface Representation for Learning on Protein Structures	While there has been significant progress in evaluating and comparing different representations for learning on protein data, the role of surface-based learning approaches remains not well-understood. In particular, there is a lack of direct and fair benchmark comparison between the best available surface-based learnin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	395,380
1807.03523	DLOPT: Deep Learning Optimization Library	Deep learning hyper-parameter optimization is a tough task. Finding an appropriate network configuration is a key to success, however most of the times this labor is roughly done. In this work we introduce a novel library to tackle this problem, the Deep Learning Optimization Library: DLOPT. We briefly describe its arc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	102,548
2310.06254	Get the gist? Using large language models for few-shot decontextualization	In many NLP applications that involve interpreting sentences within a rich context -- for instance, information retrieval systems or dialogue systems -- it is desirable to be able to preserve the sentence in a form that can be readily understood without context, for later reuse -- a process known as ``decontextualizati...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	398,496
2312.00742	Scalable Meta-Learning with Gaussian Processes	Meta-learning is a powerful approach that exploits historical data to quickly solve new tasks from the same distribution. In the low-data regime, methods based on the closed-form posterior of Gaussian processes (GP) together with Bayesian optimization have achieved high performance. However, these methods are either co...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	412,156
2408.09675	Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey	Reinforcement Learning (RL) is a potent tool for sequential decision-making and has achieved performance surpassing human capabilities across many challenging real-world tasks. As the extension of RL in the multi-agent system domain, multi-agent RL (MARL) not only need to learn the control policy but also requires cons...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	true	false	false	false	481,537
2401.07049	Quantum Denoising Diffusion Models	In recent years, machine learning models like DALL-E, Craiyon, and Stable Diffusion have gained significant attention for their ability to generate high-resolution images from concise descriptions. Concurrently, quantum computing is showing promising advances, especially with quantum machine learning which capitalizes ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	421,399
2402.17615	A Multi-Agent Model for Opinion Evolution under Cognitive Biases	We generalize the DeGroot model for opinion dynamics to better capture realistic social scenarios. We introduce a model where each agent has their own individual cognitive biases. Society is represented as a directed graph whose edges indicate how much agents influence one another. Biases are represented as the functio...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	433,073
2202.11377	Multi-scale Sparse Representation-Based Shadow Inpainting for Retinal OCT Images	Inpainting shadowed regions cast by superficial blood vessels in retinal optical coherence tomography (OCT) images is critical for accurate and robust machine analysis and clinical diagnosis. Traditional sequence-based approaches such as propagating neighboring information to gradually fill in the missing regions are c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	281,872
2403.03149	Robust Federated Learning Mitigates Client-side Training Data Distribution Inference Attacks	Recent studies have revealed that federated learning (FL), once considered secure due to clients not sharing their private data with the server, is vulnerable to attacks such as client-side training data distribution inference, where a malicious client can recreate the victim's data. While various countermeasures exist...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	435,078
2107.02794	Improving Coherence and Consistency in Neural Sequence Models with Dual-System, Neuro-Symbolic Reasoning	Human reasoning can often be understood as an interplay between two systems: the intuitive and associative ("System 1") and the deliberative and logical ("System 2"). Neural sequence models -- which have been increasingly successful at performing complex, structured tasks -- exhibit the advantages and failure modes of ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	244,944
2404.02499	Learning Generalized Policies for Fully Observable Non-Deterministic Planning Domains	General policies represent reactive strategies for solving large families of planning problems like the infinite collection of solvable instances from a given domain. Methods for learning such policies from a collection of small training instances have been developed successfully for classical domains. In this work, we...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	443,881
2110.02411	Voice Aging with Audio-Visual Style Transfer	Face aging techniques have used generative adversarial networks (GANs) and style transfer learning to transform one's appearance to look younger/older. Identity is maintained by conditioning these generative networks on a learned vector representation of the source content. In this work, we apply a similar approach to ...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	259,111
1911.04133	IMNet: A Learning Based Detector for Index Modulation Aided MIMO-OFDM Systems	Index modulation (IM) brings the reduction of power consumption and complexity of the transmitter to classical multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. However, due to the introduction of IM, the complexity of the detector at receiver is greatly increased. Furthermo...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	152,904
2304.11370	SAILER: Structure-aware Pre-trained Language Model for Legal Case Retrieval	Legal case retrieval, which aims to find relevant cases for a query case, plays a core role in the intelligent legal system. Despite the success that pre-training has achieved in ad-hoc retrieval tasks, effective pre-training strategies for legal case retrieval remain to be explored. Compared with general documents, le...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	359,783
1710.05719	Lung Cancer Screening Using Adaptive Memory-Augmented Recurrent Networks	In this paper, we investigate the effectiveness of deep learning techniques for lung nodule classification in computed tomography scans. Using less than 10,000 training examples, our deep networks perform two times better than a standard radiology software. Visualization of the networks' neurons reveals semantically me...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	82,673
2305.03201	Enhancing Pashto Text Classification using Language Processing Techniques for Single And Multi-Label Analysis	Text classification has become a crucial task in various fields, leading to a significant amount of research on developing automated text classification systems for national and international languages. However, there is a growing need for automated text classification systems that can handle local languages. This stud...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	362,301
2406.02744	DPDR: Gradient Decomposition and Reconstruction for Differentially Private Deep Learning	Differentially Private Stochastic Gradients Descent (DP-SGD) is a prominent paradigm for preserving privacy in deep learning. It ensures privacy by perturbing gradients with random noise calibrated to their entire norm at each training step. However, this perturbation suffers from a sub-optimal performance: it repeated...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	460,915
2305.09887	Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation	Distributed training of GNNs enables learning on massive graphs (e.g., social and e-commerce networks) that exceed the storage and computational capacity of a single machine. To reach performance comparable to centralized training, distributed frameworks focus on maximally recovering cross-instance node dependencies wi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	364,811
2111.09083	Trajectory Prediction & Path Planning for an Object Intercepting UAV with a Mounted Depth Camera	A novel control & software architecture using ROS C++ is introduced for object interception by a UAV with a mounted depth camera and no external aid. Existing work in trajectory prediction focused on the use of off-board tools like motion capture rooms to intercept thrown objects. The present study designs the UAV arch...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	266,902
1701.03961	Communication-Efficient Algorithms for Decentralized and Stochastic Optimization	We present a new class of decentralized first-order methods for nonsmooth and stochastic optimization problems defined over multiagent networks. Considering that communication is a major bottleneck in decentralized optimization, our main goal in this paper is to develop algorithmic frameworks which can significantly re...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	66,786
2106.02792	Weakly-Supervised Methods for Suicide Risk Assessment: Role of Related Domains	Social media has become a valuable resource for the study of suicidal ideation and the assessment of suicide risk. Among social media platforms, Reddit has emerged as the most promising one due to its anonymity and its focus on topic-based communities (subreddits) that can be indicative of someone's state of mind or in...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	239,026
2011.10487	Normalization effects on shallow neural networks and related asymptotic expansions	We consider shallow (single hidden layer) neural networks and characterize their performance when trained with stochastic gradient descent as the number of hidden units $N$ and gradient descent steps grow to infinity. In particular, we investigate the effect of different scaling schemes, which lead to different normali...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	207,526
2003.05212	A Mobile Robot Hand-Arm Teleoperation System by Vision and IMU	In this paper, we present a multimodal mobile teleoperation system that consists of a novel vision-based hand pose regression network (Transteleop) and an IMU-based arm tracking method. Transteleop observes the human hand through a low-cost depth camera and generates not only joint angles but also depth images of paire...	true	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	167,806
2208.01462	Physics-informed Deep Super-resolution for Spatiotemporal Data	High-fidelity simulation of complex physical systems is exorbitantly expensive and inaccessible across spatiotemporal scales. Recently, there has been an increasing interest in leveraging deep learning to augment scientific data based on the coarse-grained simulations, which is of cheap computational expense and retain...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	311,173
2009.06181	Mitigation and Resiliency of Multi-Agent Systems Subject to Malicious Cyber Attacks on Communication Links	This paper aims at investigating a novel type of cyber attack that is injected to multi-agent systems (MAS) having an underlying directed graph. The cyber attack, which is designated as the controllability attack, is injected by the malicious adversary into the communication links among the agents. The adversary, lever...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	195,552
0911.3872	Equivalence perspectives in communication, source-channel connections and universal source-channel separation	An operational perspective is used to understand the relationship between source and channel coding. This is based on a direct reduction of one problem to another that uses random coding (and hence common randomness) but unlike all prior work, does not involve any functional computations, in particular, no mutual-infor...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	4,983
1904.09924	On the Sum-Rate Capacity of Poisson Multiple Access Channel with Non-Perfect Photon-Counting Receiver	We first investigate two-user nonasymmetric sum-rate Poisson capacity with non-perfect photoncounting receiver under certain condition and demonstrate three possible transmission strategy, including only one active user and both active users, in sharp contrast to Gaussian multiple access channel (MAC) channel. The two-...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	128,514
2311.12480	Speaker-Adapted End-to-End Visual Speech Recognition for Continuous Spanish	Different studies have shown the importance of visual cues throughout the speech perception process. In fact, the development of audiovisual approaches has led to advances in the field of speech technologies. However, although noticeable results have recently been achieved, visual speech recognition remains an open res...	false	false	true	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	409,355
2412.08189	Breaking the Bias: Recalibrating the Attention of Industrial Anomaly Detection	Due to the scarcity and unpredictable nature of defect samples, industrial anomaly detection (IAD) predominantly employs unsupervised learning. However, all unsupervised IAD methods face a common challenge: the inherent bias in normal samples, which causes models to focus on variable regions while overlooking potential...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	515,985
2102.02664	Digital twins based on bidirectional LSTM and GAN for modelling the COVID-19 pandemic	The outbreak of the coronavirus disease 2019 (COVID-19) has now spread throughout the globe infecting over 150 million people and causing the death of over 3.2 million people. Thus, there is an urgent need to study the dynamics of epidemiological models to gain a better understanding of how such diseases spread. While ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	218,480
2211.10530	Provable Defense against Backdoor Policies in Reinforcement Learning	We propose a provable defense mechanism against backdoor policies in reinforcement learning under subspace trigger assumption. A backdoor policy is a security threat where an adversary publishes a seemingly well-behaved policy which in fact allows hidden triggers. During deployment, the adversary can modify observed st...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	331,336
2502.14514	A Mobile Robotic Approach to Autonomous Surface Scanning in Legal Medicine	Purpose: Comprehensive legal medicine documentation includes both an internal but also an external examination of the corpse. Typically, this documentation is conducted manually during conventional autopsy. A systematic digital documentation would be desirable, especially for the external examination of wounds, which i...	false	false	false	false	false	false	false	true	false	false	true	true	false	false	false	false	false	false	535,865
2210.03256	Not another Negation Benchmark: The NaN-NLI Test Suite for Sub-clausal Negation	Negation is poorly captured by current language models, although the extent of this problem is not widely understood. We introduce a natural language inference (NLI) test suite to enable probing the capabilities of NLP methods, with the aim of understanding sub-clausal negation. The test suite contains premise--hypothe...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	321,954
1809.02052	Eigenvalue analogy for confidence estimation in item-based recommender systems	Item-item collaborative filtering (CF) models are a well known and studied family of recommender systems, however current literature does not provide any theoretical explanation of the conditions under which item-based recommendations will succeed or fail. We investigate the existence of an ideal item-based CF method...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	106,948
1603.04163	A BP-MF-EP Based Iterative Receiver for Joint Phase Noise Estimation, Equalization and Decoding	In this work, with combined belief propagation (BP), mean field (MF) and expectation propagation (EP), an iterative receiver is designed for joint phase noise (PN) estimation, equalization and decoding in a coded communication system. The presence of the PN results in a nonlinear observation model. Conventionally, the ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	53,205
2403.02867	Scalable Continuous-time Diffusion Framework for Network Inference and Influence Estimation	The study of continuous-time information diffusion has been an important area of research for many applications in recent years. When only the diffusion traces (cascades) are accessible, cascade-based network inference and influence estimation are two essential problems to explore. Alas, existing methods exhibit limite...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	434,969
2203.06153	Symmetry Group Equivariant Architectures for Physics	Physical theories grounded in mathematical symmetries are an essential component of our understanding of a wide range of properties of the universe. Similarly, in the domain of machine learning, an awareness of symmetries such as rotation or permutation invariance has driven impressive performance breakthroughs in comp...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	285,024
2212.00986	Masked Contrastive Pre-Training for Efficient Video-Text Retrieval	We present a simple yet effective end-to-end Video-language Pre-training (VidLP) framework, Masked Contrastive Video-language Pretraining (MAC), for video-text retrieval tasks. Our MAC aims to reduce video representation's spatial and temporal redundancy in the VidLP model by a mask sampling mechanism to improve pre-tr...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	334,267
1904.03620	Teaching GANs to Sketch in Vector Format	Sketching is more fundamental to human cognition than speech. Deep Neural Networks (DNNs) have achieved the state-of-the-art in speech-related tasks but have not made significant development in generating stroke-based sketches a.k.a sketches in vector format. Though there are Variational Auto Encoders (VAEs) for genera...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	126,794
1809.03956	Abstraction Learning	There has been a gap between artificial intelligence and human intelligence. In this paper, we identify three key elements forming human intelligence, and suggest that abstraction learning combines these elements and is thus a way to bridge the gap. Prior researches in artificial intelligence either specify abstraction...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	107,437
2406.13151	von Mises Quasi-Processes for Bayesian Circular Regression	The need for regression models to predict circular values arises in many scientific fields. In this work we explore a family of expressive and interpretable distributions over circle-valued random functions related to Gaussian processes targeting two Euclidean dimensions conditioned on the unit circle. The resulting pr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	465,718
1611.05066	Sparse Control for Dynamic Movement Primitives	This paper describes the use of spatially-sparse inputs to influence global changes in the behavior of Dynamic Movement Primitives (DMPs). The dynamics of DMPs are analyzed through the framework of contraction theory as networked hierarchies of contracting or transversely contracting systems. Within this framework, spa...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	63,944
2009.06027	ReviewViz: Assisting Developers Perform Empirical Study on Energy Consumption Related Reviews for Mobile Applications	Improving the energy efficiency of mobile applications is a topic that has gained a lot of attention recently. It has been addressed in a number of ways such as identifying energy bugs and developing a catalog of energy patterns. Previous work shows that users discuss the battery-related issues (energy inefficiency or ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	195,507
2011.01439	A Scenario-Based Development Framework for Autonomous Driving	This article summarizes the research progress of scenario-based testing and development technology for autonomous vehicles. We systematically analyzed previous research works and proposed the definition of scenario, the elements of the scenario ontology, the data source of the scenario, the processing method of the sce...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	204,583
1907.00374	Fooling a Real Car with Adversarial Traffic Signs	The attacks on the neural-network-based classifiers using adversarial images have gained a lot of attention recently. An adversary can purposely generate an image that is indistinguishable from a innocent image for a human being but is incorrectly classified by the neural networks. The adversarial images do not need to...	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	137,022
1903.01422	Database Alignment with Gaussian Features	We consider the problem of aligning a pair of databases with jointly Gaussian features. We consider two algorithms, complete database alignment via MAP estimation among all possible database alignments, and partial alignment via a thresholding approach of log likelihood ratios. We derive conditions on mutual informatio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	123,252
2407.15877	Gaussian Process Model with Tensorial Inputs and Its Application to the Design of 3D Printed Antennas	In simulation-based engineering design with time-consuming simulators, Gaussian process (GP) models are widely used as fast emulators to speed up the design optimization process. In its most commonly used form, the input of GP is a simple list of design parameters. With rapid development of additive manufacturing (also...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	475,384
2206.10324	Online progressive instance-balanced sampling for weakly supervised object detection	Based on multiple instance detection networks (MIDN), plenty of works have contributed tremendous efforts to weakly supervised object detection (WSOD). However, most methods neglect the fact that the overwhelming negative instances exist in each image during the training phase, which would mislead the training and make...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	303,874
2306.10491	A Study on Quantifying Sim2Real Image Gap in Autonomous Driving Simulations Using Lane Segmentation Attention Map Similarity	Autonomous driving simulations require highly realistic images. Our preliminary study found that when the CARLA Simulator image was made more like reality by using DCLGAN, the performance of the lane recognition model improved to levels comparable to real-world driving. It was also confirmed that the vehicle's ability ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	374,255
1902.04320	IEEE 802.11be Extremely High Throughput: The Next Generation of Wi-Fi Technology Beyond 802.11ax	Wi-Fi technology is continuously innovating to cater to the growing customer demands, driven by the digitalisation of everything, both in the home as well as the enterprise and hotspot spaces. In this article, we introduce to the wireless community the next generation Wi-Fi$-$based on IEEE 802.11be Extremely High Throu...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	121,315
2211.11315	Beyond Attentive Tokens: Incorporating Token Importance and Diversity for Efficient Vision Transformers	Vision transformers have achieved significant improvements on various vision tasks but their quadratic interactions between tokens significantly reduce computational efficiency. Many pruning methods have been proposed to remove redundant tokens for efficient vision transformers recently. However, existing studies mainl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	331,679
2110.02054	NoiER: An Approach for Training more Reliable Fine-TunedDownstream Task Models	The recent development in pretrained language models trained in a self-supervised fashion, such as BERT, is driving rapid progress in the field of NLP. However, their brilliant performance is based on leveraging syntactic artifacts of the training data rather than fully understanding the intrinsic meaning of language. ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	258,989
2501.17206	Integrating Reinforcement Learning and AI Agents for Adaptive Robotic Interaction and Assistance in Dementia Care	This study explores a novel approach to advancing dementia care by integrating socially assistive robotics, reinforcement learning (RL), large language models (LLMs), and clinical domain expertise within a simulated environment. This integration addresses the critical challenge of limited experimental data in socially ...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	528,258
2502.06022	Nested subspace learning with flags	Many machine learning methods look for low-dimensional representations of the data. The underlying subspace can be estimated by first choosing a dimension $q$ and then optimizing a certain objective function over the space of $q$-dimensional subspaces (the Grassmannian). Trying different $q$ yields in general non-neste...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	531,884
2210.02226	Null Hypothesis Test for Anomaly Detection	We extend the use of Classification Without Labels for anomaly detection with a hypothesis test designed to exclude the background-only hypothesis. By testing for statistical independence of the two discriminating dataset regions, we are able to exclude the background-only hypothesis without relying on fixed anomaly sc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	321,574
2102.00983	Mosaics of combinatorial designs for information-theoretic security	We study security functions which can serve to establish semantic security for the two central problems of information-theoretic security: the wiretap channel, and privacy amplification for secret key generation. The security functions are functional forms of mosaics of combinatorial designs, more precisely, of group d...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	217,972
1009.5773	Fast Reinforcement Learning for Energy-Efficient Wireless Communications	We consider the problem of energy-efficient point-to-point transmission of delay-sensitive data (e.g. multimedia data) over a fading channel. Existing research on this topic utilizes either physical-layer centric solutions, namely power-control and adaptive modulation and coding (AMC), or system-level solutions based o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	7,711
1604.06242	Novelty Detection in MultiClass Scenarios with Incomplete Set of Class Labels	We address the problem of novelty detection in multiclass scenarios where some class labels are missing from the training set. Our method is based on the initial assignment of confidence values, which measure the affinity between a new test point and each known class. We first compare the values of the two top elements...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	54,918
2104.10538	Guided Table Structure Recognition through Anchor Optimization	This paper presents the novel approach towards table structure recognition by leveraging the guided anchors. The concept differs from current state-of-the-art approaches for table structure recognition that naively apply object detection methods. In contrast to prior techniques, first, we estimate the viable anchors fo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	231,617
2402.11221	MOB-Net: Limb-modularized Uncertainty Torque Learning of Humanoids for Sensorless External Torque Estimation	Momentum observer (MOB) can estimate external joint torque without requiring additional sensors, such as force/torque or joint torque sensors. However, the estimation performance of MOB deteriorates due to the model uncertainty which encompasses the modeling errors and the joint friction. Moreover, the estimation error...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	430,294
2308.11509	SwinFace: A Multi-task Transformer for Face Recognition, Expression Recognition, Age Estimation and Attribute Estimation	In recent years, vision transformers have been introduced into face recognition and analysis and have achieved performance breakthroughs. However, most previous methods generally train a single model or an ensemble of models to perform the desired task, which ignores the synergy among different tasks and fails to achie...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	387,167
0810.5636	On the Possibility of Learning in Reactive Environments with Arbitrary Dependence	We address the problem of reinforcement learning in which observations may exhibit an arbitrary form of stochastic dependence on past observations and actions, i.e. environments more general than (PO)MDPs. The task for an agent is to attain the best possible asymptotic reward where the true generating environment is un...	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	false	2,589
1706.07450	Revised Note on Learning Algorithms for Quadratic Assignment with Graph Neural Networks	Inverse problems correspond to a certain type of optimization problems formulated over appropriate input distributions. Recently, there has been a growing interest in understanding the computational hardness of these optimization problems, not only in the worst case, but in an average-complexity sense under this same i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	75,842
2306.07852	Globally convergent homotopies for discrete-time optimal control	Homotopy methods are attractive due to their capability of solving difficult optimisation and optimal control problems. The underlying idea is to construct a homotopy, which may be considered as a continuous (zero) curve between the difficult original problem and a related, comparatively easy one. Then, the solution of...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	373,167
2301.07389	Towards Models that Can See and Read	Visual Question Answering (VQA) and Image Captioning (CAP), which are among the most popular vision-language tasks, have analogous scene-text versions that require reasoning from the text in the image. Despite their obvious resemblance, the two are treated independently and, as we show, yield task-specific methods that...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	340,907
2106.13043	AudioCLIP: Extending CLIP to Image, Text and Audio	In the past, the rapidly evolving field of sound classification greatly benefited from the application of methods from other domains. Today, we observe the trend to fuse domain-specific tasks and approaches together, which provides the community with new outstanding models. In this work, we present an extension of th...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	242,941
2306.15777	"Is a picture of a bird a bird": Policy recommendations for dealing with ambiguity in machine vision models	Many questions that we ask about the world do not have a single clear answer, yet typical human annotation set-ups in machine learning assume there must be a single ground truth label for all examples in every task. The divergence between reality and practice is stark, especially in cases with inherent ambiguity and wh...	true	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	376,149
1904.07595	Detecting the Unexpected via Image Resynthesis	Classical semantic segmentation methods, including the recent deep learning ones, assume that all classes observed at test time have been seen during training. In this paper, we tackle the more realistic scenario where unexpected objects of unknown classes can appear at test time. The main trends in this area either le...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	127,838
2309.17437	Learning Decentralized Flocking Controllers with Spatio-Temporal Graph Neural Network	Recently a line of researches has delved the use of graph neural networks (GNNs) for decentralized control in swarm robotics. However, it has been observed that relying solely on the states of immediate neighbors is insufficient to imitate a centralized control policy. To address this limitation, prior studies proposed...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	395,771
2003.09852	Multiview Neural Surface Reconstruction by Disentangling Geometry and Appearance	In this work we address the challenging problem of multiview 3D surface reconstruction. We introduce a neural network architecture that simultaneously learns the unknown geometry, camera parameters, and a neural renderer that approximates the light reflected from the surface towards the camera. The geometry is represen...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	169,162
2501.14964	Personalized Layer Selection for Graph Neural Networks	Graph Neural Networks (GNNs) combine node attributes over a fixed granularity of the local graph structure around a node to predict its label. However, different nodes may relate to a node-level property with a different granularity of its local neighborhood, and using the same level of smoothing for all nodes can be d...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	527,339
2501.00184	TrajLearn: Trajectory Prediction Learning using Deep Generative Models	Trajectory prediction aims to estimate an entity's future path using its current position and historical movement data, benefiting fields like autonomous navigation, robotics, and human movement analytics. Deep learning approaches have become key in this area, utilizing large-scale trajectory datasets to model movement...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	521,564
1707.01959	Well-Founded Operators for Normal Hybrid MKNF Knowledge Bases	Hybrid MKNF knowledge bases have been considered one of the dominant approaches to combining open world ontology languages with closed world rule-based languages. Currently, the only known inference methods are based on the approach of guess-and-verify, while most modern SAT/ASP solvers are built under the DPLL archite...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	76,625

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