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Papers 6,751–6,780 of 6,861

Human-In-The-Loop Machine Learning for Safe and Ethical Autonomous Vehicles: Principles, Challenges, and Opportunities
Aug 22, 2024Yousef Emami, Mohammadhossein Homaei, Miguel Gutiérrez Gaitán +4Autonomous Driving Human-In-The-Loop
AIR: Analytic Imbalance Rectifier for Continual Learning
Aug 19, 2024Di Fang, Yinan Zhu, Zhiping Lin +3Extreme Class Imbalance Learning-Augmented Algorithms
School of Future Technology, South China University of Technology, Guangzhou, China · Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China
ProSpec RL: Plan Ahead, then Execute
Jul 31, 2024Liangliang Liu, Yi Guan, BoRan Wang +5Model-Free Reinforcement Learning Deep Reinforcement Learning
1The Faculty of Computing, Harbin Institute of Technology, Harbin, China · 2The Artificial Intelligence Institute, Harbin Institute of Technology, ShenZhen, China · 3The Artificial Intelligence Institute, Harbin Institute of Technology, Harbin, China
Enhancing Hardware Fault Tolerance in Machines with Reinforcement Learning Policy Gradient Algorithms
Jul 21, 2024Sheila Schoepp, Mehran Taghian, Shotaro Miwa +3Fault Tolerance Agent Framework
Department of Computing Science, University of Alberta, 8900 114 St NW, Edmonton, Alberta, T6G 2S4, Canada · Advanced Technology R&D Center, Mitsubishi Electric Corporation, 8-1-1,Tsukaguchi-honmachi, Amagasaki-shi, Hyogo, 661-8661, Japan · Information Technology R&D Center, Mitsubishi Electric Corporation, 5-1-1, Ofuna, Kamakura-shi, Kanagawa, 247-8501, Japan +1
Open-Vocabulary Object-Goal Navigation by Generalizing Semantic Mapping with Dense CLIP
Jul 12, 2024Meng Wei, Chenyang Wan, Tai Wang +6Vision-Language Navigation Open-Vocabulary
Shanghai AI Lab · Zhejiang University · The University of Hong Kong
Event-based vision sensing and its application to pedestrian detection for intelligent transportation and surveillance
Jul 5, 2024Han Wang, Juntao Wu, Jingyuan Bao +5Pedestrian Detection Vision Sensors
Lifelong Learning of Video Diffusion Models From a Single Video Stream
Jun 7, 2024Jason Yoo, Yingchen He, Saeid Naderiparizi +4
University of British Columbia · KU Leuven · Vector Institute +1
Federated Class-Incremental Learning with Hierarchical Generative Prototypes
Jun 4, 2024Riccardo Salami, Pietro Buzzega, Matteo Mosconi +2Domain Incremental Learning Learnable Prototypes
AImageLab - University of Modena and Reggio Emilia, Modena, Italy
Active Exploration via Autoregressive Generation of Missing Data
May 29, 2024Tiffany Tianhui Cai, Hongseok Namkoong, Daniel Russo +1Efficient Exploration Uncertainty-Aware Inference
Department of Statistics Columbia University New York, NY 10025, USA · Decision, Risk, and Operations Division Columbia Business School New York, NY 10025, USA · Department of Mathematics Imperial College London London SW7 2AZ, United Kingdom
Invariant Graph Representations for Continuous-Time Dynamic Graphs Under Distribution Shifts
May 29, 2024Lanting Fang, Yulian Yang, Yawei Zhang +3Graph Representation Learning Distribution Shifts
1Beijing Institue of Technology · Southeast University · Wuhan University
On the Approximation and Convergence of Distributional Policy Gradient Algorithms for Risk-Sensitive Reinforcement Learning
May 23, 2024Xian Yu, Minheng Xiao, Lei YingConditional-Value-At-Risk
Department of Integrated Systems Engineering, The Ohio State University, Columbus, OH, USA · Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA
Realistic Continual Learning Approach using Pre-trained Models
Apr 11, 2024Nadia Nasri, Carlos Gutiérrez-Álvarez, Sergio Lafuente-Arroyo +2Efficient Continual Learning Continual Learning Methods
University of Alcala, Department of Signal Theory and Communications, GRAM Research group, Alcala de Henares, 28805, Spain · Univesity of Alicante, Department of Computer Science and Artificial Intelligence, San Vicente del Raspeig, 03690, Spain
A Probabilistic Approach for Model Alignment with Human Comparisons
Mar 16, 2024Junyu Cao, Mohsen BayatiReinforcement Learning From Human Feedback Model Evaluation
McCombs School of Business, The University of Texas at Austin · Graduate School of Business, Stanford University
FedReview: Review and Dispose Poisoned Updates without Validation Datasets or Historic Knowledge
Feb 26, 2024Tianhang Zheng, Yanlu Li, Bohan Deng +1Federated Learning Data Poisoning
University of Missouri-Kansas City · University of Toronto
HiQA: A Hierarchical Contextual Augmentation RAG for Multi-Documents QA
Feb 1, 2024Xinyue Chen, Pengyu Gao, Jiangjiang Song +1Multi-Hop Question Answering Benchmarks Multimodal Documents
1Nanjing University of Aeronautics and Astronautics. · 2Southeast University, Nanjing, Jiangsu, China.
TERC: A Transfer Entropy Redundancy Criterion for State Variable Selection in Reinforcement Learning
Jan 21, 2024Charles Westphal, Stephen Hailes, Mirco MusolesiEntropy Regularized Reinforcement Learning Proximal Policy Optimization
UCL Centre for Artificial Intelligence Department of Computer Science University College London Gower Street, London WC1E 6BT, United Kingdom · Department of Computer Science University College London Gower Street, London WC1E 6BT, United Kingdom · Department of Computer Science and Engineering University of Bologna Viale Del Risorgimento 2, 40136 Bologna, Italy
Bridging Language and Action: A Survey of Language-Conditioned Robot Manipulation
Dec 17, 2023Xiangtong Yao, Hongkuan Zhou, Oier Mees +12Generalizable Robotic Manipulations Language-Conditioning Space Policy
Technical University of Munich, Munich, Germany · Corporate Research, Robert Bosch GmbH, Renningen, Germany · Institute for Artificial Intelligence, University of Stuttgart, Stuttgart, Germany +10
Uncertainty Quantification in Machine Learning for Biosignal Applications -- A Review
Nov 15, 2023Ivo Pascal de Jong, Andreea Ioana Sburlea, Matias Valdenegro-ToroMultimodal Physiological Signals Reliable Uncertainty Quantification
Department of Artificial Intelligence, Bernoulli Institute, University of Groningen, Groningen, The Netherlands
DIRA-SS:Dynamic Domain Incremental Regularised Adaptation -- Self-Supervised
Nov 13, 2023Abanoub Ghobrial, Kerstin EderDomain Adaptation Self-Supervised
University of Bristol, Bristol, UK
Causal Discovery in Mixtures of Populations
Nov 13, 2023Bijan Mazaheri, Spencer Gordon, Yuval Rabani +1Causal Foundation Models Structural Equation Models
Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire, USA · Fragment Data Technologies, San Francisco, California, USA · Department of Computer Science, Hebrew Univeristy of Jerusalem, Jerusalem, Israel +1
Data Market Design through Deep Learning
Oct 31, 2023Sai Srivatsa Ravindranath, Yanchen Jiang, David C. ParkesBayesian Experimental Design First-Price Auctions
Harvard John A. Paulson School of Engineering and Applied Sciences
UWA360CAM: A 360 $^{\circ}$ 24/7 Real-Time Streaming Camera System for Underwater Applications
Sep 22, 2023Quan-Dung Pham, Yipeng Zhu, Tan-Sang Ha +3Underwater Image Enhancement Onboard Robot Cameras
Hong Kong University of Science and Technology, Hong Kong SAR. · Trinity College Dublin, Ireland.
ETHER: Aligning Emergent Communication for Hindsight Experience Replay
Jul 28, 2023Kevin Yandoka Denamganaï, Daniel Hernandez, Ozan Vardal +2Goal-Conditioned Reinforcement Learning Reinforcement Learning From Human Feedback
Department of Computer Science University of York York, UK
Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents
Jun 5, 2023Nika Haghtalab, Chara Podimata, Kunhe YangMulticalibration and Calibration
University of California, Berkeley · Massachusetts Institute of Technology
Context-Aware System Synthesis, Task Assignment, and Routing
Jun 14, 2017Jason Ziglar, Ryan Williams, Alfred WicksPatient-To-Room Assignment Problem Humanoid Robotics
RoMu4o: A Robotic Manipulation Unit For Orchard Operations Automating Proximal Hyperspectral Leaf Sensing
Date pendingMehrad Mortazavi, David J. Cappelleri, Reza EhsaniAgricultural Robots Robotic Perception
Department of Mechanical Engineering, University of California, Merced, CA, 95343, USA · School of Mechanical Engineering and Weldon School of Biomedical Engineering (By Courtesy), Purdue University, West Lafayette, IN USA 47907
Safe Learning Under Irreversible Dynamics via Asking for Help
Date pendingBenjamin Plaut, Juan Liévano-Karim, Hanlin Zhu +1Markov Decision Processes Near-Optimal Regret Guarantees
Division of Computer Science University of California Berkeley, CA 94720-1776, USA
FLOAT Drone: A Fully-actuated Coaxial Aerial Robot for Close-Proximity Operations
Date pendingJunxiao Lin, Shuhang Ji, Yuze Wu +3Aerial Robots Drone
State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou, 310027, China
LLM-BabyBench: Can Language Models Plan in Worlds They Can Simulate?
Date pendingIdriss Malek, Omar Choukrani, Daniil Orel +5Large Language Model Planning
Discovering Temporal Structure: An Overview of Hierarchical Reinforcement Learning
Date pendingMartin Klissarov, Akhil Bagaria, Ziyan Luo +3Hierarchical Reinforcement Learning Hierarchical
Mila, McGill University · Amazon · Amii, University of Alberta Canada CIFAR AI Chair

Aug 22, 2024, cs.LGJ/K move · Enter open · S save

Human-In-The-Loop Machine Learning for Safe and Ethical Autonomous Vehicles: Principles, Challenges, and Opportunities

Yousef Emami, Mohammadhossein Homaei, Miguel Gutiérrez Gaitán, Luis Almeida+3

Autonomous Driving Human-In-The-Loop Machine Learning Obstacle Avoidance

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Machine Learning (ML) has become central to Autonomous Vehicles (AVs), supporting perception, prediction, planning, control, and decision-making in dynamic environments. However, achieving full autonomy in cluttered and complex scenarios, such as intricate intersections, diverse scenes, varied trajectories, and complex missions, remains challenging; moreover, data labeling is still a major bottleneck. These limitations motivate Human-in-the-Loop Machine Learning (HITL-ML), in which human input is incorporated through validation, annotation, task organization, reward design, action correction, preference feedback, and supervisory intervention. To advance safe and ethical autonomy, this paper presents a tutorial survey of HITL-ML for AVs, focusing on Curriculum Learning (CL), Human-in-the-Loop Reinforcement Learning (HITL-RL), Human-in-the-Loop Large Language Models (HITL-LLMs), Active Learning (AL), and ethical principles. We first review CL methods that structure training from simple to complex tasks, covering navigation, path planning, obstacle avoidance, data collection, landing, intersection handling, motion planning, and UAV swarm coordination. We then examine HITL-RL through reward shaping, action injection, demonstrations, preference-based feedback, and interactive learning, emphasizing improved learning efficiency, safer policy exploration, and real-time intervention. Next, we review HITL-LLM through collaboration and oversight and specify key challenges. After that, we discuss AL for perception, anomaly detection, semantic mapping, object detection, vehicle recognition, and security-related classification. Ethical principles are reviewed as technical requirements for transparency, accountability, human oversight, safety, security, regulatory compliance, and reliability of human input.