Results 101 to 110 of about 127,719 (261)
Stochastic Hyperparameter Optimization through Hypernetworks
, 2018 Machine learning models are often tuned by nesting optimization of model weights inside the optimization of hyperparameters. We give a method to collapse this nested optimization into joint stochastic optimization of weights and hyperparameters. Our process trains a neural network to output approximately optimal weights as a function of hyperparameters.
Lorraine, Jonathan, Duvenaud, David
openaire +2 more sources
Reducing Personalization Time and Energy Cost While Walking Outdoors with a Portable Exosuit
Advanced Robotics Research, EarlyView.Rapid Real‐World Optimization! An AF‐based human‐in‐the‐loop optimization strategy rapidly personalizes a portable hip extension exosuit for incline walking. Real‐time Bayesian optimization of assistive force significantly reduces metabolic energy—up to 16.2%—while converging in just 3 min 24 s.
Kimoon Nam +7 more
wiley +1 more source
Liquid Metal Sensors for Soft Robots
Advanced Robotics Research, EarlyView.This review thoroughly reviews liquid metal sensors in soft robots. Their unique material properties like high conductivity and good biocompatibility are analyzed. Working principles are classified, and applications in environmental perception, motion detection, and human—robot interaction are introduced.
Qi Zhang +7 more
wiley +1 more source
3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends
Advanced Robotics Research, EarlyView.Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu +5 more
wiley +1 more source
ACHO: Adaptive Conformal Hyperparameter Optimization
, 2022 Several novel frameworks for hyperparameter search have emerged in the last decade, but most rely on strict, often normal, distributional assumptions, limiting search model flexibility. This paper proposes a novel optimization framework based on upper confidence bound sampling of conformal confidence intervals, whose weaker assumption of ...
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Advanced Robotics Research, EarlyView.Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley +1 more source
Overtuning in Hyperparameter Optimization
Accepted at the Fourth Conference on Automated Machine Learning (Methods Track).
Schneider, Lennart +2 more
openaire +2 more sources
Hyperparameters: Optimize, or Integrate Out? [PDF]
, 1996 I examine two approximate methods for computational implementation of Bayesian hierarchical models, that is, models which include unknown hyperparameters such as regularization constants. In the ‘evidence framework’ the model parameters are integrated over, and the resulting evidence is maximized over the hyperparameters.
openaire +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Advanced Robotics Research, EarlyView.Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
ModellingSocial media users often express their emotions through text in posts and tweets, and these can be used for sentiment analysis, identifying text as positive or negative.
Hussam Alawneh +2 more
doaj +1 more source