Concept
Bayesian optimization
Publications associées (42)
Mesh-based topology, shape and sizing optimization of ribbed plates
In this paper, we present a new parameterization and optimization procedure for minimizing the weight of ribbed plates. The primary goal is to reduce embodied CO2 in concrete floors as part of the effort to diminish the carbon footprint of the construction ...
Springer2024Bayesian Optimization for Chemical Reactions
Philippe Schwaller, Jeff Guo, Bojana Rankovic
Reaction optimization is challenging and traditionally delegated to domain experts who iteratively pro-pose increasingly optimal experiments. Problematically, the reaction landscape is complex and often requires hundreds of experiments to reach convergence ...
Bern2023Robust Outlier Rejection for 3D Registration with Variational Bayes
Mathieu Salzmann, Jiancheng Yang, Zheng Dang, Zhen Wei, Haobo Jiang
Learning-based outlier (mismatched correspondence) rejection for robust 3D registration generally formulates the outlier removal as an inlier/outlier classification problem. The core for this to be successful is to learn the discriminative inlier/outlier f ...
Los Alamitos2023Improving Generalization of Pretrained Language Models
In this dissertation, we propose multiple methods to improve transfer learning for pretrained language models (PLMs). Broadly, transfer learning is a powerful technique in natural language processing, where a language model is first pre-trained on a data-r ...
EPFL2023Neural System Level Synthesis: Learning over All Stabilizing Policies for Nonlinear Systems
Giancarlo Ferrari Trecate, Luca Furieri, Clara Lucía Galimberti
We address the problem of designing stabilizing control policies for nonlinear systems in discrete-time, while minimizing an arbitrary cost function. When the system is linear and the cost is convex, the System Level Synthesis (SLS) approach offers an effe ...
IEEE2022Bayesian Inversion for Nonlinear Imaging Models Using Deep Generative Priors
Michaël Unser, Thanh-An Michel Pham, Pakshal Narendra Bohra, Jonathan Yuelin Dong
Most modern imaging systems incorporate a computational pipeline to infer the image of interest from acquired measurements. The Bayesian approach to solve such ill-posed inverse problems involves the characterization of the posterior distribution of the im ...
2022Optimizing Latent Space Directions For GAN-based Local Image Editing
Sabine Süsstrunk, Tong Zhang, Ehsan Pajouheshgar
Generative Adversarial Network (GAN) based localized image editing can suffer from ambiguity between semantic attributes. We thus present a novel objective function to evaluate the locality of an image edit. By introducing the supervision from a pre-traine ...
IEEE2021Optimization methods for collaborative learning
Sai Praneeth Reddy Karimireddy
A traditional machine learning pipeline involves collecting massive amounts of data centrally on a server and training models to fit the data. However, increasing concerns about the privacy and security of user's data, combined with the sheer growth in the ...
EPFL2021