Machine LearningArgyriou, A., Evgeniou, T., Pontil, M.: Convex multi-task feature learning. Ma- chine Learning 73(3), 243-272 (2008)Andreas Argyriou, Theodoros Evgeniou, and Massimiliano Pontil. Convex multi-task feature learning. Machine Learning, 73(3):243-272, 2008....
Convex multi-task feature learning We present a method for learning sparse representations shared across multiple tasks. This method is a generalization of thewell-known single-task 1-norm regularization. It is based on a novel non-convex regularizer which controls the nu... Andreas,Argyriou,Theo...
http://scholar.google.com/scholar?q=%222008%22+Convex+Multi-task+Feature+Learning http://dl.acm.org/citation.cfm?id=1455903.1455908&preflayout=flat#citedby Quotes Author Keywords Collaborative Filtering;Inductive Transfer;Kernels;Multi-Task Learning;Regularization;Transfer Learning;Vector-Valued Functions...
Multi-task learning is a learning paradigm which seeks to improve the generalization performance of a learning task with the help of some other related tasks. In this paper, we propose a regularization formulation for learning the relationships between tasks in multi-task learning. This formulation ...
%convexAdam + Hyperparameter Optimisation TMI @article{siebert2024convexadam, title={ConvexAdam: Self-Configuring Dual-Optimisation-Based 3D Multitask Medical Image Registration}, author={Siebert, Hanna and Gro{\ss}br{\"o}hmer, Christoph and Hansen, Lasse and Heinrich, Mattias P}, journal={IEEE...
The existence of uncoupled no-regret learning dynamics converging to correlated equilibria in normal-form games is a celebrated result in the theory of multi-agent systems. Specifically, it has been known for more than 20 years that when all players seek to minimize their internal regret in a ...
Qiao. A discriminative feature learning approach for deep face recognition. In European Conference on Computer Vision, pages 499–515. Springer, 2016. [27] K. Zhang, Z. Zhang, Z. Li, and Y. Qiao. Joint face detection and alignment using multitask cascaded convolutional net- works. IEEE ...
However, due to the gene expression datasets have the characteristics of small sample size, high dimensionality and high noise, the application of biostatistics and machine learning methods to analyze gene expression data is a challenging task, such as the low reproducibility of important biomarkers ...
Inverse multiobjective optimization provides a general framework for the unsupervised learning task of inferring parameters of a multiobjective decision making problem (DMP), based on a set of observed decisions from the human expert. However, the performance of this framework relies critically on the...
NasJobOutput.MultiTrialJobOutputOrBuilder NasJobOutputOrBuilder NasJobSpec.MultiTrialAlgorithmSpec.MetricSpecOrBuilder NasJobSpec.MultiTrialAlgorithmSpec.SearchTrialSpecOrBuilder NasJobSpec.MultiTrialAlgorithmSpec.TrainTrialSpecOrBuilder NasJobSpec.MultiTrialAlgorithmSpecOrBuilder Nas...