Theoretical bounds on estimation error for meta-learning

14 October 2020

Papers citing "Theoretical bounds on estimation error for meta-learning"

23 / 23 papers shown

Title
A No-Free-Lunch Theorem for MultiTask Learning Steve Hanneke Samory Kpotufe 114 39 0 29 Jun 2020
Minimax Lower Bounds for Transfer Learning with Linear and One-hidden Layer Neural Networks Seyed Mohammadreza Mousavi Kalan Zalan Fabian A. Avestimehr Mahdi Soltanolkotabi 45 32 0 16 Jun 2020
Few-Shot Learning via Learning the Representation, Provably S. Du Wei Hu Sham Kakade Jason D. Lee Qi Lei SSL 46 260 0 21 Feb 2020
On the Value of Target Data in Transfer Learning Steve Hanneke Samory Kpotufe 62 74 0 12 Feb 2020
A Theoretical Analysis of the Number of Shots in Few-Shot Learning Tianshi Cao M. Law Sanja Fidler 63 63 0 25 Sep 2019
Learning-to-Learn Stochastic Gradient Descent with Biased Regularization Giulia Denevi C. Ciliberto Riccardo Grazzi Massimiliano Pontil 67 110 0 25 Mar 2019
Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response Functions M. Mackay Paul Vicol Jonathan Lorraine David Duvenaud Roger C. Grosse 78 164 0 07 Mar 2019
Provable Guarantees for Gradient-Based Meta-Learning M. Khodak Maria-Florina Balcan Ameet Talwalkar FedML 122 150 0 27 Feb 2019
A Theoretical Analysis of Contrastive Unsupervised Representation Learning Sanjeev Arora H. Khandeparkar M. Khodak Orestis Plevrakis Nikunj Saunshi SSL 100 779 0 25 Feb 2019
Meta-Learning Update Rules for Unsupervised Representation Learning Luke Metz Niru Maheswaranathan Brian Cheung Jascha Narain Sohl-Dickstein SSL OOD 72 123 0 31 Mar 2018
Marginal Singularity, and the Benefits of Labels in Covariate-Shift Samory Kpotufe Guillaume Martinet 136 95 0 05 Mar 2018
Recasting Gradient-Based Meta-Learning as Hierarchical Bayes Erin Grant Chelsea Finn Sergey Levine Trevor Darrell Thomas Griffiths BDL 88 509 0 26 Jan 2018
Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory Ron Amit Ron Meir BDL MLT 69 176 0 03 Nov 2017
Prototypical Networks for Few-shot Learning Jake C. Snell Kevin Swersky R. Zemel 300 8,134 0 15 Mar 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 823 11,909 0 09 Mar 2017
RL $^2$ : Fast Reinforcement Learning via Slow Reinforcement Learning Yan Duan John Schulman Xi Chen Peter L. Bartlett Ilya Sutskever Pieter Abbeel OffRL 96 1,019 0 09 Nov 2016
Learning to learn by gradient descent by gradient descent Marcin Andrychowicz Misha Denil Sergio Gomez Colmenarejo Matthew W. Hoffman David Pfau Tom Schaul Brendan Shillingford Nando de Freitas 108 2,006 0 14 Jun 2016
Matching Networks for One Shot Learning Oriol Vinyals Charles Blundell Timothy Lillicrap Koray Kavukcuoglu Daan Wierstra VLM 373 7,323 0 13 Jun 2016
A PAC-Bayesian bound for Lifelong Learning Anastasia Pentina Christoph H. Lampert CLL 80 210 0 12 Nov 2013
Minimax Multi-Task Learning and a Generalized Loss-Compositional Paradigm for MTL Nishant A. Mehta Dongryeol Lee Alexander G. Gray 58 11 0 13 Sep 2012
New Analysis and Algorithm for Learning with Drifting Distributions M. Mohri Andrés Munoz Medina 133 125 0 19 May 2012
A Model of Inductive Bias Learning Jonathan Baxter 109 1,214 0 01 Jun 2011
$Minimax rates of estimation for high-dimensional linear regression over $\ell_q$-balls$ Minimax rates of estimation for high-dimensional linear regression over $\ell_q$ -balls Garvesh Raskutti Martin J. Wainwright Bin Yu 220 575 0 11 Oct 2009