Representation Learning Beyond Linear Prediction Functions

31 May 2021

Papers citing "Representation Learning Beyond Linear Prediction Functions"

12 / 12 papers shown

Title
Provable Model-based Nonlinear Bandit and Reinforcement Learning: Shelve Optimism, Embrace Virtual Curvature Kefan Dong Jiaqi Yang Tengyu Ma 49 33 0 08 Feb 2021
On the Theory of Transfer Learning: The Importance of Task Diversity Nilesh Tripuraneni Michael I. Jordan Chi Jin 100 219 0 20 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
Acquiring Knowledge from Pre-trained Model to Neural Machine Translation Rongxiang Weng Heng Yu Shujian Huang Shanbo Cheng Weihua Luo 48 66 0 04 Dec 2019
Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks Mahyar Fazlyab Alexander Robey Hamed Hassani M. Morari George J. Pappas 87 456 0 12 Jun 2019
A Survey on Deep Transfer Learning Chuanqi Tan F. Sun Tao Kong Wenchang Zhang Chao Yang Chunfang Liu 64 2,584 0 06 Aug 2018
Lipschitz regularity of deep neural networks: analysis and efficient estimation Kevin Scaman Aladin Virmaux 75 527 0 28 May 2018
Size-Independent Sample Complexity of Neural Networks Noah Golowich Alexander Rakhlin Ohad Shamir 126 547 0 18 Dec 2017
Automated Curriculum Learning for Neural Networks Alex Graves Marc G. Bellemare Jacob Menick Rémi Munos Koray Kavukcuoglu 69 523 0 10 Apr 2017
Hypothesis Transfer Learning via Transformation Functions S. Du Jayanth Koushik Aarti Singh Barnabás Póczós 51 58 0 03 Dec 2016
The Benefit of Multitask Representation Learning Andreas Maurer Massimiliano Pontil Bernardino Romera-Paredes SSL 84 375 0 23 May 2015
Model-based Reinforcement Learning and the Eluder Dimension Ian Osband Benjamin Van Roy 80 188 0 07 Jun 2014