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Teaching with Commentaries

Teaching with Commentaries

5 November 2020
Aniruddh Raghu
M. Raghu
Simon Kornblith
David Duvenaud
Geoffrey E. Hinton
ArXivPDFHTML

Papers citing "Teaching with Commentaries"

19 / 19 papers shown
Title
Curriculum Learning with Adam: The Devil Is in the Wrong Details
Curriculum Learning with Adam: The Devil Is in the Wrong Details
Leon Weber
Jaap Jumelet
Paul Michel
Elia Bruni
Dieuwke Hupkes
ODL
18
3
0
23 Aug 2023
Auxiliary Learning as an Asymmetric Bargaining Game
Auxiliary Learning as an Asymmetric Bargaining Game
Aviv Shamsian
Aviv Navon
Neta Glazer
Kenji Kawaguchi
Gal Chechik
Ethan Fetaya
35
8
0
31 Jan 2023
On Implicit Bias in Overparameterized Bilevel Optimization
On Implicit Bias in Overparameterized Bilevel Optimization
Paul Vicol
Jon Lorraine
Fabian Pedregosa
David Duvenaud
Roger C. Grosse
AI4CE
33
37
0
28 Dec 2022
The Forward-Forward Algorithm: Some Preliminary Investigations
The Forward-Forward Algorithm: Some Preliminary Investigations
Geoffrey E. Hinton
25
258
0
27 Dec 2022
Compute-Efficient Deep Learning: Algorithmic Trends and Opportunities
Compute-Efficient Deep Learning: Algorithmic Trends and Opportunities
Brian Bartoldson
B. Kailkhura
Davis W. Blalock
31
47
0
13 Oct 2022
Simple and Effective Gradient-Based Tuning of Sequence-to-Sequence
  Models
Simple and Effective Gradient-Based Tuning of Sequence-to-Sequence Models
Jared Lichtarge
Chris Alberti
Shankar Kumar
37
4
0
10 Sep 2022
Teacher Guided Training: An Efficient Framework for Knowledge Transfer
Teacher Guided Training: An Efficient Framework for Knowledge Transfer
Manzil Zaheer
A. S. Rawat
Seungyeon Kim
Chong You
Himanshu Jain
Andreas Veit
Rob Fergus
Surinder Kumar
VLM
18
2
0
14 Aug 2022
Remember the Past: Distilling Datasets into Addressable Memories for
  Neural Networks
Remember the Past: Distilling Datasets into Addressable Memories for Neural Networks
Zhiwei Deng
Olga Russakovsky
FedML
DD
41
92
0
06 Jun 2022
Learning to Scaffold: Optimizing Model Explanations for Teaching
Learning to Scaffold: Optimizing Model Explanations for Teaching
Patrick Fernandes
Marcos Vinícius Treviso
Danish Pruthi
André F. T. Martins
Graham Neubig
FAtt
25
22
0
22 Apr 2022
Adaptive Mixing of Auxiliary Losses in Supervised Learning
Adaptive Mixing of Auxiliary Losses in Supervised Learning
D. Sivasubramanian
Ayush Maheshwari
Pradeep Shenoy
A. Prathosh
Ganesh Ramakrishnan
29
5
0
07 Feb 2022
When less is more: Simplifying inputs aids neural network understanding
When less is more: Simplifying inputs aids neural network understanding
R. Schirrmeister
Rosanne Liu
Sara Hooker
T. Ball
24
5
0
14 Jan 2022
Lyapunov Exponents for Diversity in Differentiable Games
Lyapunov Exponents for Diversity in Differentiable Games
Jonathan Lorraine
Paul Vicol
Jack Parker-Holder
Tal Kachman
Luke Metz
Jakob N. Foerster
25
7
0
24 Dec 2021
Noether Networks: Meta-Learning Useful Conserved Quantities
Noether Networks: Meta-Learning Useful Conserved Quantities
Ferran Alet
Dylan D. Doblar
Allan Zhou
J. Tenenbaum
Kenji Kawaguchi
Chelsea Finn
73
26
0
06 Dec 2021
Meta-Learning to Improve Pre-Training
Meta-Learning to Improve Pre-Training
Aniruddh Raghu
Jonathan Lorraine
Simon Kornblith
Matthew B. A. McDermott
David Duvenaud
19
30
0
02 Nov 2021
Back to Square One: Superhuman Performance in Chutes and Ladders Through
  Deep Neural Networks and Tree Search
Back to Square One: Superhuman Performance in Chutes and Ladders Through Deep Neural Networks and Tree Search
Dylan R. Ashley
Anssi Kanervisto
Brendan Bennett
19
2
0
01 Apr 2021
Complex Momentum for Optimization in Games
Complex Momentum for Optimization in Games
Jonathan Lorraine
David Acuna
Paul Vicol
David Duvenaud
17
9
0
16 Feb 2021
Meta Pseudo Labels
Meta Pseudo Labels
Hieu H. Pham
Zihang Dai
Qizhe Xie
Minh-Thang Luong
Quoc V. Le
VLM
262
656
0
23 Mar 2020
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness
  of MAML
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML
Aniruddh Raghu
M. Raghu
Samy Bengio
Oriol Vinyals
183
639
0
19 Sep 2019
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
344
11,684
0
09 Mar 2017
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