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1Statistical Learning Theory - VideoLectures.NET
Statistical Learning Theory - VideoLectures.NET MLSS 2004 John Shawe Taylor
4 years ago by @kirk86
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3Analyses of Deep Learning
Analyses of Deep Learning (STATS 385)
4 years ago by @kirk86
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1Tutorial on PAC Bayes NIPS 2017
Tutorial on PAC Bayes NIPS 2017
5 years ago by @kirk86
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1A Primer on PAC-Bayesian Learning
A Primer on PAC-Bayesian Learning Tutorial
5 years ago by @kirk86
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1ML Theory Workshop - Agenda
ML Theory Workshop - Agenda Google
5 years ago by @kirk86
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1Support Vector Machines
http://svms.org/vc-dimension/
5 years ago by @kirk86
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1COS 511, Spring 2013: Home
https://www.cs.princeton.edu/courses/archive/spring13/cos511/
5 years ago by @kirk86
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1Index of /~tom/10701_sp11/recitations
https://www.cs.cmu.edu/~tom/10701_sp11/recitations/
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19.520/6.860, Fall 2018
http://www.mit.edu/~9.520/fall18/#psets
5 years ago by @kirk86
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1Mehryar Mohri -- Foundations of Machine Learning - Book
https://cs.nyu.edu/~mohri/mlbook/
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2The sample complexity of pattern classification with neural networks: the size of the weights is more important than the size of the network
P. Bartlett. (1998)
5 years ago by @kirk86
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4A Tutorial Introduction to the Minimum Description Length Principle
P. Grunwald. (2004)
5 years ago by @kirk86
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1Quantum hardness of learning shallow classical circuits
S. Arunachalam, B. Grilo, and A. Sundaram. (2019)
5 years ago by @kirk86
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2Neural Task Graphs: Generalizing to Unseen Tasks from a Single Video Demonstration
D. Huang, S. Nair, D. Xu, Y. Zhu, A. Garg, L. Fei-Fei, S. Savarese, and J. Niebles. (2018)cite arxiv:1807.03480Comment: CVPR 2019.
5 years ago by @kirk86
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2Stiffness: A New Perspective on Generalization in Neural Networks
S. Fort, P. Nowak, and S. Narayanan. (2019)cite arxiv:1901.09491.
5 years ago by @kirk86
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3Detecting Overfitting via Adversarial Examples
R. Werpachowski, A. György, and C. Szepesvári. (2019)cite arxiv:1903.02380Comment: 25 pages.
5 years ago by @kirk86
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2The Lottery Ticket Hypothesis at Scale
J. Frankle, G. Dziugaite, D. Roy, and M. Carbin. (2019)cite arxiv:1903.01611.
5 years ago by @kirk86
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1High probability generalization bounds for uniformly stable algorithms with nearly optimal rate
V. Feldman, and J. Vondrak. (2019)cite arxiv:1902.10710Comment: arXiv admin note: text overlap with arXiv:1812.09859.
5 years ago by @kirk86
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3Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate
M. Belkin, D. Hsu, and P. Mitra. (2018)cite arxiv:1806.05161.
5 years ago by @kirk86
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2For valid generalization, the size of the weights is more important than the size of the network
P. Bartlett. NeurIPS, (1996)
5 years ago by @kirk86
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1Statistical Learning Theory - VideoLectures.NET

3Analyses of Deep Learning

1Tutorial on PAC Bayes NIPS 2017

1A Primer on PAC-Bayesian Learning

1ML Theory Workshop - Agenda

1Support Vector Machines

1COS 511, Spring 2013: Home

1Index of /~tom/10701_sp11/recitations

19.520/6.860, Fall 2018

1Mehryar Mohri -- Foundations of Machine Learning - Book

publications (hide)210
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2The sample complexity of pattern classification with neural networks: the size of the weights is more important than the size of the network

4A Tutorial Introduction to the Minimum Description Length Principle

1Quantum hardness of learning shallow classical circuits

2Neural Task Graphs: Generalizing to Unseen Tasks from a Single Video Demonstration

2Stiffness: A New Perspective on Generalization in Neural Networks

3Detecting Overfitting via Adversarial Examples

2The Lottery Ticket Hypothesis at Scale

1High probability generalization bounds for uniformly stable algorithms with nearly optimal rate

3Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate

2For valid generalization, the size of the weights is more important than the size of the network

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