Tracking the l\(_\mbox2\) Norm with Constant Update Time.
Chi-Ning Chou; Zhixian Lei; and Preetum Nakkiran.
In
APPROX/RANDOM 2019, September 20-22, 2019, volume 145, of
LIPIcs, pages 2:1–2:15, 2019. Schloss Dagstuhl - Leibniz-Zentrum für Informatik
Paper
doi
link
bibtex
@inproceedings{DBLP:conf/approx/ChouLN19,
author = {Chi{-}Ning Chou and
Zhixian Lei and
Preetum Nakkiran},
title = {Tracking the l\({}_{\mbox{2}}\) Norm with Constant Update Time},
booktitle = {{APPROX/RANDOM} 2019, September 20-22, 2019},
series = {LIPIcs},
volume = {145},
pages = {2:1--2:15},
publisher = {Schloss Dagstuhl - Leibniz-Zentrum f{\"{u}}r Informatik},
year = {2019},
url = {https://doi.org/10.4230/LIPIcs.APPROX-RANDOM.2019.2},
doi = {10.4230/LIPIcs.APPROX-RANDOM.2019.2},
}
Computational Limitations in Robust Classification and Win-Win Results.
Akshay Degwekar; Preetum Nakkiran; and Vinod Vaikuntanathan.
In Alina Beygelzimer; and Daniel Hsu., editor(s),
Conference on Learning Theory, COLT 2019, 25-28 June 2019, Phoenix, AZ, USA, volume 99, of
Proceedings of Machine Learning Research, pages 994–1028, 2019. PMLR
Paper
link
bibtex
@inproceedings{DBLP:conf/colt/DegwekarNV19,
author = {Akshay Degwekar and
Preetum Nakkiran and
Vinod Vaikuntanathan},
editor = {Alina Beygelzimer and
Daniel Hsu},
title = {Computational Limitations in Robust Classification and Win-Win Results},
booktitle = {Conference on Learning Theory, {COLT} 2019, 25-28 June 2019, Phoenix,
AZ, {USA}},
series = {Proceedings of Machine Learning Research},
volume = {99},
pages = {994--1028},
publisher = {{PMLR}},
year = {2019},
url = {http://proceedings.mlr.press/v99/degwekar19a.html},
timestamp = {Mon, 08 Jul 2019 16:13:41 +0200},
biburl = {https://dblp.org/rec/conf/colt/DegwekarNV19.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Algorithmic Polarization for Hidden Markov Models.
Venkatesan Guruswami; Preetum Nakkiran; and Madhu Sudan.
In
10th Innovations in Theoretical Computer Science Conference, ITCS 2019, January 10-12, 2019, San Diego, California, USA, volume 124, of
LIPIcs, pages 39:1–39:19, 2019. Schloss Dagstuhl - Leibniz-Zentrum für Informatik
Paper
doi
link
bibtex
@inproceedings{DBLP:conf/innovations/GuruswamiNS19,
author = {Venkatesan Guruswami and
Preetum Nakkiran and
Madhu Sudan},
title = {Algorithmic Polarization for Hidden Markov Models},
booktitle = {10th Innovations in Theoretical Computer Science Conference, {ITCS}
2019, January 10-12, 2019, San Diego, California, {USA}},
series = {LIPIcs},
volume = {124},
pages = {39:1--39:19},
publisher = {Schloss Dagstuhl - Leibniz-Zentrum f{\"{u}}r Informatik},
year = {2019},
url = {https://doi.org/10.4230/LIPIcs.ITCS.2019.39},
doi = {10.4230/LIPIcs.ITCS.2019.39},
timestamp = {Tue, 11 Feb 2020 15:52:14 +0100},
biburl = {https://dblp.org/rec/conf/innovations/GuruswamiNS19.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
SGD on Neural Networks Learns Functions of Increasing Complexity.
Preetum Nakkiran; Gal Kaplun; Dimitris Kalimeris; Tristan Yang; Benjamin L. Edelman; Fred Zhang; and Boaz Barak .
In
Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, 8-14 December 2019, Vancouver, BC, Canada, pages 3491–3501, 2019.
Paper
link
bibtex
@inproceedings{DBLP:conf/nips/KalimerisKNEYBZ19,
author = {
Preetum Nakkiran and
Gal Kaplun and
Dimitris Kalimeris and
Tristan Yang and
Benjamin L. Edelman and
Fred Zhang and,
Boaz Barak},
title = {{SGD} on Neural Networks Learns Functions of Increasing Complexity},
booktitle = {Advances in Neural Information Processing Systems 32: Annual Conference
on Neural Information Processing Systems 2019, NeurIPS 2019, 8-14
December 2019, Vancouver, BC, Canada},
pages = {3491--3501},
year = {2019},
url = {http://papers.nips.cc/paper/8609-sgd-on-neural-networks-learns-functions-of-increasing-complexity},
timestamp = {Fri, 06 Mar 2020 16:59:09 +0100},
biburl = {https://dblp.org/rec/conf/nips/KalimerisKNEYBZ19.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Adversarial Robustness May Be at Odds With Simplicity.
Preetum Nakkiran.
CoRR, abs/1901.00532. 2019.
Paper
link
bibtex
@article{DBLP:journals/corr/abs-1901-00532,
author = {Preetum Nakkiran},
title = {Adversarial Robustness May Be at Odds With Simplicity},
journal = {CoRR},
volume = {abs/1901.00532},
year = {2019},
url = {http://arxiv.org/abs/1901.00532},
archivePrefix = {arXiv},
eprint = {1901.00532},
timestamp = {Thu, 31 Jan 2019 00:00:00 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-1901-00532.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
More Data Can Hurt for Linear Regression: Sample-wise Double Descent.
Preetum Nakkiran.
CoRR, abs/1912.07242. 2019.
Paper
link
bibtex
@article{DBLP:journals/corr/abs-1912-07242,
author = {Preetum Nakkiran},
title = {More Data Can Hurt for Linear Regression: Sample-wise Double Descent},
journal = {CoRR},
volume = {abs/1912.07242},
year = {2019},
url = {http://arxiv.org/abs/1912.07242},
archivePrefix = {arXiv},
eprint = {1912.07242},
timestamp = {Tue, 07 Jan 2020 00:00:00 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-1912-07242.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}