https://github.com/daskol/paper-reviews
https://github.com/daskol/paper-reviews
neural-network paper review
Last synced: 4 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/daskol/paper-reviews
- Owner: daskol
- License: mit
- Created: 2017-03-23T20:13:38.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2018-10-24T20:12:32.000Z (over 7 years ago)
- Last Synced: 2025-01-12T21:29:27.487Z (over 1 year ago)
- Topics: neural-network, paper, review
- Language: TeX
- Size: 8.28 MB
- Stars: 3
- Watchers: 4
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Citation: citations/Ben-David S. et al. - On the power of randomization in on-line algorithms - 1994.bib
Awesome Lists containing this project
README
# Papers
*papers & review*
Here I stores all article I have ever read and reviews them.
## Review List
1. **A**
1. [Albers S. - Online Algorithms - 2006](reviews/Albers%20S.%20-%20Online%20Algorithms%20-%202006.md)
2. **B**
1. [Bed-Devide S. et al - On the Power of Randomization in Online Algorithms - 1990](reviews/Bed-Devide%20S.%20et%20al%20-%20On%20the%20Power%20of%20Randomization%20in%20Online%20Algorithms%20-%201990.md)
2. [Benetka J. R. et al - Anticipating Information Needs Based on Check-in Activity - 2017](reviews/Benetka%20J.%20R.%20et%20al%20-%20Anticipating%20Information%20Needs%20Based%20on%20Check-in%20Activity%20-%202017.md)
3. [Biamonte J. et al. Quantum machine learning - 2017](reviews/Biamonte%20J.%20et%20al.%20Quantum%20machine%20learning%20-%202017.md)
3. **G**
1. [Girshick R. et al - Rich feature hierarchies for accurate object detection and semantic segmentation - 2014](reviews/Girshick%20R.%20et%20al%20-%20Rich%20feature%20hierarchies%20for%20accurate%20object%20detection%20and%20semantic%20segmentation%20-%202014.md)
2. [Giovannetti V., Lloyd S., Maccone L. - Quantum random access memory - 2008](reviews/Giovannetti%20el%20al%20-%20Quantum%20random%20access%20memory%20-%202008.md)
4. **K**
1. [Kirkpatrick J. et al - Overcoming catastrophic forgetting in neural networks - 2017](reviews/Kirkpatrick%20J.%20et%20al%20-%20Overcoming%20catastrophic%20forgetting%20in%20neural%20networks%20-%202017.md)
2. [Kingma D. et al - Glow: Generative flow with invertible 1x1 convolutions - 2018](reviews/Kingma%20D.%20et%20al%20-%20Glow:%20Generative%20flow%20with%20invertible%201x1%20convolutions%20-%202018.md)
5. **L**
1. [Lv K. et al - Learning Gradient Descent: Better Generalization and Longer Horizons - 2017](reviews/Lv%20K.%20et%20al%20-%20Learning%20Gradient%20Descent:%20Better%20Generalization%20and%20Longer%20Horizons%20-%202017.md)
6. **N**
1. [Novikov A. et al - Tensorizing neural networks - 2015](reviews/Novikov%20A.%20et%20al%20-%20Tensorizing%20neural%20networks%20-%202015.md)
## List
1. [S. Albers. *Online algorithms* // In Interactive Computation: The New Paradigm edited by D.Q. Goldin, S.A. Smolka and P. Wegner, 143-164, 2006.](http://www14.in.tum.de/personen/albers/papers/inter.pdf)
2. [Ben-David S. et al. *On the Power of Randomization in Online Algorithms* // 1990](https://pdfs.semanticscholar.org/0705/e28b8ec561884ae37fde887a4ded5d2df107.pdf)
3. [Lv K. et al. *Learning Gradient Descent: Better Generalization and Longer Horizons* // arXiv:1703.03633v2](https://arxiv.org/abs/1703.03633)
4. [Benetka J. R. et al. *Anticipating Information Needs Based on Check-in Activity* // WSDM. - 2017](http://zero-query.com/paper/benetka-wsdm2017-activity.pdf)
5. [Novikov A. et al. *Tensorizing neural networks* // Advances in Neural Information Processing Systems. – 2015](http://papers.nips.cc/paper/5787-tensorizing-neural-networks.pdf)
6. [Kirkpatrick J. et al. *Overcoming catastrophic forgetting in neural networks* // 2017](https://arxiv.org/abs/1612.00796)