Research output per year
Research output per year
- 16 results
Search results
-
2022
Efficient Learning of CNNs using Patch Based Features
Brutzkus, A., Globerson, A., Malach, E., Netser, A. R. & Shalev-Shwartz, S., 2022, In: Proceedings of Machine Learning Research. 162, p. 2336-2356 21 p.Tel Aviv University, The Hebrew University of Jerusalem
Research output: Contribution to journal › Conference article › peer-review
Open Access -
2021
The Connection Between Approximation, Depth Separation and Learnability in Neural Networks
Malach, E., Yehudai, G., Shalev-Shwartz, S. & Shamir, O., 2021, In: Proceedings of Machine Learning Research. 134, p. 3265-3295 31 p.Weizmann Institute of Science, The Hebrew University of Jerusalem
Research output: Contribution to journal › Conference article › peer-review
Open Access -
2020
Distribution Free Learning with Local Queries
Bary-Weisberg, G., Daniely, A. & Shalev-Shwartz, S., 2020, In: Proceedings of Machine Learning Research. 117, p. 133-147 15 p.The Hebrew University of Jerusalem
Research output: Contribution to journal › Conference article › peer-review
Open Access -
The implications of local correlation on learning some deep functions
Malach, E. & Shalev-Shwartz, S., 2020, In: Advances in Neural Information Processing Systems. 2020-DecemberThe Hebrew University of Jerusalem
Research output: Contribution to journal › Conference article › peer-review
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2019
Is deeper better only when shallow is good?
Malach, E. & Shalev-Shwartz, S., 2019, In: Advances in Neural Information Processing Systems. 32The Hebrew University of Jerusalem
Research output: Contribution to journal › Conference article › peer-review
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2017
Decoupling "when to update" from "how to update"
Malach, E. & Shalev-Shwartz, S., 2017, In: Advances in Neural Information Processing Systems. 2017-December, p. 961-971 11 p.The Hebrew University of Jerusalem
Research output: Contribution to journal › Conference article › peer-review
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2016
Complexity theoretic limitations on learning DNF's
Daniely, A. & Shalev-Shwartz, S., 6 Jun 2016, In: Proceedings of Machine Learning Research. 49, June, p. 815-830 16 p.The Hebrew University of Jerusalem
Research output: Contribution to journal › Conference article › peer-review
Open Access -
2015
Beyond convexity: Stochastic quasi-convex optimization
Hazan, E., Levy, K. Y. & Shalev-Shwartz, S., 2015, In: Advances in Neural Information Processing Systems. 2015-January, p. 1594-1602 9 p.Technion - Israel Institute of Technology, The Hebrew University of Jerusalem
Research output: Contribution to journal › Conference article › peer-review
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2014
On the computational efficiency of training neural networks
Livni, R., Shalev-Shwartz, S. & Shamir, O., 8 Dec 2014, In: Advances in Neural Information Processing Systems. 1, January, p. 855-863 9 p.The Hebrew University of Jerusalem, Weizmann Institute of Science
Research output: Contribution to journal › Conference article › peer-review
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Optimal learners for multiclass problems
Daniely, A. & Shalev-Shwartz, S., 2014, In: Proceedings of Machine Learning Research. 35, p. 287-316 30 p.The Hebrew University of Jerusalem
Research output: Contribution to journal › Conference article › peer-review
Open Access -
The complexity of learning halfspaces using generalized linear methods
Daniely, A. & Shalev-Shwartz, S., 2014, In: Proceedings of Machine Learning Research. 35, p. 244-286 43 p.The Hebrew University of Jerusalem
Research output: Contribution to journal › Conference article › peer-review
Open Access -
2013
Accelerated mini-batch stochastic dual coordinate ascent
Shalev-Shwartz, S. & Zhang, T., 2013, In: Advances in Neural Information Processing Systems.The Hebrew University of Jerusalem
Research output: Contribution to journal › Conference article › peer-review
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More data speeds up training time in learning halfspaces over sparse vectors
Daniely, A., Linial, N. & Shalev-Shwartz, S., 2013, In: Advances in Neural Information Processing Systems.The Hebrew University of Jerusalem
Research output: Contribution to journal › Conference article › peer-review
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2012
Using more data to speed-up training time
Shalev-Shwartz, S., Shamir, O. & Tromer, E., 2012, In: Proceedings of Machine Learning Research. 22, p. 1019-1027 9 p.The Hebrew University of Jerusalem, Tel Aviv University
Research output: Contribution to journal › Conference article › peer-review
Open Access -
2011
Collaborative filtering with the trace norm: Learning, bounding, and transducing
Shamir, O. & Shalev-Shwartz, S., 2011, In: Proceedings of Machine Learning Research. 19, p. 661-678 18 p.The Hebrew University of Jerusalem
Research output: Contribution to journal › Conference article › peer-review
Open Access -
Multiclass learnability and the ERM principle
Daniely, A., Sabato, S., Ben-David, S. & Shalev-Shwartz, S., 2011, In: Proceedings of Machine Learning Research. 19, p. 207-232 26 p.The Hebrew University of Jerusalem
Research output: Contribution to journal › Conference article › peer-review
Open Access