Natasa Krklec Jerinkic

Artificial Intelligence · 2013–2018

A researcher in the Science corpus: 2 papers; trusts 20 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 16 citations into it
• Optimization & Training — 15 citations into it; #2,223 of 2,601 by trust here, #2,484 by citations
• Computational Mechanics — 14 citations into it; #7,861 of 10,001 by trust here, #9,582 by citations
• Numerical Analysis — 11 citations into it; #2,854 of 3,586 by trust here, #2,832 by citations
• Computational Theory and Mathematics — 5 citations into it
• Management Science and Operations Research — 5 citations into it

Whom Natasa Krklec Jerinkic trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. James C. Spall
2. Farbod Roosta-Khorasani
3. Yurii E. Nesterov
4. Richard H. Byrd
5. Joel A. Tropp
6. W. Hoeffding
7. Stanislav Minsker
8. Raghu Bollapragada
9. Jorge Nocedal
10. Michael W. Mahoney

Who trusts Natasa Krklec Jerinkic overall

1. Sharan Vaswani

Papers from Natasa Krklec Jerinkic's perspective

Ordered by how strongly the researchers Natasa Krklec Jerinkic trusts endorse each paper. Same corpus, a different order for every researcher.

1. INEXACT NEWTON METHODS
2. On the Use of Stochastic Hessian Information in Optimization Methods for Machine Learning
3. Convergence rates of sub-sampled Newton methods
4. Hybrid Deterministic-Stochastic Methods for Data Fitting
5. Sub-Sampled Newton Methods II: Local Convergence Rates
6. Sub-sampled Newton Methods with Non-uniform Sampling
7. Newton Sketch: A Near Linear-Time Optimization Algorithm with Linear-Quadratic Convergence
8. Optimization Methods for Large-Scale Machine Learning
9. Sample size selection in optimization methods for machine learning
10. Exact and Inexact Subsampled Newton Methods for Optimization

Their papers

• Line search methods with variable sample size for unconstrained optimization (2013) — 26 citations
• Subsampled inexact Newton methods for minimizing large sums of convex functions (2018) — 31 citations