Jan Vondr'ak

Computational Theory and Mathematics · 2004–2018

A researcher in the Science corpus: 12 papers; trusts 64 researchers and is trusted by 62 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 48 citations into it; #263 of 12,182 by trust here, #578 by citations
• Artificial Intelligence — 37 citations into it; #3,373 of 35,345 by trust here, #8,619 by citations
• Optimization & Training — 30 citations into it; #1,515 of 2,601 by trust here, #1,866 by citations
• Computer Graphics and Computer-Aided Design — 19 citations into it; #167 of 1,584 by trust here, #388 by citations
• Computer Networks and Communications — 16 citations into it; #645 of 9,886 by trust here, #2,539 by citations
• Algorithms & Complexity — 15 citations into it
• Management Science and Operations Research — 15 citations into it
• Statistics and Probability — 10 citations into it

Whom Jan Vondr'ak trusts overall

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

1. Uriel Feige
2. Maxim Sviridenko
3. George L. Nemhauser
4. Alexander Schrijver
5. Alexander A. Ageev
6. Michael P. Cummings
7. Laurence A. Wolsey
8. Gruia Calinescu
9. Chandra Chekuri
10. Lisa Fleischer

Who trusts Jan Vondr'ak overall

1. Moran Feldman
2. Ashwinkumar Badanidiyuru
3. Aranyak Mehta
4. Jan Vondr
5. Shayan Oveis Gharan
6. Vahab S. Mirrokni
7. Alex Kulesza
8. Andreas Krause
9. Joseph (Seffi) Naor
10. Chandra Chekuri

Papers from Jan Vondr'ak's perspective

Ordered by how strongly the researchers Jan Vondr'ak trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. A threshold of ln n for approximating set cover (preliminary version)
4. An analysis of approximations for maximizing submodular set functions—I
5. Learning Multiple Layers of Features from Tiny Images
6. Gradient-based learning applied to document recognition
7. Submodular functions and convexity
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. Long Short-Term Memory

Their papers

• Lazier Than Lazy Greedy (2014) — 472 citations
• Generalization Bounds for Uniformly Stable Algorithms (2018) — 105 citations
• Maximizing Non-Monotone Submodular Functions (2011) — 710 citations
• Maximizing a Submodular Set Function Subject to a Matroid Constraint (Extended Abstract) (2007) — 478 citations
• Optimal approximation for the submodular welfare problem in the value oracle model (2008) — 613 citations
• Maximizing a Monotone Submodular Function Subject to a Matroid Constraint (2011) — 919 citations
• Submodular function maximization via the multilinear relaxation and contention resolution schemes (2011) — 394 citations
• Submodular maximization by simulated annealing (2010) — 191 citations
• Fast algorithms for maximizing submodular functions (2014) — 347 citations
• Optimal approximation for submodular and supermodular optimization with bounded curvature (2013) — 292 citations
• The taxonomy of the Caloplaca citrina group (Teloschistaceae) in the Black Sea region; with contributions to the cryptic species concept in lichenology (2009) — 113 citations
• Approximating the stochastic knapsack problem: the benefit of adaptivity (2004) — 400 citations