Aranyak Mehta
Computer Networks and Communications · 2003–2013
A researcher in the Science corpus: 5 papers; trusts 35 researchers and is trusted by 20 researchers here, as inferred from the citation graph.
Subfields
- Computer Networks and Communications — 19 citations into it; #2,915 of 9,886 by trust here, #3,993 by citations
- Management Science and Operations Research — 17 citations into it; #2,845 of 11,946 by trust here, #2,799 by citations
- Computational Theory and Mathematics — 6 citations into it; #5,174 of 12,182 by trust here, #8,756 by citations
- Economics and Econometrics — 6 citations into it; #16,599 of 23,481 by trust here, #15,581 by citations
- Game & Decision Theory — 6 citations into it; #192 of 249 by trust here, #186 by citations
- Marketing — 6 citations into it
- Algorithms & Complexity — 5 citations into it
- Artificial Intelligence — 5 citations into it; #18,306 of 35,345 by trust here, #32,362 by citations
Whom Aranyak Mehta trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Niv Buchbinder
- Kamal Kumar Jain
- Mohammad Mahdian
- Jan Vondr'ak
- Yoav Freund
- Gagan Goel
- Nikhil R. Devanur
- Chandra Chekuri
- Sanjeev Arora
- Atila Abdulkadiroglu
Who trusts Aranyak Mehta overall
- Mohammad Mahdian
- Niv Buchbinder
- Martin Mladenov
- Nikhil R. Devanur
- Qiqi Yan
- Benjamin E. Birnbaum
- Isabelle Stanton
- Kamal Kumar Jain
- Yongxin Tong
- Paul Dütting
Papers from Aranyak Mehta's perspective
Ordered by how strongly the researchers Aranyak Mehta trusts endorse each paper. Same corpus, a different order for every researcher.
- Online Primal-Dual Algorithms for Maximizing Ad-Auctions Revenue (Embedded Systems and Applications)
- AdWords and generalized on-line matching (IEEE Annual Symposium on Foundations of Computer Science)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- A Polynomial Time Approximation Scheme for the Multiple Knapsack Problem (SIAM journal on computing (Print))
- Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
- A new greedy approach for facility location problems
Their papers
- Online Matching and Ad Allocation (2013) — 489 citations
- Playing large games using simple strategies (2003) — 440 citations
- Online Stochastic Matching: Beating 1-1/e (2009) — 370 citations
- AdWords and generalized on-line matching (2005) — 944 citations
- Online budgeted matching in random input models with applications to Adwords (2008) — 357 citations