Sanjay Shakkottai
Computer Networks and Communications · 2000–2021
A researcher in the Science corpus: 13 papers; trusts 65 researchers and is trusted by 19 researchers here, as inferred from the citation graph.
Subfields
- Computer Networks and Communications — 77 citations into it; #2,156 of 9,886 by trust here, #1,912 by citations
- Artificial Intelligence — 71 citations into it
- Electrical and Electronic Engineering — 54 citations into it; #3,041 of 16,539 by trust here, #6,291 by citations
- Management Science and Operations Research — 24 citations into it
- Federated & Distributed Learning — 16 citations into it
- Optimization & Training — 15 citations into it
- Computational Theory and Mathematics — 14 citations into it
- Computational Mechanics — 10 citations into it
Whom Sanjay Shakkottai trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alexander L. Stolyar
- Sean P. Meyn
- Tom Kelly
- Thomas Bonald
- Rayadurgam Srikant
- Laurent Massoulié
- Douglas J. Leith
- Steven H. Low
- Frank P. Kelly
- Kirthevasan Kandasamy
Who trusts Sanjay Shakkottai overall
- Xiaojun Lin
- Iordanis Koutsopoulos
- Ness B. Shroff
- Xin Liu
- Atilla Eryilmaz
- Alexander L. Stolyar
- D. P. Palomar
- Angelia Nedić
- Qingwen Liu
- Mihaela van der Schaar
Papers from Sanjay Shakkottai's perspective
Ordered by how strongly the researchers Sanjay Shakkottai trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Going deeper with convolutions
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Identifying Best Interventions through Online Importance Sampling (2017) — 82 citations
- Exploiting Shared Representations for Personalized Federated Learning (2021) — 1,173 citations
- Contextual Bandits with Latent Confounders: An NMF Approach (2016) — 50 citations
- FlashLinQ: A Synchronous Distributed Scheduler for Peer-to-Peer Ad Hoc Networks (2013) — 431 citations
- Joint Scheduling of URLLC and eMBB Traffic in 5G Wireless Networks (2017) — 387 citations
- Scheduling algorithms for a mixture of real-time and non-real-time data in HDR (2001) — 431 citations
- Network Optimization and Control (2008) — 337 citations
- Cross-layer design for wireless networks (2003) — 578 citations
- Multi-Fidelity Black-Box Optimization with Hierarchical Partitions (2018) — 58 citations
- Multi-Path TCP: A Joint Congestion Control and Routing Scheme to Exploit Path Diversity in the Internet (2006) — 438 citations
- Hop-by-Hop Congestion Control Over a Wireless Multi-Hop Network (2004) — 296 citations
- Unreliable sensor grids: coverage, connectivity and diameter (2003) — 685 citations
- Scheduling for multiple flows sharing a time-varying channel: the exponential rule (2000) — 380 citations