Anant Sahai
Computer Networks and Communications · 2004–2020
A researcher in the Science corpus: 10 papers; trusts 25 researchers and is trusted by 57 researchers here, as inferred from the citation graph.
Subfields
- Computer Networks and Communications — 35 citations into it; #577 of 9,886 by trust here, #925 by citations
- Electrical and Electronic Engineering — 32 citations into it; #392 of 16,539 by trust here, #3,639 by citations
- Artificial Intelligence — 28 citations into it
- Scaling & Learning Theory — 24 citations into it
- Statistics and Probability — 20 citations into it
- Computational Mechanics — 17 citations into it
- Statistical Learning Theory — 14 citations into it
- Control and Systems Engineering — 11 citations into it; #7,000 of 8,257 by trust here, #6,083 by citations
Whom Anant Sahai trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Sekhar Chandra Tatikonda
- Sanjoy K. Mitter
- Nicola Elia
- L. Varshney
- Dimitri P. Bertsekas
- Bruno Sinopoli
- Rahul Tandra
- Vladimir Naumovich Vapnik
- Roman Vershynin
- Peter L. Bartlett
Who trusts Anant Sahai overall
- Wei Zhang
- Yonghong Zeng
- Ying-Chang Liang
- Khaled Ben Letaief
- Ian F. Akyildiz
- Rui Zhang
- Rahul Tandra
- Jun Ma
- Geoffrey Y. Li
- Shridhar Mubaraq Mishra
Papers from Anant Sahai's perspective
Ordered by how strongly the researchers Anant Sahai trusts endorse each paper. Same corpus, a different order for every researcher.
- Information Theory: 1948-1998 - Guest Editorial
- 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)
- Learning Multiple Layers of Features from Tiny Images
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Understanding deep learning requires rethinking generalization
- Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
Their papers
- Classification vs regression in overparameterized regimes: Does the loss function matter? (2020) — 172 citations
- Harmless interpolation of noisy data in regression (2019) — 213 citations
- Shannon meets Tesla: Wireless information and power transfer (2010) — 1,067 citations
- SNR Walls for Signal Detection (2008) — 1,622 citations
- Cooperative Sensing among Cognitive Radios (2006) — 1,608 citations
- Fundamental limits on detection in low SNR under noise uncertainty (2005) — 674 citations
- What is a Spectrum Hole and What Does it Take to Recognize One? (2009) — 516 citations
- The Necessity and Sufficiency of Anytime Capacity for Stabilization of a Linear System Over a Noisy Communication Link—Part I: Scalar Systems (2006) — 438 citations
- Some Fundamental Limits on Cognitive Radio (2004) — 754 citations
- Stochastic linear control over a communication channel (2004) — 447 citations