Indranil Gupta
Artificial Intelligence · with Koyejo · 2003–2020
A researcher in the Science corpus: 12 papers; trusts 192 researchers and is trusted by 42 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 145 citations into it; #5,355 of 35,345 by trust here, #7,657 by citations
- Optimization & Training — 111 citations into it; #703 of 2,601 by trust here, #843 by citations
- Computer Vision and Pattern Recognition — 66 citations into it
- Computer Networks and Communications — 52 citations into it; #1,396 of 9,886 by trust here, #2,196 by citations
- Federated & Distributed Learning — 52 citations into it; #76 of 319 by trust here, #158 by citations
- ML Systems & Hardware — 51 citations into it; #160 of 575 by trust here, #312 by citations
- Safety, Robustness & Interpretability — 31 citations into it
- Efficiency & Compression — 27 citations into it
Whom Indranil Gupta trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Mu Li
- Lili Su
- Cong Xie
- Sebastian U. Stich
- Yudong Chen
- H. Brendan McMahan
- Geoffrey E. Hinton
- D. Andersen
- Alex Smola
Who trusts Indranil Gupta overall
- Cong Xie
- Oluwasanmi Koyejo
- John Risson
- Xinyang Cao
- Lie He
- Sai Praneeth Karimireddy
- Frank Dabek
- Shashank Rajput
- Chen Chen
- Virat Shejwalkar
Papers from Indranil Gupta's perspective
Ordered by how strongly the researchers Indranil Gupta trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- CSER: Communication-efficient SGD with Error Reset (2020) — 48 citations
- Practical Distributed Learning: Secure Machine Learning with Communication-Efficient Local Updates (2019) — 14 citations
- Zeno++: Robust Fully Asynchronous SGD (2019) — 142 citations
- Local AdaAlter: Communication-Efficient Stochastic Gradient Descent with Adaptive Learning Rates (2019) — 46 citations
- Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation (2019) — 358 citations
- Asynchronous Federated Optimization (2019) — 771 citations
- SLSGD: Secure and Efficient Distributed On-device Machine Learning (2019) — 62 citations
- Zeno: Distributed Stochastic Gradient Descent with Suspicion-based Fault-tolerance (2018) — 324 citations
- Phocas: dimensional Byzantine-resilient stochastic gradient descent (2018) — 62 citations
- Generalized Byzantine-tolerant SGD (2018) — 304 citations
- Zeno: Byzantine-suspicious stochastic gradient descent (2018) — 48 citations
- Kelips: Building an Efficient and Stable P2P DHT through Increased Memory and Background Overhead (2003) — 353 citations