Radha Poovendran
Artificial Intelligence · 2004–2024
A researcher in the Science corpus: 12 papers; trusts 313 researchers and is trusted by 29 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 173 citations into it; #11,386 of 35,345 by trust here, #8,810 by citations
- Safety, Robustness & Interpretability — 74 citations into it; #777 of 2,251 by trust here, #910 by citations
- Computer Networks and Communications — 66 citations into it; #2,223 of 9,886 by trust here, #2,927 by citations
- Computer Vision and Pattern Recognition — 64 citations into it; #16,585 of 21,575 by trust here, #13,815 by citations
- Electrical and Electronic Engineering — 40 citations into it; #2,677 of 16,539 by trust here, #8,038 by citations
- Reinforcement Learning — 31 citations into it
- Signal Processing — 26 citations into it; #4,206 of 7,572 by trust here, #2,001 by citations
- Evaluation & Benchmarks — 18 citations into it
Whom Radha Poovendran trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Ian J. Goodfellow
- Geoffrey E. Hinton
- Karen Simonyan
- Christian Szegedy
- Yoshua Bengio
- Yann LeCun
- Ilya Sutskever
- Srdjan Čapkun
- Diederik P. Kingma
Who trusts Radha Poovendran overall
- Jennifer Yick
- Jean-Pierre Hubaux
- Donggang Liu
- Vaishaal Shankar
- Xiangqian Chen
- Dan Hendrycks
- Biswanath Mukherjee
- Bryan Parno
- Joni O. Salminen
- Neel Jain
Papers from Radha Poovendran's perspective
Ordered by how strongly the researchers Radha Poovendran 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)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Google's Cloud Vision API is Not Robust to Noise (2017) — 133 citations
- Deceiving Google's Perspective API Built for Detecting Toxic Comments (2017) — 369 citations
- Semantic Adversarial Examples (2018) — 219 citations
- Assessing Shape Bias Property of Convolutional Neural Networks (2018) — 40 citations
- SeRLoc: secure range-independent localization for wireless sensor networks (2004) — 529 citations
- AMOEBA: Robust Location Privacy Scheme for VANET (2007) — 426 citations
- ROPE: robust position estimation in wireless sensor networks (2005) — 301 citations
- Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing (2024) — 357 citations
- FRESH: Interactive Reward Shaping in High-Dimensional State Spaces using Human Feedback (2020) — 28 citations
- Attacking Automatic Video Analysis Algorithms: A Case Study of Google Cloud Video Intelligence API (2017) — 25 citations
- Optimal Jamming Attacks and Network Defense Policies in Wireless Sensor Networks (2007) — 309 citations
- CARAVAN: Providing Location Privacy for VANET (2005) — 474 citations