Aditya Gopalan
Artificial Intelligence · 2014–2018
A researcher in the Science corpus: 5 papers; trusts 66 researchers and is trusted by 17 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 38 citations into it; #8,920 of 35,345 by trust here, #21,878 by citations
- Management Science and Operations Research — 38 citations into it; #2,101 of 11,946 by trust here, #5,548 by citations
- Reinforcement Learning — 34 citations into it; #1,093 of 2,242 by trust here, #1,973 by citations
- Computer Networks and Communications — 15 citations into it
- Statistical Learning Theory — 8 citations into it
- Statistics and Probability — 8 citations into it
- Electrical and Electronic Engineering — 5 citations into it; #3,914 of 16,539 by trust here, #13,165 by citations
- Optimization & Training — 5 citations into it
Whom Aditya Gopalan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Gábor Lugosi
- Peter L. Bartlett
- Ambuj Tewari
- Yisong Yue
- Ronen I. Brafman
- Apostolos N. Burnetas
- Xiaotong Shen
- Taeryon Choi
- Emilie Kaufmann
- Ian Osband
Who trusts Aditya Gopalan overall
- Aadirupa Saha
- Aldo Pacchiano
- Tor Lattimore
- Huasen Wu
- Ben M. Hambly
- Yonathan Efroni
- Ian Osband
- Csaba Szepesvari
- Suprovat Ghoshal
- Lin F. Yang
Papers from Aditya Gopalan's perspective
Ordered by how strongly the researchers Aditya Gopalan 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
- Reinforcement Learning: An Introduction
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Human-level control through deep reinforcement learning
Their papers
- PAC Battling Bandits in the Plackett-Luce Model (2018) — 40 citations
- Active Ranking with Subset-wise Preferences (2018) — 31 citations
- On Kernelized Multi-armed Bandits (2017) — 581 citations
- Battle of Bandits (2018) — 48 citations
- Thompson Sampling for Learning Parameterized Markov Decision Processes (2014) — 125 citations