C. Dovrolis
Artificial Intelligence · 2001–2022
A researcher in the Science corpus: 11 papers; trusts 252 researchers and is trusted by 13 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 97 citations into it
- Computer Vision and Pattern Recognition — 75 citations into it; #15,743 of 21,575 by trust here, #11,950 by citations
- Representation & Self-Supervised Learning — 44 citations into it
- Meta & Continual Learning — 24 citations into it
- Computer Networks and Communications — 22 citations into it; #2,663 of 9,886 by trust here, #1,992 by citations
- Cognitive Neuroscience — 21 citations into it
- Cellular and Molecular Neuroscience — 18 citations into it
- Electrical and Electronic Engineering — 17 citations into it
Whom C. Dovrolis trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Alex Krizhevsky
- Yann LeCun
- Arslan Chaudhry
- Marc'Aurelio Ranzato
- Kaiming He
- Matthew D. Zeiler
- Ilya Sutskever
Who trusts C. Dovrolis overall
- Ningning Hu
- Manish Jain
- Peter Steenkiste
- R. Venkatesha Prasad
- Aleksandar Kuzmanovic
- Gregor Maier
- Junxian Huang
- Yunhong Gu
- Yang Guo
- James Smith
Papers from C. Dovrolis's perspective
Ordered by how strongly the researchers C. Dovrolis 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
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Bandwidth estimation: metrics, measurement techniques, and tools (2003) — 901 citations
- End-to-end available bandwidth: measurement methodology, dynamics, and relation with TCP throughput (2002) — 486 citations
- NISPA: Neuro-Inspired Stability-Plasticity Adaptation for Continual Learning in Sparse Networks (2022) — 57 citations
- Unsupervised Progressive Learning and the STAM Architecture (2019) — 41 citations
- Unsupervised Continual Learning and Self-Taught Associative Memory Hierarchies (2019) — 12 citations
- What happens when HTTP adaptive streaming players compete for bandwidth? (2012) — 352 citations
- An experimental evaluation of rate-adaptation algorithms in adaptive streaming over HTTP (2011) — 680 citations
- Packet-dispersion techniques and a capacity-estimation methodology (2004) — 378 citations
- Passive estimation of TCP round-trip times (2002) — 359 citations
- Pathload: A Measurement Tool for End-to-End Available Bandwidth (2002) — 497 citations
- What do packet dispersion techniques measure? (2001) — 681 citations