Jinyang Li
Artificial Intelligence · ACM/IEEE International Conference on Mobile Computing and Networking · 2000–2020
A researcher in the Science corpus: 14 papers; trusts 182 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 123 citations into it
- Computer Networks and Communications — 81 citations into it; #3,236 of 9,886 by trust here, #578 by citations
- Computer Vision and Pattern Recognition — 72 citations into it
- Graph Learning — 47 citations into it
- Information Systems — 34 citations into it
- Model Architectures — 32 citations into it
- Hardware and Architecture — 30 citations into it
- Efficiency & Compression — 27 citations into it
Whom Jinyang Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Ilya Sutskever
- Thomas Hofmann
- Brad Karp
- Geoffrey E. Hinton
- Yoshua Bengio
- Sepp Hochreiter
- Muthu Dayalan
- Oriol Vinyals
- Kaiming He
Who trusts Jinyang Li overall
- Ivan Stojmenovic
- Sylvia Ratnasamy
- Jean-Pierre Hubaux
- Silvia Giordano
- Fabian Kuhn
- Henggang Cui
- Eiman Mohammed Alotaibi
- Andrei Z. Broder
- Lei Chen
- Brad Karp
Papers from Jinyang Li's perspective
Ordered by how strongly the researchers Jinyang Li trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
Their papers
- Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs (2019) — 884 citations
- Supporting Very Large Models using Automatic Dataflow Graph Partitioning (2018) — 175 citations
- SwapAdvisor: Pushing Deep Learning Beyond the GPU Memory Limit via Smart Swapping (2020) — 233 citations
- A scalable location service for geographic ad hoc routing (2000) — 1,887 citations
- CarNet: a scalable ad hoc wireless network system (2000) — 314 citations
- Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks. (2019) — 1,357 citations
- Low latency RNN inference with cellular batching (2018) — 103 citations
- Using One-Sided RDMA Reads to Build a Fast, CPU-Efficient Key-Value Store (2013) — 456 citations
- Transactional storage for geo-replicated systems (2011) — 426 citations
- Piccolo: Building Fast, Distributed Programs with Partitioned Tables (2010) — 311 citations
- Sybil-Resilient Online Content Voting (2009) — 340 citations
- Designing a DHT for Low Latency and High Throughput (2004) — 432 citations
- On the Feasibility of Peer-to-Peer Web Indexing and Search (2003) — 377 citations
- Capacity of Ad Hoc wireless networks (2001) — 1,902 citations