Haixun Wang
Computer Networks and Communications · 2000–2014
A researcher in the Science corpus: 14 papers; trusts 54 researchers and is trusted by 43 researchers here, as inferred from the citation graph.
Subfields
- Computer Networks and Communications — 90 citations into it; #1,284 of 9,886 by trust here, #891 by citations
- Artificial Intelligence — 82 citations into it; #6,464 of 35,345 by trust here, #4,979 by citations
- Information Systems — 75 citations into it; #3,617 of 8,771 by trust here, #2,406 by citations
- Signal Processing — 63 citations into it; #3,147 of 7,572 by trust here, #1,388 by citations
- Statistical and Nonlinear Physics — 62 citations into it; #6,415 of 10,127 by trust here, #4,633 by citations
- Computer Vision and Pattern Recognition — 33 citations into it; #12,738 of 21,575 by trust here, #9,187 by citations
- Computational Theory and Mathematics — 21 citations into it
- Algorithms & Complexity — 11 citations into it
Whom Haixun Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Mark Newman
- William W. Cohen
- Vagelis Hristidis
- Pedro M. Domingos
- Yizong Cheng
- Geoff Hulten
- Yoav Freund
- Charu C. Aggarwal
- Steven L. Salzberg
- Sanjay Agrawal
Who trusts Haixun Wang overall
- Ludmila I. Kuncheva
- Tak-Chung Fu
- Alexey Tsymbal
- Stanislav Busygin
- Yixiang Fang
- Jiawei Han
- Stephen Coggeshall
- Tyler L. Hayes
- Charu C. Aggarwal
- Rui Xu
Papers from Haixun Wang's perspective
Ordered by how strongly the researchers Haixun Wang 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Probase: a probabilistic taxonomy for text understanding (2012) — 890 citations
- Moment: maintaining closed frequent itemsets over a stream sliding window (2004) — 362 citations
- Enhanced biclustering on expression data (2003) — 341 citations
- Local search of communities in large graphs (2014) — 313 citations
- A Distributed Graph Engine for Web Scale RDF Data (2013) — 346 citations
- Trinity: a distributed graph engine on a memory cloud (2013) — 483 citations
- Efficient Subgraph Matching on Billion Node Graphs (2012) — 425 citations
- Managing and Mining Graph Data (2010) — 565 citations
- BLINKS: ranked keyword searches on graphs (2007) — 651 citations
- ViST: a dynamic index method for querying XML data by tree structures (2003) — 339 citations
- Mining concept-drifting data streams using ensemble classifiers (2003) — 1,530 citations
- Clustering by pattern similarity in large data sets (2002) — 581 citations
- /spl delta/-clusters: capturing subspace correlation in a large data set (2002) — 365 citations
- Landmarks: a new model for similarity-based pattern querying in time series databases (2000) — 317 citations