Peter James Stuckey
Artificial Intelligence · 2006–2020
A researcher in the Science corpus: 11 papers; trusts 69 researchers and is trusted by 16 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 118 citations into it; #13,046 of 35,345 by trust here, #22,463 by citations
- Computational Theory and Mathematics — 52 citations into it
- Algorithms & Complexity — 38 citations into it
- Information Systems — 34 citations into it; #5,733 of 8,771 by trust here, #8,258 by citations
- Statistical Learning Theory — 23 citations into it
- Computer Networks and Communications — 18 citations into it; #6,467 of 9,886 by trust here, #6,788 by citations
- Optimization & Training — 16 citations into it
- Safety, Robustness & Interpretability — 15 citations into it
Whom Peter James Stuckey trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alexey Ignatiev
- Siegfried Nijssen
- Nina Narodytska
- Florent Avellaneda
- Sicco Verwer
- Peter Clark
- Leo Breiman
- Gaël Aglin
- R. Rivest
- Cynthia Rudin
Who trusts Peter James Stuckey overall
- Vinícius G. Costa
- Hao Hu
- Emilio Carrizosa
- Erik S. Wright
- Carlos Eduardo Pedreira
- Mohamed Siala
- W. Sheng
- Hitomi Hasegawa
Papers from Peter James Stuckey's perspective
Ordered by how strongly the researchers Peter James Stuckey 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)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Human-level control through deep reinforcement learning
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Et al
Their papers
- MUSTANG: A multiple structural alignment algorithm (2006) — 718 citations
- Core-Boosted Linear Search for Incomplete MaxSAT (2019) — 61 citations
- Optimal Decision Trees for Nonlinear Metrics (2020) — 31 citations
- MurTree: Optimal Decision Trees via Dynamic Programming and Search (2020) — 89 citations
- Optimal Decision Lists using SAT (2020) — 10 citations
- MurTree: Optimal Classification Trees via Dynamic Programming and Search (2020) — 19 citations
- Computing Optimal Decision Sets with SAT (2020) — 29 citations
- Techniques Inspired by Local Search for Incomplete MaxSAT and the Linear Algorithm: Varying Resolution and Solution-Guided Search (2019) — 17 citations
- Searching with Consistent Prioritization for Multi-Agent Path Finding (2018) — 301 citations
- MUSTANG-MR Structural Sieving Server: Applications in Protein Structural Analysis and Crystallography (2010) — 52 citations
- MiniZinc: Towards a Standard CP Modelling Language (2007) — 994 citations