Pradeep K. Dubey
Artificial Intelligence · 2001–2022
A researcher in the Science corpus: 19 papers; trusts 148 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 125 citations into it; #15,511 of 35,345 by trust here, #7,413 by citations
- Computer Vision and Pattern Recognition — 115 citations into it; #10,023 of 21,575 by trust here, #4,555 by citations
- Efficiency & Compression — 58 citations into it; #1,187 of 1,264 by trust here, #673 by citations
- Natural Language Processing — 38 citations into it
- Optimization & Training — 36 citations into it
- Computer Networks and Communications — 35 citations into it
- Hardware and Architecture — 35 citations into it
- Model Architectures — 23 citations into it
Whom Pradeep K. Dubey trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Tomas Mikolov
- Yoshua Bengio
- Geoffrey E. Hinton
- Ilya Sutskever
- Alex Krizhevsky
- Kaiming He
- Yann LeCun
- Diederik P. Kingma
- Alex Graves
- Ruslan Salakhutdinov
Who trusts Pradeep K. Dubey overall
Papers from Pradeep K. Dubey's perspective
Ordered by how strongly the researchers Pradeep K. Dubey 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)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- 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)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- BlackOut: Speeding up Recurrent Neural Network Language Models With Very Large Vocabularies (2015) — 77 citations
- Ternary Neural Networks with Fine-Grained Quantization (2017) — 112 citations
- A Study of BFLOAT16 for Deep Learning Training (2019) — 492 citations
- Faster CNNs with Direct Sparse Convolutions and Guided Pruning (2016) — 189 citations
- Mixed Precision Training of Convolutional Neural Networks using Integer Operations (2018) — 169 citations
- FP8 Formats for Deep Learning (2022) — 285 citations
- 3.5-D Blocking Optimization for Stencil Computations on Modern CPUs and GPUs (2010) — 315 citations
- Parallelizing Word2Vec in Shared and Distributed Memory (2016) — 72 citations
- FAST: fast architecture sensitive tree search on modern CPUs and GPUs (2010) — 358 citations
- Efficient implementation of sorting on multi-core SIMD CPU architecture (2008) — 261 citations
- MISIM: An End-to-End Neural Code Similarity System (2020) — 24 citations
- SysML: The New Frontier of Machine Learning Systems (2019) — 23 citations
- MLSys: The New Frontier of Machine Learning Systems (2019) — 25 citations
- GraphMat: High performance graph analytics made productive (2015) — 344 citations
- Navigating the maze of graph analytics frameworks using massive graph datasets (2014) — 202 citations
- Debunking the 100X GPU vs. CPU myth: an evaluation of throughput computing on CPU and GPU (2010) — 854 citations
- Sort vs. Hash Revisited: Fast Join Implementation on Modern Multi-Core CPUs (2009) — 327 citations
- Larrabee: a many-core x86 architecture for visual computing (2008) — 878 citations
- Efficient Rijndael Encryption Implementation with Composite Field Arithmetic (2001) — 312 citations