M. Musuvathi

Artificial Intelligence · 2004–2018

A researcher in the Science corpus: 4 papers; trusts 11 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 24 citations into it; #30,837 of 35,345 by trust here, #25,809 by citations
• Computational Theory and Mathematics — 15 citations into it; #7,484 of 12,182 by trust here, #8,756 by citations
• Optimization & Training — 9 citations into it
• Hardware and Architecture — 6 citations into it; #801 of 1,551 by trust here, #1,220 by citations
• Software — 6 citations into it; #517 of 1,227 by trust here, #602 by citations

Whom M. Musuvathi trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Cormac Flanagan
2. Shaz Qadeer
3. Dimitris Achlioptas
4. Stephen N. Freund
5. Dinghao Wu
6. Patrice Godefroid
7. William B. Johnson
8. John C. Duchi
9. B. Recht
10. Alekh Agarwal

Who trusts M. Musuvathi overall

1. Claire Le Goues
2. Koushik Sen
3. Thanhvu Nguyen
4. Ranjit Jhala
5. Stephanie Forrest

Papers from M. Musuvathi's perspective

Ordered by how strongly the researchers M. Musuvathi trusts endorse each paper. Same corpus, a different order for every researcher.

1. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
2. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. Gradient-based learning applied to document recognition
6. Learning Multiple Layers of Features from Tiny Images
7. Extended static checking for Java (ACM-SIGPLAN Symposium on Programming Language Design and Implementation)
8. Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
9. Type-based race detection for Java (ACM-SIGPLAN Symposium on Programming Language Design and Implementation)
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• Iterative context bounding for systematic testing of multithreaded programs (2007) — 503 citations
• CHET: Compiler and Runtime for Homomorphic Evaluation of Tensor Programs (2018) — 14 citations
• Semantics-Preserving Parallelization of Stochastic Gradient Descent (2018) — 6 citations
• Using model checking to find serious file system errors (2004) — 379 citations