Subhash Khot
Computational Theory and Mathematics · 2002–2011
A researcher in the Science corpus: 8 papers; trusts 25 researchers and is trusted by 41 researchers here, as inferred from the citation graph.
Subfields
- Computational Theory and Mathematics — 23 citations into it; #515 of 12,182 by trust here, #777 by citations
- Artificial Intelligence — 17 citations into it; #4,331 of 35,345 by trust here, #10,566 by citations
- Discrete Mathematics and Combinatorics — 7 citations into it
- Optimization & Training — 7 citations into it
- Computer Graphics and Computer-Aided Design — 5 citations into it; #977 of 1,584 by trust here, #605 by citations
- Geometry and Topology — 5 citations into it
- Statistical Learning Theory — 5 citations into it
Whom Subhash Khot trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Sanjeev Arora
- Elchanan Mossel
- J. Håstad
- Jean Bourgain
- Uriel Feige
- Shmuel Safra
- Michel X. Goemans
- Guy Kindler
- N. Linial
- Irit Dinur
Who trusts Subhash Khot overall
- Prasad Raghavendra
- Elchanan Mossel
- Oded Goldreich
- Irit Dinur
- Guy Kindler
- Jochen Könemann
- Vitaly Feldman
- Nisheeth K. Vishnoi
- Ryan O'Donnell
- Per Austrin
Papers from Subhash Khot's perspective
Ordered by how strongly the researchers Subhash Khot 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)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Long Short-Term Memory
Their papers
- On Agnostic Learning of Parities, Monomials, and Halfspaces (2009) — 96 citations
- Ruling out PTAS for graph min-bisection, densest subgraph and bipartite clique (2004) — 369 citations
- Optimal inapproximability results for MAX-CUT and other 2-variable CSPs? (2004) — 885 citations
- On the power of unique 2-prover 1-round games (2002) — 1,061 citations
- The unique games conjecture, integrality gap for cut problems and embeddability of negative type metrics into l/sub 1/ (2005) — 322 citations
- Vertex cover might be hard to approximate to within 2-/spl epsiv/ (2003) — 637 citations
- Inapproximability of NP-complete Problems, Discrete Fourier Analysis, and Geometry (2011) — 48 citations
- The Unique Games Conjecture, Integrality Gap for Cut Problems and Embeddability of Negative Type Metrics into 1 (Extended Abstract) (2005) — 130 citations