Sanjay Krishnan

Artificial Intelligence · 2014–2019

A researcher in the Science corpus: 23 papers; trusts 177 researchers and is trusted by 59 researchers here, as inferred from the citation graph.

Subfields

Artificial Intelligence — 260 citations into it; #3,440 of 35,345 by trust here, #2,822 by citations
Management Science and Operations Research — 120 citations into it; #1,414 of 11,946 by trust here, #646 by citations
Reinforcement Learning — 96 citations into it
Computer Networks and Communications — 72 citations into it
Information Systems — 54 citations into it
Computer Vision and Pattern Recognition — 52 citations into it; #7,691 of 21,575 by trust here, #5,565 by citations
Computer Science Applications — 43 citations into it; #1,765 of 1,855 by trust here, #1,276 by citations
Control and Systems Engineering — 43 citations into it; #8,058 of 8,257 by trust here, #1,943 by citations

Whom Sanjay Krishnan trusts overall

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

Who trusts Sanjay Krishnan overall

Papers from Sanjay Krishnan's perspective

Ordered by how strongly the researchers Sanjay Krishnan 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
Learning Multiple Layers of Features from Tiny Images
Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Going deeper with convolutions

Their papers

Multi-Level Discovery of Deep Options (2017) — 132 citations
DDCO: Discovery of Deep Continuous Options for Robot Learning from Demonstrations (2017) — 89 citations
Communication-Efficient Distributed Dual Coordinate Ascent (2014) — 363 citations
SWIRL: A sequential windowed inverse reinforcement learning algorithm for robot tasks with delayed rewards (2018) — 77 citations
Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations (2016) — 80 citations
Learning to Optimize Join Queries With Deep Reinforcement Learning (2018) — 250 citations
A sample-and-clean framework for fast and accurate query processing on dirty data (2014) — 127 citations
Data Cleaning: Overview and Emerging Challenges (2016) — 559 citations
Composing Meta-Policies for Autonomous Driving Using Hierarchical Deep Reinforcement Learning (2017) — 26 citations
ActiveClean: Interactive Data Cleaning For Statistical Modeling (2016) — 282 citations
Stale View Cleaning: Getting Fresh Answers from Stale Materialized Views (2015) — 28 citations
Wisteria: Nurturing Scalable Data Cleaning Infrastructure (2015) — 43 citations
ActiveClean: Interactive Data Cleaning While Learning Convex Loss Models (2016) — 29 citations
Towards reliable interactive data cleaning: a user survey and recommendations (2016) — 72 citations
Learning accurate kinematic control of cable-driven surgical robots using data cleaning and Gaussian Process Regression (2014) — 84 citations
ActiveClean: An Interactive Data Cleaning Framework For Modern Machine Learning (2016) — 71 citations
Multilateral surgical pattern cutting in 2D orthotropic gauze with deep reinforcement learning policies for tensioning (2017) — 147 citations
AlphaClean: Automatic Generation of Data Cleaning Pipelines (2019) — 61 citations
PALM: Machine Learning Explanations For Iterative Debugging (2017) — 86 citations
BoostClean: Automated Error Detection and Repair for Machine Learning (2017) — 116 citations