Ajit Singh

Management Science and Operations Research · with Agarwal · 2013

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom Ajit Singh trusts overall

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

  1. J. Langford
  2. Peter Auer

Who trusts Ajit Singh overall

  1. Lihong Li
  2. Daniel Russo

Papers from Ajit Singh's perspective

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

  1. Reinforcement Learning: An Introduction
  2. Finite-time Analysis of the Multiarmed Bandit Problem
  3. Exploration scavenging
  4. The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information
  5. Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms
  6. Predicting clicks: estimating the click-through rate for new ads (The Web Conference)
  7. Exploration-exploitation tradeoff using variance estimates in multi-armed bandits
  8. Web-Scale Bayesian Click-Through rate Prediction for Sponsored Search Advertising in Microsoft's Bing Search Engine
  9. Multi-armed Bandit Algorithms and Empirical Evaluation
  10. Ad click prediction: a view from the trenches

Their papers