6 papers:
ICML-2015-KomiyamaHN #analysis #multi #probability #problem- Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays (JK, JH, HN), pp. 1152–1161.
KDD-2015-IkonomovskaJD #predict #realtime #using- Real-Time Bid Prediction using Thompson Sampling-Based Expert Selection (EI, SJ, AD), pp. 1869–1878.
SAC-2015-HsiehNKC #approximate #performance #query #recommendation- Efficient approximate thompson sampling for search query recommendation (CCH, JN, TK, JC), pp. 740–746.
- ICML-c1-2014-GopalanMM #online #problem
- Thompson Sampling for Complex Online Problems (AG, SM, YM), pp. 100–108.
- ICML-c3-2013-AgrawalG #linear
- Thompson Sampling for Contextual Bandits with Linear Payoffs (SA, NG), pp. 127–135.
WIA-1999-GiammarresiPW #graph- Thompson Digraphs: A Characterization (DG, JLP, DW), pp. 91–100.
