Ramesh Johari
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| title | conference | date |
|---|---|---|
| Learning Preferences with Latent State | Agency in Collaborative Learning 2026 | 2026-04-13 |
Claims that preferences are recoverable when the human uses an unknown finite-state machine, gives a concrete estimator and proofs of consistency. Method fits… | ||
| Quality Selection in Two-Sided Markets: A Price Discrimination Approach | Information Design and Data Science 2019 | 2019-10-01 |
Reduction shows platform quality selection maps to a price-discrimination reduction: two stylized two-sided models (sellers choose quantity under platform-set… | ||
| Bandit Learning with Positive Externalities | Societal Networks 2018 | 2018-03-26 |
Model with arrivals more likely to prefer arms that have earned rewards; positive externality f(x)=x^α (typically linear). Shows UCB can suffer linear expected… | ||
| Always Valid Inference: Continuous Monitoring of A/B Tests | Optimization and Decision-Making Under Uncertainty (Simons Institute, September 2016) | 2016-09-19 |
Optimizely implements always-valid p-values computed from a MSPRT (mixture SPRT) so type I error remains bounded under arbitrary user stopping rules (fixes the… | ||
| Dynamic Pricing in Ride-Sharing Platforms | Algorithmic Game Theory and Practice 2015 | 2015-11-16 |
Model couples strategic passengers and drivers, a platform price multiplier p(A) that depends on number of available drivers, and exponential service times so… | ||
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