Convex Optimization
The Winner's Curse: Why it Happens and What to Do About It
When running an A/B test with many variants, say, more than 5, we often run into a phenomenon known as the Winner’s Curse, where the winning variant performs worse when we adopt it universally than it had during the test itself. In this post, we discuss why this phenomenon occurs and what to do about it.
Robust Portfolio Optimization in Models with Diminishing Returns
In our last post, we discussed how model uncertainty poses a risk when allocating resources among productive assets. In this post, we expand the discussion to models with diminishing returns. Such models are common in economics. As before, we can incorporate model uncertainty directly into the problem, achieving good performance regardless of the true model, with minimal impact to nominal performance. Robust optimization is both powerful and practical.
Robust Portfolio Optimization in Generalized Linear Models
Often we run an A/B test in order to inform some decision. But every A/B test involves uncertainty, no matter the sample size. This uncertainty poses a risk to our decision, which can be hedged by a process analogous to diversifying an investment portfolio. Finding a robust-optimal portfolio is both practical and fast.
Optimal Experiment Design
We can plan sample sizes to control the width of confidence intervals.
