This monograph portrays optimization as a process. In many practical applications the
environment is so complex that it is infeasible to lay out a comprehensive theoretical model …

Abstract We study unconstrained Online Linear Optimization with Lipschitz losses. The goal
is to simultaneously achieve (i) second order gradient adaptivity; and (ii) comparator norm …

We design and analyze minimax-optimal algorithms for online linear optimization games
where the player's choice is unconstrained. The player strives to minimize regret, the …

We consider the classical problem of prediction with expert advice. In the fixedtime setting,
where the time horizon is known in advance, algorithms that achieve the optimal regret are …

Classic option pricing models, such as the Black-Scholes formula, often depend on some
rigid assumptions on the dynamics of the underlying asset prices. These assumptions are …

The decision-making behind cyber operations is complex. Dynamics around issues such as
cyber arsenal management, target assessment, and the timing of drop** a destructive …

We consider a sequential decision-making setting where, at every round $ t $, a market
maker posts a bid price $ B_t $ and an ask price $ A_t $ to an incoming trader (the taker) …

We consider a popular problem in finance, option pricing, through the lens of an online
learning game between Nature and an Investor. In the Black-Scholes option pricing model …

This work examines online linear optimization with full information and switching costs (SCs)
and focuses on regret bounds that depend on properties of the loss sequences. The SCs …

A European option is the right to buy or sell an underlying asset at a fixed point in the future
at a fixed price, also known as the strike. A call option gives the right to buy an asset and a …