The most significant progress in recent years in online display advertising is what is known
as the Real-Time Bidding (RTB) mechanism to buy and sell ads. RTB essentially facilitates …

Mining and analyzing the valuable knowledge hidden behind the amount of data available
in social media is becoming a fundamental prerequisite for any effective and successful …

We study online learning problems in which a decision maker has to take a sequence of
decisions subject to $ m $ long-term constraints. The goal of the decision maker is to …

Privacy policies have disrupted the multi-billion dollar online advertising market by making
real-time and precise user data untraceable, which poses significant challenges to the …

Real-time bidding (RTB) based display advertising has become one of the key technological
advances in computational advertising. RTB enables advertisers to buy individual ad …

Budgets play a significant role in real-world sequential auction markets such as those
implemented by internet companies. To maximize the value provided to auction participants …

We consider online convex optimization with stochastic constraints where the objective
functions are arbitrarily time-varying and the constraint functions are independent and …

We consider a class of online decision-making problems with exchangeable actions, where
in each period a controller is presented an input type drawn from some stochastic arrival …

In targeted online advertising, advertisers look for maximizing campaign performance under
delivery constraint within budget schedule. Most of the advertisers typically prefer to impose …

We study online learning problems in which a decision maker has to make a sequence of
costly decisions, with the goal of maximizing their expected reward while adhering to budget …