2 citations · 3 across the 6 of their papers we have counts for
6 papers
Decentralized Online Convex Optimization with Unknown Feedback Delays
Hao Qiu, Mengxiao Zhang, Juliette Achddou
Decentralized online convex optimization (D-OCO), where multiple agents within a network collaboratively learn optimal decisions in real-time, arises naturally in applications such…
Distributed Online Optimization with Stochastic Agent Availability
Juliette Achddou, Nicolò Cesa-Bianchi, Hao Qiu
Motivated by practical federated learning settings where clients may not be always available, we investigate a variant of distributed online optimization where agents are active wi…
Multitask Online Learning: Listen to the Neighborhood Buzz
Juliette Achddou, Nicolò Cesa-Bianchi, Pierre Laforgue
We study multitask online learning in a setting where agents can only exchange information with their neighbors on an arbitrary communication network. We introduce $\texttt{MT-CO}_…
Stochastic Direct Search Method for Blind Resource Allocation
Juliette Achddou, Olivier Cappe, Aurélien Garivier
Motivated by programmatic advertising optimization, we consider the task of sequentially allocating budget across a set of resources. At every time step, a feasible allocation is c…
Fast Rate Learning in Stochastic First Price Bidding
Juliette Achddou, Olivier Cappé, Aurélien Garivier
First-price auctions have largely replaced traditional bidding approaches based on Vickrey auctions in programmatic advertising. As far as learning is concerned, first-price auctio…
Efficient Algorithms for Stochastic Repeated Second-price Auctions
Juliette Achddou, Olivier Cappé, Aurélien Garivier
Developing efficient sequential bidding strategies for repeated auctions is an important practical challenge in various marketing tasks. In this setting, the bidding agent obtains…