South America
Particle Cloud Generation with Message Passing Generative Adversarial Networks
However, despite jets having a natural representation as a set of particles in momentum-space, a.k.a. a particle cloud, there exist no generative
No-regret Learning in Price Competitions under Consumer Reference Effects
We study long-run market stability for repeated price competitions between two firms, where consumer demand depends on firms' posted prices and consumers'
Adversarial Attacks on Deep Graph Matching
Despite achieving remarkable performance, deep graph learning models, such as node classification and network embedding, suffer from harassment caused by small adversarial perturbations.
Posted Pricing and Dynamic Prior-independent Mechanisms with Value Maximizers
We study posted price auctions and dynamic prior-independent mechanisms for (ROI-constrained) value maximizers.
Combiner: Full Attention Transformer with Sparse Computation Cost
Transformers provide a class of expressive architectures that are extremely effective for sequence modeling.
Bandits with many optimal arms
We consider a stochastic bandit problem with a possibly infinite number of arms.
Consistent Plug-in Classifiers for Complex Objectives and Constraints
Our approach reduces the problem into a sequence of plug-in classifier learning tasks.