The study of transportability aims to identify conditions under which causal information learned from experiments can be reused in a different environment where only passive obser...
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...
We propose a new cryptographic primitive called oblivious signaturebased envelope (OSBE). Informally, an OSBE scheme enables a sender to send an envelope (encrypted message) to a ...
Over the course of a day a human interacts with tens or hundreds of individual objects. Many of these articles are nomadic, relying on human memory to manually index, inventory, o...
Aditya Nemmaluri, Mark D. Corner, Prashant J. Shen...
Regret minimization has proven to be a very powerful tool in both computational learning theory and online algorithms. Regret minimization algorithms can guarantee, for a single de...