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cs.LG2026
Active Learning on Adversarially Corrupted Graphs
Marco Bressan, Nicolò Cesa-Bianchi, Tommaso d`Orsi +2
Motivated by real-world scenarios where malicious entities tamper with existing networks, we define a model where an adversary seeks to hide a set of \emph{corrupted vertices} insi…
cs.CC2026
Strongly Refuting Random CSP without Literals
Siu On Chan, Tommaso d'Orsi, Jeff Xu
Under what condition is a random constraint satisfaction problem hard to refute by the sum-of-squares (SoS) algorithm? A sufficient condition is t-wise uniformity, that is, each co…