We present a model of adaptive attacks which we combine with information-theoretic metrics to quantify the information revealed to an adaptive adversary. This enables us to expres...
Some online algorithms for linear classification model the uncertainty in their weights over the course of learning. Modeling the full covariance structure of the weights can prov...
Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer...
Current research on data stream classification mainly focuses on certain data, in which precise and definite value is usually assumed. However, data with uncertainty is quite natu...
We present our experiments in context-free recognition of non-lexical responses. Non-lexical verbal responses such as mmm-hmm or uh-huh are used by listeners to signal confirmati...
In this paper, a new adaptive beamforming algorithm with joint robustness against covariance matrix uncertainty as well as steering vector mismatch is proposed. First, the theoret...