Discrepancy is a versatile bound in communication complexity which can be used to show lower bounds in the distributional, randomized, quantum, and even unbounded error models of ...
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
We consider a class of two-prover interactive proof systems where each prover returns a single bit to the verifier and the verifier’s verdict is a function of the XOR of the tw...
Richard Cleve, William Slofstra, Falk Unger, Sarva...
We consider the problem of bounded-error quantum state identification: given either state 0 or state 1, we are required to output `0', `1' or `?' ("don't ...
Dmitry Gavinsky, Julia Kempe, Oded Regev, Ronald d...