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Found 4 papers, 0 papers with code
Online TSP with Predictions
We initiate the study of online routing problems with predictions, inspired by recent exciting results in the area of learning-augmented algorithms.
On the Concurrent Composition of Quantum Zero-Knowledge
We study the notion of zero-knowledge secure against quantum polynomial-time verifiers (referred to as quantum zero-knowledge) in the concurrent composition setting.
Quantum Physics
Sample Efficient Algorithms for Learning Quantum Channels in PAC Model and the Approximate State Discrimination Problem
In the problem of PAC learning quantum process, we want to learn an $\epsilon$-approximate of an unknown quantum process $c^*$ from a known finite concept class $C$ with probability $1-\delta$ using samples $\{(x_1, c^*(x_1)),(x_2, c^*(x_2)),\dots\}$, where $\{x_1, x_2, \dots\}$ are computational basis states sampled from an unknown distribution $D$ and $\{c^*(x_1), c^*(x_2),\dots\}$ are the (possibly mixed) quantum states outputted by $c^*$.
On the Algorithmic Power of Spiking Neural Networks
Our main technical insight is a dual view of the SNN dynamics, under which SNN can be viewed as a new natural primal-dual algorithm for the l1 minimization problem.
