5 citations · 13 across the 7 of their papers we have counts for
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quant-ph2020
Global Optimum Search in Quantum Deep Learning
Lanston Hau Man Chu, Tejas Bhojraj, Rui Huang
This paper aims to solve machine learning optimization problem by using quantum circuit. Two approaches, namely the average approach and the Partial Swap Test Cut-off method (PSTC)…
quant-ph2020★ 4 cited
Quantum algorithmic randomness
Tejas Bhojraj
Quantum Martin-Löf randomness (q-MLR) for infinite qubit sequences was introduced by Nies and Scholz. We define a notion of quantum Solovay randomness which is equivalent to q-MLR.…
cs.IT2020★ 2 cited
Generating Randomness from a Computable, Non-random Sequence of Qubits
Tejas Bhojraj
Nies and Scholz introduced the notion of a state to describe an infinite sequence of qubits and defined quantum-Martin-Lof randomness for states, analogously to the well known conc…