35 citations · 302 across the 30 of their papers we have counts for
31 papers
Secure PAC Learning: Sample-Budget Laws and Quantum Data-Path Admissibility
Jeongho Bang
Security in machine learning is fragile when data are exfiltrated or perturbed, yet existing frameworks rarely connect the definition and analysis of the security to learnability.…
Ensuring superior learning outcomes and data security for authorized learner
Jeongho Bang, Wooyeong Song, Kyujin Shin +1
The learner's ability to generate a hypothesis that closely approximates the target function is crucial in machine learning. Achieving this requires sufficient data; however, unaut…
Resource-compact time-optimal quantum computation
Taewan Kim, Kyunghyun Baek, Yongsoo Hwang +1
Fault-tolerant quantum computation enables reliable quantum computation but incurs a significant overhead from both time and resource perspectives. To reduce computation time, Aust…
Generalized Euler angles for a unitary control of the Hamiltonian system
Seungjin Lee, Kyunghyun Baek, Jeongho Bang
We provide an angular parametrization of the special unitary group generalizing Euler angles for by successively applying the KAK decompositio…
-depth-optimized Quantum Search with Quantum Data-access Machine
Jung Jun Park, Kyunghyun Baek, M. S. Kim +3
Quantum search algorithms offer a remarkable advantage of quadratic reduction in query complexity using quantum superposition principle. However, how an actual architecture may acc…
Polynomial T-depth Quantum Solvability of Noisy Binary Linear Problem: From Quantum-Sample Preparation to Main Computation
Wooyeong Song, Youngrong Lim, Kabgyun Jeong +4
The noisy binary linear problem (NBLP) is known as a computationally hard problem, and therefore, it offers primitives for post-quantum cryptography. An efficient quantum NBLP algo…