Results 51 to 60 of about 4,491,165 (327)

Oracle inequalities for weighted group lasso in high-dimensional misspecified Cox models

Journal of Inequalities and Applications, 2020
We study the nonasymptotic properties of a general norm penalized estimator, which include Lasso, weighted Lasso, and group Lasso as special cases, for sparse high-dimensional misspecified Cox models with time-dependent covariates.
Yijun Xiao, Ting Yan, Huiming Zhang, Yuanyuan Zhang   +3 more
doaj   +1 more source

Effects of Noisy Oracle on Search Algorithm Complexity

, 2003
Grover's algorithm provides a quadratic speed-up over classical algorithms for unstructured database or library searches. This paper examines the robustness of Grover's search algorithm to a random phase error in the oracle and analyzes the complexity of
B. Pablo-Norman, C.H. Bennett, D. Bacon, D. Shapira, E. Farhi, E. Novak, G.L. Long, J. Preskill, K. Birgitta Whaley, Kenneth R. Brown, L.K. Grover, M. Boyer, Neil Shenvi, P.W. Shor   +13 more
core   +1 more source

Oblivious Transfer Based on NTRUEncrypt

IEEE Access, 2018
Oblivious transfer (OT) is the most fundamental process in cryptosystems and serves as the basic building block for implementing protocols, such as the secure multi-party computation and the fair electronic contract.
Bo Mi, Darong Huang, Shaohua Wan, Libo Mi, Jianqiu Cao   +4 more
doaj   +1 more source

Customizing Tactile Sensors via Machine Learning‐Driven Inverse Design

Advanced Science, EarlyView.
ABSTRACT Replicating the sophisticated sense of touch in artificial systems requires tactile sensors with precisely tailored properties. However, manually navigating the complex microstructure‐property relationship results in inefficient and suboptimal designs.
Baocheng Wang, Depeng Kong, Zhiao He, Jikai Liang, Yuyao Lu, Zikang Deng, Honghe Li, Mengke Wang, M. Jamal Deen, Zhiqiu Ye, Shuyao Zhou, Huayong Yang, Honghao Lyu, Jun Chen, Kaichen Xu, Geng Yang   +15 more
wiley   +1 more source

Certificateless signature scheme without random oracles

Tongxin xuebao, 2015
The security of certificateless signature schemes can be proved under the random oracle model.However，any implementation of the random oracle may result in insecure schemes.Some certificateless signature schemes without random oracles are not secure ...
Yan-qiong LI, Ji-guo LI, Yi-chen ZHANG
doaj   +2 more sources

Strengths and Weaknesses of Quantum Computing

, 1996
Recently a great deal of attention has focused on quantum computation following a sequence of results suggesting that quantum computers are more powerful than classical probabilistic computers. Following Shor's result that factoring and the extraction of
Charles H. Bennett, Ethan Bernstein, Gilles Brassard, Umesh Vazirani, Université De Montréal   +4 more
core   +4 more sources

Las Vegas Computability and Algorithmic Randomness [PDF]

, 2015
In this article we try to formalize the question “What can be computed with access to randomness?” We propose the very fine-grained Weihrauch lattice as an approach to differentiate between different types of computation with access to randomness.
GHERARDI, GUIDO, Rupert Hölzl, Vasco Brattka   +2 more
core   +2 more sources

Tighter proofs of CCA security in the quantum random oracle model

IACR Cryptology ePrint Archive, 2019
We revisit the construction of IND-CCA secure key encapsulation mechanisms (KEM) from public-key encryption schemes (PKE). We give new, tighter security reductions for several constructions.
Nina Bindel, Michael Hamburg, Andreas Hülsing, Edoardo Persichetti   +3 more
semanticscholar   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Flexible Memory: Progress, Challenges, and Opportunities

Advanced Intelligent Discovery, EarlyView.
Flexible memory technology is crucial for flexible electronics integration. This review covers its historical evolution, evaluates rigid systems, proposes a flexible memory framework based on multiple mechanisms, stresses material design's role, presents a coupling model for performance optimization, and points out future directions.
Ruizhi Yuan, Sen Chen, Minghui Guo, Ziliang Cui, Yujie Du, Jing Liu   +5 more
wiley   +1 more source