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PET
2005
Springer
15 years 3 months ago
An Analysis of Parallel Mixing with Attacker-Controlled Inputs
Parallel mixing [7] is a technique for optimizing the latency of a synchronous re-encryption mix network. We analyze the anonymity of this technique when an adversary can learn the...
Nikita Borisov
CRYPTO
2010
Springer
151views Cryptology» more  CRYPTO 2010»
14 years 10 months ago
Leakage-Resilient Pseudorandom Functions and Side-Channel Attacks on Feistel Networks
Abstract. A cryptographic primitive is leakage-resilient, if it remains secure even if an adversary can learn a bounded amount of arbitrary information about the computation with e...
Yevgeniy Dodis, Krzysztof Pietrzak
BMCBI
2008
138views more  BMCBI 2008»
14 years 9 months ago
Using neural networks and evolutionary information in decoy discrimination for protein tertiary structure prediction
Background: We present a novel method of protein fold decoy discrimination using machine learning, more specifically using neural networks. Here, decoy discrimination is represent...
Ching-Wai Tan, David T. Jones
GECCO
2009
Springer
124views Optimization» more  GECCO 2009»
15 years 2 months ago
Reinforcement learning for games: failures and successes
We apply CMA-ES, an evolution strategy with covariance matrix adaptation, and TDL (Temporal Difference Learning) to reinforcement learning tasks. In both cases these algorithms se...
Wolfgang Konen, Thomas Bartz-Beielstein
IJCNN
2008
IEEE
15 years 4 months ago
Learning adaptive subject-independent P300 models for EEG-based brain-computer interfaces
Abstract— This paper proposes an approach to learn subjectindependent P300 models for EEG-based brain-computer interfaces. The P300 models are first learned using a pool of exis...
Shijian Lu, Cuntai Guan, Haihong Zhang