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PET
2005
Springer
14 years 6 days 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»
13 years 7 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»
13 years 6 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»
13 years 11 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
14 years 1 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