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- SourceAvailable from: sci.brooklyn.cuny.edu[Show abstract] [Hide abstract]
ABSTRACT: Trust is a natural mechanism by which an autonomous party, an agent, can deal with the inherent uncertainty regarding the behaviours of other parties and the uncertainty in the information it shares with those parties. Trust is thus crucial in any decentralised system. This paper builds on recent efforts to use argumentation to reason about trust. Specifically, a set of schemes is provided, and abstract patterns of reasoning that apply in multiple situations geared towards trust. Schemes are described in which one agent, A, can establish arguments for trusting another agent, B, directly, as well as schemes that A can use to construct arguments for trusting C, where C is trusted by B. For both sets of schemes, a set of critical questions is offered that identify the situations in which these schemes can fail.Argument and Computation 05/2014; 5(2-3). DOI:10.1080/19462166.2014.913075
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ABSTRACT: We present our approach to unsupervised training of speech recognizers. Our approach iteratively adjusts sound units that are optimized for the acoustic domain of interest. We thus enable the use of speech recognizers for applications in speech domains where transcriptions do not exist. The resulting recognizer is a state-of-the-art recognizer on the optimized units. Specifically we propose building HMM-based speech recognizers without transcribed data by formulating the HMM training as an optimization over both the parameter and transcription sequence space. Audio is then transcribed into these self-organizing units (SOUs). We describe how SOU training can be easily implemented using existing HMM recognition tools. We tested the effectiveness of SOUs on the task of topic classification on the Switchboard and Fisher corpora. On the Switchboard corpus, the unsupervised HMM-based SOU recognizer, initialized with a segmental tokenizer, performed competitively with an HMM-based phoneme recognizer trained with 1 h of transcribed data, and outperformed the Brno University of Technology (BUT) Hungarian phoneme recognizer (Schwartz et al., 2004). We also report improvements, including the use of context dependent acoustic models and lattice-based features, that together reduce the topic verification equal error rate from 12% to 7%. In addition to discussing the effectiveness of the SOU approach, we describe how we analyzed some selected SOU n-grams and found that they were highly correlated with keywords, demonstrating the ability of the SOU technology to discover topic relevant keywords.Computer Speech & Language 01/2014; 28(1):210–223. DOI:10.1016/j.csl.2013.05.002
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ABSTRACT: We address the problem of how efficiently information can be encoded into and read out reliably from a passive reflective surface that encodes classical data by modulating the amplitude and phase of incident light. We show that nature imposes no fundamental upper limit to the number of bits that can be read per expended probe photon and demonstrate the quantum-information-theoretic trade-offs between the photon efficiency (bits per photon) and the encoding efficiency (bits per pixel) of optical reading. We show that with a coherent-state (ideal laser) source, an on-off (amplitude-modulation) pixel encoding, and shot-noise-limited direct detection (an overly optimistic model for commercial CD and DVD drives), the highest photon efficiency achievable in principle is about 0.5 bits read per transmitted photon. We then show that a coherent-state probe can read unlimited bits per photon when the receiver is allowed to make joint (inseparable) measurements on the reflected light from a large block of phase-modulated memory pixels. Finally, we show an example of a spatially entangled nonclassical light probe and a receiver design—constructible using a single-photon source, beam splitters, and single-photon detectors—that can in principle read any number of error-free bits of information. The probe is a single photon prepared in a uniform coherent superposition of multiple orthogonal spatial modes, i.e., a W state. The code and joint-detection receiver complexity required by a coherent-state transmitter to achieve comparable photon efficiency performance is shown to be much higher in comparison to that required by the W-state transceiver, although this advantage rapidly disappears with increasing loss in the system.Physical Review A 06/2013; 87(6). DOI:10.1103/PhysRevA.87.062306
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