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1 - 10 of 62 search results for KaKaoTalk:PC53 24 / |u:www.mlmi.eng.cam.ac.uk where 0 match all words and 62 match some words.

  1. Results that match 1 of 2 words

  2. Probabilistic Bellman Consistency in Reinforcement Learning

    https://www.mlmi.eng.cam.ac.uk/files/biggio_dissertation.pdf
    18 Nov 2019: Probabilistic Bellman Consistency inReinforcement Learning. Luca Biggio. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy. Robinson College August 2019. Declaration. I, Luca

  3. Waveform Level Synthesis

    https://www.mlmi.eng.cam.ac.uk/files/dou_thesis.pdf
    30 Oct 2019: Forthe network in figure 3.6, F L = 2, NL = 4, and HL = 24 = 16. ... 24 Unconditional synthesis. baseline synthesis system. 2254 utterances are used for training, 70 for validation and 72for testing.

  4. Compression without Quantization Gergely Flamich Department of…

    https://www.mlmi.eng.cam.ac.uk/files/compression_without_quantization_flamich_reduced.pdf
    18 Nov 2019: Compression without Quantization. Gergely Flamich. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine Intelligence. St John’s College August 2019.

  5. Distributed Variational Inferenceand Privacy

    https://www.mlmi.eng.cam.ac.uk/files/dissertation_-_xiping_liu.pdf
    18 Nov 2019: A(D) = iI. f (xi) σ ηηη (2.24). where ηi N(0,1) for i = 1,.,n and I is a subset of indices in which each index is chosenindependently ... 24 Experiments and Results. Exponential family distributions take the following form:.

  6. Constrained Bayesian Optimization for Automatic Chemical Design

    https://www.mlmi.eng.cam.ac.uk/files/griffiths_dissertation.pdf
    30 Oct 2019: 24 Background. termed the evidence [71]) encompasses the Occam factor [93] in so far as it favours models ofintermediate complexity. ... 2.24). 12. y(Qff diag[Kff Qff] σ 2y I)1y︸ ︷︷ ︸encourages fit with data.

  7. Sum Product Network with VAE LeavesP. L. Tan*, R. ...

    https://www.mlmi.eng.cam.ac.uk/files/sum_product_network_with_vae_leaves_ping_liang_tan.pdf
    6 Nov 2019: 1 23 4. 24. 131 2 3 4. 1 23 4.

  8. Model Uncertainty for Adversarial Examples using Dropouts

    https://www.mlmi.eng.cam.ac.uk/files/ambrish_rawat_8224901_assignsubmission_file_rawat_ambrish_thesis1.pdf
    30 Oct 2019: In 2015 IEEE Conference. 24 References. on Computer Vision and Pattern Recognition (CVPR), pages 427–436.

  9. Neural Program Lattices

    https://www.mlmi.eng.cam.ac.uk/files/rampersad_dissertation.pdf
    30 Oct 2019: 24. 4.2 When constrained through β0 and β1 the controller avoids having to learn thecorrect program embeddings by calling the correct number of PUSH and POPoperations but in such a

  10. One-shot Learning in DiscriminativeNeural Networks Jordan Burgess…

    https://www.mlmi.eng.cam.ac.uk/files/jordan_burgess_8224871_assignsubmission_file_burgess_jordan_thesis1.pdf
    30 Oct 2019: 24. When enough data has been seen, the posterior distribution on the weights should.

  11. BachBot: Automatic composition in thestyle of Bach chorales…

    https://www.mlmi.eng.cam.ac.uk/files/feynman_liang_8224771_assignsubmission_file_liangfeynmanthesis.pdf
    30 Oct 2019: 24. 4.3 Distortion introduced by quantization to semiquavers. 254.4 Example encoding of a score containing two chords, both one quaver in dura-. ... Experiments in Music Intelligence (EMI) by Cope [24, 23] is one of the first rule-basedcomposition

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