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1 - 17 of 17 search results for Psychology |u:www.mlmi.eng.cam.ac.uk
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  2. Improving Sample Efficiency forGradient-based Policy Optimisation;…

    https://www.mlmi.eng.cam.ac.uk/files/wang_dissertation.pdf
    30 Oct 2019: Inspired by this kind ofbehaviorist psychology, the field of Reinforcement Learning (RL) emerges as a frameworkfor solving sequential decision-making problems through interaction with the environment.[Sutton and Barto, 1998] provides
  3. Curiosity-Driven Reinforcement Learning for Dialogue Management

    https://www.mlmi.eng.cam.ac.uk/files/paulawesselmann_mlsalt.pdf
    6 Nov 2019: 2.3.1 Optimal Challenge. Psychology suggests that curiosity or interest is only "engaged by what is just beyond currentknowledge, neither too well known nor too far beyond what is understandable"
  4. Combining Diverse Neural Network Language Models for Speech…

    https://www.mlmi.eng.cam.ac.uk/files/xianrui_zheng.pdf
    18 Nov 2019: Modern technologies for analysingspeech require knowledge from fields including but not limited to linguistics, engineeringand psychology.
  5. A model-based design tool for 3D GUI layout design that accommodates…

    https://www.mlmi.eng.cam.ac.uk/files/2020-2021_dissertations/a_model-based_design_tool.pdf
    15 Nov 2021: The ‘optimality’ of these layouts is often variable to human perception,psychology, and preference; an optimal design for one user will usually not be optimal for allother users. ... designknowledge. The key challenge with designing an optimal UI is
  6. Fair Policy Learning

    https://www.mlmi.eng.cam.ac.uk/files/2020-2021_dissertations/fair_policy_learning.pdf
    24 Jan 2022: Fair Policy Learning. Tennison Liu. Supervisor: Prof. Mihaela van der. Schaar. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine Intelligence. St
  7. Compression without Quantization Gergely Flamich Department of…

    https://www.mlmi.eng.cam.ac.uk/files/compression_without_quantization_flamich_reduced.pdf
    18 Nov 2019: from several otherdisciplines, such as mathematics, neuroscience, psychology and photography.
  8. Stochastic Memory for Sequence Models Making Good Compressors Use ...

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_dissertations/stochastic_memory_for_sequence_models.pdf
    2 Mar 2023: Stochastic Memory for Sequence Models. Making Good Compressors Use Less Memory. David Michael Goldfarb. Supervisor: Dr. Christian Steinruecken. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster
  9. Knowledge Distillation for End-to-End Automatic Speech Recognition

    https://www.mlmi.eng.cam.ac.uk/files/2020-2021_dissertations/knowledge_distillation_for_end-to-end_asr.pdf
    9 Dec 2021: Knowledge Distillation for End-to-EndAutomatic Speech Recognition. Xiaoyu Yang. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine Intelligence.
  10. Beyond independent masking in tabular self-supervision

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_dissertations/beyond_independent_masking_in_tabular_self-supervision.pdf
    25 Nov 2022: Beyond independent maskingin tabular self-supervision. Stuart Andrew Burrell. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy. Corpus Christi College September 2022. Declaration.
  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: BachBot: Automatic composition in thestyle of Bach chorales. Developing, analyzing, and evaluating a deep LSTM modelfor musical style. Feynman Liang. Department of EngineeringUniversity of Cambridge. M.Phil in Machine Learning, Speech, and Language
  12. Information-Theoretic Exploration with Successor Uncertainties

    https://www.mlmi.eng.cam.ac.uk/files/2019-2020_dissertations/information_theoretic_exploration_with_successor_uncertainties.pdf
    11 Feb 2021: Inspired by behaviorist psychology, RL was created as an area of machinelearning with the purpose of mimicking the way humans learn.
  13. Mitigating Gender Bias in Dialogue Generation Gabrielle (Ming Yi) ...

    https://www.mlmi.eng.cam.ac.uk/files/2020-2021_dissertations/mitigating_gender_bias_in_dialogue_generation.pdf
    15 Nov 2021: Mitigating Gender Bias in. Dialogue Generation. Gabrielle (Ming Yi) Lau. Department of Engineering. University of Cambridge. This dissertation is submitted for the degree of. Master of Philosophy in Machine Learning and Machine Intelligence.
  14. Distilling and Forgetting in Large Pre-Trained Models

    https://www.mlmi.eng.cam.ac.uk/files/2022_-_2023_dissertations/distilling_and_forgetting_in_pre-trained_models_public.pdf
    17 Nov 2023: Distilling and Forgetting in LargePre-Trained Models. Tony Wu. Supervisors: Prof. Mark Gales. Dr. Mengjie Qian. Adian Liusie. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in
  15. Causal Representation Learning for Latent Space Optimization

    https://www.mlmi.eng.cam.ac.uk/files/2020-2021_dissertations/causal_representation_learning_for_latent_space_optimization.pdf
    15 Nov 2021: Causal Representation Learning forLatent Space Optimization. Wenlin Chen. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine Intelligence. St
  16. Graph Representation Learning for Child Mental Health Prediction

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_dissertations/graph_representation_learning_for_child_mental_health_prediction.pdf
    25 Nov 2022: Graph Representation Learning forChild Mental Health Prediction. Ryan Crowley. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine Intelligence.
  17. Improving Machine Learning Systems by Eliciting and Incorporating…

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_dissertations/improving_ml_systems_with_additional_human_knowledge_16.11.22.pdf
    25 Nov 2022: Improving Machine Learning Systemsby Eliciting and Incorporating. Additional Human Knowledge. Katherine M. Collins. Supervisors: Dr. Adrian Weller MBE. Umang Bhatt. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for
  18. Understanding and Fixing the Modality Gap in Vision-Language Models

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_dissertations/understanding_and_fixing_the_modality_gap_in_vision-language_models_reduced.pdf
    25 Nov 2022: Understanding and Fixing the ModalityGap in Vision-Language Models. Vishaal Udandarao. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine Intelligence

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