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1 - 10 of 29 search results for Economics test |u:www.mlmi.eng.cam.ac.uk where 4 match all words and 25 match some words.

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  2. Better Encoders for Neural Process Family Models

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_dissertations/better_encoders_for_neural_process_family_models.pdf
    6 Dec 2022: representation can be learnt. However, once meta-training has been performed, the test-. ... having the true observations passed through to make realistic predictions at test-time.

  3. Interpretability for Conditional Average Treatment Effect Estimation

    https://www.mlmi.eng.cam.ac.uk/files/2020-2021_dissertations/interpretability_for_conditional_average_treatment_effect_estimation_-_javier_abad.pdf
    24 Jan 2022: Introduction. Inferring the causal effect of interventions is a fundamental problem in many domains,including economics, education, and healthcare.

  4. Non-Gaussian Lévy Processes in Machine Learning

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_dissertations/non-gaussian_levy_processes_in_machine_learning_reduced.pdf
    25 Nov 2022: Non-Gaussian Lévy Processes inMachine Learning. Trevor Clark. Machine Learning and Machine IntelligenceDepartment of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy. Fitzwilliam College

  5. Joint Learning of Practical Dialogue Systems and User Simulators

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_dissertations/joint_learning_of_practical_dialogue_systems_and_user_simulators_reduced.pdf
    6 Dec 2022: US User Simulator. 3, 6. Chapter 1. Introduction. 1.1 Motivation. Language is a fundamentally important part of human intelligence, and is at the heart of many ofthe most important economic ... The full dataset contains approximately 10,400 dialogues,

  6. Results that match 1 of 2 words

  7. AML-poster

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_advanced_machine_learning_posters/variational_continual_learning_1_2022_0.pdf
    9 Dec 2022: Train T1/Test T1 Train T2/Test T1 Train T2/Test T2. • Continual Learning (CL) requires balance between:• Plasticity (Catastrophic Forgetting)• Stability (Inability to adapt).

  8. Conditional Neural ProcessesWeisz S., Buonomo, A, Yuang, L,…

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_advanced_machine_learning_posters/conditional_neural_processes_1_2022.pdf
    17 May 2022: Extension: ConvCNPs. Maximum Likelihood Training. Desirable Properties1. Data-efficient (using meta-learning)2. Fast predictions at test time: 𝒪 𝑛 𝑚 for predicting.

  9. Strengths/Weaknesses Synthetic 1-D Distributions Towards a Neural…

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_advanced_machine_learning_posters/towards_a_neural_statistician_2022.pdf
    17 May 2022: 3.2. 5.4. Statistics Network. StatisticsNetwork. 2.3. Trained on OMNIGLOT, test imagex is classified to a seen dataset:.

  10. PowerPoint Presentation

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_advanced_machine_learning_posters/first-order_approximations_for_efficient_meta-learning_2022.pdf
    17 May 2022: zero. Lastly, overfitting on the test task can be seen after about 20 ADAM inner-loop iterations when trained for many meta iterations. ... Figure 5: Example 5-way classifier: 1-shot images (top row) and test images (bottom row).

  11. Conclusions• UCI Mushroom Bandit: agent selects action (eat vs. ...

    https://www.mlmi.eng.cam.ac.uk/files/2020-2021_advanced_machine_learning_posters/weight_uncertainty_in_neural_networks_2021.pdf
    25 Jan 2022: Monte Carlo (MC) Dropout [3] Bayesian interpretation of dropout i.e. draw samples at test time by repeatedly masking random weights.

  12. AML Poster (A1 841 × 594mm)

    https://www.mlmi.eng.cam.ac.uk/files/2021-2022_advanced_machine_learning_posters/few-shot_learning_with_novel_metrics_1_2022.pdf
    17 May 2022: 2017) are 5-shot 60-way train, 20-way test with 15 query points for each.

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