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Optimal Predictors: A Bayesian Notion of Approximation Algorithm
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abstract.tex untitled.tex From_the_perspective_of_frequentist__.tex The_idea_of_assigning_probabilities__.tex In_the_present_work_we__.tex Optimal_predictors_turn_out_to__.tex Assignment_of_probabilities_to_mathematical__.tex The_structure_of_the_paper__.tex setcounter_section_1_section_Notation__.tex subsection_Measures_and_Probabilities_For__.tex subsection_Algorithms_Words_is_the__.tex section_Fundamentals_subsection_Optimal_Predictors__.tex Note_that_the_characterization_of__.tex We_now_introduce_our_abstraction__.tex In_the_motivational_model_the__.tex begin_example_For_any_n__.tex We_now_introduce_our_notion__.tex Fix_Gamma_a_pair_of__.tex We_note_a_few_simple__.tex We_are_now_ready_to__.tex TODO_Advice_is_more_powerful__.tex subsection_Orthogonality_Theorems_There_is__.tex The_following_theorem_is_the__1.tex To_prove_theorem_ref_thm__.tex begin_proof_Proof_of_Theorem__.tex subsection_Simple_Example_TBD__.tex section_Optimal_Predictors_and_Probability__.tex section_Reductions_and_Completeness_TBD__.tex section_Existence_and_Uniqueness_TBD__.tex section_Reflective_Systems_and_Game__.tex section_Discussion_TBD_subsection_Acknowledgments__.tex appendix_section_Appendix_One_Way__.tex subsection_Acknowledgments_TBD__.tex