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Covers the basics of risk management, major accidents, and the uncertainties of the future in decision-making processes.
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Delves into the economic fundamentals of innovation, exploring historical context, entrepreneurial risk, societal challenges, and the role of private entrepreneurs.
Applying the learning bound to kernel regression
Discusses the application of the main theorem to least square regression in a RKHS, focusing on LR of the Rademacher bound and Lipschitz constant.
Coherent Risk Measures: Spectral Approach
Explores coherent risk measures and the spectral approach to risk aversion, covering VaR, ES, subadditivity, convexity, and the creation of new risk measures.
Risk Management in Project Analysis
Explores risk management in project analysis, emphasizing the importance of lean management and numerical simulation.
Generalization in Deep Learning
Explores generalization in deep learning, covering model complexity, implicit bias, and the double descent phenomenon.
Quantitative Risk Management: Risk Measures
Covers risk measures used in determining risk capital and insurance premiums.
Asset Pricing: Risk-Neutral Measure and State Prices
Covers risk-neutral measure, state prices, utility functions, and risk aversion in asset pricing.
Decision Trees: Regression and Classification
Covers decision trees for regression and classification, explaining tree construction, feature selection, and criteria for induction.
Principles of Finance: Risk and Return
Explores risk and return in finance, covering securities' performance, rates of return, variance, volatility, and portfolio diversification.

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