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Related lectures (31)
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Elements of computational complexity
Covers classical and quantum computational complexity concepts and implications.
Energy System Modelling: Overview and Optimization Problems
Covers energy system modelling, optimization, scenarios, predictions, complexities, and controversies in energy models.
Learning from Probabilistic Models
Delves into challenges of learning from probabilistic models, covering computational complexity, data reconstruction, and statistical gaps.
Optimal Power Flow Solvers: Next Generation Advancements
Explores advancements in optimal power flow solvers, focusing on multiperiod and security-constrained optimization.
Complexity of Algorithms
Explores algorithm complexity, analyzing efficiency and worst-case scenarios of sorting algorithms.
Simulating Molecular Biology: Challenges and Opportunities
Explores simulating molecular biology dynamics, addressing challenges and opportunities in computational research.
State Space Models: Expressivity of Transformers
Covers state space models and the expressivity of transformers in sequence copying tasks.
Belief propagation simplification
Explores simplifying belief propagation equations for pairwise models, reducing computational complexity from order n cubed to order n.
Discrete Optimization: The Curse of Dimensionality
Delves into the curse of dimensionality in discrete optimization, highlighting the challenges of exponential computational time growth with problem size.
Projection Pursuit Regression: Nonlinear Modeling and Interpretability
Explores Projection Pursuit Regression for nonlinear modeling and the trade-offs with interpretability in neural networks.
