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Explore combinatorial theorems on RSK process applied to random words, focusing on Young diagram majorization in different scenarios.
Explore high-dimensional expanders, focusing on 2-dimensional cases, graphs of constant link, and group-theoretic constructions. Gain insights into advanced mathematical concepts and recent research developments.
Explore quantum computing fundamentals and the Elitzur-Vaidman bomb detection algorithm using a single qubit, covering key concepts and practical applications in this engaging lecture.
Explore improved quantum shadow tomography, focusing on optimal dependence on observables, dimension, and error tolerance. Learn connections to adaptive data analysis in this advanced talk.
Explore Dinur's PCP Theorem proof, covering degree-reduction, expanderizing, and alphabet-reduction in theoretical computer science. Gain insights into advanced concepts for research in computational complexity.
Explore deterministic communication complexity, protocols, matrices, and the Log Rank conjecture in this graduate-level lecture on theoretical computer science fundamentals.
Explore treewidth, CSPs, and graph theory fundamentals for theoretical computer science research, focusing on trees and series-parallel graphs.
Explore Constraint Satisfaction Problems, their formal definition, examples, and algorithms. Learn about the Dichotomy Theorem and its implications for theoretical computer science research.
Efficient algorithm for approximating maximum graph cuts using semidefinite programming and randomized rounding, with guaranteed performance ratio of 0.878.
Explore SDP relaxation for Max-Cut, transforming a quadratic program into a semidefinite program solvable by the Ellipsoid Algorithm. Part of CMU's graduate-level CS Theory Toolkit course.
Explore the Ellipsoid Algorithm for solving Linear Programming and convex optimization, focusing on its polynomial-time efficiency and use of separation oracles in theoretical computer science.
Explore bit complexity in Linear Programming, feasible solutions, and the implications for NP ∩ coNP. Delve into fundamental concepts for theoretical computer science research.
Explore linear programming duality, Farkas Lemma, and Fourier-Motzkin elimination in this graduate-level lecture on fundamental concepts for theoretical computer science research.
Explore derandomization techniques using expander graphs to reduce error in randomized algorithms without significantly increasing random bits used.
Explore explicit expander graph constructions, including Gabber-Galil, Ramanujan, and Zig-Zag product expanders. Learn about their properties, applications, and mathematical foundations in theoretical computer science.
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