Lectures related to From Algorithms to Architectures: Isomorphic Mapping and Efficiency Assessment

Covers classical and quantum computational complexity concepts and implications.

Covers the Shor algorithm for quantum factorization using tensor methods and graded solutions.

Covers the details of the Shor algorithm circuit and its complexity.

Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.

Theory of Computation: Monotone Complexity and XOR-SAT Lower Bounds

Explores monotone complexity, XOR-SAT lower bounds, and their implications in computational theory.

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Theory of Computability: Solvability and Complexity

Explores the theory of computability, decision problems, complexity classes, and the 'P vs. NP' conundrum.

Deutsch and Josza Problem

Covers the Deutsch and Josza problem in quantum computation, focusing on boolean functions and oracles.

Simon Problem 4: Quantum State and Complexity Analysis

Explores the Simon Problem 4, analyzing quantum states and algorithm complexity.

Subquadratic Attention Mechanisms: State Space Models Overview

Covers subquadratic attention mechanisms and state space models, focusing on their theoretical foundations and practical implementations in machine learning.

Complexity Classes: P and NP

Explores complexity classes P and NP, highlighting solvable and verifiable problems, including NP-complete challenges.

Theory of Computation: Countability and Undecidable Problems

Explores countability and undecidable problems in the theory of computation.

Improved Algorithm: Three-Color Parity Games

Introduces an improved algorithm for three-color parity games, focusing on progress measures, acceleration, and practical speed-up.

Complexity & Induction: Algorithms & Proofs

Covers worst-case complexity, algorithms, and proofs including mathematical induction and recursion.

Dijkstra's Algorithm: All-Pairs

Covers Dijkstra's algorithm and its application to the all-pairs shortest path problem.

Elements of Computational Complexity

Introduces computational complexity, decision problems, quantum complexity, and probabilistic algorithms, including NP-hard and NP-complete problems.

Dynamic Programming: Knapsack

Explores dynamic programming for the Knapsack problem, discussing strategies, algorithms, NP-hardness, and time complexity analysis.

Coin Rendering: Part 1

Covers coin rendering and the limitations of the greedy algorithm in finding optimal solutions.

Optimal Power Flow Solvers: Next Generation Advancements

Explores advancements in optimal power flow solvers, focusing on multiperiod and security-constrained optimization.

State Space Models: Expressivity of Transformers

Covers state space models and the expressivity of transformers in sequence copying tasks.