Courses from 1000+ universities
Buried in Coursera’s 300-page prospectus: two failed merger attempts, competing bidders, a rogue shareholder, and a combined market cap that shrank from $3.8 billion to $1.7 billion.
600 Free Google Certifications
Bitcoin and Cryptocurrency Technologies
The Emergence of the Modern Middle East - Part I
Six Sigma Part 1: Define and Measure
Organize and share your learning with Class Central Lists.
View our Lists Showcase
Explore sublinear algorithms for correlation clustering, focusing on a 3+eps approximation method using LCA probes, MPC rounds, and dynamic updates. Analyze technical results for maximal independent set computation.
Explore approaches for designing fast dynamic algorithms for approximate matchings, focusing on fully dynamic settings and the concept of matching sparsifiers in graph theory.
Explore an algorithm for approximating maximum matching in dynamic streams, achieving O(1)-approximation in O(log log n) passes and O(n poly log n) space, with lower bound proof.
Explore sublinear additive spanners in graph theory, focusing on optimal stretch functions and size bounds for undirected unweighted graphs. Learn about recent advancements and their implications.
Explore planar graph partition oracles for bounded degree graphs, focusing on hyperfinite decompositions and their applications in sublinear algorithms and property testing.
Explore graph sparsification, CSP compression, and code sparsification techniques. Learn about cutting-edge research in sublinear graph simplification and its applications to various domains.
Explore robust optimization's history and its modern machine learning applications, focusing on performance certification and practical challenges in ML systems.
Explore conditional sampling techniques for distribution testing, focusing on efficient algorithms and their applications in statistical analysis.
Explore strategies for designing signaling in games with asymmetric information, focusing on principal-agent interactions and their applications in real-world scenarios.
Explore innovative abstraction-refinement techniques for LTL synthesis, enhancing scalability and addressing infinite-state challenges through liveness refinements and symbolic representations.
Explore attractor decompositions in graphs, their role in parity games, and applications to automata theory. Learn about structural complexity measures and strategy analysis.
Explore logics capturing distributed computing and neural network models, including graph neural networks. Dive into game-theoretic semantics and computational logic connections.
Algebraic approach to modeling non-determinism in computational processes, using promise algebra and history-dependent choice functions to analyze complexity and generate strategies.
Explore symbolic methods for solving infinite-state games, focusing on localized attractor computations in sub-games to enhance efficiency and tackle complex problem instances.
Efficient algorithm for computing fixed points of contraction maps, with potential implications for solving simple stochastic games and related computational problems.
Get personalized course recommendations, track subjects and courses with reminders, and more.