Courses from 1000+ universities
$7.2 billion in combined revenue since 2020. $8 billion in lost market value. This merger marks the end of an era in online education.
600 Free Google Certifications
Computer Science
Artificial Intelligence
OpenAI
Divide and Conquer, Sorting and Searching, and Randomized Algorithms
Introduction to Graphic Illustration
The Science of Gastronomy
Organize and share your learning with Class Central Lists.
View our Lists Showcase
Explore insights from Tal Herman's presentation at the Workshop on Local Algorithms, delving into cutting-edge research in computer science and mathematics.
Explore tools for sharing sensitive data with untrusted analysts, focusing on differentially private algorithms and privacy wrappers for black-box functions on datasets.
Explore optimal passes for semi-streaming maximal independent set, focusing on O(log log n) algorithm and new lower bound proof using extremal graphs and round elimination techniques.
Explore instance optimality in detecting collisions and subgraphs, examining how structural knowledge impacts algorithm efficiency for various detection tasks in functions and graphs.
Explore the connection between PAC-learning of graphical models and efficient graph structure sampling, leveraging online learning algorithms for new insights in high-dimensional distribution learning.
Explore interactive proofs for verifiable data science, enhancing trust and reliability in scientific computations and analyses.
Explore directed isoperimetry and its application to monotonicity testing, analyzing directed random walks on product domains for optimal testers in Boolean functions on hypergrids.
Explore property testing with adversarial input manipulation, examining complexity and relationships to offline models. Learn fundamental computational tasks in this challenging scenario.
Explore sublinear subgraph counting and sampling techniques, focusing on the advantages of counting seeds in graph analysis.
Explore connections between monotonicity testing, routing on hypercubes, and Lehman-Ron theorem. Gain insights into efficient property testers and low-congestion flows on directed hypercubes.
Explore efficient algorithms for testing intersecting k-uniform set families, including tolerant and one-sided error non-adaptive methods. Compare results to non-uniform families and discover optimal query complexities.
Explore recent advancements in testing bounded-degree graphs, including locally-characterized expander graphs, graph isomorphism studies, and applications of robustly self-ordered graphs.
Explore root causes of safety concerns and attacks on LLMs, evaluate defense strategies, and examine broader implications for machine learning safety and robustness.
Explore edge connectivity in simple graphs using cut queries, introducing star contraction for efficient graph simplification and discussing randomized and quantum algorithms for connectivity determination.
Explore efficient parallel algorithms for locally checkable problems in sparse graphs, focusing on techniques beyond graph sparsification for improved performance in sublinear regimes.
Get personalized course recommendations, track subjects and courses with reminders, and more.