Oracle Complexity
Overview
Oracle complexity measures the number of calls an algorithm needs when it can access a problem only through responses such as gradients, stochastic samples, membership answers, or proximal updates. Researchers develop algorithms and matching lower bounds for settings including convex and nonconvex optimization, online learning, monotone inclusions, and sampling, using methods such as variance reduction, proximal iterations, and higher-order updates. A central finding is that query costs depend not only on accuracy and dimension, but also on randomness, memory, oracle fidelity, and the cost or strength of each response. For many settings upper and lower bounds now match, while gaps remain across oracle models and regimes, including how to trade query budgets against wall-clock cost or memory.
Latest papers
30 papers6 papers in the last four weeks, down 33% on the four weeks before. 0.0% of all new papers.