Research map / Learning theory and algorithms / Sample complexity
Optimal Bounds between f-Divergences and Integral Probability Metrics
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- (f,Gamma)-Divergences: Interpolating between f-Divergences and Integral Probability Metrics (NeurIPS 2022 · similarity 0.88)
- Function-space regularized Rényi divergences (ICLR 2023 · similarity 0.87)
- Integral Probability Metrics PAC-Bayes Bounds (NeurIPS 2022 · similarity 0.87)
- Local Minimax Complexity of Stochastic Convex Optimization (NeurIPS 2016 · similarity 0.87)
- Bounds on $L_p$ Errors in Density Ratio Estimation via $f$-Divergence Loss Functions (ICLR 2025 · similarity 0.86)
- Stability and Sharper Risk Bounds with Convergence Rate $\tilde{O}(1/n^2)$ (NeurIPS 2025 · similarity 0.85)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.