Research map / Learning theory and algorithms / Prediction and decision losses
Dynamic Determinantal Point Processes
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
- Kronecker Determinantal Point Processes (NeurIPS 2016 · similarity 0.92)
- Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes (ICLR 2021 · similarity 0.91)
- Low-Rank Factorization of Determinantal Point Processes (AAAI 2017 · similarity 0.90)
- Scalable Sampling for Nonsymmetric Determinantal Point Processes (ICLR 2022 · similarity 0.90)
- State-of-art minibatches via novel DPP kernels: discretization, wavelets, and rough objectives (NeurIPS 2026 · similarity 0.89)
- Small coresets via negative dependence: DPPs, linear statistics, and concentration (NeurIPS 2024 · similarity 0.86)
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.