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Daniel Sheldon

9 papers at tracked venues · 6 at CORE A* · active 2024–2025

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Venues

NeurIPS ×4AAAI ×1AISTATS ×1ECCV ×1ICCV ×1UAI ×1

Frequent coauthors

Subhransu Maji
×4
Jinlin Lai
×2
Grant Van Horn
×2
Gustavo Pérez
×2
Brett C. Mullins
×2
Miguel Fuentes
×2
Cameron Musco
×2
Justin Domke
×2
Max Hamilton
×1
Wenlong Zhao
×1
Justin Kay
×1
Sara Beery
×1

Papers

  1. Active Measurement: Efficient Estimation at Scale
    NeurIPS 2025 ·
    Max Hamilton
    ,
    Jinlin Lai
    ,
    Wenlong Zhao
    ,
    Subhransu Maji
    , Daniel R. Sheldon
  2. Consensus-Driven Active Model Selection
    ICCV 2025 ·
    Justin Kay
    ,
    Grant Van Horn
    ,
    Subhransu Maji
    , Daniel Sheldon,
    Sara Beery
  3. DISCount: Counting in Large Image Collections with Detector-Based Importance Sampling
    AAAI 2024 ·
    Gustavo Pérez
    ,
    Subhransu Maji
    , Daniel Sheldon
  4. Efficient and Private Marginal Reconstruction with Local Non-Negativity
    NeurIPS 2024 ·
    Brett Mullins
    ,
    Miguel Fuentes
    ,
    Yingtai Xiao
    ,
    Daniel Kifer
    ,
    Cameron Musco
    , Daniel R. Sheldon
  5. Gaussian Process Bandits for Top-k Recommendations
    NeurIPS 2024 ·
    Mohit Yadav
    ,
    Cameron Musco
    , Daniel R. Sheldon
  6. Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models
    NeurIPS 2024 ·
    Jinlin Lai
    ,
    Justin Domke
    , Daniel R. Sheldon
  7. Human-in-the-Loop Visual Re-ID for Population Size Estimation
    ECCV 2024 ·
    Gustavo Pérez
    , Daniel Sheldon,
    Grant Van Horn
    ,
    Subhransu Maji
  8. Joint Selection: Adaptively Incorporating Public Information for Private Synthetic Data
    AISTATS 2024 ·
    Miguel Fuentes
    ,
    Brett C. Mullins
    ,
    Ryan McKenna
    ,
    Gerome Miklau
    , Daniel Sheldon
  9. Sample Average Approximation for Black-Box Variational Inference
    UAI 2024 ·
    Javier Burroni
    ,
    Justin Domke
    , Daniel Sheldon